Chen Dandan, Zhang Yong, Gao Liangpeng, Geng Nana, Li Xuefeng
School of Transportation, Southeast University, Nanjing, Jiangsu Province, China.
PLoS One. 2017 Sep 5;12(9):e0183574. doi: 10.1371/journal.pone.0183574. eCollection 2017.
This paper focuses on the impact of rainfall on the temporal and spatial distribution of taxi passengers. The main objective is to provide guidance for taxi scheduling on rainy days. To this end, we take the occupied and empty states of taxis as units of analysis. By matching a taxi's GPS data to its taximeter data, we can obtain the taxi's operational time and the taxi driver's income from every unit of analysis. The ratio of taxi operation time to taxi drivers' income is used to measure the quality of taxi passengers. The research results show that the spatio-temporal evolution of urban taxi service demand differs based on rainfall conditions and hours of operation. During non-rush hours, taxi demand in peripheral areas is significantly reduced under increasing precipitation conditions, whereas during rush hours, the demand for highly profitable taxi services steadily increases. Thus, as an intelligent response for taxi operations and dispatching, taxi services should guide cruising taxis to high-demand regions to increase their service time and ride opportunities.
本文聚焦于降雨对出租车乘客时空分布的影响。主要目的是为雨天出租车调度提供指导。为此，我们将出租车的载客和空载状态作为分析单位。通过将出租车的GPS数据与其计价器数据相匹配，我们可以获得每个分析单位的出租车运营时间以及出租车司机的收入。出租车运营时间与出租车司机收入的比率用于衡量出租车乘客的质量。研究结果表明，城市出租车服务需求的时空演变因降雨条件和运营时间而异。在非高峰时段，随着降水量增加，周边地区的出租车需求显著减少，而在高峰时段，高利润出租车服务的需求稳步增加。因此，作为出租车运营和调度的智能响应，出租车服务应引导巡游出租车前往高需求地区，以增加其服务时间和载客机会。
