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1. Actuated signal Control

1. 4 __ 1 necne m E 5 Bp A pU Figure 1 1 Typical Intersection Layout Ring 1 r G gt WBL EBT NBL SBT I gt f lt gt EBL WBT Ring 2 SBL NBT Left side of barrier Right Side of barrier E W Movements N S Movements Barrier Figure 1 2 Dual ring concurrent phasing scheme with assigned movements 1 2 2 Modeling vehicle detection The vehicle detection is an important part of the actuated signal system There are three groups of detectors in each approach for the typical intersection in the real world 1 Stopline detectors located in the through lanes and very close to the stop line for the presence detection of through vehicles There may be 2 3 presence detectors for a lane that are typically about six feet by six feet in size 2 Advance loop detector located at almost 150 300 feet from the stop bar used to detect vehicles for the extension of the through movement phase and 3 Long loop detector for left turns with the length of about 50 70 feet for the presence detection of left turn vehicles In some cases a set of individual detectors are used instead of a single long one For some intersections there may be no advance detector at some approaches of an intersection If presence detectors are only placed on the minor cross street the signal has semi actuated control To better simulate the functionality
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3. 4 32 Recall Phase 8 Lanes RightTumlaes too Detector2 ich ss 100265 jcb3S Detector3 28 1 7 5 The priorities information for the example intersection actions 1167 phase offset 0 00 sec phase 1 0 00 max 100 00 red phase 0 00 fill all barred except from 1416 to 299 minor from 1610 to 1416 minor from 1610 to 1533 major from 299 to 1416 major from 299 to 1533 minor from 1533 to 1610 minor phase 2 0 00 max 100 00 red phase 0 00 fill all barred except from 1416 to 299 minor from 1610 to 1416 minor from 299 to 1416 major from 299 to 1533 minor from 299 to 1610 major from 1533 to 1610 minor phase 3 0 00 max 100 00 red phase 0 00 fill all barred except from 1416 to 299 minor from 1610 to 1416 minor from 1610 to 299 major from 1610 to 1533 major from 299 to 1533 minor from 1533 to 1610 minor phase 4 0 00 max 100 00 red phase 0 00 fill 29 all barred except from 1416 to 299 minor from 1610 to 1416 minor from 1610 to 299 major from 299 to 1533 minor from 299 to 1610 major from 1533 to 1610 minor phase 5 0 00 max 100 00 red phase 0 00 fill all barred except from 1416 to 299 minor from 1416 to 1610 major from 1610 to 1416 minor from 299 to 1533 minor from 1533 to 299 major from 1533 to 1610 minor phase 6 0 00 max 100 00 red phase 0 00 fill all barred except from 1416 to 299 minor
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5. PARAMICS This report discusses the logic of this plugin as well as its implementation 1 2 Plugin implementation 1 2 1 Control logic The layout of a typical actuated signal intersection is shown in Figure 1 1 The control logic that is implemented in the plugin is for an eight phase dual ring concurrent controller actuated signal The dual ring concurrent concept is illustrated briefly in Figure 1 2 Note that eight phases are shown each of which accommodates one of the through or left turning movements A barrier separates the north south phases from the east west phases Any phase in the top group Ring 1 may be displayed with any phase in the bottom group Ring 2 on the same side of the barriers without introducing any traffic conflicts For simplicity the right turns are omitted and assumed to proceed with the through movements In the fully actuated signal control all phases at an intersection are actuated Therefore the length of each phase and consequently the cycle length will vary with each cycle Some phases may be skipped if there is no vehicle actuation To simulate the real controller better the order and sequence of phases can also be altered The detailed description on how actuated signal works can be found in the textbook by McShane et al 1998 I I Presence detector
6. RAMP uci ramp get parameters char rampnode _ declspec dllimport float uci ramp get tod rate char rampnode 5 5 Technical Supports 5 5 Limitations of this plugin The controllers in the real world have more capabilities than this plugin For example SATMS one of Caltrans ramp metering algorithm contains local mainline responsive control i e demand capacity control and time of day control i e pre timed control However this plugin only emulates pre timed control In version 3 of PARAMICS sometimes the presence detector does not work correctly 1 e sometimes a vehicle cannot be detected though it is present on the detector This case is very rare however this may cause severe problems in the simulation since all the following vehicles are blocked and the signal may remain red all the time To solve this problem a green signal is given as long as the time of red signal is over RAMP CYCLE The maximum number of timing plans is 256 for each entrance ramp signal The length of green time for single entry metering is 2 0 seconds and for platoon metering is 4 0 seconds which are pre set by the plugin No queue control is involved in this plugin If a queue control is required please use queue control plugin together with this plugin 59 5 5 2 FAQ 1 PARAMICS can model ramp metering Why do you develop this plugin PARAMICS can model fixed time ramp metering with multiple timing plans However a ramp met
7. The second part shows the calculated saturation densities of mainline detector stations The Sample size required to compute saturation density is a user specified variable ranging from 6 to 1200 Its default value is 200 The second part has 5 columns i e the time of calculation name of detector station original saturation density calculated saturation density and the smoothed saturation 94 density The calculation of the smoothed saturation density uses a parameter i e Smoothing factor for saturation density computation defined in the second part of swarm global The default value of this parameter is 0 05 smoothed sat _ 1 sat a If you not know the saturation density at a detector station we strongly recommend users to use the first simulation run to calculate saturation density values at all detector stations The value shown in the column of new sat is a good value of the saturation density because it does not involve the use of the smoothing factor Then you can update the saturation density values in vds control For a following simulation run the saturation density values shown in vds control are applied before enough data are collected for the calculation of new saturation density values If a new saturation density is calculated the smoothed saturation density will be applied instead of the value shown in vds control As a result the first simulation run wil
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9. regulator 70 0 metering level occupancy threshold metering cycle There are three parts of this control file The first part is the basic information of the BOTTLEENECK algorithm The option of checking control file is used for checking if there are any mistakes in the control file If yes this API will print out the information obtained from bottleneck control file when this API is loaded update cycle of metering rate is the time interval of metering rate calculation The option time period to accumulate detector data determines if more than one observation of loop data will be used for metering rate calculation For example if time period to accumulate detector data is 60 and metering rate update cycle is 30 the loop data at time interval t 1 and t 2 will be accumulated first and then used for calculating the metering rate at time t The value of time period to accumulate detector data must be integer times of the value of metering rate update cycle During the time period between algorithm activation time and algorithm deactivation time the ramp metering algorithm is functional 77 If report metering rate is yes the metering information of all BOTTLENECK controlled ramps will be output every update cycle to a file named BOTTLENECK rampRate txt The current applied local algorithm should be also specified The local algorithms can be either OCCUPANCY CONTROL or ALI
10. the metering rate is vehicle per minute If the value of the metering rate is 1 it means there is no metering at the on ramp or called greenball The queue override flag can be a value of either 1 or 0 1 represents that the metering at the on ramp is under the default queue override strategy control The default queue override strategy can be described as follows If the occupancy value of the queue detector exceeds a threshold 1 50 the maximum metering rate will be applied to the corresponding meter in order to release more vehicles to freeway The corresponding metering rate of the on ramp will be the maximum rate defined in the swarm control 2 Log sat density Log sat density used to store the calculated saturation density at each mainline detector station The following is an example of the resulting Log sat density file time 405n5 74ml 405n5 55ml 405n4 03ml 405n3 86ml 405n2 99ml 405n1 93ml 405nl 11ml 405n0 93ml 405n0 6ml 06 30 00 45 45 45 45 45 45 35 45 45 time vds name old sat new sat smoothed sat 08 13 30 405n0 93ml 45 45 45 08 15 00 405n2 99ml 45 44 45 08 16 30 405n4 03ml 45 52 45 08 17 00 405n3 86ml 45 45 45 08 19 30 405n1 93ml 45 47 45 08 28 00 405n1 1lml 35 34 35 There are two parts in Log sat density In the first part the first row listed names of all mainline loop detector stations The second row shows the saturation density values of these stations obtained from vds control
11. 0 30 0 range 10 0 to 30 0 precision 1 88 9 0 Absolute maximum effective loop length 6 0 10 0 range 6 0 to 10 0 precision 1 9 Volume threshold to compute a new effective loop length 4 14 range 4 to 14 precision 0 3 0 Absolute minimum effective loop length 2 0 6 0 range 2 0 to 6 0 precision 1 55 Speed threshold to compute a new effective loop length 50 90 range 50 to 90 precision 0 0 02 Smoothing factor for the effective loop length 0 0 1 0 range 0 0 to 1 0 precision 2 65 0 Free speed 55 0 85 0 range 55 0 to 85 0 precision 1 The second part includes parameters used for the calculation of the saturation density for each loop station 2200 Maximum hourly lane volume 1800 2500 range 1800 to 2500 precision 0 200 Sample size required to compute saturation density 6 1200 range 6 to 1200 precision 0 0 05 Smoothing factor for saturation density computation 0 0 1 0 range 0 0 to 1 0 precision 2 The third part includes parameters of Kalman filtering used in the SWARM 1 algorithm 1 Max number of VDSs to search if bottleneck VDS is failed 1 4 range 1 to 4 precision 0 30 Number of previous time intervals used for the forecast 2 60 range 2 to 60 precision 0 6 Number of points used to estimate slope for Kalman filter 2 9 range 2 to 9 precision 0 30 Number of time intervals into the future to forecast 1 60 range 1 to 60 precision 0 0 04 Variation in the accuracy of the density m
12. 168 66 0 11 0 098 46 0 079 72 1 79 1 14 0 083 74 0 150 095 67 5 0 057 Figure 4 1 Output file of loop data aggregator plugin 48 4 3 4 Error checking This plugin is easy to use if loop control is prepared correctly If any mistakes happened in the control file the plugin will be disabled The report window of PARAMICS will show whether this plugin is working If the plugin is not working you may need to check if there is any error in loop control This plugin generates a file named Log loop txt under the network directory which can be used to check if the control file has been understood by this plugin correctly 4 4 PROGRAMMER capabilities 4 4 Interface functions This plugin provides three interface functions The first one is used to obtain the current polling report cycle of data aggregation defined in the second row of control If an ATMS application such as an adaptive ramp metering control is based on aggregated loop data this interface can provide the polling cycle of aggregated loop data int uci loop agg interval void Return Value The polling cycle of aggregated loop data Parameters None The second interface function is used to tell users if a loop detector has been specified in loop control file for getting aggregated loop data Bool uci loop aggregation char name Return Value If the name of a loop detector has been specified in control file
13. 4 3 Split phases 16 Except the above mentioned cases users may need to make signals work under split phases For example there are only two possible phase combinations 1 amp 6 and 2 amp 5 in the first phase group Under this situation the signal timing chart from the local transportation agency may provide phase information which may not make this plugin work as expected 1 4 3 1 2 amp 5 first and 1 amp 6 second The signal control file can be configured as movements 2 1 3 4 9 9 7 8 ini green 10 5 5 8 0 0 5 8 extension 4 3 3 5 0 0 3 5 max green 32 24 24 32 0 0 24 32 recall 4 8 lanes 5 5 2 3 0 0 2 3 rightturn 0 1 0 1 detector1 icbsw N A N A icbuw detector2 icbss N A N A icbus detector3 icbse N A N A icbue detector4 icbsn N A N A icbun There is no phase 5 and 6 Only phases 1 and 2 exist Note that movement 1 e phase 1 includes all lanes of link 13 10 and phase 2 includes all lanes of link 14 10 no matter the lane is reserved for left turns or through movements We can also configure the signal control file in another way i e without phases 1 and 2 but with phases 5 and 6 as shown below The previous phase 1 goes to phase 6 and the previous phase 2 goes to phase 5 movements 9 9 3 4 6 7 8 ini green 0 0 5 8 10 5 5 8 extension 0 0 3 5 3 3 5 max green 0 0 24 32 32 24 24 32 recall 4 8 lanes 0 0 2 3 5 5 2 3 rightturn 0 1 0 1 detector1 icbsw N A N A icbuw detector2 icbss N A N A icbus detector3 icbse N A N
14. API plug in is moe freeway control which should be placed to the network directory The format of this input file can be demonstrated through an example of the file shown below number of sections 3 checking control file yes report cycle 300 collection start time 06 00 00 collection end time 10 00 00 loop detectors 405n0 93ml 405n5 55ml links 2 3 12 16 sample rate 10 destination zone 2 entrance ramp no loop detectors 405n0 93orspill 405 0 93 links 426 524 33 34 sample rate 50 destination zone 2 entrance ramp yes There are two parts in freeway control The first part is the global options that need to be specified for the API plug in number of sections is the number of sections that needs to perform a travel time related data collection The option of checking control file is used for checking if there are any mistakes in the control file If yes this 99 API plug in will print out the information obtained from freeway control file when the API plug in is loaded The data collection interval 1s specified as report cycle Its unit is second For example if the report cycle is 300 seconds it means all collected data will be output once every 300 seconds collection start time and collection end time are the time period that data are collected The second parts are used to input the information of each section There are two sections in the example The first one is an
15. Ye ead 83 9 ER EQUOS eoe nee ie mesi abes mel toe Sel 83 9 2 Pluem amplementatiotis se eMe a tr reed tha oe 84 9 3 Step by step user lr tbe t Ren ia a 87 9 4 Technical Suppor seer eno dad sto rom In i e ena hand ease E Pe De iba Mon 96 DOS APPENDIX recs dete te audae E UE NL NE 98 IQ Freeway eae rs adeo edu adi dada e ER Ve deae needs 99 10 1 e e Ng et 99 10 2 Step by step user 2 real ela a Hed 99 10 3 PROGRAMMER capabilities eese enne enne 101 1 Actuated signal Control 1 1 Introduction Generally modes of traffic signal operation can be divided into three primary categories USDOT 1996 pre timed actuated and traffic responsive PARAMICS can basically model the fixed time signal control Besides PARAMICS also provides a plan phase language i e a kind of script language to simulate some simple actuated signal control logic However in the field the widely used actuated signal controller uses the complex NEMA logic or type 170 logic Our experiences found this script language is difficult to be used to model these types of complex control schemes and to replicate these schemes to multiple signalized intersections A plugin was developed in order to easily model actuated signal control within
16. algorithm proposed by Papageorgiou et al is a local feedback ramp metering policy The algorithm attempts to maximize the mainline throughput by maintaining a desired occupancy on the downstream mainline freeway As shown in Figure 7 1 two detector stations are required for the implementation of the ALINEA algorithm The first loop detector is located on the mainline freeway immediately downstream of the entrance ramp where the congestion caused by the excessive traffic flow originated from the ramp entrance can be detected The second loop station is on the downstream end of the entrance ramp and used for counting the on ramp volume 1 reeway E Demand detector detector Surface street Figure 7 1 Detector layout for the implementation of the ALINEA algorithm For an on ramp under ALINEA control its metering rate during time interval t At is calculated as r t T t At K O O t At where At is the update cycle of ramp metering implementation 7 t is the measured metering rate of the time interval of t At t O t At is the measured occupancy of time interval t At t at the downstream detector station is a regulator parameter used for adjusting the constant disturbances of the feedback control O is the desired occupancy at the downstream detector station The value of O 15 typically set equal to or slightly less than the critical occupancy or occupancy at capacity
17. based on vehicle length loop detector length and vehicle speed Therefore we need to convert from time occupancy to percent occupancy N OCC OCC f i where 1 is the time occupancy of vehicle i N is the total number of vehicles having passed the detector during last time interval 7T is the interval of aggregation If at the aggregation time a vehicle is just on a loop the duration the vehicle is on the detector this value can be obtained from simulation is used for aggregation Based on aggregated data of each lane the grouped aggregated data including grouped volume occupancy and speed of this detector station are also calculated The grouped volume represents the total number of vehicles having passed the detector station including several detectors each lane has one detector during last time interval which can be expressed as 44 where i is the index of the detector station j is the loop index at detector station i n is the total number of lanes or loops at detector station i N t is the number of vehicles passing loop j of detector station 7 during time interval 1 1 t The grouped occupancy represents the average percent occupancy of a detector station during last time interval which can be expressed as n 300 O t LY 0 TT k l where i is the index of the detector station j is the loop index at detector station i n is the total number of lanes o
