lili (leo) luo, p.e., its & safety engineer

Can Multi-Resolution Dynamic Traffic Assignment live up to the Expectation of Reliable Analysis of

Incident Management Strategies

Lili (Leo) Luo, P.E., ITS & Safety EngineerSarath Joshua, P.E., Ph.D., ITS & Safety Program Manager

13th TRB Planning Application Conference

Basic need for evaluation of ITS operational strategies

Low cost Efficient Reliable Capable of evaluating area

wide impact


How did we get started? Neither the static Macroscopic Travel

Demand Model nor the Microscopic simulation model met our needs

Decision to test the emerging Mesoscopic simulation-based DTA model through a Case Study


The Case Study Approach Convert the 4-step TDM model into DTA

(DynusT) model Study a major freeway traffic incident that

occurred on I-10 during morning peak period Calibrate the subarea baseline (Normal)

model Perform scenario analysis Convert stretch of interest into microscopic

simulation model for visualization The modeling effort was conducted in house

at MAG


Purpose of the case study Test if the DTA model can be used as

an operations planning tool to evaluate strategies

Obtain hands-on experience on DTA model from model calibration to scenario analysis

Experiment with the concept of Multi-Resolution modeling method


MAG Regional DTA model 2006 TAZs Over 10,000

SQ Miles 20508 Links 9893 Nodes 2364

Signalized intersections

2.78M Trips during 5 hours of morning peak


Impacted Area of a major Incident


Model Calibration—Count Calibration

87 sensors Collected

over a three year time frame

0 2000 4000 6000 8000 10000 12000 14000 16000 180000

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

DUE Count Calibration

UE


Model Calibration – AM Peak Period Travel Time V.S. GPS Run

Freeway Morning Peak Period GPS Run Travel Time Model Travel Time

I-10 WB 46MIN 24SEC 46MIN 30SEC


US60 WB 20MIN 20MIN 30SEC


202 Santan WB 5MIN 5MIN 24SEC


202 RedMountain WB 20MIN 18MIN 54SEC


101 NB 32MIN 31MIN


143 NB 5MIN 4MIN 42SEC


Space-Time Diagram showing bottleneck locations

Loop202 Red Mountain WB

5:00

10:0

0L1

01

Rur

al

24th S

t

Airp

ort

Loop 101 NB

Fry

US60

5:00 10:00

McKellipsUS 60 WB

5:00

10:

00

Loop

101

Rur

al R

d

Mill

Ave

I-10

Prie

st D

r.

Loop 202 Santan WB

5:00

10:0

0L1

01

Kyr

en

I-10


Time-Dependent Travel Time By Freeway


Real-life Incident

February 4, 2010 Location: Salt River

Bridge on I-10 Westbound

Time 6:20AM Duration: 3 hour 20

minutes Severity: Three lanes

blocked all the time, I-10 completely shut down three times.


Incident Scenario

Scenario 0 — Baseline (Normal Condition)

Scenario 1— With ITS Infrastructure (DMS and Ramp Metering) turned on

Scenario 2 — Without ITS Infrastructure


Traveler Information and Congestion Response Pre-trip and In-route information DMS congestion warning Driver congestion response behavior


Scenario 1 With ITS Infrastructure


Scenario 1: With ITS infrastructure Tempe to Downtown Phoenix Travel

TimeSouth Tempe & Northwest Chandler

Downtown Phoenix

South Tempe/Northwest Chandler To Phoenix Downtown Travel Time

Baseline Incident With DMS & Ramp Meter

28 Min 52 Min


Affected Routes


3 Mile Upstream of Crash Site on I-10


Samples of impacted vehicle

Vehicle ID: 682622 Departure Time: 7:02 AM

Origin:Santan Freeway @ Alma School Road

Destination: Glendale Avenue @ 16th Street

Scenarios BaselineDMS & Ramp

MeteringTravel Time 78MIN 139MIN


Another Vehicle

Vehicle ID: 481654 Departure Time: 6:40 AM Origin: US 60 @ Dobson RdDestination: Dunlap Ave @ 43th Ave




Scenario 2 (No ITS Infrastructure) Tempe to Downtown Phoenix Travel

Time

South Tempe & Northwest Chandler

Downtown Phoenix

South Tempe/Northwest Chandler To Phoenix Downtown Travel Time

BaselineIncident without ITS Infrastructure

28 Min 51 Min


Scenario 2 (No ITS Infrastructure)


Baseline VS incident with ITS VS Incident without ITS


Scenario 2 (No ITS Infrastructure)


Vehicles under No ITS scenario



Destination: Glendale Avenue @ 16th StreetScenarios Baseline No ITSTravel Time 45MIN 123MIN



Destination: Glendale Avenue @ 16th Street




Another Vehicle


ScenariosBaseline Incident Without ITS

Travel Time 45MIN 129MIN


ScenariosBaseline Incident with DMS &

Ramp MeteringTravel Time 45MIN 110MIN


Summary Vehicle Hours Travel (VHT)

Freeways Baseline DMS & Ramp MeterNo ITS

infrastructure

I-10 4154.858 6004.067 6196.473

US60 4413.682 6795.597 6891.945

L202RedMountain 2698.81 2885.447 2848.178

South Tempe/Northwest Chandler To Downtown Phoenix Travel Time

Baseline Incident with DMS & Ramp Meter

Incident without ITS infrastructure

28 Min 52 Min 51 Min


Meso-Micro conversion Selected area subarea cut for VISSIM micro

simulation using DynusT-VISSIM converter All time-dependent routes and flows are

converted A little more network clean up More detail timing and crash setup


VISSIM Microscopic Simulation


Conclusions Mesoscopic Simulation-based DTA

model DynusT: Capable of demonstrating the status of

our freeway system operation in a capacity restraint and time-dependent manner.

Able to match field observed data following relatively simple procedure for model calibration.


Conclusions Logical scenario analysis outcomes Demonstrate the benefit of traveler

information/ITS during an incident with region wide impact

Reasonable cost and effort Combined with Macro and Micro models

for Multi-Resolution Modeling to answer complicated questions

Appear useful for operations planning


Lessons Learnt Leverage data collection efforts with Travel

Demand Model More sensitive to network and data errors

—Very Important!!! Could extract more useful information from

the model Start with the entire regional model


Questions

Email: [email protected]: 602-452-5072

mailto:[email protected]

lili (leo) luo, p.e., its & safety engineer

Documents

peak period travel time

final travel time calibration

microscopic simulation

morning peak periodcalibrate

hours of morning peak

step tdm model

major incident

major freeway traffic