The Experts below are selected from a list of 459 Experts worldwide ranked by ideXlab platform
Zhigang Xu - One of the best experts on this subject based on the ideXlab platform.
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How Safe Is Safe Enough for Self‐Driving Vehicles?
Risk Analysis, 2018Co-Authors: Peng Liu, Run Yang, Zhigang XuAbstract: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.
Peng Liu - One of the best experts on this subject based on the ideXlab platform.
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How Safe Is Safe Enough for Self‐Driving Vehicles?
Risk Analysis, 2018Co-Authors: Peng Liu, Run Yang, Zhigang XuAbstract: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.
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How Safe Is Safe Enough for Self-Driving Vehicles?
Risk analysis : an official publication of the Society for Risk Analysis, 2018Co-Authors: Peng Liu, Run YangAbstract: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.
Run Yang - One of the best experts on this subject based on the ideXlab platform.
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How Safe Is Safe Enough for Self‐Driving Vehicles?
Risk Analysis, 2018Co-Authors: Peng Liu, Run Yang, Zhigang XuAbstract: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.
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How Safe Is Safe Enough for Self-Driving Vehicles?
Risk analysis : an official publication of the Society for Risk Analysis, 2018Co-Authors: Peng Liu, Run YangAbstract: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.
Yun Luo - One of the best experts on this subject based on the ideXlab platform.
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Societal Risk acceptance criteria for pressure pipelines in China
Safety Science, 2018Co-Authors: Jingjing Pei, Guantao Wang, Sida Luo, Yun LuoAbstract:Abstract When a pressure pipeline accident occurs in the vicinity of people, it may cause a large number of injuries and deaths. Risk management has become one of the most effective means of preventing pressure pipeline accidents. However, there are no clearly proposed pipeline Risk acceptance criteria in China. To improve the level of safety supervision and strengthen the decision-making ability of enterprises and governments at all levels, this paper attempted to establish societal Risk acceptance criteria for pressure pipelines in China. FN-curves were used as the indicator of societal Risk. A large amount of historical accident data was analyzed via linear regression. Then, the role of interval estimation derived from the regression equation was utilized in combination with the ALARP principle to form the Acceptable criteria for societal Risk. Graphical results were disclosed and showed that the upper limits of tolerable Risk and Broadly Acceptable Risk respectively started from about 10−4.6/a and 10−5.3/a and declined with a slope of 1.47. The approach was reasonable in that it accurately reflected the characteristics and rules of pressure pipeline accidents in China. Simultaneously, to ensure stability and continuous improvement, the use and applicability of societal Risk acceptance criteria were discussed from both dynamic and regional factors based on the Chinese environment for making related suggestions.
Jingjing Pei - One of the best experts on this subject based on the ideXlab platform.
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Societal Risk acceptance criteria for pressure pipelines in China
Safety Science, 2018Co-Authors: Jingjing Pei, Guantao Wang, Sida Luo, Yun LuoAbstract:Abstract When a pressure pipeline accident occurs in the vicinity of people, it may cause a large number of injuries and deaths. Risk management has become one of the most effective means of preventing pressure pipeline accidents. However, there are no clearly proposed pipeline Risk acceptance criteria in China. To improve the level of safety supervision and strengthen the decision-making ability of enterprises and governments at all levels, this paper attempted to establish societal Risk acceptance criteria for pressure pipelines in China. FN-curves were used as the indicator of societal Risk. A large amount of historical accident data was analyzed via linear regression. Then, the role of interval estimation derived from the regression equation was utilized in combination with the ALARP principle to form the Acceptable criteria for societal Risk. Graphical results were disclosed and showed that the upper limits of tolerable Risk and Broadly Acceptable Risk respectively started from about 10−4.6/a and 10−5.3/a and declined with a slope of 1.47. The approach was reasonable in that it accurately reflected the characteristics and rules of pressure pipeline accidents in China. Simultaneously, to ensure stability and continuous improvement, the use and applicability of societal Risk acceptance criteria were discussed from both dynamic and regional factors based on the Chinese environment for making related suggestions.
