Park and Ride Behavior in Stochastic Multimodal Network under ATIS
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摘要: 为考察交通信息对停车换乘行为的影响,建立了随机多方式交通网络均衡模型.其中,假设出行方式有小汽车、步行换乘地铁和停车换乘3种;出行者按有无信息装置分为2类,其出行方式、旅行路径/线路和停车设施选择决策基于Probit模型,以随机方式进行.构建了与均衡条件等价的变分不等式模型,并采用基于模拟的启发式算法求解该模型.算例结果表明,信息质量对停车换乘行为、设施利用率以及信息装置市场占有率有明显影响.Abstract: To investigate the effects of ATIS(advanced traveler information system) on P&R(park and ride) behavior,a multi-class network equilibrium formulation was proposed in a stochastic multi-modal network.The formulation is based on the following assumption that commuters can complete their journeys by three approaches,i.e.,auto mode,walk-metro mode and P&R mode,and make their travel decisions following a Probit-based stochastic manner whether they are equipped or unequipped with ATIS.A variational inequality model equivalent to the equilibrium conditions was established and solved using a simulation-based heuristic algorithm.Numerical results show that the quality of information has a significant influence on P&R behavior,P&R facility usage and ATIS market penetration.
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