18. dection c If left green time gt 0 Check if this phase should be forced off pp force off If force off Find the next phase by vehicle presence else 1 excute the current signal plan pp excute If left green time extension amp amp vehicle presence for extension amp amp expired green lt maximal green extension green time increased by extension left green If left green time lt time step 36 Find the next phase by vehicle presence j else Amber and red time are counted If amber and red time are reached Set the next signal phase parameters through signal action 3 3 Step by step user manual 3 3 1 Understanding actuated signal coordination The implemented actuated signal coordination logic has some new concepts The correct understanding of them is important for the use of the actuated signal coordination plugin The following is a good description of these terms 1 Background Cycle Length To provide synchronization and maintain the background cycle length all coordinated intersection have the same system clock reference point which is usually the start point of signal coordination plan 2 Yield Point The sync phase of every coordinated intersection has fixed series of yield points and the difference between yield points is the background cycle length 3 Sync Phase These yield points are also local clock reference points to other non syn
19. detection in later versions of PARAMICS later than Build V 3 0 7 we can use one long loop instead of three stopline loop detectors for vehicle presence As a result we only need to model 8 detectors for an intersection That is to say detectors 1 5 9 and 13 are long loops with a typical length of 50 feet and there is no need to code detectors 2 3 6 7 10 11 14 and 15 This is our recommended method to model detectors of an actuated signal intersection In version 4 of PARAMICS detectors can be lane specific This plugin does not support the use of this type of detector 12 9 ft or 4m Stop line L 49 5 f or 15m Figure 1 3 Modeling the left turn long loop detector 8C Approach 2 JE Approach 1 So Ion fre eos EN CT E ATE ee DE ce cet rV MED e eu S feiert rea eus rera or a St E eg dope NEMA Phase 3 i lt Detector number 14 Approach 3 Detector 15 Approach 4 J 16 Figure 1 4 Typical Intersection Layout in PARAMICS with NEMA phases 1 2 3 Pseudo code The pseudo code for the main control logic of this plugin is given as follows 1 Initialize the actuated signal plugin including signal data input memory allocation and initial signal phase set up 2 Atevery time step of simulation net action is called For controller intersection 1 n a Inq
20. detector The queue override strategy implemented in this plugin is based on a queue detector which is generally located at the end of the entrance ramp in the real world The ramp meter design manual of Caltrans has the following descriptions of the location of queue detectors loop per entrance ramp lane should be installed for queue detection near the connection of the surface street This location of queue detector can be modified in order to improve the control performance A study shows that when the queue detector is located at 75 of the physical ramp length of the on ramp the performance of queue control is better than the cases when the queue detector is located at 100 and 62 5 length of the on ramp Hasan M 1999 62 6 3 2 Preparation of the queue control file The queue control file includes the queuing control information which is the input of this plugin The file should be located at the same directory as any other network files An example of queue control is shown below total number of queuing controlled on ramps is 7 checking control file yes control cycle 30 algorithm activation time 06 00 00 algorithm deactivation time 09 00 00 report queuing condition yes on ramp signal 33 queue detector 405n0 93orspill override occupancy threshold 0 5 override control plan METER ON with 1 veh per 5 sec on ramp signal 36 queue detector 405nl 11orspill override occupancy threshold 0 5 override c
21. each ramp based on ramp demand queue storage capacity etc The most restrictive volume reduction is then utilized at each ramp location Density Se I I I 123195 EROE COO TN CET j T AT tbe E ENT AT 1 TECUM F TATEM UC RON MANT EN ber Ege codsDhnsity pat iatibn ei 1 EjeedjsDpnsity Density open ee ene S Pe Ink okra ss bcm EOM UD ec TE eC line aal I Lu I I Lu 1 Lu I FS drop dq wd E ABS A jr nu ML e s ee n ds ERIT MED joe doe b Spe ed e se al ad I j j ia do B NA MS HET DNE OR pog a a el ob ut TBI Pet Ve eT or NETS ee I Tori mnc ETT TTL Df EC oe Mee Time Figure 9 1 SWARM forecasting 9 1 2 SWARM 2 SWARM 2a uses a density function to compute local metering rates based on headway theory Theoretically it attempts to maintain headway at the detector station upstream
22. example of the point to point travel time collection Two loop detectors are the boundaries of a section The names of them are specified on the line of loop detectors The first detector is located at the upstream of freeway and the second one 15 located at the downstream The links where these two loop detectors are located also need be specified on the line of links Since there will be many vehicles passing through a section if all of them are traced in order to get travel time delay information it will take a lot of computation time As a solution users can specify the percentage of passing vehicles on the line of sample rate In order to make sure that all vehicles that are traced at the first loop detector station will pass the second loop detector station users need to specify the destination zone of passing vehicles The zone should be located at the downstream end of the freeway on the line destination zone If there are not many vehicles heading for the end of the freeway users can specify another zone which should be located at the downstream side of the second loop detector station Since the current section is a freeway section it is not located on the entrance ramp entrance ramp is no The second one is an example of the on ramp delay collection The loop detectors specified here should be located on the entrance ramp The first detector is the queue detector The second detector is located at the link b
23. from 1416 to 1533 major from 1416 to 1610 major from 1610 to 1416 minor from 299 to 1533 minor from 1533 to 1610 minor phase 7 0 00 max 100 00 red phase 0 00 fill all barred except from 1416 to 299 minor from 1610 to 1416 minor from 299 to 1533 minor from 1533 to 1416 major from 1533 to 299 major from 1533 to 1610 minor phase 8 0 00 max 100 00 30 red phase 0 00 fill all barred except from 1416 to 299 minor from 1416 to 1533 major from 1610 to 1416 minor from 299 to 1533 minor from 1533 to 1416 major from 1533 to 1610 minor 31 2 Multiple Actuated Signal Plan 2 1 Introduction The actuated signal plug in only supports one timing plan for each actuated signal In order to allow multiple signal timing plans this plug in can be used 2 2 Plug in Implementation This plug in is developed based on actuated signal plug in The pseudo code for the main control logic of this plugin is given as follows 1 Read the multi plan signal control file and initialize the multiple actuated signal plugin 2 Atevery time step of simulation For controller intersection 1 n If time to switch timing plan Update signal timing plan using uci signal set parameters 2 3 Step by step user manual 2 3 Preparation of multi plan signal control file In order to use this plug in the input file of the plug in multi plan signal control needs to be prepared first An example of this file is total number
24. in this file has a very similar format to that of the worksheet There are two signals modeled in Figure 1 5 The first one uses 16 detectors and the second used 8 detectors signal control total number of actuated node 1167 ICD amp BARRANCA movements 2 3 ini_green 5 5 extension 4 3 max green 2 32 24 recall 8 lanes US 2 0 2 0 2 0 2 0 l0 XD detectori1 ichsw icbzw ich3w icbuw detector2 icbss icb2s ich3s icbus detector3 icbse icb2e icb3e icbue detector4 icbsn ich2n icb3n node 142 ALTON amp ICD movements 1 ini_green 5 extension 3 max green 24 recall lanes rightturn 1 0 detectorl aisw detector2 aiss detector3 aise detector4 aisn Figure 1 5 An example of signal_control file 1 3 5 Preparation of priorities information The priorities file defines what movement can be allowed under each phase of an intersection For pre timed signal control the priorities information can be edited through the PARAMICS GUI However for the actuated signal the file priorities must be edited directly with a text editor We need to generate the priorities information of an actuated signalized intersection based on the worksheet we made on step 2 in which the node names of adjacent nodes of an intersection have been written down Figure 1 6 is an example of the node designations for a four legged intersection approach 1 is considered to be in the direction starting a
25. of data aggregation The unit is seconds This cycle is corresponding to the time interval of real world loop data collection A typical value of the report cycle is 30 seconds Basically this polling cycle is not related to aggregated data outputs It is used for ATMS applications such as adaptive ramp metering that are based on aggregated loop data 3 The next two rows specify the activation time and deactivation time of the loop data aggregation 4 The fifth row specifies whether to gather smoothed loop data including speed occupancy If no raw data will be gathered There are two kinds of loop data that can be provided by PARAMICS at each time step raw data or smoothed data Smoothed refers to a value ty at time step N smoothed using the expression ty pty Pty where fy is the current value and p is the co efficient of smoothing 5 The sixth row specifies whether to output aggregated loop data to files If say ves a file generally named as XYZ txt XYZ is the name of the corresponding loop will be generated for storing the aggregated volume occupancy and speed data based on the gather interval specified in the second part of this control file The second part of the file contains the information of each loop detector including the name of detector and the time interval that loop data are aggregated and reported to text files There is a blank row between the information of any two loops The name
26. of detectors ideally detectors should be modeled in PARAMICS according to the real world configuration However in Build 3 of PARAMICS detectors are not lane specific A detector covers all lanes of a link and thus a PARAMICS detector represents a detector station Therefore we cannot model a separate long loop for left turn use in the actuated signal system As a result we use three small detectors instead of a long loop as shown in Figure 1 3 Three 2 m or 6 6 ft detectors are used to mimic one 50 ft long loop detector These detectors model the stopline presence detectors as well as the left turn detectors The default length of detectors in PARAMICS is 2 meters or 6 6 feet The lengths of these detectors in PARAMICS do not match the common real world length of six feet but for the purposes of simulation this works fine As illustrated in Figure 1 4 we modeled 16 detectors for a typical intersection in PARAMICS and each detector covers all lanes of a link For each approach there are three detectors close to the stop line for through and left turn vehicle presence detection and one advance detector located at about 150 300 feet to the stop line for detecting vehicles for the extension of the through movement phase For stopline detectors all three of them employ the vehicle presence of left turn lanes the two detectors close to the stop line are used for detecting the presence of through vehicles Due to improvements in the long loop
27. plan of the corresponding queuing strategy is not specified METER OFF is applied If there is no queue detector nothing needs to be filled in this line 6 3 3 Loading plugin This plugin has two files queue controller dll Modeller Plugin queue controller p dll Processor Plugin This plugin needs the support of loop data aggregator plugin and ramp metering plugin 64 They should be specified earlier than this plugin in the plugins or programming file ex loop_agg dll ramp_controller dll queue controller dll In order to load and run this plugin correctly please satisfy the following requirements 1 The queue detectors in the queue control file should be specified in loop control file 2 The report cycle in the loop control file should be the same as the control cycle specified in the queue control file 6 3 4 Output file If report queuing condition in the queue control file is specified as yes the queuing information of all controlled ramps will be output every update cycle to a file named moe rampQueue txt It can be found in the subdirectory network Log run xxx where network is the name of the current working directory and xxx is a three digit sequence number For each on ramp queuing condition of last control cycle will be output If the queuing control is enabled due to a long queue spillback on an entrance ramp the output value 15 1 Otherwise it is 0 At
28. rate to be finally implemented should be within the range of the pre specified minimum and maximum metering rates 8 2 Plugin implementation Figure 6 1 illustrates the hierarchical development framework of advanced ramp metering algorithm plugins in PARAMICS In the framework the advanced ramp metering algorithm plugin is built on top of two basic plugin modules i e ramp metering controller and loop data aggregator The control logic of the BOTTLENECK algorithm plugin is implemented as the following pseudo codes 1 Communicating with ramp metering API and loop data aggregator API in order to obtain up to date traffic information and historical metering rates 2 Calculating and then checking if the two conditions are met If they are met the system metering rate and local metering rate are calculated and the most restrictive one is selected for further adjustment Otherwise the local metering rate is selected for further adjustment Metering rate restriction Checking if the queuing strategy needs to be activated HOV adjustment Sending its computed metering rate to the ramp metering API for implementation ON cs 75 8 3 Step by step user manual 8 3 1 Adding detectors BOTTLENECK needs to put mainline detectors at the spacing of 0 5 to 1 0 mile to the target freeway in order to capture the traffic congestion dynamics As a result the freeway segment under control is divided into several sections each of which is def
29. return TRUE Otherwise return FALSE Parameters Name of the loop detector The third interface function is used for querying the aggregated loop data of the latest time interval at a detector station The aggregated loop data includes grouped volume average occupancy and average speed and lane based volume average occupancy and average speed LOOPAGG uci loop agg int index Return Value The aggregated detector data of a loop detector Parameters index the network wide index number for a loop detector LOOPAGG is a structure that has the following definition typedef struct loopagg LOOPAGG struct loopagg int index float time 49 int g vol float g occ float g spd int lane int vol float occ float spd P where index is the network wide index for the detector time is the time stamp for the calculation of aggregation decided by the gather interval of each loop g_vol is the total traffic volume passing all lanes of a detector station within last time interval g occ is the average occupancy of all lanes of a detector station g spdis the average speed of all vehicles passing all lanes of a detector station lane is the total number of lanes at the detector station vol occ spd are pointers for recording values of volume occupancy and average speed of each lane of a detector station Most items in this structure can be found in the output file of aggregated loop data whose fields are de
30. the end of this file a summary of the percentage of time that the queue override strategy is activated 1s provided An example of this file is shown in Figure 6 2 6 3 5 Error checking If there is any mistake in the queue control file or the input files of the two supporting plugins i e loop data aggregator and ramp metering control this plugin will be disabled The report window of PARAMICS will show whether this plugin is working Through enabling the option checking control file in the queue control file you can check if there is any error in the queue control file 65 36 E J t Ru 07 00 30 0 0 0 0 0 0 0 07 01 00 0 0 0 0 0 0 0 07 01 30 0 0 0 0 0 0 0 07 02 00 0 0 0 0 0 0 07 02 30 0 0 0 0 0 0 0 07 03 00 0 0 0 0 0 0 07 03 30 0 0 0 0 0 0 0 07 04 00 0 0 0 0 0 07 04 30 0 0 0 0 0 0 0 07 05 00 0 0 0 0 0 0 0 07 05 30 0 0 0 0 0 0 0 07 06 00 0 0 0 0 0 0 0 07 06 30 0 0 0 0 0 0 0 08 58 00 0 0 0 0 0 0 0 08 58 30 0 0 0 0 0 0 0 08 59 00 0 0 0 1 0 0 0 08 59 30 0 0 0 1 0 0 0 09 00 00 0 0 0 1 0 0 0 SUMMARY 0 42 0 00 0 00 23 33 0 00 0 83 1 67 AVERAGE 3 75 Figure 6 2 Example of the moe rampQueue txt file 6 4 Technical supports References 1 Hasan M 1999 Evaluation of ramp Control Algorithms using a Microscopic Simulation Laboratory Mitsim Master thesis Massachusetts Institute of Technology 66 7 ALINEA ramp metering control 7 1 Introduction The ALINEA
31. time for always OFF Else If the running phase is 2 amp amp green left time lt time step Set the next green time for phase 1 Else if the running phase is 1 1 If no vehicle presence If the running time is less than RAMP CYCLE continue to increment green time for phase 1 Else the running time is equal to RAMP CYCLE set the next green time for phase 2 else Set the next green time for phase 2 j 54 5 3 Step by step user manual In order to use this ramp metering plugin two files need to be prepared 1 priorities file is a system file of PARAMICS provided with the action and phase definition of a ramp signal 2 control file is the input of actuated ramp API including the ramp control information such as ramp name control type cycle effective time etc 5 3 Data preparation The following documents are required in order to correctly use this plugin 1 Ramp meter design map including the layout of detectors 2 Entrance ramp control plans obtained from the proper government agency 5 3 2 Adding demand detectors The demand detector should be added to the PARAMICS network which should be put just before the stop line based on the design map of the entrance ramp The number of demand loops installed in the real world and the layout of these loops will decide the length of the demand detector in PARAMICS The ramp metering API can work with or without detectors If with detectors the
