While previous studies have provided insights into the relationship between weather and ridership, how historical and future weather conditions affect bus travel behavior remains to be addressed. And the differences among advancing, current, and lagging effects, between different traveler profiles are not clear. This research aims to fill the gaps by exploring the effects of historical, current, and future weather on bus ridership at hourly scales in Dingjiazhuang, Nanjing, with a typical humid subtropical climate. More than 4 million smart card records, 4 million Global Positioning System (GPS) records, and weather measurements were used over a three-month period. Seasonal autoregressive integrated moving average (SARIMAX) time-series techniques were applied to assess the advancing, current, and lagging effects that five weather conditions, including air temperature, heat index, relative humidity, horizontal visibility, and precipitation, exert on bus ridership at two spatial scales: overall level and origin-destination (OD) pairs. The results showed significant advancing, current, and lagging negative effects of relative humidity on both weekdays and weekends. While current precipitation was negatively associated with bus ridership, the lagging effect was positive. Only significant advancing and current effects of horizontal visibility were captured. Hourly elderly travelers were more affected than younger travelers. In particular, we found that the elderly were more affected by future weather conditions, especially on weekdays. Results yield implications for policymakers to incorporate weather variation information in transit demand monition, which can support requirements for future transport models and develop decision support tools.

虽然以前的研究已经提供了对天气和乘客量之间关系的见解，但历史和未来的天气状况如何影响公交出行行为仍有待解决。不同旅客概况之间的前进效应、当前效应和滞后效应之间的差异尚不清楚。本研究旨在通过探索历史、当前和未来天气对南京丁家庄（典型的潮湿亚热带气候）每小时公交车乘客量的影响来填补空白。在三个月的时间里，使用了 400 多万条智能卡记录、400 万条全球定位系统 （GPS） 记录和天气测量。应用季节性自回归综合移动平均 （SARIMAX） 时间序列技术来评估五种天气条件（包括气温、热指数、相对湿度、水平能见度和降水）在两个空间尺度上对公交乘客量的前进、当前和滞后影响：总体水平和起点-目的地 （OD） 对。结果显示，相对湿度在工作日和周末都有显著的前进、当前和滞后负面影响。虽然目前的降水量与公交车乘客量呈负相关，但滞后效应是积极的。仅捕获了水平能见度的显著前进和电流影响。小时工的老年旅行者比年轻旅行者受到的影响更大。特别是，我们发现老年人更容易受到未来天气状况的影响，尤其是在工作日。结果为政策制定者将天气变化信息纳入交通需求监测提供了启示，这可以支持未来运输模型的要求并开发决策支持工具。