Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies

Hong Tan, Fuquan Zhao, Han Hao and Zongwei Liu
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Hong Tan: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Fuquan Zhao: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Han Hao: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Zongwei Liu: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China

IJERPH, 2021, vol. 18, issue 17, 1-12

Abstract: The Intelligent and Connected Vehicle (ICV) is regarded as a high-tech solution to reducing road traffic crashes in many countries across the world. However, it is not clear how effective these technologies are in avoiding crashes. This study sets out to summarize the evidence for the crash avoidance effectiveness of technologies equipped on ICVs. In this study, three common methods for safety benefit evaluation were identified: Field operation test (FOT), safety impact methodology (SIM), and statistical analysis methodology (SAM). The advantages and disadvantages of the three methods are compared. In addition, evidence for the crash avoidance effectiveness of Advanced Driver Assistance Systems (ADAS) and Vehicle-to-Vehicle communication Systems (V2V) are presented in the paper. More specifically, target crash scenarios and the effectiveness of technologies including FCW/AEB, ACC, LDW/LDP, BSD, IMA, and LTA are different. Overall, based on evidence from the literature, technologies on ICVs could significantly reduce the number of crashes.

Keywords: road safety; technological efficacy; autonomous vehicle (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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