32. to approximate volume occupancy relationships which will be used to calculate the predetermined set of metering rates The coordination algorithm is the unique aspect of BOTTLENECK The freeway segment under control is divided into several sections each of which is defined by the stretch of freeway between two adjacent mainline loop stations A section is identifies as a bottleneck if it satisfies two conditions i e capacity condition and vehicle storage condition The capacity condition can be described as i t i 3 where Odown i t is the average occupancy of the downstream detector station of section i over the past one minute period 1 1 t is a pre defined loop station occupancy threshold when it is operating near capacity The vehicle storage condition can be formulated as bot 60 t GO Qin 0 0 20 4 where Qyeduction i t is the number of vehicles stored in section 7 during the past minute Oup i t and Qdown i t are the volume entering section i across the upstream detector station and the volume exiting section across the downstream detector station during the past minute respectively Qon i t is the total volume entering section i from on ramps during the past minute t is the total volume exiting section i to off ramps during the past minute The number of vehicles stored in the bottleneck section Q eduction i t should be reduced E
33. up loop char down loop Function Obtain travel time statistics between up loop and down loop Return Value Average travel time and its variance Parameters up loop and down loop are names of the upstream loop detector and downstream loop detector PROBE is a data structure with the following format type PROBE int index int time int interval int sampleRate int num float tt float var where index is the ID of the travel time collection sampleRate is the sampling rate of the travel time collection interval is the report cycle of the travel time data collection num is the number of traced vehicles of the last report cycle tt is the average travel time between two loop stations var is the variance of all collected travel times 102
34. which can be found in the volume occupancy relationship 67 7 2 Plugin implementation Figure 6 1 illustrates the hierarchical development framework of advanced ramp metering algorithm plugins in PARAMICS We implement the ALINEA algorithm plugin with the following pseudo codes 1 Communicating with ramp metering API and loop data aggregator API in order to obtain related up to date traffic information and historical metering rates 2 Calculating the next metering rate based on formula 1 3 Metering rate restriction An on ramp volume restriction which requires the implemented metering rate to be limited within some pre defined maximum and minimum values is also included in this API 4 HOV adjustment The ideal ramp metering algorithm should control all vehicles entering freeway from entrance ramps If there is a HOV preferential lane on the entrance ramps the HOV traffic volume can either be considered or not considered in the calculation of future metering rate 5 Sending its computed metering rate to the ramp metering API for implementation 7 3 Step by step user manual 7 3 1 Adding detectors ALINEA needs two detector stations The first one is located on the mainline freeway immediately downstream of the entrance ramp where the congestion caused by the excessive traffic flow originated from the ramp entrance can be detected The second one is located on the downstream end of the entrance ramp and used for counting th
35. which is the difference between two green initiations of the sync phase for two adjacent intersections However for the traffic actuated signal coordination the sync phase of every coordinated intersection has fixed series of yield points and the difference between yield points is the background cycle length These yield points are also local clock reference points to other non sync phases The sync phase has minimal bandwidth i e the sync phase has to start at the time of minimal bandwidth earlier than yield point To do so all other phases have to be cut at certain points which are so called force off points These force off points are usually referenced to the local clock reference point Figure 1 is the phase diagram of coordinated intersection 35 Local Clock Reference Point 0 sec Yield Point Sync Phase Initial Green Background Cycle Length N System Clock Reference Point 0 sec Figure 1 Actuated Signal Coordination 3 2 2 Control Logic and Pseudo Codes In order to implement the above concept the pseudo code for the main control logic is given in the following 1 Actuated Signal API set up using api setup includes signal data input memory allocation and initial signal phase set up 2 Atevery time step net action is called For controller intersection 1 n a Inquiry the current signal information using signal inquiry b Vehicle presence detection pp presence
36. 0 71 name 405n0 93orb gather interval 00 00 30 7 3 4 Output file If report metering rate in the alinea control file is specified as yes the applied metering rate of all ALINEA controlled on ramps will be output every update cycle to a file named moe ALINEA txt The file can be found in the subdirectory network Log run xxx where network is the name of the current working directory and xxx is a three digit sequence number 7 3 5 Error checking If there is any mistake in the alinea control file or the input files of the two supporting plugins i e loop data aggregator and ramp metering control this plugin will be disabled The report window of PARAMICS will show whether this plugin works Through enabling the option checking control file in the alinea control file you can check if there is any error in the alinea control file 7 4 Technical Supports 7 4 1 Calibration of ALINEA algorithm In order to maximize the performance of ALINEA metering control parameters of the ALINEA algorithm need to be calibrated and optimized Basically ALINEA has four parameters to be calibrated including the location of the downstream detector station the desired occupancy of the downstream detector station the update cycle of metering rate and a constant regulator parameter Kr The following is a summary of currently applied parameter values 1 The desired occupancy can be equal to or around the occupa
37. 0 or PARAMICS speed 1 0 1 range 0 to 1 precision 0 These parameters are universal parameters used in SWARM If you want to know more about the functionality of any a parameter in SWARM please find related information from the references listed at the end of this document 9 3 3 Preparation of vds control vds control includes the information of loop detector stations in the simulation network The format of this file is number of freeways 1 polling cycle 30 number of mainline detectors 9 405n5 74ml 405 N 5 74 5 45 yes 405n5 55ml 405 N 555 4 45 no number of off ramp detectors 5 405n5 55fr 405 N 5 55 There are three parts in vds control The first part includes the general information i e the number of freeways and the loop detector aggregation cycle i e polling cycle polling cycle should be the same as report cycle in the control file and metering rate update interval in the swarm control file The format for mainline detectors 15 Freeway ID direction pri direction loop name post mile number of lanes saturation density whether this loop station is a bottleneck The format for off ramp detectors is Freeway ID direction pri direction loop name post mile The VDSs listed in the vds control file are ordered by freeway id direction from downstream to upstream direction can be one of N S W and E pri direction refers to the direction of p
38. 00 00 red phase 0 00 fill all barred except from 14 to 11 major from 14 to 12 major from 14 to 13 major from 11 to 14 minor from 13 to 11 minor from 12 to 13 minor phase 2 0 00 max 100 00 red phase 0 00 13 fill all barred except from 13 to 12 major from 14 to 11 major from 11 to 14 minor from 13 to 11 minor from 14 to 12 minor from 12 to 13 minor phase 3 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 14 major from 13 to 11 major from 14 to 13 major from 14 to 12 major from 11 to 14 minor from 12 to 13 minor phase 4 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 14 major from 13 to 12 major from 13 to 11 major from 11 to 14 minor from 14 to 12 minor from 12 to 13 minor phase 5 0 00 max 100 00 red phase 4 00 fill all barred except If we want link 13 10 as the lead leg signal control will be movements 1 2 3 4 6 5 7 8 ini green 5 10 5 8 10 5 5 8 extension 3 4 3 5 4 3 3 5 max green 24 32 24 32 32 24 24 32 recall 4 8 lanes 2 2 2 3 2 2 2 3 14 rightturn 1 1 detector1 icbsw N A detector2 icbss N A detector3 icbse N A detector4 icbsn N A 1 N A N A N A N A 1 icbuw icbus icbue icbun The corresponding proiorities file will not be listed here Users can easily figure out 1 4 2 Through movement first Based on the description of the last section we can deduce that the phase 2 and 6 should be put to the location of the columns of mov
39. 1 9 3 1 Adding detectors 1 Real world ramp metering system The configuration of a typical ramp metering system in California is shown in Figure 9 2 Mainline Station e Passage Demand Queue Figure 9 2 Typical ramp metering configuration 87 Five types detectors can be possibly installed for a ramp meter including on ramp detector demand detector passage detector queue detector and ramp detector The on ramp detector is used for counting total number of vehicles entering freeway from entrance ramps The demand and passage detectors i e corresponding to the check in and check out detectors are used for the operation of on ramp signals The demand detector employs to initiate green and the passage detector employs to return the signal to red The queue detector is located at the upstream end of the entrance ramp used for detecting the excessive queue length in order to avoid interference with the arterial traffic The ramp HOV detector is used for counting the number of carpool vehicles entering freeway from entrance ramps Caltrans currently has three ramp metering systems SATMS SDRMS and SJRMS TOS of them use the 170 type controllers as hardware SATMS SDRMS and SJRMS TOS are names of their software algorithms installed in the 170 controllers The SWARM algorithm is designed for the ramp metering system of SATMS used in District 7 and 12 The local controller and its ramp metering software of S
40. 1 0 allowed range is from 0 5 to 10 We think these two default values need to be calibrated 9 4 2 References 1 Advanced Transportation Management System Traffic Engineer s Manual Revision 1 Prepared by NET for Caltrans District 7 June 2000 2 Integrated Ramp Meter Arterial Signal Control Project Detailed Design System Wide Adaptive Ramp Metering Prepared by NET for FHWA FOT City of Irvine and Caltrans Distrct 12 August 30 1996 3 System Wide Adaptive Ramp Metering High Level Design Final Draft Prepared by NET for Caltrans and FHWA June 19 1996 97 obtained from Caltrans 0 742 IRVINE CENTER DR 99 e infrastructure layout DE TE WES I 0 726 CENTER An example of the IRVINE CENTER OR OC 0 91 Ln B E m By t E jos d s s JocM05 dgn Feb 07 2001 14 57 43 9 5 APPENDIX 98 Gan 01100 CR 33 408 oL LHP Gym _ dT 2 980 LOTET sw Carte Ap 7 7 4 H 3 721 JEFFERY Rh UNINERSITY 0 t 1 i i i 5 1 10 Freeway MOE 10 1 Introduction This API plug in can be used to collect the following two types of data e Point to point travel time between two loop detectors along freeway On ramp delay 10 2 Step by step user manual 10 2 1 Preparation of the freeway control file The name of the input file of this
41. 612 major from 7511 to 7612 minor from 7612 to 7614 minor from 7612 to 7510 major from 7614 to 7510 minor In this example the movements of each phase are major while all right turns are minor We set the default signal time of each phase as 0 sec This is the reason that we cannot edit these actions information through GUI The plugin will assign a certain length of time to each phase based on the presence of vehicles Then update the above priorities information of the corresponding signalized node in the priorities file of the network Please note that the network with modified priorities file must use together with this actuated signal plugin Without this plugin all movements of those actuated signal intersections are in red light 1 3 6 Loading plugin This plugin has two files actuated signal dll Modeller Plugin 10 actuated signal p dll Processor Plugin After the completion of the signal control file and the update the priorities file you can load the simulation network together with this plugin PARAMICS introduces a network specified method to load plugins Each network has a programming file which contains the plugins used together with the network If you put this plugin in the PARAMICS root directory where you can find other Quadstone s plugins including HOV Loop aggregator Monitor etc you do not need to specify the path of this plugin in the programming file actuated s
42. A icbue detector4 icbsn N A N A icbun For the priorities file phase 1 2 and 3 have the same allowed movements actions 10 phase offset 0 00 sec phase 1 0 00 17 max 100 00 red phase 0 00 fill all barred except from 14 to 11 major from 14 to 12 major from 14 to 13 major from 11 to 14 minor from 13 to 11 minor from 12 to 13 minor phase 2 0 00 max 100 00 red phase 0 00 fill all barred except from 14 to 11 major from 14 to 12 major from 14 to 13 major from 11 to 14 minor from 13 to 11 minor from 12 to 13 minor phase 3 0 00 max 100 00 red phase 0 00 fill all barred except from 14 to 11 major from 14 to 12 major from 14 to 13 major from 11 to 14 minor from 13 to 11 minor from 12 to 13 minor phase 4 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 14 major from 13 to 12 major from 13 to 11 major from 11 to 14 minor from 14 to 12 minor from 12 to 13 minor 18 phase 5 0 00 max 100 00 red phase 0 00 fill all barred except 1 4 3 2 1 amp 6 first and 2 amp 5 second The signal control file needs to be one of the following two movements 1 2 3 ini green 5 10 5 extension 3 4 3 max green 24 32 24 recall 4 8 lanes 5 5 2 rightturn 0 1 0 detector1 icbsw N A N A detector2 icbss N A N A detector3 icbse N A N A detector4 icbsn N A N A movements 9 9 3 ini green 0 0 5 extension 0 0 3 max green 0 0 24 recall 4 8 lanes 0 0 2 rightturn 0 1 0 detector1 icbsw N A N A det
43. ATMS support centralized metering control i e the application of the requested metering rate from TMC 2 Detectors required for this plugin The demand detector has been used in the ramp metering control plugin which is a supporting module of the SWARM plugin The ramp metering control plugin acts like the local controller in the real world In order to make this plugin work three additional detectors or detector stations are required to be put to the simulation network They are the on ramp detector queue detector and the mainline detector station shown in Figure 9 2 If your simulated network in the real world does not have the required detector configuration for the SWARM control please add demand detector on ramp detector mainline detector and queue detector to the simulation network based on Figure 9 2 in order to correctly use this plugin 9 3 2 Preparation of swarm global SWARM has several global parameters They are defined in the swarm global file Totally there are 27 parameters The first part of this file is about loop data acquisition Please see Section 2 6 of reference 1 for more detailed description The value shown on the leftmost side of each line is actually the recommended value 25 0 Ave veh length for the right lane 10 0 30 0 range 10 0 to 30 0 precision 1 22 0 Ave veh length for the 2nd right lane 10 0 30 0 range 10 0 to 30 0 precision 1 18 0 Ave veh length for other ML and HOV lanes 10
44. BOTTLENCK plugin depends on other two plugins ramp metering control and loop data aggregator These two plugins should be specified earlier than this plugin in the plugins or programming file i e loop agg dll ramp controller dll bottleneck controller dll If you want to implement BOTTLENCK with another queue override strategy which can be implemented by the on ramp queue control plugin you will need to leave the queue detector line in the bottleneck control file blank which disables the internal queue 79 override strategy of BOTTLENCK Then you will need to add on ramp queue control plugin to the plugins or programming file with the following sequence in order to give the on ramp queue control strategy higher priority than BOTTLENCK loop agg dll ramp controller dll queue control dll bottleneck controller dll In addition in order to correctly load and run this plugin please satisfy the following requirements 1 For ramp metering control plugin on ramp signals controlled by the BOTTLENCK algorithm should be specified in the ramp control file For example the correspondent on ramp signal 33 needs to be specified in the ramp control file on ramp signal 33 name 405N amp ICD 1 0 93 demand detector 405n0 93orb number of control plans 2 from 6 0 to 9 0 METER ON with 1 veh per 6 sec from 15 0 to 19 0 METER ON with 1 veh per 6 sec 2 For the loop data aggregator plugin all loops
45. CALIFORNIA PATH PROGRAM INSTITUTE OF TRANSPORTATION STUDIES UNIVERSITY OF CALIFORNIA BERKELEY Development of the Capability Enhanced PARAMICS Simulation Environment Lianyu Chu Henry Liu Michael McNally Will Recker California PATH Research Report UCB ITS PRR 2005 12 This work was performed as part of the California PATH Program of the University of California in cooperation with the State of California Business Transportation and Housing Agency Department of Transportation and the United States Department of Transportation Federal Highway Administration The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein The contents do not necessarily reflect the official views or policies of the State of California This report does not constitute a standard specification or regulation Final Report for Task Order 4304 April 2005 ISSN 1055 1425 CALIFORNIA PARTNERS FOR ADVANCED TRANSIT AND HIGHWAYS Final Report for TO 4304 Development of the Capability Enhanced PARAMICS Simulation Environment Lianyu Chu Henry Liu Michael McNally Will Recker California ATMS testbed University of California Irvine Irvine CA August 2004 ACKNOWLEDGEMENTS Scott Aitken and Ewan Speirs from Quadstone in Scotland provided invaluable technical supports in the process of applying the PARAMICS model Their continuous collaboration to the project gre
