Abstract:

The method to accurately simulate users travel behavior in the network design problem (NDP) is one of the most crucial problems. Most research in the network design problem ignores the unreliability as- pect of travel time. Specifically, the mean travel time (MTT), the travel time budget (TTB), and the α - reli- able mean-excess travel time (METT) are employed in the transportation network design problem under an uncertain environment due to stochastic link capacity. Numerical are presented to examine how these models affects decisions under the condition of travel time variability. The experimental results show that the perfor- mance of DRUE and METTUE is better than DUE which is employed in network design problem under vari- ation degrees because of considering travel time variability.

Key words: urban traffic, transportation network design, link capacity variation, travel time reliability, par- ticle swarm optimization

摘要：

交通网络设计问题中较为关键的问题之一是如何准确合理的反映网络用户 出行行为，符合实际的行为描述有助于决策者做出正确的决策.已有文献在用户均衡基础 上对网络设计问题做出研究,假设所有用户均为风险中性的，忽略了出行时间不确定性给 网络设计决策带来的差异性影响.本文在随机路段能力导致的不确定环境下，引入期望出 行时间（MTT）、出行时间预算（TTB）和 α -可靠性的平均额外行程时间（METT），并采用 数据结果对比分析不同用户均衡模式（DUE、DRUE、METTUE）对网络设计问题决策的 影响.实验结果表明，在不同路段能力随机变化程度下，考虑用户出行时间的不确定性因 素，较传统用户均衡更贴近现实，同时也为网络设计决策提供更准确的指导.

关键词: 城市交通, 交通网络设计, 路段能力随机变化, 出行时间可靠性, 粒子群算法