华盛顿特区电动自行车路径选择建模：路径尺寸Logit方法
Modeling E-Bike Route Choice in Washington, DC: A Path Size Logit Approach
AI总结：
本研究以华盛顿特区共享电动自行车为对象，采用Path Size Logit模型，结合GPS轨迹、GIS基础设施与街景视觉数据，明确电动自行车路径选择的影响因素，为相关基础设施规划提供实证依据。
AI中文摘要：
理解电动自行车（e-bike）的路径选择对构建有效的骑行基础设施至关重要，但相关实证证据仍较为有限。本研究利用Capital Bikeshare系统的全球定位系统（GPS）轨迹数据，调查华盛顿特区共享电动自行车的路径选择行为。采用由观测路径和对应最短路径组成的混合选择集估计Path Size Logit模型，整合基于地理信息系统（GIS）的基础设施变量与从街景图像（SVI）提取的计算机视觉生成的街景视觉特征。结果表明，电动自行车骑行者倾向选择能最小化与机动车及行人冲突同时保持出行连续性的路径；道路等级显著调节自行车设施的影响，主干道上自行车设施的存在对路径选择的影响远大于次要道路；长途出行对骑行基础设施的偏好更强。纳入街景视觉特征可提升模型性能，尽管其影响通常小于道路基础设施，其中树木是唯一呈现持续正向影响的绿化组成部分。标准化效应量进一步确定了行为上最重要的路径属性。这些发现为电动自行车时代的骑行基础设施规划提供了实用证据。
英文摘要：
Understanding e-bike route choice is essential for developing effective cycling infrastructure, yet empirical evidence remains limited. This study investigates shared e-bike route choice in Washington, DC, using Global Positioning System (GPS) trajectory data from the Capital Bikeshare system. A Path Size Logit model is estimated using a hybrid choice set consisting of observed routes and corresponding shortest paths, integrating Geographic Information System (GIS)-based infrastructure variables with computer vision-derived street-level visual features extracted from Street View images (SVI). The results indicate that e-bike riders tend to choose routes that minimize conflicts with both motor vehicles and pedestrians while maintaining travel continuity. Roadway hierarchy substantially moderates the influence of bicycle facilities, with the presence of bicycle facilities having a much greater impact on route choice along major roads than along minor roads. Longer trips also exhibit stronger preferences for cycling infrastructure. Incorporating street-level visual features improves model performance, although their effects are generally smaller than those of road infrastructure, with trees being the only greenery component showing a consistently positive effect. Standardized effect sizes further identify the most behaviorally important route attributes. These findings provide practical evidence for cycling infrastructure planning in the e-bike era.
