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Influence of Built Environment on Micromobility–Pedestrian Accidents

Author

Listed:
  • Songhyeon Shin

    (Department of Urban Planning, Hongik University, Seoul 04066, Republic of Korea)

  • Sangho Choo

    (Department of Urban Design & Planning, Hongik University, Seoul 04066, Republic of Korea)

Abstract

The use of micromobility (MM), a form of sustainable urban mobility which has expected effects such as reducing traffic congestion and greenhouse gases, has been rapidly increasing across the world. However, this growth has resulted in a considerable number of MM-related accidents. Most previous studies have explored MM user injuries to improve the safety of MM users, but the threat to pedestrians by MM is not yet fully understood. Therefore, this study aims to identify built environment factors which contribute to MM–pedestrian accidents by using MM–pedestrian crash data in Seoul, Korea from 2020 to 2021. Setting the spatial unit of analysis as a hexagonal grid with an apothem of 150 m, we developed the SZINB (spatial zero-inflated negative binomial) models for the accidents, controlling spatial autocorrelation, zero-inflated, and overdispersion. The model results showed that road intersections, sidewalks, and subway entrances have significant impacts on MM–pedestrian accidents. Thus, it should be suggested that safety measures for both MM and pedestrians are reducing MM speed limits in intersections, preventing MM use on sidewalks through modified sidewalk designs, and installing MM stations near subway stations.

Suggested Citation

  • Songhyeon Shin & Sangho Choo, 2022. "Influence of Built Environment on Micromobility–Pedestrian Accidents," Sustainability, MDPI, vol. 15(1), pages 1-11, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:582-:d:1018774
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    References listed on IDEAS

    as
    1. Jihun Oh & Jeongseob Kim, 2021. "Where to Ride? An Explorative Study to Investigate Potential Risk Factors of Personal Mobility Accidents," IJERPH, MDPI, vol. 18(3), pages 1-15, January.
    2. Sujae Kim & Sangho Choo & Gyeongjae Lee & Sanghun Kim, 2022. "Predicting Demand for Shared E-Scooter Using Community Structure and Deep Learning Method," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
    Full references (including those not matched with items on IDEAS)

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