论文标题
具有性能保证的共享自动电动汽车的实时调度策略
A Real-Time Dispatching Strategy for Shared Automated Electric Vehicles with Performance Guarantees
论文作者
论文摘要
传统汽车共享系统中的实时车辆派遣操作是已经具有挑战性的调度问题。电气化只会加剧计算困难，因为电荷级别的限制开始起作用。 To overcome this complexity, we employ an online minimum drift plus penalty (MDPP) approach for SAEV systems that (i) does not require a priori knowledge of customer arrival rates to the different parts of the system (i.e. it is practical from a real-world deployment perspective), (ii) ensures the stability of customer waiting times, (iii) ensures that the deviation of dispatch costs from a desirable dispatch cost can be controlled, and (iv) has一种计算时间复杂性，允许实时实现。使用为SAEV系统开发的基于代理的模拟器，我们在具有现实世界中校准的需求和充电器分布的两个方案下测试了MDPP方法：1）长途旅行的低需求方案，以及2）较短旅行的高点场景。在两种情况下，与其他算法的比较都表明，在减少客户等待时间和车辆调度成本方面，提议的在线MDPP均优于所有其他算法。
Real-time vehicle dispatching operations in traditional car-sharing systems is an already computationally challenging scheduling problem. Electrification only exacerbates the computational difficulties as charge level constraints come into play. To overcome this complexity, we employ an online minimum drift plus penalty (MDPP) approach for SAEV systems that (i) does not require a priori knowledge of customer arrival rates to the different parts of the system (i.e. it is practical from a real-world deployment perspective), (ii) ensures the stability of customer waiting times, (iii) ensures that the deviation of dispatch costs from a desirable dispatch cost can be controlled, and (iv) has a computational time-complexity that allows for real-time implementation. Using an agent-based simulator developed for SAEV systems, we test the MDPP approach under two scenarios with real-world calibrated demand and charger distributions: 1) a low-demand scenario with long trips, and 2) a high-demand scenario with short trips. The comparisons with other algorithms under both scenarios show that the proposed online MDPP outperforms all other algorithms in terms of both reduced customer waiting times and vehicle dispatching costs.
