基于信息传播的互联和自主车辆激励式分散路由
Incentive-based Decentralized Routing for Connected and Autonomous Vehicles using Information Propagation
摘要：
文献中提出了动态交通分配下的路由策略，以优化系统性能。然而，由于对旅行者行为和网络级实时交通信息的可用性的固有强假设，以及与实时计算网络范围流量相关联的高计算负担，挑战一直存在于其部署能力和有效性中。这项研究提出了一种基于激励的分散式路由策略，以使网络性能更接近所有车辆连接和自动驾驶车辆（CAV）的情况下的系统最佳值。该战略包括三个阶段。第一阶段结合了一个分散的本地路径切换动态系统，以近似系统的最优路径流在本地区域的基础上车辆的本地交通信息的知识。第二阶段通过考虑旅行者偏好的个体异质性（例如，时间的价值）以最大化当地所有旅行者的效用。约束条件也被纳入，以确保这些路线可以实现近似的本地系统最优流量的第一阶段。第三阶段利用一个预期的无嫉妒的激励机制，以确保在当地的旅行者可以接受在第二阶段确定的最佳路线。解析地讨论了局部路由切换动力系统的收敛性。我们还表明，所提出的激励机制是预期的个人理性和利益平衡，这将确保旅行者愿意参与和保证支付和补偿之间的平衡，分别。进一步分析和证明了激励机制的期望激励相容条件，保证了信息披露行为的诚实性。
英文摘要：
Routing strategies under the aegis of dynamic traffic assignment have been proposed in the literature to optimize system performance. However, challenges have persisted in their deployment ability and effectiveness due to inherent strong assumptions on traveler behavior and availability of network-level real-time traffic information, and the high computational burden associated with computing network-wide flows in real-time. This study proposes an incentive-based decentralized routing strategy to nudge the network performance closer to the system optimum for the context where all vehicles are connected and autonomous vehicles (CAVs). The strategy consists of three stages. The first stage incorporates a decentralized local route switching dynamical system to approximate the system optimal route flow in a local area based on vehicles' knowledge of local traffic information. The second stage optimizes the route for each CAV by considering individual heterogeneity in traveler preferences (e.g., the value of time) to maximize the utilities of all travelers in the local area. Constraints are also incorporated to ensure that these routes can achieve the approximated local system optimal flow of the first stage. The third stage leverages an expected envy-free incentive mechanism to ensure that travelers in the local area can accept the optimal routes determined in the second stage. The study analytically discusses the convergence of the local route switching dynamical system. We also show that the proposed incentive mechanism is expected individual rational and budget-balanced, which ensures that travelers are willing to participate and guarantee the balance between payments and compensations, respectively. Further, the conditions for the expected incentive compatibility of the incentive mechanism are analyzed and proved, ensuring behavioral honesty in disclosing information.
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。
