How Infrastructure and Streetscape Shape E-Scooter Route Choice: Evidence from Washington, DC

2026-08-05

AI Summary

This study addresses the limited understanding of electric scooter users’ route choice behavior, particularly the joint influence of infrastructure and streetscape characteristics. Integrating GPS trajectory data with Google Street View imagery, it pioneers the incorporation of computer vision–derived streetscape features—such as tree canopy coverage and building enclosure—alongside conventional roadway infrastructure variables into a route-scale logit model to analyze path selection in Washington, D.C. The results reveal that protected bike lanes significantly enhance route attractiveness on arterials, while designated lanes are effective on collectors; paved sidewalks alone exert a positive utility. Moreover, greener streetscapes and greater building enclosure substantially increase route choice probability. Although infrastructure exerts a stronger influence, streetscape attributes provide significant additional explanatory power.

Abstract

E-scooters have emerged as an important micromobility mode for short urban trips, yet evidence on route choice behavior remains limited. This study examines e-scooter route choice in Washington, DC using GPS trajectory data and a Path Size Logit model. In addition to roadway and infrastructure characteristics, the model incorporates visual streetscape features extracted from Google Street View imagery using computer vision techniques. The results show that the effectiveness of cycling infrastructure depends strongly on roadway context. On major roads, only protected bicycle facilities significantly increase route attractiveness, whereas on minor roads both protected and designated lanes provide utility gains. Sidewalks constitute the most frequently used riding environment, yet only asphalt-paved sidewalks are associated with positive utility, suggesting that sidewalk riding may reflect the absence of attractive on-street alternatives rather than a preference for pedestrian infrastructure. Tree coverage, particularly during summer, as well as building and wall coverage, are positively associated with route choice. Likelihood ratio tests and value-of-distance analysis indicate that roadway infrastructure exerts a stronger influence on route choice than visual streetscape features, although the latter provide additional explanatory power. These findings support targeted infrastructure investment and the integration of streetscape improvements as a complementary strategy for enhancing micromobility route attractiveness.

Problem

• e-scooter
• route choice
• urban infrastructure
• streetscape
• micromobility

Innovation

• computer vision
• streetscape features
• route choice modeling
• micromobility
• Path Size Logit