46. INEA algorithm Calibrated parameters Calibrated values Location of downstream detector station 60m Desired occupancy 18 Update cycle of the metering rate 30 seconds Regulation parameter Ka 70 veh hour 7 4 2 References 1 Papageorgiou M Hadj Salem H and Blosseville J M 1991 ALINEA A Local Feedback Control Law for On Ramp Metering Transp Res Rec 1320 58 64 2 Papageorgiou Hadj Salem and H Middelham 1997 ALINEA Local Ramp Metering Summary of field Results Transp Res Rec 1603 90 98 73 8 BOTTLENECK ramp metering control The BOTTLENECK algorithm has been applied in Seattle Washington for several years Jacobsen et al 1989 This plugin is to implement the BOTTLENECK ramp metering algorithm in PARAMICS 8 1 Introduction The BOTTLENECK algorithm has three components a local algorithm computing local level metering rates based on local conditions a coordination algorithm computing system level metering rates based on system capacity constraints and adjustment to the metering rates based on local ramp conditions The local metering algorithm employed by the BOTTLENECK algorithm is occupancy control The metering rate for the occupancy control is selected from a predetermined finite set of discrete metering rates on the basis of occupancy levels upstream of the given metered ramp Historical data collected from the given detector station are used
47. NEA Therefore ALINEA algorithm has been integrated in this API The second part is the section information upstream loop and downstream loop are the names of upstream and downstream loop detectors number of influenced ramps is the number of on ramps in the area of influence of this section ramps is the node name of influenced on ramps If there is more than one on ramp please use a space between any two on ramp names reduction factors is the correspondent reduction factors of on ramps specified in the last row number of onramps is the number of on ramp in the section If there is more than one on ramp in the section their names should be specified in the row of onramp loops If there is no on ramp in the section please leave blank nothing in the row of onramp loops number of offramps is the number of off ramps in the section If there is more than one off ramp in the section their names should be specified in the row of offramp loops Otherwise leave blank nothing number of unmetered ramps is the number of un metered on ramps in the section If there is more than one un metered on ramp in the section their names should be specified in the row of unmetered ramp loops Otherwise leave blank desired downstream occupancy is the occupancy threshold of the downstream loop detector station The third part of the file is the entrance ramp part If a queue detector is specified the queuing strate
48. P CLOSURE 1 if RAMP ON with single entry metering 2 if RAMP ON with platoon metering and 9 if RAMP OFF void uci_ramp_set_parameters RAMP ramp Bool parameter Function Setting a new metering rate to a specific ramp meter Return Value None Parameters ramp stores the new metering control data of a specific on ramp status is a Boolean value parameter TRUE means to set a new metering rate based on an external algorithm parameter FALSE means to restore the default time of day timing plans 58 float uci ramp get tod rate char rampnode Function Querying the current time of day metering plan of a specific ramp meter Return Value The current time of day metering plan of an on ramp signal TOD rate 0 ramp off TOD rate 1 metering off others metering rate Parameters rampnode is the name of an on ramp signal node 5 4 2 How to use interface functions in other plugins These interface functions can be called in other plugins The following setting is required 1 In the workspace of your plugin that wants to use these interface functions specify the library file controller lib of the actuated signal plugin as an input object library module The path of ramp controller lib should be specified as well 2 Specify the prototype of the interface function at the beginning of your plugin as follows _ declspec dllimport void uci ramp set parameters RAMP ramp Bool parameter _ declspec dllimport
49. Y 29 99S 8 04 gt 2 0 4 998 JZ 2 t 0v 2 295 29 p O 4 2 8 O 08S p 295 Qp 9 04 9 04 ve 7 8 295 e 02 29 095 99 gt O 9 9 9 9 295 9 295 9 gt 4 0E 1 0L L YWAN 295 7 01 E 095 gt O S 0 YOO D 2201 OL UIOd 4 Detector Data Aggregator 4 Introduction PARAMICS can output two types of loop detector data for analysis Point loop data including flow speed headway occupancy and acceleration of a vehicle and e Link loop data including flow average speed density lane use and lane changing on a link Point data is gathered at every time step when an individual vehicle passes over the loop link data analyses the traffic data over a link where loops locate at a user defined time period However many Advanced Traffic Management and Information Systems ATMIS applications demand point traffic data but in an aggregated manner over user defined time intervals e g 30 seconds The objective of this plugin is to emulate the outputs of real world data collection from induction loops in PARAMICS It is implemented through gathering point loop data at each time step of simulation and then aggregating at any time interval specified by users The gathered data can be raw data or smooth
50. a long time simulation run and then check if there are any serious congestion happened at actuated signal intersections If an actuated signal control is not working correctly all input files need to be double checked for any mistakes The correct use of this plugin depends on your knowledge of signal control If necessary please have a look at related chapters in the textbooks 11 1 3 8 Exercises In APPENDIX Section 1 7 1 7 2 and 1 7 3 show the Signal Timing Chart and Geometric layout of the intersection ICD amp BARRANCA Based on Section 1 2 2 we filled in the worksheet shown in 1 7 4 Based on this worksheet the signal control information is shown in Section 1 3 4 Its priorities information is shown in 1 7 5 This plugin can be used to model more complex actuated signal control through proper configurations of the priorities and signal control information Users can learn more from one of our example Irvine networks which includes 37 actuated signals 1 4 Working with different phasing sequences In dual ring operation full actuated signal controllers are capable of a number of phase sequences between barriers For each of the two major phase groups there are three basic phase sequences 1 Left turn first 2 Lead leg left turns and 3 Through movement first The developed full actuated signal plugin can work with all three sequences We have described how to work with the left turn first cas
51. ach section needs to define an area of influence that consists of a number of upstream 74 on ramps for the volume reduction The amount of volume reduction from an on ramp is determined by a weighting factor pre defined according to how far it is to the downstream detector station of the bottleneck section and the historical demand pattern from the on ramp If on ramp involves in the volume reduction of any bottleneck section its system level metering rate is calculated as r 0 Q Gt 71 7 MAX O ist WF EWF 5 where MAX is defined as the operator of selecting the maximum volume reduction if the on ramp is located within more than one section s area of influence Q j t 1 is the entrance volume from on ramp j during the past minute WF is the weighting factor of on ramp j within the area of influence for section i Q i t e VF WF is the j reduction volume reduction of on ramp j because of section 7 The more restrictive of the local rate and the system rate will be selected for further adjustments including queue adjustment ramp volume adjustment and advanced queue override The queue adjustment and advanced queue override are used for preventing traffic spillback onto arterials Ramp volume adjustment copes with the condition that more vehicles have entered the freeway compared to the number of vehicles assumed to enter which may be caused by HOV traffic or HOV lane violators The metering
52. and SWARM 2b We provide a brief description of these three algorithms below Details about them can be found in the listed references 9 1 1 SWARM I SWARM 1 forecasts the traffic state at predetermined problem points bottlenecks and adjusts metering rates based on forecasts It treats the freeway network as sections Each section is defined as the two adjacent detectors that have reliable data outputs The operation of SWARM 1 is based on traffic density with the goal of maintaining real time density below a pre determined saturation density for each section of freeway The linear regression and a Kalman filtering process are applied to pass detector data to forecast a density trend at each detector location for each control interval The time into the future to forecast is a tunable parameter named 7 Once the forecast density trend is obtained it can be combined with Tcrit to calculate the excess density the portion above the saturation density in the following Figure 1 Excess density 15 used to calculate the target density for the next metering cycle Target Density Current Density 1 Tcrit Excess Density Then the volume reduction at each detector is Volume Reduction Local Density Target Density 83 Number of lanes Distance to next Station These volume reduction values are then distributed to upstream ramps within the defined area of influence for each site using pre defined weighting factors at
53. ation density For each mainline VDS Collect enough VDS data in one day If enough VDS data SAMPLE SIZE SAT DENSITY Calculate the saturation density for the VDS SWARM 2a For each on ramp Starting from the furthest downstream ramp on the freeway Calculate station speed at upstream loop station ft sec Calculate time headway from upstream loop to downstream loop Calculate the speed reduction per mile Calculate the desired metering rate Minimum rate control Maximum rate control Rate smoothing Startup shutdown strategy SWARM 2b 85 For each on ramp on freeway Starting from the furthest downstream ramp on the freeway 1 Calculate estimated storage in the storage zone based on density values of upstream and downstream loop stations Calculate volume change of the storage zone Calculate cumulative storage Calculate storage within a zone Calculate critical storage Calculate maximum available capacity Calculate desired available capacity Calculate metering rate for this ramp Minimum rate control Maximum rate control Rate smoothing Startup shutdown strategy j Kalman Filtering 1 For each bottleneck ramp 1 Update observations Time update Measurement update Forecast the density ahead oftime FORECAST LEAD TIME j j Determine local max as the upper limit of calculation of SWARM 41 rate Based on the metering mode such as SWARM 2A 2B Traffic apportionment 1 If excess volume at a bottleneck Assign des
54. atly facilitated the work We would like to thank Steve Hague of Caltrans Headquarter Traffic Operations for his supports and comments on our development ii EXECUTIVE SUMMARY This report summarizes research work conducted under TO4304 at the University of California Irvine Under this task order the research team provided Caltrans with on call direct support technical guidance and research related support A series of Paramics plug ins were developed and have been released to Caltrans These plug ins include actuated signal multiple actuated signal timing plan actuated signal coordination detector data aggregator ramp metering control on ramp queue override control ALINEA ramp metering control BOTTLENECK ramp metering control SWARM Ramp metering control and Freeway MOE They complement the current Paramics simulation model and enhance its functionalities This report describes how we developed these plug ins and the step by step procedure to use them It can be used as user manuals iii Table of Contents BCRNOWLEBDGEMENTS casae e nea ERR REESE NE de ne nee ii EXECUTIVE SUMMARY iii Table of Contents teen eec eme even pride t t Unt dd fate a ue ed ua eo iv 1 Actuated signal C OBDEOL a deo eo tete eed te e etse uli astu e atus 1 1 09 M D 1 1 2 implementatiQ i cse p eet creer aeneae erp aede eet qii
55. c phases The sync phase has minimal bandwidth i e the sync phase has to start at the time of minimal bandwidth earlier than yield point 4 Force Off To do so all other phases have to be cut at certain points which are so called force off points These force off points are usually referenced to the local clock reference point 3 3 2 Data requirement 37 As the actuated signal API two files need to be prepared for the use of signal coordination API One is the priorities file provided by Paramics to be used to identify the hierarchy of movements for all phases The other is the so called signal coordination control file which contains all the signal timing information intersection layout information and coordination information The following is an example of the part of signal coordination control file for one intersection total number of actuated signals is 4 node 6 ALTON amp ICD movements 1 2 3 4 5 6 7 8 ini green 5 5 5 5 5 5 5 extension 3 5 3 5 3 5 3 5 max_green 24 60 24 32 24 32 24 32 recall 2 6 lanes 2 3 2 3 2 3 2 3 rightturn 1 1 1 1 detector1 aisw ai2w ai3w aiuw detector2 aiss ai2s ai3s aius detector3 aise ai2e ai3e aiue detector4 aisn ai2n ai3n aiun sync phase 2 6 cycle length 60 force off 36 60 18 27 36 60 18 27 yield point 5 system clock 0 The data for signal coordination has been attached after the intersection layout data for each intersection Besides to the yield point o
56. control file 8 4 Technical Supports 8 4 Calibration of BOTTLENECK algorithm Basically the calibration of the BOTTLENECK algorithm involves five aspects 1 Calibration of local algorithm If ALINEA 15 used its calibration requirements have been described in Section 6 if occupancy control is used its calibration involves the analysis the allowed traffic flow from on ramps and mainline occupancy based on a plot of historical volume occupancy data collected at its correspondent mainline loop detector station 2 Defining each section in the study network basically the stretch of freeway between two adjacent mainline loop detector stations The typical spacing of two adjacent loop detector stations is to 1 mile 3 Calibrating the threshold occupancy of the downstream detector station of each section based on the volume occupancy diagram at the downstream loop detector station of each section The typical threshold occupancy is the occupancy at capacity 81 4 Defining the area of influence of each section including several upstream on ramps that are responsible for the volume reduction according to how far it is to the downstream detector station and the historical demand level of the on ramp A typical definition is that entrance ramps in the area of influence should be within a maximum distance of two miles to the location of the downstream detector of the section 5 Defining the weighting factor of each on ramp in
57. d at a location near the start or the end of a link 2 More than one vehicle are on a loop at the same time 45 3 One vehicle stays over a loop for more than certain time period which may happen when an incident or congestion appears 4 One vehicle is just on a loop at the time of aggregation 3 At every time step PARAMICS overload API function net action For detector 1 n 1 If it is the time to calculate and report the aggregated data of a loop 1 Calculate count average speed and percent occupancy of a detector Calculate grouped count occupancy and speed of all detectors at a detector station Output these data to output files and the interface function j j 4 3 Step by step user manual 4 3 Preparation of the loop control file loop control is the input file of the loop data aggregator plugin This file should be put to the same directory as any other network files An example of Joop control file is shown as follows detector count 42 report cycle 30 activation time 06 00 00 deactivation time 10 00 00 gather smoothed data no output to files yes name 405n0 6ml gather interval 00 00 30 name 405n0 93fr gather interval 00 00 60 There are two parts in the file The first part is the general information about data aggregation 1 The first row of the file shows the number of detectors that are required to do the aggregation operation 46 2 The second row specifies the polling report cycle
58. detector is equal to the length that a demand detector can cover 5 2 3 Control logic The ramp signal generally provides two indications green and red Based on the time of day metering rate the metering cycle can be calculated as cycle 3600 rate If one car per green is applied we assume the green time a vehicle needs to pass the metering signal is 2 seconds If two car per green is applied we assume the green time for two vehicles to pass the metering signal is 4 seconds Then the length of red signal is red cycle green If there is no demand detector or check in detector metering signal will show red and green based on the above red and green time This guarantees that vehicles are released from ramp to the mainline freeway at a fixed ramp metering rate If there is a demand detector or check in detector every vehicle has to stop before the stop lane waiting for the green signal The detector for sensing the presence of a vehicle allows the signal to rest in red avoiding potential confusion to a driver approaching the signal due to the short greens The following three principles are used for metering signal control 1 If the length of red signal is longer than red and the demand detector has detected the presence of a vehicle waiting the green signal will be given with the length of green 2 If the length of red signal is shorter than red green signal will not be given even there are waiting vehicle
59. e detector is located at the upstream end of the entrance ramp used for detecting the excessive queue length in order to avoid interference with the arterial traffic The ramp HOV detector is used for counting the number of carpool vehicles entering freeway from entrance ramps 51 Mainline Station lt Passage Demand Queue Figure 5 1 Typical ramp metering configuration in the real world Mainline Traffic Figure 5 2 Typical ramp metering layout in Paramics 5 2 2 Modeling vehicle detection This plugin is designed to implement the pre timed metering control The plugin can work with or without detectors Due to a legacy issue the plug in only supports the use of check in detector or demand detector in the actuated ramp metering case The simplified layout of ramp metering system is shown in Figure 5 2 The check in and check out logic of the real world ramp metering system needs accurate detection of passing vehicles However in an older version of Paramics detectors cannot be used to accurately detect traffic This 1s the reason we did not use the check out detector in the plug in 52 The length of the demand detector 15 based on the real world design of ramp meter Based on the design manual of Caltrans District 11 typically uses 4 demand loops Districts 3 4 6 8 typically use 3 demand loops Districts 7 12 typically use 2 demand loops As a result the length of the demand
