With the rising demand of smart mobility, ride-hailing service is getting popular in the urban regions. These services maintain a system for serving the incoming trip requests by dispatching available vehicles to the pickup points. As the process should be socially and economically profitable, the task of vehicle dispatching is highly challenging, specially due to the time-varying travel demands and traffic conditions. Due to the uneven distribution of travel demands, many idle vehicles could be generated during the operation in different subareas. Most of the existing works on vehicle dispatching system, designed static relocation centers to relocate idle vehicles. However, as traffic conditions and demand distribution dynamically change over time, the static solution can not fit the evolving situations. In this paper, we propose a dynamic future demand aware vehicle dispatching system. It can dynamically search the relocation centers considering both travel demand and traffic conditions. We evaluate the system on real-world dataset, and compare with the existing state-of-the-art methods in our experiments in terms of several standard evaluation metrics and operation time. Through our experiments, we demonstrate that the proposed system significantly improves the serving ratio and with a very small increase in operation cost.
翻译:随着智能机动性需求的不断增长,乘车服务在城市地区日益普及。这些服务维持了一个通过向小卡车点派遣现有车辆满足来港旅行要求的系统。由于这一过程应该具有社会和经济效益,车辆的运送任务非常具有挑战性,特别是由于旅行需求和交通条件变化不定。由于旅行需求分布不均,许多闲置车辆可以在不同分区的运行中产生。大多数关于车辆调度系统的现有工程,设计了固定的搬迁中心,以转移闲置车辆。然而,随着交通条件和需求分配的动态变化,静态解决方案无法适应不断变化的情况。在本文件中,我们提出一个动态的未来需求意识车辆调度系统。它可以动态地搜索搬迁中心,同时考虑旅行需求和交通条件。我们用现实世界数据集对该系统进行评估,并在几个标准评价尺度和运行时间的实验中与现有最先进的方法进行比较。我们通过实验,证明拟议的系统大大改进了服务比率,业务成本也略有提高。