NoIncident Model July 23 2014 Outline Arterial LoopRacetrack NoIncident Model Model components with calibration set Model run Model validation with validation set 2 Model Components ID: 1040210
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1. Arterial Loop+RacetrackNo-Incident ModelJuly 23, 2014
2. OutlineArterial Loop+Racetrack No-Incident ModelModel components (with calibration set)Model runModel validation (with validation set)2
3. Model Components3Generate FDFixed capacityFixed jam densitySpeed limit from Nokia mapSR/BF Calibrationcc-scenario buildingcc-scenarioFDSR, BFRacetrack flow1Loop flow3Loop SR4Racetrack SR2Signal Timing6Data ProcessingModel Components:FD / BF / SR / SignalsCTM Forward SimulationMetrics:TT, Delay, LOS, VHT, VMTComparison:Travel Time, Flowcc-network
4. Family of Fundamental DiagramsFixed jam density = 150 veh/km/laneFixed capacity = 1800 veh/hr/laneFree flow speed = speed limit from Nokia mapsFlowDensity4[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
5. SR/BF Calibration5Set SRDefault SRDefault BFScale racetrack flowBF OptimizationTarget flowsGenerate BF profileCheck whether side street BF reasonableApply engineering judgmentGenerateGeneric flow profileFlowTimeSRSRBFloop SR4Racetrack SR2Racetrack flow where loop is available at the same location1aRacetrack flow where loop is not available at the same location1bloop flow3loop flow3[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
6. Process to Generate Split RatiosUse racetrack dataUse default values when racetrack data unavailableApply engineering judgment to obtain reasonable boundary flows in subsequent steps6[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
7. HuntingtonSanta Anita1st2nd5thGateway35%26%10%I210WI210E10%82%18%65%90%74%90%6%19%75%19%8%73%6%91%3%8%41%51%10%17%73%17%11%72%27%68%5%17%19%64%2%98%95%5%100%7%56%37%Santa ClaraColorado Pl92%8%23%77%Colorado10%90%10%90%100%10%90%10%90%10%90%100%5%5%90%5%5%90%10%90%10%90%MichillindaBaldwin / OxfordColorado BlvdColorado PlColorado BlvdI210WHuntington6%94%93%7%45%55%49%7%44%18%24%58%12%77%11%7%22%71%50%50%50%50%100%10%90%10%90%31%69%10%90%10%90%46%54%50%33%50%50%50%50%60%37%50%50%50%50%Engineering judgmentRacetrack dataDefault values100%Split RatiosColor coding:[ Input for CTM Simulation of Arterial Loop+Racetrack No-Incident Model ]Split ratio from loop7
8. Reasons for finetuning split ratios with Engineering judgment@ 1st both Northern and Southern approaches: change split ratio from [ left=10%, thru=90%, right=0% ] to [50%, 50%, 0%]Side street is small; it is therefore unlikely that many drivers go thru; instead, they most likely turn towards the main street@ 5th N/S: ditto8[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
9. Reasons for finetuning split ratios with Engineering judgment@ Santa Anita South: change from [ left=17%, thru=64%, right=19% ] to [17%, 50%, 33%]Too little traffic predicted on Huntington at 2nd WFurther hypothesis: After racetrack event, people leave via Santa Anita (among others) and want to go to the freeway. The split ratio estimated by the racetrack study are therefore overestimated in the thru direction.9[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
10. Reasons for finetuning split ratios with Engineering judgment@ Huntington & Colorado East: change from [ left=77%, right=23% ] to [ 54%, 46% ]Too little traffic predicted on Colorado & Colorado SEAnalysis of loop data at advance and left-turn locations showed that splitratios differ a lot between loops and racetrack study10[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
11. Reasons for finetuning split ratios with Engineering judgment@ 2nd West: change from [ left=3%, thru=91%, right=6% ] to [3%, 60%, 37%] :Too much traffic predicted on Huntington at I210E and I210WFurther hypothesis: After racetrack event, people leave via Huntington (among others) and want to go to the freeway. The split ratio estimated by the racetrack study are therefore overestimated in the thru direction.11[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
12. SR/BF Calibration12Set SRDefault SRDefault BFScale racetrack flowBF OptimizationTarget flowsGenerate BF profileCheck whether side street BF reasonableApply engineering judgmentGenerateGeneric flow profileFlowTimeSRSRBFloop SR4Racetrack SR2Racetrack flow where loop is available at the same location1aRacetrack flow where loop is not available at the same location1bloop flow3loop flow3[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
13. Process to Generate Boundary FlowsOverviewGenerate static (constant in time) boundary flows using an optimization procedureGenerate generic flow profile based on loop dataScale generic flow profile of step 2 by optimal values obtained in step 113[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
14. Process to Generate Boundary FlowsStep 1Generate static boundary flows using an optimization procedureDecision variables: boundary flowsData:Split ratios as specified previouslyTarget flows to matchMeasured flows from loop (calibration dataset), where availableFlows from racetrack study, then scaled down by 6% or down by 35%Default values, when loop and racetrack data unavailableObjective: minimize RMSE between simulated and target flows14[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]weight of measurementSet of locations where target flows are available
15. Process to Generate Boundary FlowsStep 1Choice of weight values wij in objective functionBased on data credibilityLoops 2014: are considered very credible w = 1Racetrack 2006: used if loop not available w = 1Default values: not very credible, used to nudge system towards realistic values w = 0.215[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]weight of measurementSet of locations where target flows are available
