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Dynamic Tolling Assignment Model for Managed Lanes. presented to Advanced Traffic Assignment Sub-Committee presented by Jim Hicks, Parsons Brinckerhoff September 14, 2012. Overview. Prior discussions on Managed Lanes in Florida Features of Phase I Model Implementing and Testing Model
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Dynamic Tolling Assignment Model for Managed Lanes presented toAdvanced Traffic Assignment Sub-Committee presented byJim Hicks, Parsons Brinckerhoff September 14, 2012
Overview • Prior discussions on Managed Lanes in Florida • Features of Phase I Model • Implementing and Testing Model • Results of Model • Discussion
Conceptual Requirements • Flexible – able to accommodate most “flavors” of managed lanes within a unified approach • Behaviorally Sensitive – Includes variables that are important to selection and use of a managed lane • Policy Sensitive – Has the ability to test different Managed Lane Policies (e.g., tolls, congestion sensitive) • Ease of use – Model implementation compatible with FSUTMS and a reasonable runtime • Understandable – No “black boxes”
Managed Lane “Flavors” • HOV - only • Express Lanes • Truck Only • Reversible lanes • HOT – SOV pay • Dynamic Tolling • Open Road Tolling • Dedicated Facilities • Pre-pay and/or Pay per use (toll booths) • ITS Solutions (Traffic calming, speed advisories, incident management)
Behavioral Variables • Time savings • Cost • Trip Purpose • Income/Value of time • Time of Day • Household Structure (e.g. daycare?) • Employment type (on-time requirements)
Managed Lane Policy Dimensions • Willingness to pay – toll cost per minute saved • Toll Cost – congestion related • Separate managed lanes and general purpose lanes
Data Requirements • Willingness to Pay • Toll Cost as a function of congestion level • Auto Demand • Highway Network
Willing to Pay Proportions • Toll Cents per Minute Saved by Demand Category • 1 2 3 4 5 6 7 8 • 0 5 5 5 5 5 5 5 5 • 8 50 50 50 50 50 50 50 50 • 10 60 60 60 60 60 60 60 60 • 16.3 75 75 75 75 75 75 75 75 • 20 81.7 81.7 81.7 81.7 81.7 81.7 81.7 81.7 • 23.7 85 85 85 85 85 85 85 85 • 31.4 90.5 90.5 90.5 90.5 90.5 90.5 90.5 90.5 • 41.7 95 95 95 95 95 95 95 95 • 51.8 96 96 96 96 96 96 96 96 • 58.3 98 98 98 98 98 98 98 98 • 66.7 98.8 98.8 98.8 98.8 98.8 98.8 98.8 98.8
Application Flow One Assignment Iteration Phase ILOOP Skim Tolls and times WTP and Toll Policy Curves Define toll segments and initial toll values Phase ILOOP In Jloop, compute toll & nontoll demand Phase ILOOP Assign toll & non-toll in multiclass assignment Phase ADJUST Compute Max VC on toll segments & new toll by segment
Testing Dynamic Toll Calculations iteration start end segment pay toll V/C node node 1 93354 93358 1 0 25 0 1 93358 93359 1 0 25 0 1 93359 93362 1 0 25 0 1 93362 93363 1 0 25 0 2 93354 93358 1 21186 304 0.86 2 93358 93359 1 21186 304 0.86 2 93359 93362 1 21186 304 0.86 2 93362 93363 1 21186 304 0.86 3 93354 93358 1 28159 800 1.14 3 93358 93359 1 28159 800 1.14 3 93359 93362 1 28159 800 1.14 3 93362 93363 1 28159 800 1.14
Adaptations • Fixed Toll – subset of toll policy • Allows multiple toll policies • Allows for multiple markets • income stratified • Purpose Stratified • Can still do accell/decell at toll booths
Strengths • Planning Level Application • No a priori assumption of toll • Assures no congestion on toll facility • Useful tool for evaluating LOS / Revenue Goals • Testing toll policies • Customized for WTP
Weaknesses • No mode shift assumed from transit • Congestion represented in daily assignment • Statewide model application • No sensitivity to SE data of travelers
FSUTMS Apps? • Urban HOT lanes • Urban Tolled Freeways • Rural Turnpike? – willingness to pay characteristics need evaluation • Not sufficient for multi-modal corridors, but could play a role