60. e furthest downstream ramp on a freeway is input first mainline detector is the corresponding mainline detector of a ramp postmile can be obtained from Caltrans which is a basic input of SWARM In general a ramp s postmile is the same as the postmile of the corresponding mainline detector of the ramp upstream ramp and apportionment factor are used for metering rate apportionment the second part of the SWARM 1 algorithm metering mode can be one of has the following DISABLED MODE SWARM 1 SWARM 2A SWARM 2B SWARM 1 2B SWARM 2A 2B SWARM 1 2A SWARM 1 2A 2B LOCAL TOD and LOCAL LMR 9 ramps should be included in swarm control If it is a freeway to freeway or unmetered ramp the metering mode can be set as DISABLED MODE minimum rate control is one of the following two TABLE MIN ABS MIN default rate control is one of TOD TABLE DEFAULT and ABS MAX swarm startup strategy is one of RUN SWARM ANYTIME and RUN SWARM DURING TOD ONLY 9 3 5 Loading plugin The plugin files includes two files swarm dll Modeller Plugin swarm p dll Processor Plugin The SWARM plugin depends on other two plugins ramp metering control and loop data aggregator These two plugins should be specified earlier than this plugin in the plugins or programming file i e loop agg dll ramp controller dll swarm dll If you want to implement SWARM with a queue ove
61. e given to that phase which has no movement allowed Then the plugin may be locked to that phase The solution is that you can repeat the movement information of a related phase Please refer to Section 1 4 3 1 6 3 Tools In order to speed up the process of coding actuated signals we also make two computer programs for the making of signal control file and the priorities information You can request these tools from California ATMS testbed 1 6 4 References 1 W R McShane Roess and E E Prassas 1998 Traffic Engineering Second Edition Prentice Hall 2 Liu X Chu L and Recker W 2001 Paramics API Design Document for Actuated Signal Signal Coordination and Ramp Control California PATH Working Paper UCB ITS PWP 2001 11 University of California at Berkeley 3 USDOT Federal Highway Administration 1996 Traffic Control Systems Handbook 23 1 7 APPENDIX 1 7 1 Worksheet Location Signal ID approach Direction approach approach Dr D S H o i H Movement 1 2 3 4 5 6 7 8 Initial Green Extension Max Green Recall Phase Lanes Right Turn lanes Detector 1 Detector 2 Detector 3 Detector 4 1 7 2 Signal Timing Chart Pad 8 YHON 17 unos unos 11 YHON vau SWA v jo 1 obed NYHL AM E LX3 9958 T AQV 8M LX3 36557 AGV 83
62. e in the previous section This section will discuss how to make the plugin to work under the second and third phase sequences Please refer to the example networks for further understanding this section 1 4 1 Lead leg left turns The layout of a typical intersection is as shown in Figure 1 8 In the signal control file the two phases on the lead leg need to be put to the columns of movement 1 and movement 5 If we want to make link 14 10 as the lead leg the phase sequence will be 2 amp 5 gt 1 amp 5 gt 2 amp 6 gt 1 amp 6 the corresponding signal control file needs to be configure as follows Movements 2 1 3 4 5 7 8 ini green 10 5 5 8 5 10 5 8 extension 4 3 3 5 3 3 5 max green 32 24 24 32 24 32 24 32 recall 4 8 lanes 2 2 2 3 2 2 2 3 rightturn 1 1 1 1 The real world controller may not have the phase combination of 1 amp 5 Our plugin cannot avoid having it But its existence does not have any negative but positive influence on the operation of the control logic 12 detector1 icbsw N A N A icbuw detector2 icbss N A N A icbus detector3 icbse N A N A icbue detector4 icbsn N A N A icbun 4 7 6 a 2 8 Figure 1 8 Phase layout of a signalized intersection Based on phase sequences 2 amp 5 gt 1 amp 5 gt 2 amp 6 gt 1 amp 6 the priorities file needs to put 2 amp 5 to phase 1 1 amp 5 to phase 2 2 amp 6 to phase 3 and 1 amp 6 to phase 4 actions 10 phase offset 0 00 sec phase 1 0 00 max 1
63. e metering control at specified on ramps 57 This plugin can work if ramp control and priorities are prepared correctly If any mistakes occurred in the ramp control file the plugin will be disabled The report window of PARAMICS will show whether this plugin works If the metering control does not work or does not work as you expected you may need to check if there is any error in the control file This plugin generates file named Log ramp txt under the network directory which can be used for this purpose 5 4 PROGRAMMER capabilities 5 4 1 Interface functions There are three interface functions used for querying current and time of day metering rate and setting a new metering rate An advanced ramp metering algorithm plugin can be developed based on them Their prototypes are shown below RAMP uci ramp get parameters char rampnode Function Querying the current metering plan of a specific ramp meter Return Value The current metering plan of an on ramp signal may not be TOD plan Parameters rampnode is the name of an on ramp signal node RAMP is the structure of ramp control data whose definition is typedef struct Ramp data RAMP struct Ramp data on ramp signal node name and its location char node char name ramp control types and parameters int type int cycle Where controlType is the status or type of the ramp metering control which can be 0 if RAM
64. e on ramp volume You can use the demand detector 1 e check in detector which is installed to the network for the vehicle presence in the ramp metering plugin If you want to implement ALINEA with a queue override strategy you may need to add a queue detector Please see the document of on ramp queue control plugin for how to use that plugin and how to add a queue detector 7 3 2 Preparation of the alinea control file The control file includes all necessary information required by this ALINEA plugin Some of inputs should be calibrated based on the modeled network before implementation An example of the file is as follows 68 total number of alinea controlled ramps 15 7 checking control file metering rate update interval algorithm activation time algorithm deactivation time report metering rate ramp mainline detector on ramp detector HOV control type desired occupancy regulator rate restriction ramp mainline detector on ramp detector HOV control type desired occupancy regulator rate restriction ramp mainline detector on ramp detector HOV control type desired occupancy regulator rate restriction yes 30 06 00 00 09 00 00 yes 33 405n0 93ml ds 405n0 93orb 0 1 0 13 70 0 300 1200 95 405n5 55ml ds 405n5 55orb 1 1 0 20 70 0 240 900 92 405n5 74ml ds 405n5 74orb 0 1 0 20 70 0 400 1500 metering rate update cycle is the time interval of mete
65. easurements 0 02 0 5 range 0 02 to 0 5 precision 2 1 0 Variance representing the inaccuracy of the model 0 5 10 range 0 5 to 10 precision 1 The fourth part includes parameters of apportionment algorithm used in the SWARM 1 algorithm 1 0 Fraction of excess traffic to propagate within a section 0 0 1 0 range 0 0 to 1 0 precision 1 0 85 Fraction of excess traffic to propagate between sections 0 0 1 0 range 0 0 to 1 0 precision 1 The fifth part includes parameters of the SWARM 2a algorithm 1 0 Target speed reduction 0 1 20 0 range 0 1 to 20 0 precision 1 The sixth part includes parameters of the SWARM 2b algorithm 0 1 Smoothing factor for the final storage computation 0 0 1 0 range 0 0 to 1 0 precision 2 0 85 Fraction of saturation density equivalent to LOS D 0 0 1 0 range 0 0 to 1 0 precision 2 The seventh part includes parameters of Phase 2 failure management used to decide if the detector data at a detector station can be used in SWARM 0 66 Fraction of good lanes required for station statistics 0 0 1 0 range 0 0 to 1 0 precision 2 The eighth part includes parameters of the startup and shutdown strategy 6 Start metering counter 1 20 range 1 to 20 precision 0 20 Stop metering counter 1 30 range 1 to 30 precision 0 89 The parameter in the last part is not a parameter of the real world SWARM but a parameter of the SWARM in the simulation world 1 Using speed estimation
66. ector2 icbss N A N A detector3 icbse N A N A detector4 icbsn N A N A The corresponding priorities file is actions 10 phase offset 0 00 sec phase 1 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 14 major qo qo 32 19 from 13 to 12 major from 13 to 11 major from 11 to 14 minor from 14 to 12 minor from 12 to 13 minor phase 2 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 14 major from 13 to 12 major from 13 to 11 major from 11 to 14 minor from 14 to 12 minor from 12 to 13 minor phase 3 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 14 major from 13 to 12 major from 13 to 11 major from 11 to 14 minor from 14 to 12 minor from 12 to 13 minor phase 4 0 00 max 100 00 red phase 0 00 fill all barred except from 14 to 11 major from 14 to 12 major from 14 to 13 major from 11 to 14 minor from 13 to 11 minor from 12 to 13 minor phase 5 0 00 max 100 00 red phase 0 00 fill 20 all barred except 1 5 PROGRAMMER capabilities 1 5 1 Interface functions Interface functions have been provided by this plugin for external modules to acquire and change the default timing plan This plugin provided a couple of interface functions for external plugin modules to acquire the current signal timing plan and set a new timing plan to a specific signal An advanced signal contr
67. ed data in term of user s choice Aggregated loop data including volume occupancy and speed can be output to text files and can be also accessed by interface functions defined in this plugin Although Paramics has a loop data aggregation plugin coming with the package we found it is not convenient for us to further develop some traffic control algorithms using APPI programming Table 4 1 is a comparison of the loop data aggregator plugins of Quadstone and UCI Table 4 1 comparison of the loop data aggregator plugins of Quadstone and UCI Quadstone ATMS testbed UCI Measurements flow count speed gap occupanc count occupancy speed Occupancy output Time occupancy Percent occupancy Output files A file only includes lane s data Grouped data and lane the grouped data Too many files will based data are in the same be opened file for a detector Restriction There are restrictions on the total No restriction on the number of files to be opened in number of files to be Paramics Problems may occur when opened users want to collect aggregated data for many loop detectors Programming Programmer users can use data in the Full supports of advanced There is another MYSQL version of Loop Data Aggregator plugin MYSQL database is used for storing aggregated loop data All aggregated loop data since the beginning of simulation can be accessed through querying the database 43 ca
68. ement 1 and movement 5 As shown in the below figure if we want phases 2 and 6 go first the following phases will be 2 amp 6 gt 1 amp 6 gt 2 amp 5 gt 1 amp 5 The signal_control file should be movements 2 1 ini_green 10 5 extension 3 max_green 32 24 recall 4 8 lanes 2 2 rightturn 1 1 detector1 icbsw N A detector2 icbss N A detector3 icbse N A detector4 icbsn N A icbuw icbus icbue icbun 5 7 8 5 5 8 3 3 5 24 24 32 2 2 3 For the priorities file we can just put 2 amp 6 1 amp 6 2 amp 5 and 1 amp 5 to the phase 1 2 3 and 4 as shown below actions 10 phase offset 0 00 sec phase 1 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 11 major from 13 to 14 major from 14 to 12 major from 14 to 13 major from 11 to 14 minor from 12 to 13 minor phase 2 15 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 11 major from 13 to 14 major from 13 to 12 major from 11 to 14 minor from 14 to 12 minor from 12 to 13 minor phase 3 0 00 max 100 00 red phase 0 00 fill all barred except from 14 to 11 major from 14 to 12 major from 14 to 13 major from 11 to 14 minor from 13 to 11 minor from 12 to 13 minor phase 4 0 00 max 100 00 red phase 0 00 fill all barred except from 13 to 12 major from 14 to 11 major from 11 to 14 minor from 13 to 11 minor from 14 to 12 minor from 12 to 13 minor phase 5 0 00 max 100 00 red phase 4 00 fill all barred except 1
69. end con dete 1 13 Step bysstep user MANUAL a t rogas Pe re oia dritto emit dus 5 1 4 Working with different phasing 12 1 5 PROGRAMMER capabilities iei os nerven te ertet Aaa oet e p 21 T 6 Technica Supports i epa Geri beca diera 22 I 7 APPENDIX qu nectit agis quiate eu 24 2 Multiple Actuated Signal rrt 32 PR introductio rM 32 2 2 Plug in cae mr d e arden UNO YE a He 32 2 3 Step by step al e ea oe e o esie e e mete odia em ace NR de dpa ee 32 3 Actuated signal Coordination Qe esed teas ROB aga Duce SPON eas det 35 EX MEO ACTION c RE 35 2 2 PIugimommiplementation ee papas in 35 3 3 Step by step user manual ice eds een er reds er re en ra ea 37 4 Detector ecce e ee cla dda aude ERN netu y ite e A e 43 4 aso obvia E a RH ERU Ea queis e eA ERR 43 4 2 Plugin implemen tat Otis eee d e os Re e CR E 44 4 3 Step by step user manual s uos ooi ee ton depre rae ciun e etta de ep NR 46 4 4 PROGRAMMER capabilities tela verse 49 5 Ramp metering Control use eee to eee itae edt tt qure esee ond ed dre 51 E Bruce ii ento MER H M 5 5 2 P
70. ering controller developed in PARAMICS API is required for the support of development of adaptive ramp metering algorithms which have more complicated control logics The ramp metering controller should provide interface functions that can be used for querying the old metering rate and setting a new metering rate based on the adaptive ramp metering algorithms When the adaptive ramp metering algorithm is not activated the pre timed metering will be the default control 2 In priorities file the two phases of ramp signal node has the input of max 18 00 will this setting affect meters controlled by this plugin Please do not use a maximum lower than 26 seconds The reason is described in Section 5 3 3 Our recommended value is 30 00 3 How 15 this plugin used by advanced ramp metering algorithms This plugin is the ramp metering controller of any advanced ramp metering algorithm such as ALINEA or BOTTLENECK This plugin provides current metering rate and sets a new metering rate based on the request of the advanced algorithm If an advanced algorithm is associated with an entrance ramp more detectors such as the queue detector HOV detector on ramp detector might be required 60 6 On ramp queue override control 6 1 Introduction The effect of ramp metering is that not all the vehicles can enter freeway from a meter and thus a waiting queue will be formed at the entrance ramp If the queue exceeds a certain leng
71. ers can start the first simulation run with the SWARM control with a series of assumed saturation values Then you can check the Log sat density file under Log directory which is used to record the saturation density values of all mainline loop detector stations in the network calculated based on the second degree polynomial method The value in the column of new sat might be a better value of saturation density that can be used to replace your assumed values 9 4 Technical Supports 9 4 1 Limitations of this plugin 1 Failure management SWARM in the real world considers the situation that loop detector data are missing or deficient However in the simulation world detector data are obtained based on another plugin module loop data aggregator which provides aggregated detector data as accurately as possible As a result this developed SWARM plugin works with good loop detector data all the time The failure management part of SWARM never has chance to be used 2 Queuing strategies Based on the design document of SWARM the central SWARM system will have four options about queuing control 1 Use local controller strategy i e when a queue is detected go to maximum rate 2 Gradually increase rate to maximum 3 Ignore queuing for a fixed number of periods then switch to gradual rate increase 4 Totally ignore queuing However the source code shows that there are only two options using the local strategy and disable queue s
72. eyond the on ramp signal Figure 9 2 shows the typical loop detector configuration at an on ramp For the current section entrance ramp is yes 10 2 2 Loading plugin This plugin has two files freeway moe dll Modeller Plugin freeway moe p dll Processor Plugin After the completion of the freeway control file you can load the simulation network together with this plugin Run simulation and then you will see that this plugin generate output files continuously 10 2 3 Output file The name of the output file of this plugin is moe freeway txt It can be found in the subdirectory 100 network Log run xxx where network is the name of the current working directory and xxx is a three digit sequence number The format of the output file is as follows 405n0 93ml 405n5 55ml time vol mean tt tt std spd spd std delay tot delay 06 05 00 9 2480 17 9 68 9 5 0 0 0 0 0 06 10 00 75 249 0 18 1 68 7 4 9 0 0 0 0 06 15 00 72 250 6 16 4 682 44 0 0 0 0 06 20 00 76 254 8 20 7 67 2 5 5 0 0 0 0 Where time is the report time which is the end time of a collection period vol is the number of vehicles having been traced in last collection period mean tt and tt std are the average travel time and its standard deviation of all traced vehicles in a time period Accordingly spd and std are the travel speed and its standard deviation of all traced vehicles delay is defined as the difference be
73. f the sync phase all other phases have force off points referenced to the local clock reference point Notice that the maximal green time of primary sync phase has to be the cycle length since the green time of sync phase may occupy the entire cycle if there is no conflict traffic 3 3 3 Example 38 Phase Interval Times Interval Phase 1 2 3 4 5 6 7 8 Wak o J PedClear Initial 1 6 14 6 8 9 10 6 10 Yellow Eme 0 JU ons MexReal E ESI PedReal j tagPhase j 39 OV 0 490 2 ajoAD lenlu VIN3N lt eseug ou S 0 1ulog E20 pI IA 0 490 2 99S 69 pL 79 095 9 8p S8 OCL Od 8 OH 01 8 gt OH 99S CL 29 21 ZO 4 9 OH 99S JI VV Vv 295 p 295 0p OO 4 2 8 OH e oK2 punoJu6xoeg o Lele 295 9 gp G OCL v OS 295 GG gp 8 9 F O2L O J 295 Gp gp G 8 7 9 v OZlL gt lL OS Uipwpueg YWAN 0 SOUBIBJOY 90J2 E20 pIelA oesep Z 9 Od 0 4 yOoUD 0 1utog YOO D 298 90952 O4 9 O4 09562
74. fined in Table 2 4 4 2 How to use interface functions in other plugins The interface functions can be called by other plugins The following setting is required 1 In the workspace of your plugin that wants to use the interface function specify the library file loop agg lib of this plugin as an input object library module The path of loop agg lib should be specified as well 2 Make sure that loop aggregator plugin is specified before the plugin that will use the interface function in the plugin file V3 located in plugins windows under the PARAMICS installed directory or the programming file V4 located at the network directory 3 Specify the prototypes of interface functions at the beginning of your plugin _declspec dllimport LOOPAGG uci loop agg int index _ declspec dllimport int uci loop agg interval void _ declspec dllimport Bool uci loop aggregation char name 50 5 Ramp metering control 5 Introduction There have been a number of strategies to release vehicles into the mainline freeway traffic each with different demands on sophistication of control and detectorization Caltrans currently has three ramp metering systems SATMS SDRMS and SJRMS AII of them use the 170 type controllers as hardware SATMS SDRMS and SJRMS are names of their software algorithms installed in the 170 controller This plugin is designed to model pre timed ramp metering control on n cars per green basi
