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A comparative analysis of the spatial determinants of e-bike and e-scooter sharing link flows
Journal of Transport Geography ( IF 5.7 ) Pub Date : 2024-08-07 , DOI: 10.1016/j.jtrangeo.2024.103959
Scarlett T. Jin , Daniel Z. Sui

Shared micromobility in the U.S. has rebound after the decline caused by the COVID-19 pandemic, with a substantial increase in the adoption of shared e-bikes nationwide. However, research on hybrid e-bike sharing, which combines station-based and dockless systems, is limited. This study addresses this gap by comparing spatial determinants of hybrid e-bike and dockless e-scooter sharing link flows in 32,965 street segments in Portland, Oregon during 2022, using gradient boosting decision tree (GBDT) models. Distance to the city center emerges as the most important determinant for both modes, with closer proximity to the city center associated with higher link flows. Factors such as the presence and types of bike facilities, the availability of streetlights and street trees, and job density also significantly influence e-bike and e-scooter link flows. A notable difference between the two modes is that e-scooter trips are more sensitive to distance to the city center than e-bike trips. Furthermore, bike facilities have a greater impact on e-bike link flows, whereas job density is more influential in determining e-scooter link flows. These findings offer strategies for policymakers and urban planners to promote and manage shared micromobility and optimize the built environment. These strategies include enforcing higher device availability requirements in underprivileged neighborhoods, transitioning e-scooter sharing systems into a hybrid model, expanding the off-street bike trial network and bikeway network, and augmenting the coverage of streetlights and street trees along the bikeway network.

中文翻译:


电动自行车和电动滑板车共享链接流的空间决定因素的比较分析



美国的共享微型交通在因新冠肺炎 (COVID-19) 大流行造成下滑后已出现反弹,全国范围内共享电动自行车的使用量大幅增加。然而,结合了基于站点和无桩系统的混合电动自行车共享的研究还很有限。本研究使用梯度提升决策树 (GBDT) 模型,比较 2022 年俄勒冈州波特兰市 32,965 个街道段中混合动力电动自行车和无桩电动滑板车共享链路流量的空间决定因素,从而解决了这一差距。到市中心的距离成为这两种模式最重要的决定因素,距离市中心越近,线路流量越高。自行车设施的存在和类型、路灯和行道树的可用性以及就业密度等因素也会显着影响电动自行车和电动滑板车的链接流量。两种模式之间的一个显着区别是,电动滑板车出行比电动自行车出行对距市中心的距离更敏感。此外,自行车设施对电动自行车链接流量的影响更大,而工作密度对确定电动滑板车链接流量的影响更大。这些研究结果为政策制定者和城市规划者提供了促进和管理共享微交通并优化建筑环境的策略。这些策略包括在贫困社区实施更高的设备可用性要求,将电动滑板车共享系统转变为混合模式,扩大街外自行车试验网络和自行车道网络,以及扩大自行车道网络沿线路灯和行道树的覆盖范围。
更新日期:2024-08-07
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