Towards peak pricing in metropolitan areas : modeling network and activity impacts.
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Towards peak pricing in metropolitan areas : modeling network and activity impacts.

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  • English

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      Final report.
    • Abstract:
      Peak-load pricing has long been seen as a way to internalize externalities and, at the same time, as a set of incentives to shift some peak-hour trips to off-peak periods. The policy has also been viewed as a mechanism to generate revenues. But it is an open question how travelers trade off time for money and respond to peak-off-peak pricing differentials. This generates some timely and related questions, including: 1) How can we model the activity location and traffic implications for multiple time-of-day periods in a major metropolitan area? and 2) What are the network level-of-service and urban development effects of implementing peak-load pricing on selected routes? It is seemingly possible to conduct simulations on actual highway networks to treat these questions, but none of the many existing basic urban models is able to examine the issues of simultaneous route choice and time-of-day choice involving millions of travelers, thousands of traffic network zones, and hundreds of thousands of network links in an equilibrium system. This research addresses these questions by extending the Southern California Planning Model (SCPM) so that it can be used to determine the time-of-day, trip distribution, and network traffic effects of various pricing schemes for the greater Los Angeles (five-county) metropolitan area. The model estimates improvements in levels of services throughout the highway network for various toll charges. It examines how drivers trade off route-choice with time-of-day choice against the option of traveling less. Our approach also estimates the implied revenues by local jurisdiction as well as possible land use effects in terms of altered development pressures throughout the region. The effects for two different tolling scenarios are compared and policy implications are discussed.
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