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Towards Understanding the Impact of Human Mobility Patterns on Taxi Drivers' Income Based on GPS Data: A Case Study in Wuhan - China

机译:了解人类流动模式对基于GPS数据的出租车司机收入的影响 - 以武汉 - 中国为例

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Taxi trajectories can reflect human mobility over urban roads' network. Although taxi drivers cruise the same city roads, there is an observed variation in their daily incomes. To reveal the reasons behind this issue, this study introduces a method for investigating and understanding the impact of human mobility patterns (taxi drivers' behavior) on drivers' income. Firstly, a method for classifying taxi drivers into three income levels according to their daily income is introduced. Secondly, cruising trips and stopping spots are extracted for each income level. Thirdly, a comparison on the income levels of drivers in terms of spatial and temporal patterns on cruising trips and stopping spots is applied. The comparison applied various methods including mash map matching method and DBSCAN clustering method. Finally, an overall analysis and discussion on the results are introduced. The results showed that there is a relationship between human mobility patterns and taxi drivers' income. High-income drivers based on their experience earn more compared to other drivers as they know which places are more active to cruise and to stop and at what times. This study provides suggestions and insights to taxi companies and taxi drivers to increase their daily income and enhance the efficiency of the taxi industry.
机译:出租车轨迹可以反映在城市道路网络上的人类流动性。虽然出租车司机巡航相同的城市道路,但他们的日常收入有一个观察到的变化。为了揭示这个问题背后的原因,本研究介绍了一种调查和理解人类流动模式(出租车司机行为)对司机收入的影响的方法。首先,介绍了根据日常收入将出租车司机分为三个收入水平的方法。其次,为每个收入水平提取巡航行程和停止点。第三,应用了在巡航行程和停止斑点的空间和时间模式方面的司机收入水平的比较。比较应用了各种方法,包括MASH映射匹配方法和DBSCAN群集方法。最后,介绍了整体分析和讨论结果。结果表明,人类流动模式和出租车司机收入之间存在关系。与其他司机相比,基于他们的经验的高收入驱动程序赢得了更多的司机,因为他们知道哪个地方更加活跃地巡航和停止和在什么时候。本研究为出租车公司和出租车司机提供了建议和见解,以提高日常收入并提高出租车行业的效率。

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