Leveraging ride-hailing services for social good: Fleet optimal routing and system optimal pricing
Leveraging ride-hailing services for social good: Fleet optimal routing and system optimal pricing
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DOI：
10.1016/j.trc.2023.104284
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发表时间：
2023-10
期刊：
影响因子：
--
通讯作者：
Zemian Ke;Sean Qian
中科院分区：
文献类型：
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作者：
Zemian Ke;Sean Qian
随着网约车服务的渗透，交通网络公司（TNC）对网络性能的影响越来越大。跨国公司有一个无处不在的传感和定价系统，公共机构可以利用它来改善运输系统的性能。本研究首先制定并解决了个人驾驶车辆和网约车车辆的混合均衡（ME），其中跨国公司集中分配路线的网约车车辆，以实现车队范围内的最优。我们提出了一种新的车队行为所需的跨国公司，命名为车队最优行为与服务约束（FOSC），它提供了一个很好的折衷之间的总车队成本最小化和公平的车手。然而，我们表明，系统状态的FOSC可以远离系统的最优状态。为此，我们提出了一种新的最优叫车定价（ORHP）计划，公共机构作为一种有效的方式来干预叫车在线平台。ORHP的基本思想是监管和补贴跨国公司，以换取有保证的网络性能改善。在ORHP下，公共机构为使用这一链接的任何跨国公司乘客设定每一链接的补贴价值。补贴是提供给跨国公司的，而不是直接提供给骑手。TNC获得补贴，并确定为偏离FOSC确定的“最短”路线的每位乘客提供补偿的最佳方式。跨国公司的最终目标是减少其总成本，包括车队总行驶时间和总补偿，减去从公共机构获得的总补贴。ORHP可能比其他定价计划争议更小，因为它要求提供多种路线选择的旅行者自愿参与。由于它是跨国公司票价系统的一部分，因此实施起来成本效益高，而且很难进行博弈。这将是一个双赢的局面：公共机构可以在不建立实体基础设施或服务的情况下，利用TNC的平台以成本效益高的方式提高系统性能; TNC可以从补贴中获利并提高服务质量。ORHP被制定为一个双层优化问题，解决了基于灵敏度分析的算法和测试两个网络意味着ORHP计划可以是有效的：一个小的总补贴提供给TNC可以导致显着改善系统性能。
With the penetration of ride-hailing services, the impacts of transportation network companies (TNC) on network performance grow. TNC comes with a ubiquitous sensing and pricing system that may be leveraged by public agencies to improve transportation system performance. This study first formulates and solves a mixed equilibrium (ME) of personal driving vehicles and ride-hailing vehicles, where TNCs centrally assign routes to ride-hailing vehicles to achieve fleet-wide optimum. We propose a novel fleet behavior desired by TNCs, named fleet-optimal behavior with service constraint (FOSC), which provides a good compromise between total fleet cost minimization and fairness among riders. However, we show that the system state of FOSC can be far from the system optimum state. To this end, we propose a novel Optimal Ride-hailing Pricing (ORHP) scheme for public agencies as an efficient manner to intervene ride-hailing online platforms. The essential idea of ORHP is to regulate and subsidize TNCs, in exchange for guaranteed network performance improvement. Under ORHP, public agencies set the value of a subsidy for each link for any TNC rider using this link. The subsidies are provided to TNCs, not directly to riders. TNC receives subsidies, and determines the best way to provide compensations for each rider who deviates from his/her ”shortest” route, determined by FOSC. TNC’s ultimate goal is to reduce their total cost, including total fleet vehicle travel time and total compensations, subtracted by the total subsidy received from public agencies. The ORHP is likely less controversial than other pricing schemes, since it calls for voluntary participation of travelers who are provided with multiple route options. Because it is built into the TNCs’ fare system, it is cost effective to implement and hard to game. This would be a win-win: a win for public agencies to cost-effectively improve system performance leveraging TNC’s platform without building physical infrastructure or services; and a win for TNC to profit from subsidies and improve service quality. ORHP is formulated as a bi-level optimization problem, solved with a sensitivity analysis based algorithm and tested on two networks implying the ORHP scheme can be effective: a small total subsidy provided to TNC can lead to significant improvement in system performance.