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Understanding E-Scooter Incidents Patterns in Street Network Perspective: A Case Study of Travis County, Texas

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  • Junfeng Jiao

    (Urban Information Lab., The School of Architecture, The University of Texas at Austin, Austin, TX 78705, USA)

  • Shunhua Bai

    (Urban Information Lab., The School of Architecture, The University of Texas at Austin, Austin, TX 78705, USA)

  • Seung Jun Choi

    (Urban Information Lab., The School of Architecture, The University of Texas at Austin, Austin, TX 78705, USA)

Abstract

Dockless electric scooter (E-scooters) services have emerged in the United States as an alternative form of micro transit in the past few years. With the increasing popularity of E-scooters, it is important for cities to manage their usage to create and maintain safe urban environments. However, E-scooter safety in U.S. urban environments remains unexplored due to the lack of traffic and crash data related to E-scooters. Our study objective is to better understand E-scooter crashes from a street network perspective. New parcel level street network data are obtained from Zillow and curated in Geographic Information System (GIS). We conducted local Moran’s I and independent Z-test to compare where and how the street network that involves E-scooter crash differs spatially with traffic incidents. The analysis results show that there is a spatial correlation between E-scooter crashes and traffic incidents. Nevertheless, E-scooter crashes do not fully replicate characteristics of traffic incidents. Compared to traffic incidents, E-scooter incidents tend to occur adjacent to traffic signals and on primary roads.

Suggested Citation

  • Junfeng Jiao & Shunhua Bai & Seung Jun Choi, 2021. "Understanding E-Scooter Incidents Patterns in Street Network Perspective: A Case Study of Travis County, Texas," Sustainability, MDPI, vol. 13(19), pages 1-13, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10583-:d:641900
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    References listed on IDEAS

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