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.

中文翻译：

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城市地区拼车运营的时空特征

拼车平台的出现带来了一种创新的交通方式，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绩效数据对拼车服务的运营进行了探索性分析。新加坡多天的观察表明可重复的需求模式，并提供了随时间和空间变化的车队运营经验估计。在高峰期，我们观察到服务费率随着飙升的价格乘数显着增加。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，并用来自驾驶员轨迹分析和拥堵模式的距离指标来解释我们的实证结果。我们对新加坡实际服务的实证观察结果有助于了解拼车服务的时空特征，并为交通规划和运营提供重要见解。