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Vehicle demand evolution analysis from the complex network perspective

机译:复杂网络视角的车辆需求演变分析

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Nowadays, with the increasing population of a city, the vehicle demand especially in rush hours of weekdays increases remarkably. To dispatch taxicabs efficiently, taxicab companies such as DiDi need to analyze the dynamic vehicle demand evolution. In this work, we analyze the order data of DiDi from complex network perspective. Firstly, we propose to divide the city into many small grids. Secondly, we analyze the order data among all areas and construct a car dispatching network in which the link weight represents the number of orders from one area to another within a given time interval. Thirdly, by analyzing the network metrics such as the degree distribution, evolution of node strength and traveling time, it can be found that the results are very interesting and useful. Finally, we further discuss hub characteristic of the network, and find that more than 95% orders are served for the top 5% areas. (C) 2019 Elsevier B.V. All rights reserved.
机译:如今,随着城市人口的增加,车辆需求尤其在平日的高峰时段显着增加。 要有效地调度出租车,因此DIDI等出租车公司需要分析动态车辆需求进化。 在这项工作中,我们从复杂的网络角度分析DIDI的订单数据。 首先,我们建议将这座城市分成许多小网格。 其次,我们分析了所有领域的订单数据,并构建了一种汽车调度网络,其中链路权重表示在给定时间间隔内的一个区域的订单数。 第三,通过分析网络指标,例如度量分布,节点强度的演化和行进时间,可以发现结果非常有趣和有用。 最后,我们进一步讨论了网络的集线器特征,并找到了超过95%的订单为前5%的区域提供服务。 (c)2019 Elsevier B.v.保留所有权利。

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