Risk-informed longitudinal control in autonomous vehicles: A safety potential field modeling approach

Author:

Shao YichangORCID,Han Zhongyi,Shi XiaomengORCID,Zhang Yuhan,Ye Zhirui

Publisher

Elsevier BV

Subject

Statistical and Nonlinear Physics,Statistics and Probability

Reference48 articles.

1. Modeling automated vehicle crashes with a focus on vehicle at-fault, collision type, and injury outcome;Kutela;J. Transp. Eng. Part Syst.,2022

2. National Highway Traffic Safety Administration, Summary Report: Standing General Order on Crash Reporting for Level 2 Advanced Driver Assistance Systems, Tech. Rep. DOT HS 813 325. US Department of Transportation (2022).

3. US report: Nearly 400 crashes of automated tech vehicles, AP News. (2022). 〈https://apnews.com/article/self-driving-car-crash-data-ae87cadec79966a9ba56e99b4110b8d6〉 (Accessed October 18, 2023).

4. A Identification Method on Traffic Accidents in the Lower Yangtze River;Zhang,2021

5. Efficient histogram-based gradient boosting approach for accident severity prediction with multisource data;Tamim Kashifi;Transp. Res. Rec. J. Transp. Res. Board.,2022

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