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Quantifying the Impact of Deployments of Autonomous Vehicles and Intelligent Roads on Road Safety in China: A Country-Level Modeling Study

Author

Listed:
  • Hong Tan

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China)

  • Fuquan Zhao

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China)

  • Haokun Song

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China)

  • Zongwei Liu

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China)

Abstract

Approximately 1.35 million people lose their lives due to road traffic collisions worldwide per year. However, the variation of road safety depending on the deployment of Autonomous Vehicles (AV), Intelligent Roads (IR), and Vehicle-to-Vehicle technology (V2V) is largely unknown. In this analysis, a bottom-up analytical framework was developed to evaluate the safety benefits of avoiding road injuries and reducing crash-related economic costs from the deployment of AVs, IRs, and V2Vs in China in 26 deployment scenarios from 2020 to 2050. The results indicate that compared with only deploying AVs, increasing the availability of IRs and V2V while reducing the deployment of fully AVs can achieve larger safety benefits in China. Increasing the deployment of V2V while reducing the deployment of IRs can sometimes achieve similar safety benefits. The deployment of AVs, IRs, and V2V plays different roles in achieving safety benefits. The large-scale deployment of AVs is the foundation of reducing traffic collisions; the construction of IRs would determine the upper limit of reducing traffic collisions, and the readiness of connected vehicles would influence the pace of reducing traffic collisions, which should be designed in a coordinated manner. Only six synergetic scenarios with full equipment of V2V can meet the SDG 3.6 target for reducing casualties by 50% in 2030 compared to 2020. In general, our results highlight the importance and the potential of the deployment of AVs, IRs, and V2V to reduce road fatalities and injuries. To achieve greater and faster safety benefits, the government should prioritize to the deployment of IRs and V2V. The framework developed in this study can provide practical support for decision-makers to design strategies and policies on the deployment of AVs and IRs, which can also be applied in other countries.

Suggested Citation

  • Hong Tan & Fuquan Zhao & Haokun Song & Zongwei Liu, 2023. "Quantifying the Impact of Deployments of Autonomous Vehicles and Intelligent Roads on Road Safety in China: A Country-Level Modeling Study," IJERPH, MDPI, vol. 20(5), pages 1-15, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4069-:d:1079281
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    References listed on IDEAS

    as
    1. Liu, Feiqi & Zhao, Fuquan & Liu, Zongwei & Hao, Han, 2019. "Can autonomous vehicle reduce greenhouse gas emissions? A country-level evaluation," Energy Policy, Elsevier, vol. 132(C), pages 462-473.
    2. Yan, Xiaoyu & Crookes, Roy J., 2009. "Reduction potentials of energy demand and GHG emissions in China's road transport sector," Energy Policy, Elsevier, vol. 37(2), pages 658-668, February.
    3. Hong Tan & Fuquan Zhao & Han Hao & Zongwei Liu, 2021. "Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies," IJERPH, MDPI, vol. 18(17), pages 1-12, September.
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