Rationalizing Safety Impacts under Connected Vehicle Operation: Case Study of Forward Collision Warning System

To systematically measure safety impact, especially reveal how the Connected Vehicles (CVs)' operation in traffic flows improve safety, a surrogate safety measurement can be used to disclose possible frequency and intensity of the traffic conflicts, as well as the likelihood of a conflict developing into a collision. Since a real crash could be difficultly estimated, the surrogate safety index can be measured in detailed safety-related events which can be realistically reproduced from the microscopic traffic flow models through the behavior adaptation of individual CV-equipped drivers. In this study, the CV-affected driving behavior parameters are integrated into the state-of-the-art traffic simulation model. The interactions between the CV functional attributes (e.g., CV function type, message type, message timing and drivers' compliance level to CV messages) and drivers' behavior attributes (e.g., perception-reaction time, desired speed and desired following distance) can be virtually observed and determined. The presented method is examined in a case study of a freeway site in the Cincinnati area, Ohio. It is found out that the CV-affected reaction time, desired headway and speed contribute to the reduced conflicting frequency and intensity of vehicles in traffic flows. This finding implies positive impact of the CV safety technologies on highway systems in the CAV environment.