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A Side-Constrained Peer-to-Peer Carpooling Stochastic User Equilibrium Model

机译:侧约束的对等拼信号随机用户均衡模型

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Peer-to-peer (P2P) carpooling has become an effective way to utilize the idle car capacity and ease traffic congestion. However, the interactive relationship between carpooling and traffic congestion has not been fully quantified. To make up for this gap, this paper constructs a side-constrained P2P carpooling stochastic user equilibrium model to disclose the effects of carpooling on traffic congestion. Next, the proposed model was transformed into a linear constrained minimization problem, and the problem was proved to have a unique solution. The case study shows that the travellers prefer carpooling at a high fuel price and a low inconvenient cost.
机译:点对点(P2P)拼车已成为利用怠速汽车能力和缓解交通拥堵的有效方法。 然而,拼车和交通拥堵之间的互动关系尚未完全量化。 为了弥补这种差距,本文构建了一个副约束的P2P拼线随机用户均衡模型,以揭示拼车对交通充血的影响。 接下来,将所提出的模型转换为线性约束最小化问题,并证明了问题具有唯一的解决方案。 案例研究表明,旅行者更喜欢以高燃料价格和低不方便的成本拼接。

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