Abstract
AbstractThis paper develops a bilevel programming model to locate park-and-ride (PR the lower-level model is a stochastic user equilibrium one simulating commuters’ reactive behaviors, which in turn affects the P&R location decision at the upper level. The paper designs a scenario to compare the solutions under the optimization criterion of SW with that under two others: consumer surplus and producer surplus. Results indicate that adopting SW maximization as the optimization objective leads to a win-win outcome for both P&R service providers and users. The paper uses Chengdu City (in China) as a case study, and it is demonstrated that the proposed P&R locating framework is applicable to a large-scale network and compatible with the regional transportation planning procedure.
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