In recent years, innovative ride-sharing systems have gained significant attention. In such systems, dynamic fleet management covers demand and fulfillment control to determine which stochastically incoming requests are to be satisfied and how vehicle resources are utilized for their fulfillment, respectively. Demand and fulfillment control can be implemented ranging from straightforward myopic to more sophisticated anticipatory. In this paper, our aim is twofold: (1) we want to classify how policies implement demand and fulfillment control in the related literature on dynamic fleet management; (2) we want to explore the effectiveness of demand and fulfillment control under varying conditions in order to identify benefits and risks for ride-sharing systems. To this end, we define policies that differ in the optimization of demand and/or fulfillment control through the exploitation of either confirmed or complete information. Our experimental results demonstrate that demand and fulfillment control affect the performance and service quality of ride-sharing systems quite differently.

中文翻译：

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共享出行系统动态车队管理中需求和履行控制的有效性

近年来，创新的拼车系统引起了广泛关注。在这样的系统中，动态车队管理涵盖需求和履行控制，以确定要满足哪些随机传入的请求以及如何利用车辆资源来实现它们。需求和履行控制的实施范围从直接的短视到更复杂的预期。在本文中，我们的目标有两个：（1）我们想在动态车队管理的相关文献中对政策如何实施需求和履行控制进行分类；(2) 我们希望探索不同条件下需求和履行控制的有效性，以确定拼车系统的收益和风险。为此，我们通过利用已确认或完整的信息来定义在优化需求和/或履行控制方面不同的政策。我们的实验结果表明，需求和履行控制对拼车系统的性能和服务质量的影响完全不同。