How Are E-Scooter Speed-Limiter Settings Associated with User Behavior? Observed Speeds and Road, Sidewalk, and Bike Lane Use in Austin, TX, and Washington, D.C.

Author:

Cicchino Jessica B.1,Chaudhary Neil K.2,Solomon Mark G.2ORCID

Affiliation:

1. Insurance Institute for Highway Safety, Arlington, VA

2. Preusser Research Group, Trumbull, CT

Abstract

Many cities limit the top speeds of shared e-scooters, but little is known about how these policies affect user behavior. This study measured speeds and observed use of roads, sidewalks, and bike lanes for 2,004 e-scooter riders in Washington, D.C., where shared e-scooters were equipped with speed governors that limited their speed to 10 mph, and Austin, TX, where the limit was 20 mph. At locations without bike lanes, riders in Washington were 51% more likely to ride on sidewalks than in Austin when accounting for environmental and rider characteristics. Over 80% of e-scooter users rode in bike lanes in both cities when they were available. Although the mean riding speed on sidewalks was not significantly higher in Austin than in Washington, demonstrating self-regulation of speed on sidewalks, the percentage of e-scooter riders traveling on sidewalks at speeds ≥10 mph (41% in Austin versus 17% in Washington) or ≥15 mph (9% in Austin versus <1% in Washington) was higher in Austin. Increased sidewalk riding associated with setting shared e-scooter speed limiters to 10 mph could potentially lead to more interactions with pedestrians, but lower e-scooter speeds at the high end of the distribution may mitigate injury risk to them. Bike lanes could provide space for e-scooters to ride where their speeds would more closely match other users. Future refinements to technology to identify sidewalk riding more accurately could potentially allow maximum e-scooter speeds to be adjusted to mix with pedestrians on sidewalks and cyclists in bike lanes.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference44 articles.

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3. Motor vehicle-related electric scooter injuries in the US: A descriptive analysis of NEISS data

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