理解电动自行车路径选择对于构建有效的骑行基础设施至关重要，但实证证据仍较为有限。本研究利用Capital Bikeshare系统提供的全球定位系统（GPS）轨迹数据，考察华盛顿特区共享电动自行车的路径选择行为。采用混合选择集（包含观测路径及对应最短路径）估计路径规模Logit（Path Size Logit）模型，并整合地理信息系统（GIS）表征的基础设施变量与基于街景图像（Street View images, SVI）的计算机视觉提取的街道级视觉特征。结果表明，电动自行车骑行者倾向于选择能最小化与机动车及行人冲突、同时保障通行连续性的路径。道路等级显著调节自行车设施的影响效应：相较于次要道路，自行车设施在主干道上的路径选择影响更为显著；长距离出行亦表现出对骑行基础设施更强的偏好。引入街道级视觉特征可提升模型性能，但其效应普遍弱于道路基础设施变量；其中，树木是唯一呈现持续正向效应的绿化要素。标准化效应量进一步识别出行为意义上最重要的路径属性。上述发现为电动自行车时代的骑行基础设施规划提供了实证依据。

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.