以公共汽车为速度探测器的实时行程时间估计

Dimitrios Tomaras, Ioannis Boutsis, V. Kalogeraki
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引用次数: 3

摘要

在城市环境中,出行时间估计对于个性化和生态友好的路线规划优化、避免拥堵、拼车和出租车调度具有重要的战略意义。然而,存储和检索特定时空区域的交通数据并非易事,因为这些系统生成的数据通常非常庞大且动态。在本文中,我们提出了一种有效的、可扩展的轨迹实时行程时间估计方法。在我们的系统中,总线作为速度探测器来获取实时交通数据信息,时空轨迹存储在一个动态索引系统中,该系统优化了实时检索时空数据的效率。我们的实验评估证明了我们的方法的效率和可扩展性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Travel time estimation in real-time using buses as speed probes
Travel time estimation is a strategically important service in urban environments for personalized and eco-friendly route planning optimization, congestion avoidance, ridesharing and taxi dispatching. However, storing and retrieving traffic data in specific spatiotemporal regions is not an easy task as the data generated by these systems are typically very large and dynamic. In this paper we propose an efficient and scalable solution for real-time travel time estimation of trajectories. In our system buses are used as speed probes to obtain real-time traffic data information and spatio-temporal trajectories are stored in a dynamic indexing system optimized for efficiently retrieving spatiotemporal data in real-time. Our experimental evaluation illustrates the efficiency and scalability of our approach.
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