A Toll Choice Probability Model Application to Examine Travel Demand at Express and Electronic Toll Lanes in Maryland 14 th TRB Planning Applications Conference May 5-9, 2013 Columbus, Ohio By Sabyasachee Mishra (University of Memphis) Birat Pandey (Baltimore Metropolitan Council) Timothy Welch (University of Maryland) Charles Baber (Baltimore Metropolitan Council) Subrat Mahapatra (Maryland State Highway Administration)
A Toll Choice Probability Model Application to Examine Travel Demand at Express and Electronic Toll Lanes in Maryland. By Sabyasachee Mishra (University of Memphis) Birat Pandey (Baltimore Metropolitan Council) Timothy Welch (University of Maryland ) - PowerPoint PPT Presentation
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A Toll Choice Probability Model Application to Examine Travel Demand at Express and Electronic Toll Lanes in
BySabyasachee Mishra (University of Memphis)Birat Pandey (Baltimore Metropolitan Council)
Timothy Welch (University of Maryland)Charles Baber (Baltimore Metropolitan Council)
Subrat Mahapatra (Maryland State Highway Administration)
Motivation
Enhance existing work Previous toll diversion models: all-or-nothing path choice
decision Disaggregate VOT in mode choice and traffic assignment Binary choice logit (probabilistic) model Analytical tool capable of producing detailed tolled
facility use Better decision support tool
Background
Ranked 19th in Population(5.8 million, 2010)
Ranked 5th in Population Density
By 2040, Maryland will have 1.1 million more people, and 0.4 million more jobs
Agencies Involved
State CountiesMD 24VA 19PA 9WV 8DE 3DC 1Total 64
Toll Facilities
Travel Model Structure
Regional Model Statewide Model
National/State/MPO Land Use Forecasts
SE Data Reconciliation
Trip Generation
Trip Distribution
Mode Choice
Trip Generation
Trip Distribution
Time of day split
Urban ModelReconciliation
Multiclass Assignment
Disaggregation
TrucksPerson Travel
Flow Estimation
EI/IE/EE tripsEI/IE/EE trips
II trips II trips
PersonLong-Distance Travel Model
NHTS FAF 3
Toll Choice Model Design
Trip Generation
Trip Distribution
Mode Choice
Traffic Assignment
MSTM Model Structure
Auto TripsModification
Toll Choice Calculation
Traffic Assignment
MSTM Toll Model Structure
Toll Share
Toll Share = 1/ (1 + eα*ΔT + β*Cost/ln(Inc) + c + etcbias) Where e = Base of natural logarithm (ln)
ΔT = time saving between toll road and non-toll road travel, in minutes
Cost = toll cost in dollars
Inc = household annual income (in thousands)
α = time coefficient
β = cost coefficient
c = toll road bias constant
etcbias = bias towards selecting toll routes with ETC payment
Toll Probability Function by Trip Purposes
Scenarios
Two scenarios are also examined. 20% increase of 2030 50% increase of 2030
Comparison is presented in Toll trip origins Toll trip destinations Elasticity of income classes
Toll Trip OriginsScenario-I
Scenario-II
20%
In
crea
se
50%
Increase
Toll Trip DestinationsScenario-I
Scenario-II
20%
Incr
eas
e
50%
Increase
Demand Elasticity
Income Quintile
Volume Class Quartile Lower Lower-middle Middle Upper-middle Upper