面向社会最优的新兴出行系统的控制框架
A Control Framework for Socially-Optimal Emerging Mobility Systems
AI总结：
本文提出一种控制框架，在交通网络中分配出行需求，以构建兼顾效率、抑制回弹效应并保障公平的社会最优出行系统。
摘要：
网联自动驾驶车辆（CAVs）通过监测网络状况并做出更优的运行决策，为用户显著提升安全性和交通效率提供了最具吸引力的机会。然而，CAVs可能改变出行倾向，最终导致高交通需求并引发回弹效应（例如车辆行驶里程增加）。本章提供了一个控制框架，用于在给定交通网络中分配出行需求，从而形成一个出行者愿意接受的社会最优出行系统。“社会最优出行系统”意味着该系统（1）是高效的（就能耗和出行时间而言），（2）能够缓解回弹效应，并且（3）确保交通公平性。
英文摘要：
Connected and automated vehicles (CAVs) provide the most intriguing opportunity for enabling users to significantly improve safety and transportation efficiency by monitoring network conditions and making better operating decisions. CAVs, however, could alter the tendency to travel, eventually leading to a high traffic demand and causing rebound effects (e.g., increasing vehicle miles traveled). This chapter provides a control framework to distribute travel demand in a given transportation network, resulting in a socially optimal mobility system that travelers would be willing to accept. A "socially optimal mobility system" implies a mobility system that (1) is efficient (in terms of energy consumption and travel time), (2) mitigates rebound effects, and (3) ensures equity in transportation.
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。
