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How Safe Is Safe Enough for Self‐Driving Vehicles?

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  • Peng Liu
  • Run Yang
  • Zhigang Xu

Abstract

Self‐driving vehicles (SDVs) promise to considerably reduce traffic crashes. One pressing concern facing the public, automakers, and governments is “How safe is safe enough for SDVs?” To answer this question, a new expressed‐preference approach was proposed for the first time to determine the socially acceptable risk of SDVs. In our between‐subject survey (N = 499), we determined the respondents’ risk‐acceptance rate of scenarios with varying traffic‐risk frequencies to examine the logarithmic relationships between the traffic‐risk frequency and risk‐acceptance rate. Logarithmic regression models of SDVs were compared to those of human‐driven vehicles (HDVs); the results showed that SDVs were required to be safer than HDVs. Given the same traffic‐risk‐acceptance rates for SDVs and HDVs, their associated acceptable risk frequencies of SDVs and HDVs were predicted and compared. Two risk‐acceptance criteria emerged: the tolerable risk criterion, which indicates that SDVs should be four to five times as safe as HDVs, and the broadly acceptable risk criterion, which suggests that half of the respondents hoped that the traffic risk of SDVs would be two orders of magnitude lower than the current estimated traffic risk. The approach and these results could provide insights for government regulatory authorities for establishing clear safety requirements for SDVs.

Suggested Citation

  • Peng Liu & Run Yang & Zhigang Xu, 2019. "How Safe Is Safe Enough for Self‐Driving Vehicles?," Risk Analysis, John Wiley & Sons, vol. 39(2), pages 315-325, February.
  • Handle: RePEc:wly:riskan:v:39:y:2019:i:2:p:315-325
    DOI: 10.1111/risa.13116
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    1. Hussain, Qinaat & Alhajyaseen, Wael K.M. & Adnan, Muhammad & Almallah, Mustafa & Almukdad, Abdulkarim & Alqaradawi, Mohammed, 2021. "Autonomous vehicles between anticipation and apprehension: Investigations through safety and security perceptions," Transport Policy, Elsevier, vol. 110(C), pages 440-451.
    2. Xing, Yingying & Zhou, Huiyu & Han, Xiao & Zhang, Meng & Lu, Jian, 2022. "What influences vulnerable road users’ perceptions of autonomous vehicles? A comparative analysis of the 2017 and 2019 Pittsburgh surveys," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Liu, Peng & Ma, Yanjiao & Zuo, Yaqing, 2019. "Self-driving vehicles: Are people willing to trade risks for environmental benefits?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 139-149.
    4. Du, Manqing & Zhang, Tingru & Liu, Jinting & Xu, Zhigang & Liu, Peng, 2022. "Rumors in the air? Exploring public misconceptions about automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 237-252.
    5. Manivasakan, Hesavar & Kalra, Riddhi & O'Hern, Steve & Fang, Yihai & Xi, Yinfei & Zheng, Nan, 2021. "Infrastructure requirement for autonomous vehicle integration for future urban and suburban roads – Current practice and a case study of Melbourne, Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 36-53.
    6. Chikaraishi, Makoto & Khan, Diana & Yasuda, Banri & Fujiwara, Akimasa, 2020. "Risk perception and social acceptability of autonomous vehicles: A case study in Hiroshima, Japan," Transport Policy, Elsevier, vol. 98(C), pages 105-115.
    7. Hemesath, Sebastian & Tepe, Markus, 2023. "Framing the approval to test self-driving cars on public roads. The effect of safety and competitiveness on citizens' agreement," Technology in Society, Elsevier, vol. 72(C).
    8. Yan, Yingying & Zhong, Shiquan & Tian, Junfang & Li, Tong, 2022. "Continuance intention of autonomous buses: An empirical analysis based on passenger experience," Transport Policy, Elsevier, vol. 126(C), pages 85-95.

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