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Experiment in Megaregional Road Pricing Using Advanced Commuter Behavior Analysis
Worsening highway congestion is a challenge to megaregional competitiveness; changing regional geographies and development location decisions, among other factors, demand that public policy responses go beyond traditional demand-management approaches. Congestion-pricing has been suggested as a remedy. In this paper, the writers analyze the outcomes of multiple congestion-pricing approaches for the capital megaregion that spans the following five metropolitan planning organization regions: (1) Washington (District of Columbia, Maryland, and Virginia), (2) Baltimore (Maryland), (3) Wilmington (Delaware), (4) Fredericksburg (Virginia), and (5) Frederick (Maryland), in addition to counties in the adjoining states of New Jersey, Pennsylvania, and West Virginia in the United States. Using a megaregional travel-demand model, the writers incorporate different values-of-time (VOTs) for travelers under different conditions. However, unlike past approaches, the writers’ VOT estimates go beyond income categories and include trip purposes across a number of scenarios. The writers demonstrate that adding the trip purpose to congestion-price determination provides added insight both at the megaregional level and for individual subregions. The results of this paper show how highway users respond differently and (in some cases) in unexpected ways to congestion charges when trips in accordance with income and purpose are assigned a unique VOT. The findings reported in this paper provide engineers, planners, and policymakers with a new analytical approach to measuring traveler elasticity to tolls while demonstrating the complexity involved with road-pricing mechanisms. The writers conclude with implications for adopting this approach and ideas for implementing them in a complex institutional setup.
Experiment in Megaregional Road Pricing Using Advanced Commuter Behavior Analysis
Worsening highway congestion is a challenge to megaregional competitiveness; changing regional geographies and development location decisions, among other factors, demand that public policy responses go beyond traditional demand-management approaches. Congestion-pricing has been suggested as a remedy. In this paper, the writers analyze the outcomes of multiple congestion-pricing approaches for the capital megaregion that spans the following five metropolitan planning organization regions: (1) Washington (District of Columbia, Maryland, and Virginia), (2) Baltimore (Maryland), (3) Wilmington (Delaware), (4) Fredericksburg (Virginia), and (5) Frederick (Maryland), in addition to counties in the adjoining states of New Jersey, Pennsylvania, and West Virginia in the United States. Using a megaregional travel-demand model, the writers incorporate different values-of-time (VOTs) for travelers under different conditions. However, unlike past approaches, the writers’ VOT estimates go beyond income categories and include trip purposes across a number of scenarios. The writers demonstrate that adding the trip purpose to congestion-price determination provides added insight both at the megaregional level and for individual subregions. The results of this paper show how highway users respond differently and (in some cases) in unexpected ways to congestion charges when trips in accordance with income and purpose are assigned a unique VOT. The findings reported in this paper provide engineers, planners, and policymakers with a new analytical approach to measuring traveler elasticity to tolls while demonstrating the complexity involved with road-pricing mechanisms. The writers conclude with implications for adopting this approach and ideas for implementing them in a complex institutional setup.
Experiment in Megaregional Road Pricing Using Advanced Commuter Behavior Analysis
Mishra, Sabyasachee (Autor:in) / Welch, Timothy F. (Autor:in) / Chakraborty, Arnab (Autor:in)
19.07.2013
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Experiment in Megaregional Road Pricing Using Advanced Commuter Behavior Analysis
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