CAV 车队的随机路由策略可能证明具有市场效率
Randomized routing strategies of fleets of CAVs may prove market efficient
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中文总结 AI 辅助
探讨未来城市中 CAV 集体路由车队市场，提出几种路由算法，发现随机 CAV 路由在人类司机态度差异大时更高效，建议通过增强市场份额目标并结合全系统平均旅行时间改进市场设计，推动合作。
中文摘要 AI 辅助
在未来城市中，每个司机可能拥有一辆可独立驾驶（HDV）或自主路由和驾驶（CAV）的车辆。自主运营可由几家竞争公司处理。哪种市场结构能使该市场与城市目标一致？本文讨论了新兴的 CAV 集体路由车队市场的一种变体，车队运营商的收入与市场份额成正比。我们提供基准场景来比较路由算法。提出几种路由算法并证明，当人类司机对 CAV 的态度表现出显著差异时，导致 HDV 旅行时间不可预测的随机 CAV 路由比按系统最优/用户均衡成比例的路由更有效。基于此，我们建议通过用全系统平均旅行时间增强市场份额目标来改进市场设计，以限制车队运营商的反社会随机策略，并推动竞争朝着以社会福利为导向的合作发展。
英文摘要
In future cities every driver may own a vehicle which could be either independently driven (HDV), or autonomously routed and piloted (CAV). The autonomous operations could be handled by a few competing companies. What is the market structure which would make this market aligned with city goals? In this paper we discuss a variant of the emerging market of collectively routed fleets of CAVs, where revenue for fleet operators is proportional to market share. We provide benchmark scenarios to compare the routing algorithms. We present several routing algorithms and demonstrate that, when the attitudes of human drivers towards CAVs exhibit significant diversity, randomised CAV routing, resulting in unpredictable travel times for HDVs, is more efficient than routing proportional to system optimum/user equilibrium. Based on this, we propose to improve the design of the market by augmenting the market-share objective with mean systemwide travel time in order to limit antisocial randomised strategies of fleet operators and drive the competition towards social welfare oriented cooperation.
