Optimization method of alternate traffic restriction scheme based on elastic demand and mode choice behavior
mode - car, mode - park and ride, mode - mass transit
Urban traffic congestion, Alternate traffic restriction, Equilibrium analysis, Bi-level programming model, Multiple modes
As a countermeasure to urban traffic congestion, alternate traffic restriction (ATR) involves a certain proportion of automobiles being prohibited from entering pre-determined ATR districts during specific time periods. The present study introduces an optimization method for ATR schemes in terms of both their restriction districts and the proportion of restricted automobiles. As a Stackelberg game between traffic policy makers and road users, the ATR scheme optimization problem is established using a bi-level programming model, with the upper-level examining an ATR scheme aimed at consumers’ surplus maximization under the condition of overload flow minimization, and the lower-level synthetically optimizing elastic demand, mode choice (private car, public transit and park-and-ride) and multi-class user equilibrium assignment. A genetic algorithm based on the graph theory is also proposed to solve the bi-level programming model with a gradient project algorithm for solving the lower-level model. To our knowledge, this study represents the first attempt to theoretically optimize an ATR scheme using a systematic approach with mathematical model specification.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Shi, F., Xu, G., Liu, B., & Huang, H. (2013). Optimization method of alternate traffic restriction scheme based on elastic demand and mode choice behaviour. Transportation Research Part C: Emerging Technologies, Volume 39, February 2014, Pages 36–52
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