Interactive Bike Lane Planning Using Sharing Bikes' Trajectories
Interactive Bike Lane Planning Using Sharing Bikes' Trajectories
复制标题
使用共享自行车轨迹进行交互式自行车道规划
DOI：
10.1109/tkde.2019.2907091
复制
发表时间：
2020-08-01
影响因子：
8.9
通讯作者：
Zheng, Yu
中科院分区：
文献类型：
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作者：
He, Tianfu;Bao, Jie;Zheng, Yu
自行车作为一种绿色交通方式，已经被世界各国政府大力推广。因此，建设有效的自行车道已成为促进自行车生活方式的关键任务，因为规划良好的自行车道可以减少交通拥堵和安全风险。不幸的是，现有的用于自行车道规划的轨迹挖掘方法没有考虑一个或多个关键的现实政府约束：1）预算限制，2）施工便利性，以及3）自行车道利用率。在本文中，我们提出了一种数据驱动的方法来制定自行车道建设计划的基础上，大规模的真实的世界自行车轨迹数据收集的无站点自行车共享系统。我们强制执行这些约束来制定我们的问题，并引入一个灵活的目标函数来调整用户的覆盖范围和他们的轨迹的长度之间的利益。为了提高自行车道规划系统的效率，本文提出了一种新的轨迹索引结构，并基于并行计算框架（Storm）部署了自行车道规划系统，以提高系统的效率。最后，大量的实验和案例研究证明了系统的效率和有效性。
Cycling as a green transportation mode has been promoted by many governments all over the world. As a result, constructing effective bike lanes has become a crucial task to promote the cycling life style, as well-planned bike lanes can reduce traffic congestions and safety risks. Unfortunately, existing trajectory mining approaches for bike lane planning do not consider one or more key realistic government constraints: 1) budget limitations, 2) construction convenience, and 3) bike lane utilization. In this paper, we propose a data-driven approach to develop bike lane construction plans based on the large-scale real world bike trajectory data collected from Mobike, a station-less bike sharing system. We enforce these constraints to formulate our problem and introduce a flexible objective function to tune the benefit between coverage of users and the length of their trajectories. We prove the NP-hardness of the problem and propose greedy-based heuristics to address it. To improve the efficiency of the bike lane planning system for the urban planner, we propose a novel trajectory indexing structure and deploy the system based on a parallel computing framework (Storm) to improve the system's efficiency. Finally, extensive experiments and case studies are provided to demonstrate the system efficiency and effectiveness.