16. HuntingtonSanta Anita1st2nd5thGatewayI210WI210ESanta ClaraColorado PlColoradoMichillindaBaldwin / OxfordColorado BlvdColorado PlColorado BlvdI210WHuntington51923010651016103081447721010875178121297553803119373679232210357084156701270940370223766Hourly flow from loop (calibration dataset)Hourly flow from racetrack, scaled down by 35%Hourly flow from racetrack, scaled down by 6%Default values200200100200200200200Color coding:Target Flows used in Boundary Flow Optimization Program to Minimize Error to Simulated Flow16[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
17. Single intersection17Decision VariableBoundary flowsDataMeasured flowsSplit ratiosweightsObjective function EWSNNinSinWoutWinEinEoutRWTWLWLETERELNTNRNRSTSLS
18. Multiple intersections18EWN1Nin1Sin1Wout1Win1Ein1=Wout2RW1TW1LW1LE1TE1RE1LN1TN1RN1RS1TS1LS1NinSin2Ein2Eout2RW2TW2LW2LE2TE2RE2LN2TN2RN2RS2TS2LS2N2S1S2Eout1=Win2
19. HuntingtonSanta Anita1st2nd5thGatewayI210WI210ESanta ClaraColorado PlColoradoMichillindaBaldwin / OxfordColorado BlvdColorado PlColorado BlvdI210WHuntingtonOptimal Static Boundary Flows that minimize error between simulated and target flows709173220891503322285182003641664871059129785678231347127102819[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
20. Process to Generate Boundary FlowsSteps 2 and 3Step 2: Create generic flow profileStep 3: Scale generic flow profile of step 2 by optimal values obtained in step 1TimeFlowBoundary Flow Profile used in Forward Simulation16:0020:0022020[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
21. Signal Timings11 intersections: use given plans2 intersection: invented reasonable plansSanta Anita1st2nd5thGatewayI210WI210ESanta ClaraColorado PlBaldwin / OxfordMichillinda21[ Input for CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
22. OutlineArterial Loop+Racetrack No-Incident ModelModel components (with calibration set)Model runModel validation (with validation set)22
23. Westbound traffic on Huntington and Colorado23[ Output from CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]
24. Eastbound traffic on Huntington and Colorado24[ Output from CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]TODO: Scale the verticle axis properly
25. OutlineArterial Loop+Racetrack No-Incident ModelModel components (with calibration set)Model runModel validation (with validation set)25
26. Comparison26Data ProcessingComparison:Travel Time, FlowCalibration Data SetValidation Data SetThe ModelData ProcessingModel Components:FD / BF / SR / SignalsCTM Forward SimulationMetrics:TT, Delay, LOS, VHT, VMTComparison:Travel Time, FlowBluetooth Travel time5Loop flow3March: 3, 11, 13, 17, 18, 19, 25, 26, 31April: 3, 14, 16, 23, 28, 29May: 5, 6, 8, 12, 13, 15Calibration DaysValidation Days
27. Simulated vs. Measured FlowsHuntington27[ Validation of CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]Based on calibration datasetBased on validation dataset
28. Simulated vs. Measured Flows, 16:00-17:0028[ Validation of CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]Individual link flowsPassed casesTargetsFlow within 100 vph for link flows < 700 vph4/5 = 80%> 85%Flow within 15% for 700 vph < link flows < 2700 vph6/9 = 67%> 85%Flow within 400 vph for link flows > 2700 vph0/0> 85%GEH statistics < 510/14 = 71%> 85%Sum of all link flowsResultsTargetsRelative Error in Total Flow3.7%< 5%GEH3.1< 4
29. Simulated vs. Measured Flows, 17:00-18:0029[ Validation of CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]Individual link flowsPassed casesTargetsFlow within 100 vph for link flows < 700 vph4/5 = 80%> 85%Flow within 15% for 700 vph < link flows < 2700 vph6/9 = 67%> 85%Flow within 400 vph for link flows > 2700 vph0/0> 85%GEH statistics < 510/14 = 71%> 85%Sum of all link flowsResultsTargetsRelative Error in Total Flow2.9%< 5%GEH3.1< 4
30. Simulated vs. Measured Flows, 18:00-19:0030[ Validation of CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]Individual link flowsPassed casesTargetsFlow within 100 vph for link flows < 700 vph10/10 = 100%> 85%Flow within 15% for 700 vph < link flows < 2700 vph3/4 = 75%> 85%Flow within 400 vph for link flows > 2700 vph0/0> 85%GEH statistics < 513/14 = 93%> 85%Sum of all link flowsResultsTargetsRelative Error in Total Flow5.0%< 5%GEH4.7< 4
31. Simulated vs. Measured Flows, 19:00-20:0031[ Validation of CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]Individual link flowsPassed casesTargetsFlow within 100 vph for link flows < 700 vph8/12 = 67%> 85%Flow within 15% for 700 vph < link flows < 2700 vph2/2 = 100%> 85%Flow within 400 vph for link flows > 2700 vph0/0> 85%GEH statistics < 510/14 = 71%> 85%Sum of all link flowsResultsTargetsRelative Error in Total Flow22.4%< 5%GEH17.0< 4
32. Simulated vs measured travel times32[ Validation of CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]Simulated WB travel time from Gateway to Santa Clara averages 147s between 4pm – 6pmMeasured WB Bluetooth travel time (validation dataset) averages 153s between 4pm – 6pm
33. Simulated vs measured travel times33[ Validation of CTM Forward Simulation of Arterial Loop+Racetrack No-Incident Model ]Journey time within networkPassed casesTargetsWithin 15% or 1 minute, whichever criteria is higher1/1 = 100%> 85%Journey time within networkPassed casesTargetsWithin 15% or 1 minute, whichever criteria is higher1/1 = 100%> 85%16:00-17:0017:00-18:00