75. g meteringRate and Log sat density They can be found in the subdirectory network Log run xxx where network is the name of the current working directory and xxx is a three digit sequence number The contents of these files are dynamically saved Users can check the progress and condition of the SWARM control during the simulation process 1 Log meteringRate Log meteringRate used to record the metering rates of all on ramps during operation with the interval of metering rate update interval defined in swarm control For example RAMP 07 25 30 07 26 00 07 26 30 07 27 00 07 27 30 07 28 00 07 28 30 07 29 00 07 29 30 07 30 00 07 30 30 07 31 00 N O N nN OOD O O gt 36 3 e e 0 0 0 0 0 Uta tA 1 1 28 0 gt gt Cn tA tA ore WW WW WwW BR wD gt ooocoo oooereee CA Cn CA 0 0 0 0 0 0 0 pe 93 07 31 30 10 10 150 150 151 10 10 300 07 32 00 10 10 150 150 151 10 10 300 07 32 30 10 10 100 100 151 10 10 300 For each on ramp there are a metering rate and a queue override flag outputs The unit of
76. gy is involved in BOTTLENECK queuing strategy is required by BOTTLENECK If there is no queue detector or no queuing strategy involved in ramp metering please specify as N A If the specified detector cannot be found in the detectors file a warning message will be given and the entrance ramp will be operated without any queue strategy If ALINEA is specified as the local algorithm in the first part of the file please fill in the rows of desired occupancy and regulator and leave rows of metering level occupancy threshold and metering cycle blank If CCUPANCY CONTROL is the local algorithm please fill in the rows of metering level occupancy threshold and metering cycle and leave rows of desired occupancy and regulator blank 78 The following is an example of the use of OCCUPANCY CONTROL as the local algorithm The example of the use of ALINEA CONTROL as the local algorithm is shown in last example local algorithm OCCUPANCY CONTROL total number of entrance ramps is 7 ramp 33 mainline detector 405n0 93ml queue detector 405n0 93orspill on ramp detector 405n0 93orb HOV 0 control type 1 rate restriction 240 900 desired occupancy regulator metering level 6 occupancy threshold 0 15 0 17 0 20 0 25 0 40 metering cycle 4 0 5 0 7 0 9 0 12 0 15 0 8 3 3 Loading plugin This plugin has two files bottleneck dll Modeller Plugin bottleneck p dll Processor Plugin The
77. he HOV lane if applicable Lane is the outside lane the rightmost lane The unit of the speed output is miles per hour The percent occupancy value is show in the format of 0 094 which represents the percent occupancy of 9 4 Figure 4 1 shows an example of the output file 405n0 6ml txt Notepad 1 B x File Edit Format View g_vol g_oce g_spd voll occi spdi vol2 occ2 spd2 13 occS spd3 vold occ4 35 0 062 73 3 7 0 042 80 8 90 059 74 5 110 077 73 2 8 0 069 48 0 094 72 3 90 055 77 6 120 076 75 5 150 129 71 0 120 115 610 112 71 1 160 100 76 5 14 0 091 73 8 180 146 70 3 13 0 112 46 0 090 70 6 78 7 150 098 73 6 170 125 68 2 8 0 038 63 0 132 68 4 75 8 190 132 72 8 180 145 67 2 15 0 185 55 0 112 66 6 75 1 180 130 68 4 17 0 157 64 0 12 0 108 55 0 103 70 9 78 4 16 0 108 72 2 16 0 126 67 5 10 0 097 53 0 100 71 1 789 5 170 117 71 4 160 154 70 0 11 0 085 54 0 113 68 6 77 5 12 0 077 74 1 18 0 176 65 5 15 0 142 51 0 091 71 3 79 4 16 0 106 73 7 19 0 142 68 7 3 0 071 52 0 097 71 5 78 4 14 0 099 73 9 170 149 67 1 6 0 043 54 0 094 70 3 77 2 17 0 111 74 7 15 0 108 68 5 11 0 087 53 0 118 70 5 78 8 120 085 74 2 200 167 70 4 15 0 148 66 0 124 70 6 75 5 21 0 140 73 0 200 157 70 3 11 0 112 50 0 104 70 2 75 0 13 0 085 74 8 170 143 69 1 11 0 131 65 0 123 69 9 76 9 180 118 74 7 21 0 165 67 3 14 0 134 53 0 104 71 1 75 8 17 0 115 73 2 190 157 68 9 10 0 081 66 0 133 68 5 79 2 20 0 135 72 6 220 200 61 7 10 0 110 61 0 117 70 0 75 5 140 094 73 2 190
78. ignal dll If this plugin is stored to a directory other than the root directory of PARAMICS the path of the loaded plugin needs to be specified Program Files ParamicsV4 uci plugins Wactuated signal dll Note PARAMICS thinks this plugin is in Drive C only If you put this plugin to Driver D or others PARAMICS will not find the plugin If you prefer to put this plugin to Driver D or others you have to use the way of version 3 of PARAMICS to load plugins 1 3 7 Error checking After the network and the plugin are loaded in Modeller you can start simulation Via GUI you will see that this plugin emulates the actuated signal control at specified intersections This plugin can work if signal control and priorities are prepared correctly If there is any mistake in the signal control file the plugin will be disabled The report window of PARAMICS will show whether this plugin works This plugin generates a file named Log signal txt under the network directory which can be used to check if the signal control file has been understood by this plugin correctly The detector information in the signal control file is connected with the priorities information of the signal intersection The mismatch of them may cause the signal work abnormally Two methods can be used to judge if the actuated signal control has the correct logic 1 Based on the observation from GUI Node gt Modify junction gt Signal display or 2 Making
79. ined by the stretch of freeway between two adjacent mainline detector stations 8 3 2 Preparation of bottleneck control file The bottleneck control file includes all necessary information required by the BOTTLENECK API Some of inputs should be calibrated based on the modeled network before implementation An example of the file is as follows total number of bottleneck controlled sections 15 13 checking control file no update cycle of metering rate 30 time period to accumulate detector data 60 algorithm activation time 07 00 00 algorithm deactivation time 09 00 00 report metering rate yes local algorithm ALINEA section 1 upstream loop 405n0 93ml downstream loop 405n1 11ml number of influenced ramps 1 ramps 33 reduction factors 1 0 number of onramps 1 onramp loops 405n0 93ora number of offramps 0 offramp loops number of unmetered ramps 0 unmetered ramp loops desired downstream occupancy 0 20 section 13 upstream loop 405n5 74ml downstream loop 405n6 21ml 76 number of influenced ramps 2 ramps 95 92 reduction factors 0 37 0 63 number of onramps 1 onramp loops 405n5 74ora number of offramps 0 offramp loops number of unmetered ramps 0 unmetered ramp loops desired downstream occupancy 0 20 total number of entrance ramps is 7 ramp 33 mainline detector 405n0 93ml queue detector 405n0 93orspill on ramp detector 405n0 93orb HOV 0 control type 1 rate restriction 240 900 desired occupancy 0 20
80. involved in the bottleneck control file should be specified in the loop control file for aggregated data collection In addition the report cycle in the control file should be the same as the metering rate update interval specified in the second row of bottleneck control file For example all relevant loops of ramp 33 needs to be specified in the control file detector count 42 report cycle 30 activation time 06 00 00 deactivation time 10 00 00 gather smoothed data no output to files yes name 405n0 93ml gather interval 00 00 30 name 405n0 93orb gather interval 00 00 30 80 8 3 4 Output file If report metering rate in the bottleneck control file is specified as yes the metering information of all BOTTLENECK controlled ramps will be output every update cycle to a file named moe BOTTLENECK txt It can be found in the subdirectory network Log run xxx where network is the name of the current working directory and xxx is a three digit sequence number 8 3 5 Error checking If there is any mistake in the control file or the input files of the two supporting plugins i e loop data aggregator and ramp metering control this plugin will be disabled The report window of PARAMICS will show whether this plugin works Through enabling the option checking control file in the bottleneck control file you can check if there is any error in the bottleneck
81. ired reduced traffic to related meters Calculate metering rate for related meters Minimum rate control Maximum rate control Rate smoothing Startup shutdown strategy j Check SWARM s start up strategy Find the metering rate based on SWARM s metering mode Queue control is required Implement new metering rate to meters through ramp metering plugin 86 9 3 Step by step user manual The SWARM plugin has three input files 1 swarm global containing global parameters of SWARM 2 vds control containing information of network detector stations and bottlenecks 3 swarm control containing the initial setup of SWARM to the target network Unlike the parser system of PARAMICS which allows flexible grammars the formats of these input files are rigid and thus any problem may cause that the SWARM plugin cannot be loaded As a result we hope users can use the example input files we provide with this plugin as the starting point to make your own input files for avoiding editing problems In order to correctly use this plugin in a target network the infrastructure layout of the target freeway network needs to be obtained from the proper government agency such as Caltrans The infrastructure layout includes the number of lanes and locations of loop detector stations This layout is also the basic information required for network coding in PARAMICS An example of this infrastructure layout can be found in APPENDIX
82. is plugin is an functionality extension of another plugin actuated signal control both these two plugins should be specified in the programming file with the following sequence actuated signal dll multi signal plan dll is developed based on the In order to support multiple signal plans please use another plugin multiple actuated signal plan together with this plugin 33 2 3 3 Error checking If any mistakes occurred in the multi plan signal control file this plugin will be disabled The report window of PARAMICS will show whether this plugin is working 34 3 Actuated signal Coordination 3 Introduction Coordination is a mode of signal operation designed to allow platoons of traffic to form and progress through several signals with minimum stops and delay Where signals are closely spaced and traffic volumes are high coordination of signals is necessary to avoid excessive delay and stops The actuated signal coordination API inherits most parts of full actuated signal API with additional force off logic to maintain the background cycle length and form green band for a particular phase sync phase 3 2 Plugin implementation 3 2 1 Control logic To provide synchronization and maintain the background cycle length all coordinated intersection have the same system clock reference point which is usually the start point of signal coordination plan For the fixed time signal coordination plan there is an offset
83. l help users know what the saturation density is at mainline detector stations In order to update an inaccurate saturation density users need to edit the vds control file manually 9 3 7 Error checking Under network directory a file named Log swarm txt is generated for storing all temporary calculations and outputs of SWARM control This file employs two purposes 1 It can be used to check if there is any problem in the global control vds control and swarm control files 2 It can be used to check if SWARM is operated as expected or if the implementation of SWARM in the target network is proper At each time step the detailed metering rate calculations including SWARM 2a SWARM 2b SWARM 1 recorded Since this file is saved to the network directory the file is generated based on the latest simulation run 9 3 8 Fine tuning parameters of SWARM There are many parameters in SWARM During the testing process users can modify all parameters A parameter or the combination of a set of parameters may be appropriate for a network but may not be appropriate for another network 95 Some performance measures are needed to fine tune parameters of SWARM Users can use the measurements file to collect statistical data or use the freeway MOE plugin we developed to collect these measures The saturation density is an important parameter of SWARM The goodness of this parameter affects the performance of SWARM Us
84. lled by this plugin 5 3 4 Preparation of control The control file includes the ramp control information which is the input of this plugin It should be located at the same directory as any other network files An example of ramp control is shown below total number of controlled entrance ramps is 7 control cycle of ramp metering 30 on ramp signal 33 name 405N amp ICD 1 0 93 demand detector 405n0 93orb number of control plans 2 from 6 0 to 9 0 METER ON with 1 veh per 6 sec from 15 0 to 19 0 METER ON with 1 veh per 6 sec on ramp signal 36 name 405 amp ICD 2 1 11 demand detector 405nl 11orb number of control plans 2 from 6 0 to 9 0 METER ON with 1 veh per 12 sec from 15 0 to 19 0 METER ON with 1 veh per 7 sec The first line defines the number of entrance ramps to be controlled by this plugin The second line defines the control cycle of the ramp metering control 56 The following is the necessary input information of each entrance ramp which always begins from a blank line 1 on ramp signal is the global node number of the on ramp signal in the PARAMICS network 2 name 15 the description of the entrance ramp such as its location p p 3 demand detector is the name of the demand detector of the entrance ramp If there is no demand detector or the demand detector is not used for on ramp signal operation please specify as N A If the specified detector can not be fou
85. loop data aggregator emulates the real world loop data collection typically with a thirty second polling interval and broadcast the latest loop data to the dynamic memory At each time increment the advanced ramp metering algorithm plugin can access the dynamic memory and obtains the required loop data through interface functions provided by the loop data aggregation plugin Then the metering rate for the next control interval is calculated based on the advanced ramp metering algorithm The new metering rate is finally sent back to the ramp controller plugin for implementation 61 PARAMICS simulation Loop Data Ramp metering Aggregator Controller Loop data Old metering rate Advanced metering algorithms Figure 6 1 Hierarchical approach for the development of advanced metering algorithms 6 2 2 Control Logic This plugin implements a queue override strategy depending on a queue detector placed on the entrance ramp A typical location of the queue detector is located at the upstream end of the entrance ramp The control logic is as follows If the percent occupancy of mainline detector is higher than the pre specified override occupancy threshold an override control plan will be applied to the corresponding meter in order to avoid interference with the arterial traffic The override control plan can be a specified metering rate such as maximum metering rate or all green 6 3 Step by step user manual 6 3 1 Adding queue
86. lugin amplerientatiott i ioco etre Eee rd 51 5 3 Step by step user 55 5 4 PROGRAMMER capabilities Nd m ado 58 5 9 Technical oou aseo eia te n tende tiae perdete aie 59 6 On ramp queue override 61 6 T Etro HOT ees ce EU De ag mti ue MN SM LAN NM eU M 61 6 2 Plugin implemientatlOtr eroe ere ub eii em pL be tee deans 61 6 3 step by step tiscrmatual earn dpa 62 6 4 Technical supports References essct stet aee cc cede aate vol ipud 66 7 ALINEA ramp metering 67 1 1 oec tub E EE E A ed M CS EL ME 67 T 2 Plugim impleraentatlON ice eo sete tee Pk cit err eee oko e ios 68 7 3 Step by step user manual For S EOS TEN IN ON DEN USER SM fs 68 TA Technical SUP POMS cans saa ad wean E 72 8 BOTTLENECK ramp metering ener 74 E B vinctos 74 8 2 Plugin iplementdtiol 4 dicere Dae t tapes bad edd 75 iv 8 3 Step by step user manual cod ossa edt en atq tia aot tdeo 76 Ban Lechnical SUDDOPS e aie qe dada d hard UNA Mo tae date E Mn oe 81 9 SWARM Ramp metering Retro ten eese dae ra AURI eu
87. ncy value at capacity which can be also found in the volume occupancy diagram Various values ranging from 0 18 to 0 31 have been found in previous applications 2 The regulator Kr used for adjusting the constant disturbances of the feedback control is found to perform well in the real life experiment when it is set to 70 Simulation results are considered to be insensitive for a wide range of values 72 3 The downstream detector should be placed at a location where the congestion caused by the excessive traffic flow originated from the ramp entrance can be detected In reported implementations this site 15 located between 40 m and 500 m downstream of the on ramp nose 4 The update cycle of ramp metering rate is also variable with the range from 40 seconds to 5 minutes In theory if the value is small the location of the downstream detector station should be close to the entrance ramp Otherwise there is a risk of congestion built up in the interior of the stretch from the ramp nose to the downstream detector These calibrated parameters of ALINEA can be obtained based on reported practices such as the regulator and your own network such as the desired occupancy The recommended values are shown in Table 7 1 Since the current loop aggregation cycle is 30 seconds the update cycle is set to 30 seconds in order to quickly feedback the variation of mainline traffic to the ramp control Table 7 1 Calibrated parameters for the AL
88. nd in the detectors file a warning message will be given and the entrance ramp will be operated without demand detector 4 number of control plans 18 the number of on ramp signal control plans The number will decide how many timing plans followed 5 The following are time of day timing plans The possible format might be one of the following from TIMEI to TIME2 METER ON with BB veh per CC sec from TIMEI to TIME2 METER OFF from TIMEI to TIME2 RAMP CLOSURE where TIME1 is the starting time of a timing period and TIME2 15 the end time of a timing period The format of TIME1 and TIME2 is HH MM only hour and minute is specified The timing periods of any two timing plans should not overlap is the type of metering operation single entry metering BB 1 or platoon metering BB 2 CC is the cycle of metering control If the status is METER ON BB and CC should be specified If there is no timing plan for a certain time period it is regarded as METER OFF 5 3 5 Loading plugin This plugin has two files ramp controller dll Modeller Plugin ramp controller p dll Processor Plugin After the completion of the control file and the update the priorities file you can load the simulation network together with this plugin 5 3 6 Error checking After the network and the plugin are loaded in Modeller you can start simulation Via GUI you will see that this plugin emulates th
