Abstract
As the demands on urban transportation networks grow rapidly, problems of network design have attracted a great deal of interest because of the need to effectively handle urban transport planning using information technology. A bi-level continuous network design model is proposed in this paper to address the optimal road capacity expansion of existing links. Based on the fact that every origin–destination demand is random and affected by traffic travel information, the network is subject to relatively minimal day-to-day events of stochastic link capacity variations. Therefore, the primary objective is to maximize the reliability of the total travel time, while the lower level model, utilizing the behaviors of stochastic route choice, is aimed at reducing drivers’ travel time uncertainty through traffic information provided by advanced traveler information systems. The Particle Swarm Optimization algorithm is used to solve the suggested model, and a numerical example using the Sioux Falls network is provided. The computation results show that travel time reliability is improved by system optimization using traffic information.
Published Version
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