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Analysis of Relationship between Road Geometry and Automated Driving Safety for Automated Vehicle-Based Mobility Service

Author

Listed:
  • Sehyun Tak

    (Center for Connected and Automated Driving Research, The Korea Transport Institute, Sejong 30147, Korea)

  • Sari Kim

    (Center for Connected and Automated Driving Research, The Korea Transport Institute, Sejong 30147, Korea)

  • Hwapyeong Yu

    (Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea)

  • Donghoun Lee

    (Center for Connected and Automated Driving Research, The Korea Transport Institute, Sejong 30147, Korea)

Abstract

Various mobility services have been proposed based on the integration of automated vehicle (AV) and road infrastructure. Service providers need to identify a set of road sections for ensuring the driving safety of an AV-based mobility service. The main objective of this research is to analyze the safety performance of AVs on the road geometrical features present during this type of mobility service. To achieve the research goal, a mobility service is classified by a combination of six road types, including expressway, bus rapid transit (BRT) lane, principal arterial road, minor arterial road, collector road, and local road. With any given road type, a field test dataset is collected and analyzed to assess the safety performance of the AV-based mobility service with respect to road geometry. Furthermore, the safety performances of each road section are explored by using a historical dataset for human-driven vehicle-involved accident cases. The result reveals that most of the dangerous occurrences in both AV and human-driven vehicles show similar patterns. However, contrasting results are also observed in crest vertical curve sections, where the AV shows a lower risk of dangerous events than that of a human-driven vehicle. The findings can be used as primary data for optimizing the physical and digital infrastructure needed to implement efficient and safe AV-based mobility services in the future.

Suggested Citation

  • Sehyun Tak & Sari Kim & Hwapyeong Yu & Donghoun Lee, 2022. "Analysis of Relationship between Road Geometry and Automated Driving Safety for Automated Vehicle-Based Mobility Service," Sustainability, MDPI, vol. 14(4), pages 1-13, February.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2336-:d:752522
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    References listed on IDEAS

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    1. Calin Iclodean & Nicolae Cordos & Bogdan Ovidiu Varga, 2020. "Autonomous Shuttle Bus for Public Transportation: A Review," Energies, MDPI, vol. 13(11), pages 1-45, June.
    2. Katarzyna Turoń & Andrzej Kubik & Feng Chen, 2021. "When, What and How to Teach about Electric Mobility? An Innovative Teaching Concept for All Stages of Education: Lessons from Poland," Energies, MDPI, vol. 14(19), pages 1-16, October.
    3. Shaheen, Susan PhD & Bansal, Apaar & Chan, Nelson & Cohen, Adam, 2017. "Mobility and the Sharing Economy: Industry Developments and Early Understanding of Impacts," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt96j5r729, Institute of Transportation Studies, UC Berkeley.
    4. Sehyun Tak & Soomin Woo & Sungjin Park & Sunghoon Kim, 2021. "The City-Wide Impacts of the Interactions between Shared Autonomous Vehicle-Based Mobility Services and the Public Transportation System," Sustainability, MDPI, vol. 13(12), pages 1-29, June.
    5. Giuseppina Pappalardo & Salvatore Cafiso & Alessandro Di Graziano & Alessandro Severino, 2021. "Decision Tree Method to Analyze the Performance of Lane Support Systems," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
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    Cited by:

    1. Sehyun Tak & Jeongyun Kim & Donghoun Lee, 2022. "Study on the Extraction Method of Sub-Network for Optimal Operation of Connected and Automated Vehicle-Based Mobility Service and Its Implication," Sustainability, MDPI, vol. 14(6), pages 1-28, March.

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