89. ng If HOV is specified as one or more than one vehicles entering freeway from the HOV lane are un metered and the calculation of the future metering rate will not consider HOV vehicles This is the HOV bypass situation whose example is the first ramp shown in the above example If HOV is specified as 0 this is the HOV metering situation Vehicles entering freeway from HOV lanes will be considered in the calculation of the future metering rate The example of this case is the second ramp shown in the above example control type means one car per green or multiple car per green There are three possible values 1 2 3 This information will be used for calculating the correct metering cycle under a certain control type desired occupancy and regulator are two parameters desired occupancy has the format like 0 20 but it represents 2096 rate restriction include a minimum rate and a maximum rate which are actually the two boundaries that metering rate can vary Its unit is vehicle per hour 7 3 3 Loading plugin This plugin has two files alinea dll Modeller Plugin alinea p dll Processor Plugin The ALINEA plugin depends on other two plugins ramp metering control and loop data aggregator These two plugins should be specified earlier than this plugin in the plugins or programming file i e 70 loop agg dll ramp controller dll alinea dll If you want to implement ALINEA with a que
90. oach 1 4 Please refer to the definition at step 4 for the definition of approaches 1 to 4 Write down these numbers in the row of Right turn lanes As in the case of lanes that allow both left and through movements lanes that allow through and right turn movements will count as one through lane and one half of a right turning lane 9 The row of detector 1 to detector 4 should be filled with the name of detectors the sequence is from stopline detectors to the advance detector seen in figure 1 on approach 1 to approach 4 Please refer to the definition at step 4 for the definition of approaches 1 to 4 In some cases one or more of the detectors for an approach does not need to be modeled Each missing detector needs to be specified as N A in the worksheet In Paramics v3 0 build 6 it was necessary to place three separate detectors at the stopline to ensure proper detection However build 7 of Paramics 3 0 and all later versions only need one long detector To allow reverse compatibility it still might be desirable to place three separate detectors 1 3 4 Preparation of signal control file The plugin requires a file titled signal control to be in the PARAMICS network directory An example of the signal control file is shown in Figure 1 5 The first line of this file specifies the number of actuated signals modeled in the network The remainder of the file contains the signal timing information The information
91. of metered ramp by optimizing density to maintain maximum flow SWARM 2b introduces a concept of storage zone which starts from the mainline upstream VDS to the next downstream mainline VDS The number of vehicles storing within this storage zone will be calculated Then SWARM 2b computes metering rates to maintain demand such that LOS D as along as possible If there are on ramps and off ramps between the two VDSs detectors are required to be placed at on ramps and off ramps for counting traffic volumes This algorithm depends on accurate loop detector data 9 2 Plugin implementation Based on the algorithm logic of SWARM and the hierarchical development framework for advaced ramp metering algorithms shown in Figure 6 2 we developed the SWARM plugin with the following pseudo codes 84 Loop data polling time i e the time to update metering rate Calculate loop station statistics 1 For mainline VDS 1 Get aggregated loop data from the loop aggregator plugin Calculate normalized station density occupancy speed Calculate the average vehicle length j For ramp VDS Get aggregated loop data from loop aggregator plugin j Query the current time of day metering rate from ramp metering plugin Query the current default rate control Query the current minimum rate control Check the status of loop detector station at known bottlenecks If bad search for a good upstream loop detector station to replace it Calculate update satur
92. of a loop can be found in the detectors file which is one of network files The time interval to aggregate loop data can be different for different detectors 4 3 2 Loading plugin This plugin has two files loop_agg dll Modeller Plugin loop agg p dll Processor Plugin After the completion of the control file you can load the simulation network together with this plugin Run simulation and then you will obtain the aggregated loop data outputs if you enable the option output to files 4 3 3 Text file outputs 47 If output to files is aggregated loop data will be output to text files Each detector specified in the control file has its own output file These output files can be found in the subdirectory network Log run xxx where network is the name of the current working directory and xxx is a three digit sequence number During the simulation process aggregated detector data are continuously calculated and then immediately stored to the output text file Each output file has several fields whose definitions are shown as follows Time stamp grouped volume grouped occupancy grouped speed volume of lane 1 occupancy of lane 1 average speed of lane 1 volume of lane 2 occupancy of lane 2 average speed of lane 2 volume of lane n occupancy of lane n average speed of lane n For right hand driving lane is the inside lane the leftmost lane it might be t
93. of actuated signals 2 total number of timing plans 2 plan 1 from 8 00 00 to 9 00 00 node 1167 ICD amp BARRANCA movements 1 2 3 4 5 6 7 8 ini green 5 5 5 8 5 5 5 8 extension 3 4 3 5 3 4 3 5 max green 24 32 24 32 24 32 24 32 32 node 142 ALTON amp ICD movements 1 2 3 4 5 6 7 8 ini green 5 5 5 5 5 5 5 5 extension 3 5 3 5 3 5 3 5 max green 24 32 24 32 24 32 24 32 plan 2 from 9 00 00 to 24 00 00 node 1167 ICD amp BARRANCA movements 1 2 3 4 5 6 7 8 ini green 5 5 5 8 5 5 5 8 extension 3 4 3 5 3 4 3 5 max green 20 28 20 28 20 28 20 28 node 142 ALTON amp ICD movements 1 2 3 4 5 6 7 8 ini green 5 5 5 5 5 5 5 5 extension 3 5 3 5 3 5 3 5 max green 20 28 20 28 20 28 20 28 The first two lines include some general information total number of actuated signals represents the number of signals that have multiple timing plans total number of timing plans is a global parameter We assume that all signals have the same number of timing plans The second part is about the timing plans For each timing plan users need to input movement initial green extension and max green information The time period of the last timing plan needs to end at 24 00 00 2 3 2 Load plugin This plugin has two files multi signal plan dll Modeller Plugin multi signal plan p dll Processor Plugin After the completion of the multi plan signal control file you can load the simulation network together with this plugin Because th
94. ol algorithm plugin can be further developed based on them The prototypes of these interface functions are shown below Signal uci signal get parameters char nodeName Function Querying the current signal timing plan of a specific actuated signal Return Value The current timing plan of an actuated signal Parameters nodeName is the name of the signal node Signal is the structure of actuated signal data whose definition is type Signal intersection name and location char node char controllerLocation signal parameters int movements 8 float maximumGreen float minimumGreen 8 float extension 8 float storedRed 8 float phaseGreenTime 8 float movementGreenTime 8 current phase information int currentPhase int expiredTime float redTimeLeft Bool cycleEndFlag Void uci signal set parameters Signal sig Function Setting a new timing plan to a specific signal Return Value None 21 Parameters sig stores the new timing plan 1 5 2 How to use interface functions in other plugins These two interface functions can be called in other plugins The following setting is required 1 In the workspace of your plugin that wants to use these interface functions specify the library file actuated signal lib of the actuated signal plugin as an input object library module The path of actuated signal lib should be specified as well 2 Specify the prototype of the interface function a
95. ontrol plan METER OFF There are two parts in this queue control file The first part is the basic information of this plugin 1 The first line defines the number of entrance ramps to be controlled by this API 2 The option of checking control file is used for checking if there are any mistakes in the control file If yes this API will print out the information obtained from queue control file during the starting process of simulation 3 The third line defines the control cycle of the ramp metering control Basically this control cycle is the loop data aggregation cycle typically 30 seconds If the queue detector detects the excessive queue length on entrance ramp the metering rate controlled by the queuing strategy will be effective for the time length equal to this control cycle 4 During the time period between algorithm activation time and algorithm deactivation time the ramp metering algorithm is activated 63 If report queuing condition is yes the metering rates of queuing control condition of all controlled ramps will be output every update cycle to a file named rampQueue txt This file can be found in the sub directory Log under the network directory The second part of the queue control file is the input information of each entrance ramp which always begins from a blank line 1 on ramp signal is the global node number of the on ramp signal in the road network
96. ost mile and thus can also be one of N S W and E For example if the post mile at downstream is higher than that at upstream pri direction is the same as 90 99 direction saturation density refers to the density of the loop detector station at capacity It can be a value between 40 45 The SWARM plugin provides capabilities to calculate the saturation density of mainline detector station based on simulation results and report to an output file named Log sat_density Since the network model may not be calibrated well the saturation density calculated based on real world loop data might not be the same as that calculated based on simulation 9 3 4 Preparation of swarm_control This file includes the design of the SWARM algorithm to the target network total number of SWARM controlled ramps is 8 metering rate update interval 30 report metering rate yes ramp 92 freeway 405 direction N postmile 5 74 mainline detector 405n5 74ml upstream ramp 95 N A N A N A apportionment factor 1 0 0 0 0 0 0 0 onramp detector 405n5 740rb queue detector 405n5 74orspill HOV 0 metering mode SWARM 1 minimum rate control ABS MIN default rate control ABS MAX swarm startup strategy RUN SWARM DURING TOD ONLY rate restriction 6 30 The unit of the metering rate in swarm control is veh minute The on ramps such as 92 listed in swarm control are ordered by freeway id direction from downstream to upstream Th
97. pabilit output files through reading them algorithm plug ins p y p g g But it is not convenient for on line developed by UCI applications 4 2 Plugin implementation 4 2 1 Aggregation method In the real world most detectors are loop detectors A loop detector station generally has multiple loop detectors and each loop detector covers a lane In PARAMICS a detector can cover all lanes or just cover a lane This plugin outputs aggregated detector data in term of a detector station The aggregated data outputs include not only aggregated data of each lane but also the grouped data of the detector station In the real world loop detectors are used to report volume and percent occupancy In the simulation besides volume and percent occupancy speed can also be obtained from simulation because it is a basic element of simulation As a result this plugin will be used to aggregate traffic volume percent occupancy and speed data The aggregated volume is defined as the number of vehicles passing the detector during last time interval The aggregated speed is the average of speeds of passing vehicles during last time interval If at the aggregation time a vehicle is just on a loop it is counted as a passed vehicle for aggregation Percent occupancy is defined as the percentage of time of a loop occupied by vehicles However the occupancy obtained from PARAMICS via API function loop occupancy is time occupancy which is calculated
98. phases can be determined based on the definition of the standard NEMA phases movements shown in figure 1 Write down all NEMA movements on the worksheet 4 Write down the approach number on the worksheet The approach that the 1st NEMA movement locates is defined as approach 1 here The counter clockwise approaches around the junction are defined as approach 2 3 4 5 Fill out the 3 5 rows Initial green Extension Max green of the table on the bottom of the worksheet The ini green corresponds to the Initial green time and the max green corresponds to the Max Green in the Signal Timing Chart 6 Find out the recall movement from Signal Timing Chart Enter the two recall movement numbers into the first two columns of the recall row If there is only one recall phase put the second one as 0 7 Find out how many lanes correspond to each NEMA movement from layout of the intersection or PARAMICS environment Fill them in the row of lanes in the worksheet The first value in the row corresponds to the number of lanes for NEMA movement 1 and the second value corresponds to NEMA movement 2 etc In many situations there are lanes that are shared by different movements For example one lane may allow both left turning and through vehicles to pass In this case the lane will count both as one through lane and as one half 0 5 of a left turning lane 8 From the layout find out how many right turn lanes for each appr
99. plugin requires a demand detector which should be specified by users in the ramp control file for the operation of on ramp signal If without detectors users need to specify the demand detector of the on ramp as N A 5 3 3 Adding on ramp signal through editing priorities file In order to let PARAMICS regard a node as a signalized node users must add or edit the priorities information of the node This can be realized through GUI or editing priorities file The priorities file a system file of PARAMICS defines movements of each phase of a signalized intersection We recommend the latter method There are two phases for each on ramp signal We define that phase 1 is the red signal to prohibit vehicles from entering the mainline freeway and phase 2 is the green signal to release the waiting vehicle into the freeway An example of the priorities information fro an on ramp signal is as follows actions 92 phase offset 0 00 sec phase 1 0 00 max 30 00 55 red phase 0 00 fill all barred except phase 2 0 00 max 30 00 red phase 0 00 fill all barred except from 91 to 93 major Where fill means no yellow will be shown The initial phase lengths for both phases are set to 0 This plugin has set the maximum cycle of an on ramp signal to 24 seconds Currently in the above example max 30 00 means the maximum length of each phase is 30 seconds This value should be larger than 24 seconds in order to make ramp meters contro
100. queue detector is the name of the queue detector for the entrance ramp If there is no queue detector or no queuing strategy is involved in ramp metering please specify as N A If the specified detector can not be found in the detectors file a warning message will be shown and the entrance ramp will be operated without any queuing strategy even a strategy has been input in the queue control file override occupancy threshold is required to be specified if the queue detector has been specified earlier in the file If the percent occupancy of the queue detector station if there is more than one queue detector at this location the maximal percent occupancy of this location will be used exceeds this threshold the queuing strategy will be applied to avoid interference with the traffic on the surface street If there is no queue detector nothing needs to be filled in this line override control plan is actually the timing plan to handle the excessive queue length which is required to be specified if the queue detector has been specified earlier in the file The format is one of the following METER ON with BB veh per CC sec METER OFF RAMP CLOSURE where BB is the type of metering operation single entry metering BB 1 or platoon metering BB 2 CC is the cycle of metering control If the status is METER ON BB and CC must be specified If the queue detector is specified but the override control plan timing
101. r loops at detector station i k is the vehicle index 1 is the number of vehicles passing loop j of detector station i during time interval 1 1 2 t is the time occupancy of vehicle k passing loop j at detector station during time interval t 1 t The grouped speed represents the average speed of a detector station during last time interval which can be expressed as n V t io SV k l where i is the index of the detector station j is the loop index at detector station i n is the total number of lanes or loops at detector station i k is the vehicle index V t is the number of vehicles passing loop j of detector station i during time interval 1 1 t t is the loop speed when vehicle k passes loop j at detector station i during time interval t 1 t 4 2 2 Pseudo code The control logic is given in the following pseudo codes 1 Initialization of loop data aggregator plugin including reading loop control file opening output files memory allocation and other initial settings 2 Atevery time step PARAMICS overload API function vehicle detector when a vehicle traverses on or passes a loop If a vehicle passed a detector the occupancy and speed of the vehicle are accumulated The following exceptional cases need to be handled in order to obtain the correct occupancy value 1 Unexpected incorrect value of occupancy from simulation which may happen when a loop is place
