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Quantifying Demand Dynamics for Supporting Optimal Taxi Services Strategies

机译:量化需求动态以支持最佳出租车服务策略

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Abstract: In recent years, mobility patterns have reasonably attracted scientific interest, especially concerning Mega-Cities. The technological advances, especially concerning sensors, facilitates the collection and access on a massive amount of empirical data capturing in high-resolution urban mobility. The introduction and spread of location tracking devices and services provide the means for collecting reliable real-time data, particularly valuable for industrial as well as for personal applications. In this study, a complex and realistic dataset is monitored and analysed, that provide the real-time occupancy status and Global Positioning System (GPS) location for three taxi fleets during of New Year's Day. The scope of this paper is a preliminary identification of alternative Taxi-Services Strategies by means of dynamic clustering as well as ‘heatmap’ analysis.
机译:摘要:近年来,出行方式已经引起了科学的兴趣,尤其是在巨型城市方面。技术的进步,尤其是在传感器方面,促进了高分辨率城市交通中大量经验数据的收集和访问。位置跟踪设备和服务的引入和普及为收集可靠的实时数据提供了手段,这些数据对于工业和个人应用而言尤其有价值。在这项研究中,监视和分析了一个复杂而现实的数据集,该数据集提供了元旦期间三个出租车队的实时占用状态和全球定位系统(GPS)位置。本文的范围是通过动态聚类和“热图”分析对替代出租车服务策略的初步确定。

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