城市网约车运营的时空特征
Spatiotemporal Characteristics of Ride-sourcing Operation in Urban Area
摘要：
网约车平台的出现为交通运输带来了一种创新的选择，从根本上改变了出行行为，并为交通规划者和运营商提出了新的方向。本文使用大规模的服务性能数据对网约车服务的运营进行了探索性分析。在新加坡进行的多天观察表明了可重复的需求模式，并提供了随时间和空间变化的船队运营经验估计。在高峰期，我们观察到服务费率的显著增加以及价格乘数的激增。我们对车队利用率进行了深入分析，并能够通过涉及班次数量、班次持续时间以及班次开始和结束时间的选择来解释基于驾驶员行为的日常模式。我们还评估了用户体验的指标，即等待和旅行时间分布，并解释了我们的实证研究结果与驾驶轨迹分析和拥堵模式的距离指标。我们对新加坡实际服务的实证观察结果有助于了解乘车外包服务的时空特征，并为交通规划和运营提供重要见解。
英文摘要：
The emergence of ride-sourcing platforms has brought an innovative alternative in transportation, radically changed travel behaviors, and suggested new directions for transportation planners and operators. This paper provides an exploratory analysis on the operations of a ride-sourcing service using large-scale data on service performance. Observations over multiple days in Singapore suggest reproducible demand patterns and provide empirical estimates of fleet operations over time and space. During peak periods, we observe significant increases in the service rate along with surge price multipliers. We perform an in-depth analysis of fleet utilization rates and are able to explain daily patterns based on drivers' behavior by involving the number of shifts, shift duration, and shift start and end time choices. We also evaluate metrics of user experience, namely waiting and travel time distribution, and explain our empirical findings with distance metrics from driver trajectory analysis and congestion patterns. Our results of empirical observations on actual service in Singapore can help to understand the spatiotemporal characteristics of ride-sourcing services and provide important insights for transportation planning and operations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
