Developing a Toll Demand Model for DelDOT s Statewide Travel Demand Model

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Developing a Toll Demand Model for DelDOT s Statewide Travel Demand Model TRB 87 th Annual Meeting Washington, D.C. Introduction DelDOT is facing the same deteriorating infrastructure, increasing congestion and funding shortfalls as state agencies throughout the country. They are more frequently considering tolling as an option for funding major transportation investments and increasing transportation revenue. 1

Introduction DelDOT set out to develop an improved toll demand model that would be sensitive to a variety of tolling policies. Background Existing Tolling DelDOT has two limited access toll roadways: I-95 SR 1 Additional Toll Bridges: Chesapeake Bay Bridge (US 50) Delaware Memorial Bridge (I-295) { tu50 tu 301 Legend Toll Plaza Toll Roadway Pennsylvania Maryland NEWARK tu 301 95 tu 301 «9 «404 95 WILMINGTON DOVER tu 13 New Jersey tu 113 Delaware Bay Delaware tu 9 tu13 «24 50 tu 2

Background Existing Tolling Toll Collection Methods: Cash E-ZPass Standard Highway-Speed Frequency of Use HOV Background Existing Model DelDOT s Statewide Travel Demand Model (Peninsula Model) Four-step model with Feedback Mode Choice model Assignment with Tranplan Logit Toll Diversion Model Peak Season Model 3

Model Selection Current State-of-the-Practice Toll Models Part of Activity Based Model Post Processor Sketch-Planning Model in Traffic Assignment Model in Mode Choice Model Selection Model in Traffic Assignment Benefits Easy to implement No re-calibration of Mode Choice Explicitly account for peak congestion 4

Model Selection Model in Traffic Assignment Drawbacks Not typically fed-back through trip distribution and mode choice Difficult to account for differences in toll use by trip type Does t account for TAZ demographics or travel characteristics Model in Mode Choice Benefits Model Selection Use existing mode choice utility function Improve estimation of highway utility Accounts for TAZ demographics and travel characteristics Accounts for value of time and operating cost by trip type Included in feedback 5

Model in Mode Choice Drawbacks Model Selection Potential for large mode specific constant Current model only implicitly accounts for peak periods in mode choice Model Selection DelDOT chose to develop an enhanced mode choice model. 6

Model Development DelDOT s existing mode choice model Choice Highway Transit SOV HOV Walk Drive Bus Rail Bus Rail Model Development DelDOT s revised mode choice model Choice Highway Transit SOV HOV Walk Drive Bus Rail No Toll Cash/E-ZPass No Toll Cash/E-ZPass Bus Rail 7

Model Development Revised Mode Choice Model Maintained variables and coefficients from existing model Determined nesting coefficients based on institutional knowledge Developed new E-ZPass ownership model Model Development E-ZPass Model E-ZPass ownership model Based on toll utilization and E-ZPass ownership data provided by DelDOT Utilization Data provided for each toll collection point: Cash, E-ZPass, HOV Vehicle Classification Frequency of Use 8

Model Development E-ZPass Model E-ZPass ownership data 109,735 accounts registered a payment 79% registered in Delaware s 65 zip codes { tu50 tu 301 LEGEND Toll Plaza Pennsylvania Toll Roadway E-ZPass Ownership Percentage 0.001-0.150 0.151-0.300 0.301-0.450 0.451-0.955 Maryland NEWARK tu 301 95 tu 301 «9 «404 95 WILMINGTON DOVER tu 13 New Jersey tu 113 Delaware Bay Delaware tu 9 tu13 «24 50 tu Model Development E-ZPass Model Variable Correlation Independent Variable Vehicles/Household Persons/Household Workers/Household Household Income ($) HBW Trips per Household HBW Trip Length (miles) Distance to Nearest Toll(miles) Impedance to Nearest Toll Proportion of Toll Trips Correlation -0.11 0.37 0.40 0.45 0.38 0.14-0.38-0.41 0.59 9

Model Development E-ZPass Model Final E-ZPass Ownership Models Initial Feedback Loop: Prob. = 0.00967 x HBW trip length + 0.00000389 x household income - 0.00248 x distance to nearest toll plaza Subsequent Loops: Prob. = 0.00427 x HBW trip length + 0.0000036 x household income - 0.7397 x proportion of toll trips Model Development Final Model Final Mode Choice Model Constant Shared Ride Constant Toll Constant Transit Constant Drive to Transit Constant Premium Constant Multinomial Coefficient -1.41 0.774-0.27-3.79 0.2 Nested Logit Coefficient -2.17 3.4-0.27-12.6 1.16 10

Model Development Calibration Calibration Results Toll Location Payment Method Count Model % Diff. I-95 Cash 40188 34985-13% E-ZPass 26106 24245-7% SR 1-Biddles Corner Cash 19615 20886 6% E-ZPass 21981 17935-18% SR 1-Dover Cash 16191 15908-2% E-ZPass 14793 13395-9% Case Studies Case Study: Old versus New toll results Biddles Corner 11

Case Studies Biddles Corner Toll Plaza Immediately South of C&D Canal with easy diversion NEWARK 95 tu 301 «9 New Jersey tu 301 Delaware Delaware Bay Maryland Case Studies Biddles Corner Easy Diversion after canal crossing Use the new bridge Don t pay toll What happens if DelDOT raises the toll? 12

Case Studies Biddles Corner Travel Demand and Revenue Results Case Studies Biddles Corner Travel Demand and Revenue Results 13

Case Studies Biddles Corner Travel Demand and Revenue Results Conclusions and Future Direction Tolling is being considered as a potential funding source on all major new projects. DelDOT developed a toll model that is sensitive to a variety of different policies such as toll rates, electronic toll collection, and policy decisions. It is closely tied to TAZ-level demographics and travel characteristics. 14

Conclusions and Future Direction It will be easy to enhance and update in the future. DelDOT is adding toll-related questions to their monthly surveys. Allow us to derive trip-type specific toll data Allow us to estimate E-ZPass ownership at household level Allow us to derive temporal toll use Conclusions and Future Direction DelDOT recently changed their toll policies. Tolls doubled on weekends Eliminated nighttime trucker discount HOV and E-ZPass discounts eliminated on SR1 Frequency of use discount remained the same 15

Conclusions and Future Direction Questions? Scott Thompson-Graves, PE, PTOE Associate Whitman, Requardt, and Associates, LLP 300 Seven Fields Blvd., Suite 130 Seven Fields, PA 16046 Phone (724) 779-7940 e-mail: stg@wrallp.com Michael DuRoss Transportation Planning Supervisor Delaware Department of Transportation Division of Planning P.O. Box 778 Dover, DE 19903 Phone (302) 760-2110 e-mail: Michael.DuRoss@State.de.us Li Li, PE Transportation Engineer Whitman, Requardt, and Associates, LLP 3701 Pender Drive, Suite 210 Fairfax, VA 22030 Phone (703) 293-9717 e-mail: lli@wrallp.com 16