A Multi-Agent Driving Simulation Approach for Evaluating the Safety Benefits of Connected Vehicles

The in-vehicle warning information provided in the CVs environment allow the driver to respond rapidly to upcoming hazardous situations. The main purpose of this study is to evaluate the safety benefits due to the provision of warning information by analyzing vehicle interactions that are defined as the behavior change of the subject vehicle and the preceding vehicle. A notable feature of this study is the use of a multi-agent driving simulation (MADS) method to analyze the vehicle interaction with various vehicle pairs that are composed of the connected vehicle (CV) capable of receiving warning information and the regular vehicle (RV) that does not receive warning information. A total of four scenarios representing different vehicle pairs, which include CV-RV, RV-CV, CV-CV, and RV-RV, are evaluated in this study. The proposed analysis consists of four parts: the characteristics of subject vehicle maneuvering, variation of relative speed, evasive maneuvering by lane change, and overall crash potential. As an example, the result of analyzing crash potential index (CPI) showed that the greatest safety benefits were obtained with the CV-CV case among aforementioned four vehicle pairs. Approximately 45% of CPI reduction was achievable with the CV-CV case, compared to the RV-RV case. In addition to the CPI, useful findings obtained by investigating safety indicators for each vehicle pair are discussed in terms of safety benefits. The results of this study are expected to be used for both deriving valuable policies and developing more effective in-vehicle warning technologies to fully exploit the benefits of CVs.