多模式城市交通网络均衡包含换乘和共享出行服务
Multimodal urban transportation network equilibrium including intermodality and shared mobility services
AI总结：
本文研究多模式交通系统中共享出行服务对交通均衡的影响，提出包含多种出行方式的交通分配模型，通过混合整数双曲线性规划方法分析用户均衡与系统最优之间的差异。
摘要：
共享出行服务（SMSs）通过提供灵活的出行选择，正在改变城市交通系统。这些服务有助于减少道路上的汽车数量，有潜力提高交通系统的性能，从而改善旅行时间和排放。本文强调了评估其对系统和用户选择的影响的重要性，特别是在复杂多模式系统中整合公共交通（PT）时。然而，许多研究忽视了SMSs与PT之间的协同作用，导致交通估计和规划不准确。本文提出了一个多模式交通系统模型的全面回顾，包括SMSs。随后引入了一个多模式交通分配模型，涵盖了城市交通系统中几乎所有出行选项，并适用于连续和整数设置，从而得到混合整数双曲线性规划（MIBLP）公式。该模型包含多种出行选项，包括SMSs，并通过允许通勤者结合不同出行方式来优化时间和费用，实现了换乘。对两个测试案例中通勤者出行方式和路径选择的深入分析，以及对价格的分析，揭示了在复杂网络中用户均衡与系统最优之间的差异。
英文摘要：
Shared Mobility Services (SMSs) are transforming urban transportation systems by offering flexible travel options. These services, which help reduce the number of cars on the roads, have the potential to enhance the transportation system's performance, leading to improvements in travel times and emissions. This emphasizes the importance of assessing their impact on the system and users' choices, particularly when integrated into complex multi-modal systems that include public transport (PT). However, many studies overlook the synergies between SMSs and PT, leading to inaccurate traffic estimations and planning. This research presents an extensive review of multi-modal transportation system models incorporating SMSs. It then introduces a multimodal traffic assignment model including almost all mobility options in urban transportation systems applicable in both continuous and integer settings, leading to a Mixed-Integer Bilinear Programming (MIBLP) formulation. The model comprises diverse travel options, including SMSs, and accounts for intermodality by allowing commuters to combine modes to optimize time and monetary expense. An in-depth examination of commuters' mode and path choices on two test cases and an analysis of the price of anarchy reveals the disparities between user equilibrium and system optimum in such complex networks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
