The usage of shared e-scooters, dockless e-bikes, and docked bicycles are correlated with weather conditions to examine the relative impact on each mode, specifically number of trips taken, their duration, and distance. Data is obtained from the City of Austin data portal. Rain, temperature and wind conditions are obtained from NOAA and a variety of analysis methods are applied, specifically Prais-Winsten and Negative Binomial regressions as well as a Random Forest model to examine the full suite of weather variables and to avoid some of the distributional issues in the trip models. In addition, controls are included for holidays, days of the week, and special events in Austin (such as the SXSW festival); all are found to be critical control variables, with SXSW associated with large increases in trips. Results suggest that docked bicycle and e-bike usage is more sensitive to adverse weather conditions than e-scooter trips, though all are reduced in colder, rainier, and windier conditions, as well as extreme heat and high relative humidity.

共享电动踏板车，无底座电动自行车和停放的自行车的使用与天气状况相关联，以检查对每种模式的相对影响，特别是行程次数，持续时间和距离。数据是从奥斯丁市数据门户网站获得的。可从NOAA获得降雨，温度和风况，并应用各种分析方法，特别是Prais-Winsten和负二项式回归以及随机森林模型，以检查整套天气变量并避免某些分布问题在旅途中的模特。此外，还包括节假日，一周中的几天以及奥斯丁的特殊事件（如SXSW节）的控件；所有这些都是关键控制变量，SXSW与行程的大幅增加相关。