Modeling Drivers’ Route Choice Behavior, and Traffic Estimation and

Prediction

Byungkyu Brian Park, Ph.D.Center for Transportation Studies

University of Virginia

DriveSense14 Workshop, Norfolk, VA

Drivers’ Route Choice Model

• Existing literature– Considers disaggregate information but ends up

with an aggregate model • Can we consider a model for each driver?

– Seems feasible with connected vehicle and smart phones and driver’s opt-in

Traffic Estimation & Prediction

• Estimates existing network condition using probe vehicles

• Estimates origin destination matrices for next 15-30 minutes

• Predicts future traffic conditions by assigning the OD matrices

• Evaluates multiple operational strategies and recommends best strategy

Motivation

• Weather vs. Route Guidance

Connected Vehicle Technology

• Wireless communications among vehicles and infrastructure

Questions on the Route Guidance

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Will connected vehicle technology improve the quality of route guidance?

What happens if multiple route guidance strategies were implemented? Will they cancel-off benefits?

Route Guidance System• Assumptions

– Every equipped vehicle provides its origin-destination information (opt-in)

– No Communications Loss• Perfect communications V-2-I and V-2-V

– On-Board Equipment (OBE or OBU) Vehicles• Act as probe vehicles

Route Guidance System• Assumptions (cont’d)

– Guided Drivers• Time varying traffic assignment• A link-weighted K-Shortest Path algorithm to create

reasonable path alternatives• Time dependant minimum travel time path

– Unguided Drivers• Static assignment• Fixed shortest distance path

Microscopic Traffic Simulation Model - VISSIM

• Microscopic, Time-step

based simulation model• Simulate traffic operations

in urban streets and freeways• Emphasize multi-modal

transportations (Bus, LRT, Heavy

Rail, etc.)

OverviewOverview

Microscopic Traffic Simulation Model – VISSIM (cont’d)

Traffic Flow ModelTraffic Flow Model Signal Control ModelSignal Control Model

Microscopic Traffic Simulation Model – VISSIM (cont’d)

• Various measures of effectiveness

(e.g., delay, travel time, queue

length, etc.)

• 2D & 3D animations

OutputOutput

Route Guidance Strategies

Guidance Strat-egy

Acro-nym

Major Information from VII

Latest Travel time -based Guidance LTG The latest link travel time

Averaged Travel time-based Guidance ATG The average of link travel

times

Routing Travel time-based Guidance RTG

Individual vehicles’ travel times of directional movements

Predicted Travel time-based Guidance PTG

Individual vehicles’ origin- destination tables

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• Travel time of directional movements at an intersection

• Gathers all individual directional travel time through individual vehicles’ trajectory

Routing Travel time-based Guidance (RTG)

Predicted Travel Time-Based Guidance (PTG)

Simulationfor current state estimation

OD table Extraction

Simulationfor link travel time prediction

Converged?

PredictedLink Travel Time

Generation ofPrediction-based Guidance

• Based on DynaMIT program (i.e., Traffic Estimation and Prediction)

• Travel info (origin-destination) obtained from equipped vehicles

Route Guidance System Evaluation• Simulation Test-Bed

– Microscopic Traffic Simulator: VISSIM– A Hypothetical Urban Network

• 118 Road Segments including

- a freeway - a major arterial

• 21 Signalized Intersections• 9 All-Way-Stop Control• 25 Origin/Destination

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Experimental Design

• Experimental factors and levels

• Experimental setup– Single operation : Total 2175 simulation runs

and 1197 computer hours– Multiple operation : Total 150 simulation runs

and 93 computer hours– Made 5 replications for each simulation

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Benefits of CV-based guidance strategies

• Single operation of guidance strategies

• Multiple operation of guidance strategies

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Benefits of individual strategies• All guidance strategies produced

benefits – Single operation of guidance

strategies

– Multiple operation of guidance strategies

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Impact of Market Penetration RateVH

T (

Vehic

le-H

ours

)

gudanceMP

PTGRTGATGLTGBASE100703051007030510070305100703050

1100

1000

900

800

700

600

500

400

300

Boxplot of VHT

Proposed Research

• Bundle drivers’ route choice behavior model and traffic estimation & prediction system

• How? – Develop each driver’s route choice behavior

model and keep model parameters on his/her smartphone or cloud

– Implement driver’s route choice behavior model in TrEP

Where Are We?

• Just completed IRB training! • Developed survey questionnaire to

understand drivers’ characteristics and their stated preferences

• Evaluate drivers’ route choice behavior using driving simulator