Uncovering cabdrivers' behavior patterns from their digital traces
Uncovering cabdrivers' behavior patterns from their digital traces
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DOI：
10.1016/j.compenvurbsys.2010.07.004
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发表时间：
2010-11-01
影响因子：
6.8
通讯作者：
Ratti, Carlo
中科院分区：
文献类型：
--
作者：
Liu, Liang;Andris, Clio;Ratti, Carlo
从数字痕迹中识别高级人类行为和决策是普适计算系统中的关键问题。在本文中，我们开发了一种新的方法，通过分析出租车司机的连续数字轨迹来揭示他们的操作模式。我们首次系统地研究了出租车司机在真实而复杂的城市环境中的行为，通过他们的日常数字痕迹。本文提出了一组有价值的特征，可以简单有效地对出租车司机进行分类，描绘出租车司机的操作模式，并对不同出租车司机的行为进行比较。方法和步骤可以在空间和时间上量化、可视化和检查不同出租车司机的操作模式。司机按日收入分为顶级司机和普通司机。我们利用3000名出租车司机的日常运营数据，在超过4800万次的行程和2.4亿公里的里程中发现：(1)空间选择行为，(2)情境感知的时空操作行为，(3)路线选择行为，以及(4)操作策略。虽然我们关注的是出租车司机的数字轨迹操作模式分析，但该方法是任何类似gps的轨迹分析的一般经验和分析方法。我们的工作展示了利用大规模普适数据集来理解人类行为和高级智能的巨大潜力。Elsevier Ltd.出版。
Recognizing high-level human behavior and decisions from their digital traces are critical issues in pervasive computing systems. In this paper, we develop a novel methodology to reveal cabdrivers' operation patterns by analyzing their continuous digital traces. For the first time, we systematically study large scale cabdrivers' behavior in a real and complex city context through their daily digital traces. We identify a set of valuable features, which are simple and effective to classify cabdrivers, delineate cabdrivers' operation patterns and compare the different cabdrivers' behavior. The methodology and steps could spatially and temporally quantify, visualize, and examine different cabdrivers' operation patterns. Drivers were categorized into top drivers and ordinary drivers by their daily income. We use the daily operations of 3000 cabdrivers in over 48 million of trips and 240 million kilometers to uncover: (1) spatial selection behavior, (2) context-aware spatio-temporal operation behavior, (3) route choice behavior, and (4) operation tactics. Though we focused on cabdriver operation patterns analysis from their digital traces, the methodology is a general empirical and analytical methodology for any GPS-like trace analysis. Our work demonstrates the great potential to utilize the massive pervasive data sets to understand human behavior and high-level intelligence. Published by Elsevier Ltd.