102. ring rate calculation The option of checking control file is used for checking if there are any mistakes in the control file If yes this API will print out the information obtained from alinea control file If report metering rate is yes the metering rates of ALINEA controlled ramps will be output every update cycle to a file named ALINEA rampRate txt under the Log directory 69 During the time period between algorithm activation time and algorithm deactivation time the ramp metering algorithm is activated The second part of alinea control is about each ALINEA controller ramps mainline detector generally corresponds to the detector placed on the downstream of an on ramp It can be specified as an upstream detector but the performance of this algorithm may be deteriorated on ramp detector generally corresponds to the demand detector shown in Figure 2 The purpose of this detector is to count the total vehicles entering freeway from an on ramp If the specified on ramp detector cannot be found in the detectors file this API will not work On the row of HOV number of HOV lane at the location of on ramp detector if the HOV lane is modeled as a separated link or there is no HOV lane please write down 0 on this row If there 1s at least one HOV lane on the in ramp and the HOV and SOV lanes are modeled on the same on ramp link there are two conditions HOV bypass and HOV meteri
103. rride strategy you will need to disable the queue override strategy in the SWARM plugin through specifying queue detector as N A in swarm control Then you need to add on ramp queue control plugin to the plugins or programming file with the following sequence loop agg dll ramp controller dll queue control dll swarm dll In addition in order to correctly load and run this plugin please satisfy the following requirements 1 For ramp metering plugin on ramp signals controlled by the SWARM algorithm should be specified in ramp control For example if the on ramp signal 33 is under SWARM control on ramp signal 33 also needs to be specified in ramp control as the following format 92 on ramp signal 33 name 405N amp ICD 1 0 93 demand detector 405n0 93orb number of control plans 2 from 6 0 to 9 0 METER ON with 1 veh per 6 sec from 15 0 to 19 0 METER ON with 1 veh per 6 sec If an on ramp signal is specified in swarm control but not in ramp control this on ramp signal will be regarded as a METER OFF meter 2 For the loop data aggregator plugin all detectors used by SWARM should be specified in control for the aggregated data collection In addition the metering rate update interval specified in the second row of swarm control must be the same as the report cycle in control 9 3 6 Output files Each simulation run will generate two output files Lo
104. s 3 If the length of red signal is longer than red and no vehicle is waiting the metering signal keeps showing the red signal This plugin allows multiple metering plans A metering rate is fixed within a specific time window For another time window another timing plan can apply As an illustration suppose the ramp signal cycle length is 10 seconds from 4pm to 6pm This is one vehicle every 10 seconds so that a setting of a 2 sec of green followed by 8 sec of red could be used The metering rate in this case is 360 vph 53 5 2 4 Pseudo code The control logic is given in the following pseudo codes 1 Read ramp control file and initialize the plug in Allocate memories for all pointers to be used Store all necessary ramp information to global data structures Check the existence of ramp nodes and correspondent detectors Initialize the ramp signals based on the initial simulation time j 2 At every time step of simulation net action is called Get simulation time For controlled ramp 1 n Check the current running phase Get green left time of the current running phase Find the correct ramp control plan according to the simulation time If ramp cycle length changed due to entering another time period Notify the operator Recalculate the green times for the 2 phases 15 If controltype is always ON set next green time for always ON Else if controltype is always OFF set next green
105. s with n gt 1 in PARAMICS It also supports multiple timing plans and the use of ramp detectors for metering control The data input of this plugin is a time of day ramp control plan and the detector information of each meter In addition this plugin is designed to support the development of advanced ramp metering algorithms and integrated control strategies ramp metering plus arterial signal control number of interface functions are provided by this plugin for external plugin modules to acquire the current metering rate and set a new metering rate to a specific ramp meter 5 2 Plugin implementation 5 2 Real world ramp metering system The easiest ramp meter is based on fixed time control Some latest ramp metering design has included the check in and check out detector for a better control and the consideration of safety Caltrans has the following basic design of ramp metering system as shown in Figure 5 1 Five types detectors can be possibly installed for a ramp meter including on ramp detector demand detector passage detector queue detector and ramp detector The on ramp detector is used for counting total number of vehicles entering freeway from entrance ramps The demand and passage detectors i e corresponding to the check in and check out detectors are used for the operation of on ramp signals The demand detector employs to initiate green and the passage detector employs to return the signal to red The queu
106. s to a four legged actuated signal intersection The exact set back distance of the advance detector can found in the Geometric layout of the intersection The following geometric information needs to be checked 1 Number of lanes for each approach 2 Lane use information at intersections for example at an approach of an intersection which lanes are assigned to the left turn through or right turn movements If the default lane configuration is not the same as that shown in the Geometric layout of the intersection the corresponding intersection needs to be re coded via the PARMICS Modeller GUI Node gt Modify junction or by editing the junctions file manually 1 3 3 Preparation of worksheet Running MODELLER zoom in to the intersection Fill out a worksheet that includes geometry and signal timing information of the intersection The worksheet has been attached in APPENDIX 1 of this document The following is a list of necessary information in the worksheet 1 Write down the name of the intersection i e Alton amp ICD and the signal ID that is shown in the first page of signal timing chart 2 Write down the two street names the direction and the PARAMICS designation of the junction node and the four adjacent nodes on four approaches 3 Find NEMA movement number 1 generally a left turn from the Signal Timing Chart Write down the turn arrow and the movement number 1 As a result all NEMA movements
107. t hurt the simulation performance the actual signal control cannot be fully simulated in this plugin Ideally we want each phase to include only one major movement and two phases can be executed at the same time Version 4 of PARAMICS provides users with this capability but we do not have time to implement this at the current time 3 Only one timing plan for each intersection is supported by the current plugin In order to support multiple signal plans please use another plugin multiple actuated signal plan together with this plugin 22 4 In version 3 of PARAMICS vehicles may stop at stop lines because of routing problem such as a through vehicle stopping on a left turn lane Version 4 has bot this problem because it introduces the re routing feature 1 6 2 FAQ 1 Grammar of input files Unlike the parser system of PARAMICS which allow flexible grammars and comments i e the format of the input file of this plugin is rigid and thus any problem in the file may cause the plugin not work well Our recommendation for users is that the input file of the example network of this plugin is a good starting point to make your own input file in order to avoid editing problems 2 Can a phase in priorities file have no movement information It is not good for a phase to have no movement information Every phase corresponds to a combination of NEMA phases if that phase is regarded to have vehicles and then a green signal will b
108. t node 7511 and heading towards the junction node 528z The priorities for a four legged full actuated intersection will have eight phases As illustrated in Figure 1 7 Phase 1 will correspond to the situation where the left turning NEMA movements and 5 will be given the green Phase 2 will account for the situation where movements 5 and 2 will be given the green and phase 3 will be for movements 1 and 6 4 will be for the through movements 2 and 6 The last four phases will follow the pattern of the first four phases starting with the left turn movements 3 and 7 7510 5287 7511 7614 7612 Figure 1 6 Intersection Layout Figure 1 7 Eight phases of the four legged full actuated signal intersection For the intersection in the previous figure the definition of phases and actions movements in priorities file would be actions 528z phase offset 0 00 sec phase 1 0 00 max 100 00 red phase 0 00 fill all barred except from 7510 to 7511 minor from 7511 to 7612 minor from 7511 to 7510 major from 7612 to 7614 minor from 7614 to 7612 major from 7614 to 7510 minor phase 2 0 00 max 100 00 red phase 0 00 fill all barred except from 7510 to 7511 minor from 7511 to 7612 minor from 7511 to 7614 major from 7511 to 7510 major from 7612 to 7614 minor from 7614 to 7510 minor phase 3 phase 8 0 00 max 100 00 red phase 0 00 fill all barred except from 7510 to 7511 minor from 7510 to 7
109. t the beginning of your plugin as follows _ declspec dllimport void uci signal set parameters Signal sig _ declspec dllimport Signal uci signal get parameters char nodeName 1 6 Technical Supports 1 6 1 Limitations of this plugin 1 During our development on this full actuated signal control plugin we found that PARAMICS did not provide a plugin function for users to control the amber time yellow light Although yellow time can be set in the configuration file it is a universal parameter for all the intersections and all the time It is not convenient in the actuated signal case since some phases may be skipped the amber time has to be skipped at the same time In order to simulate the real world better our developed plugins have to have a handle on the control of the amber time associated with each phase 2 In PARAMICS phase and movement are different For the current actuated signal plugin implementation each phase usually includes two major movements and some minor movements For instance phase 1 may include dual left turn movements and some right turn minor movements PARAMICS runs through phase 1 to phase 8 some phases may be skipped depending on the vehicle presence However each movement has its own initial green and extension in the signal timing sheet Only one set of parameters could be used in each phase Although a reasonable set of parameters is calculated and used during the simulation and doing this does no
110. th it will interfere with the adjacent street traffic The queue override strategy is often used to solve this problem through the placement of a queue detector at the ramp entrance usually at the end of the entrance ramp An example of the queue override policy is that if the occupancy value of the queue detector exceeds a threshold e g 50 a high metering rate will be applied to the corresponding meter in order to release more vehicles to freeway This pluign is a complementary module of the ramp metering control plugin which implements pre timed metering control but does not include any queue override strategy The purpose of this plugin is to implement a typical queue override strategy that uses the queue detector This plugin can be used together with the ramp metering control plugin Also this plugin can be used together with other advanced ramp metering control algorithms such as ALINEA which do not integrate a queue override strategy with them 6 2 Plugin implementation 6 2 1 Development framework Figure 6 1 illustrates the hierarchical development framework of advanced ramp metering algorithm plugins in PARAMICS The advanced ramp metering algorithm plugin is built on top of two basic plugin modules i e ramp metering controller and loop data aggregator The on ramp signals in the simulation network are controlled by the ramp metering plugin through which metering rates can be queried and set by other plugin modules The
111. the area of influence of each section based on historical demands pattern 8 4 2 References Jacobsen L Henry K and Mahyar 1989 Real Time Metering Algorithm for Centralized Control Transp Res Rec 1232 17 26 82 9 SWARM Ramp metering control The purpose of this plugin is to allow users to implement the System Wide Adaptive Ramp Metering System SWARM of Caltrans in the PARAMICS simulation environment This plugin is developed based on source codes of SWARM obtained from Caltrans 9 Introduction SWARM is a coordinated traffic responsive ramp metering operation strategy which is developed as a component of the Advanced Transportation Management System ATMS at Traffic Management Center TMC by National Engineering Technologies NET System It has drawn wide interests because of the introduction of traffic flow forecasting in the algorithm The initial field tests were attempted in the Field Operational Test FOT of an integrated corridor level adaptive control system from fall 1994 through spring 1999 in the City of Irvine California The system is currently tested in the I 210 freeway within the Los Angeles transportation network The SWARM algorithm actually consists of two independent algorithms SWARM 1 and SWARM 2 SWARM 1 is a forecasting and system wide apportioning algorithm using a forecasting methodology SWARM 2 includes two local traffic responsive ramp metering algorithms SWARM 2a
112. trategy See the following for reference typedef enum RMS queue strat 1 QUEUE STRAT UNKNOWN 0 DISABLED QUEUE STRATEGY LOCAL CONTROLLER RMS queue strat enum 96 In the Traffic Engineer s manual of District 7 there is another description of queuing strategy Local queuing strategies such as forcing maximum rates when a queue is detected affect SWARM 1 operations The final SWARM 1 metering rate will have a lower bound equal to the rate selected by the queuing strategy The difference between the forced rate due to local queuing strategies and the desired SWARM 1 rate will be propagated by SWARM apportionment to upstream metered ramps Therefore we can judge that the earlier design of SWARM was not implemented If this description is right the queuing strategies should be operated before the calculation of SWARM 1 rate However we cannot find any code in the source code As a result we only implement the local controller strategy in this SWARM plugin 3 Kalman filtering The default forecast lead time is 15 minutes or 30 intervals ahead The number of points used to estimate density slope as input to the Kalman filter is 6 The accumulated density is used in Kalman filtering which has a typical trend like the following 29 60 87 119 150 However the variation in the accuracy of the density measurements is 0 04 allowed range is from 0 02 to 0 5 the variance representing the inaccuracy of the model is
113. tween actual travel time and ideal travel time calculated based on the speed limit of freeway sections If the actual travel time is higher than the ideal travel time delay will be a value larger than 0 otherwise delay is 0 delay will be calculated if delay is higher than 0 delay represents the total delay experienced by all traced vehicles delay and delay are estimated based on mean tt and the ideal travel time They may be larger than 0 although spd average speed is higher than the speed limit of the corresponding section The reason is that spd is equal to the average speed of all traced vehicles while mean tt is equal to the average travel time of all traced vehicles The value of spd times mean tt is not exactly equal to the length of two measurement points 10 2 4 Error checking If any mistakes happened in the freeway control file this plugin will be disabled The report window of PARAMICS will show whether this plugin is working Through enabling the option checking control file in the moe freeway control file you can check if there is any error in the moe freeway control file 10 3 PROGRAMMER capabilities An interface function has been provided by this plugin for external modules to acquire the point to point travel time between two loop detectors The prototype of the interface function is as follows 101 PROBE uci probe travel time char
114. ue override strategy you will need to add on ramp queue control plugin to the plugins or programming file with the following sequence in order to give the on ramp queue control strategy higher priority than ALINEA loop agg dll ramp controller dll queue control dll alinea dll In addition in order to correctly load and run this plugin please satisfy the following requirements 1 For ramp metering control plugin on ramp signals controlled by the ALINEA algorithm should be specified in the ramp control file For example the correspondent on ramp signal 33 needs to be specified in the ramp control file on ramp signal 33 name 405N amp ICD 1 0 93 demand detector 405n0 93orb number of control plans 2 from 6 0 to 9 0 from 15 0 to 19 0 METER ON with 1 veh per 6 sec METER ON with 1 veh per 6 sec 2 For the loop data aggregator plugin all loops involved in the alinea control file should be specified in the loop control file for aggregated data collection In addition the report cycle in the control file should be the same as the metering rate update interval specified in the second row of alinea control file For example all relevant loops of ramp 33 needs to be specified in the control file detector count 42 report cycle 30 activation time 06 00 00 deactivation time 10 00 00 gather smoothed data no output to files yes name 405n0 93ml gather interval 00 00 3
115. uiry the current signal information using signal inquiry b If left green time 0 1 Amber and red time are counted If amber and red time are reached Set the next signal phase parameters through signal action j else vehicle presence detection pp presence dection excute the current signal plan pp excute plan 1 If left green time extension amp amp vehicle presence for extension amp amp expired green lt maximal green extension green time increased by extension left green If left green time lt time step Find the next phase by vehicle presence 1 3 Step by step user manual 1 3 1 Data preparation The data input to this plugin is the signal timing plan the geometry and detector information of actuated signal intersections If the purpose of simulation is to model a real world network the following information is required in order to make actuated signals 1 Signal Timing Chart obtained from the proper government agency 2 Geometric layout of the intersection the best source of this information is usually from as built plans If the purpose of simulation is to evaluate an intersection design or test signal timing plans you can obtain the signal timing from traffic signal software such as SYNCHRO based on historical traffic patterns 1 3 2 Adding detectors and checking network coding Based on the previous discussion we can either code 16 detectors or 8 detector

1. Actuated signal Control

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