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

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.

Automated summary

This study summarizes the evidence for the crash avoidance effectiveness of technologies equipped on Intelligent and Connected Vehicles (ICVs), comparing three common methods for safety benefit evaluation (FOT, SIM, SAM) and presenting evidence for different technologies in various crash scenarios. Overall, technologies on ICVs have been shown to significantly reduce the number of crashes according to literature evidence.