“工程管理论坛”系列讲座
( 2023年第14期，总第28期)
题目:Designing a Forward-looking Matching Policy for Dynamic Ridepooling Service动态拼车的前瞻性派单策略
主讲人：王晓蕾，同济大学教授
时间：2023年10月12日（星期四）下午15:00
地点：新主楼A716
主持人：郭仁拥教授
讲座语言：中文
Abstract
The fast development of information technologies in recent decade has greatly facilitated large-scale implementation of dynamic ridepooing services, e.g., Uber Pool, Didi Pinche. In dynamic ridepooling services, service providers respond to on-demand mobility requests immediately, dispatch (vacant or partially occupied) vehicles in real-time, and keep searching for matching orders along the trip. Most existing dispatching strategies ignore forthcoming matching opportunities, therefore having short-sighted limitations. In this paper, we argue that the system may benefit from strategically giving up certain current matches, and propose a probabilistic matching policy under which appeared matching opportunities are accepted with varying probabilities. Assuming that each ridepooling passenger shares vehicle space with at most one another during the entire trip, and ridepooling orders between each OD pair appear following a Poisson process with a given rate in each study period, we propose a system of nonlinear equations to predict the system performance and the matching potential of each OD pair under any probabilistic matching policy. Based on the model, we then propose an efficient solution algorithm to optimize the probabilistic matching policy (i.e., the acceptance probability of each match) for minimal expected total ride distance per unit period. The optimized probabilistic matching policy allows us to make decisions encompassing a consideration of all potential matches during each trip; therefore, it has a forward-looking feature. Through simulation experiments conducted on grid networks and the real road network of Haikou (China) utilizing a real order dataset, we demonstrate that our model yields accurate predictions of the average ride/shared distance for each origin-destination (OD) pair across various matching policies. Furthermore, the optimal matching policy generated by our method can reduce the average total ride distance per unit period by over 5% when demand is high.
个人简介：
王晓蕾，同济大学经济与管理学院教授，同济大学青年“五四”奖章获得者，同济大学“三八红旗手”。2008年本科毕业于中国科技大学，2012年博士毕业于香港科技大学，就读期间曾分别获得郭沫若奖学金和SENG PhD Research Excellence Award。长期从事城市交通系统管理方向的研究，主要在城市交通需求管理政策设计和共享出行服务运营优化两个方面取得了一系列成果。发表SCI/SSCI论文20余篇，其中11篇发表于交通领域顶级期刊《Transportation Science》和《Transportation Research Part B》，篇均引用77。主持和参与国家自然科学基金7项，2020年获自科优秀青年基金资助，创新群体“综合运输系统运营管理”项目骨干成员。
