Influence of dynamic congestion with scheduling preferences on carpooling matching with heterogeneous users
研究了动态交通拥堵与用户调度偏好如何双向影响异质性用户的拼车匹配，构建了双层优化模型并给出启发式算法，适合交通经济学和运筹学研究者判断是否深入阅读。
Carpooling is an efficient measure to fight car ownership and reduce vehicle kilometres travelled. By individuals sharing their commutes, vehicle occupancy increases and congestion is reduced. We develop a dynamic ADL (Arnott, de Palma, Lindsey)–Vickrey approach for a corridor monocentric city à la Hotelling. First, we formulate the matching problem of heterogeneous users in carpooling as an MILP problem and we discuss its analytical properties when there is no congestion. Next, we construct a bi-level optimization problem involving matching (first stage) and dynamic traffic congestion with scheduling preferences (second stage) when congestion is endogenous. We provide a heuristic to attain an optimal matching for a dynamic traffic equilibrium with congestion. Such a template allows studying the two-way causality between dynamic congestion and carpooling matching.