ABSTRACT Autonomous vehicles (AV) can solve vehicle relocation problems faced by traditional one-way vehicle-sharing systems. This paper explores the deterministic time-dependent system optimum of mixed shared AVs (SAV) and human vehicles (SHV) system to provide the benchmark for the situation of mixed vehicle flows. In such a system, the system planner determines vehicle-traveller assignment and optimal vehicle routing in transportation networks to serve predetermined travel demand of heterogeneous travellers. Due to large number of vehicles involved, travel time is considered endogenous with congestion. Using link transmission model (LTM) as a traffic flow model, the deterministic time-dependent system optimum is formulated as linear programming (LP) model to minimize the comprehensive cost including travellers’ travel time cost, waiting time cost and empty vehicle repositioning time cost. Numerical examples are conducted to show system performances and model effectiveness.

中文翻译：

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面向异构出行者的共享自主和人类车辆系统的动态系统优化性能

摘要 自动驾驶汽车 (AV) 可以解决传统单向车辆共享系统面临的车辆搬迁问题。本文探讨了混合共享自动驾驶汽车 (SAV) 和人类车辆 (SHV) 系统的确定性时间相关系统优化，为混合车辆流动的情况提供基准。在这样的系统中，系统规划器确定交通网络中的车辆-旅客分配和最佳车辆路线，以满足异类旅客的预定旅行需求。由于涉及大量车辆，交通时间被认为是拥堵的内生因素。使用链路传输模型（LTM）作为交通流模型，将确定性时变系统优化公式化为线性规划（LP）模型，以最小化包括旅客出行时间成本在内的综合成本，等待时间成本和空车重新定位时间成本。进行数值示例以显示系统性能和模型有效性。