Risk Assessment for Improved Vehicle Safety using Front Vehicle Dynamic States through Vehicular Communication

Abstract

In recent years, advanced driver assistance systems or highly automated driving systems are expected to enhance road traffic safety, transport efficiency, and driver comfort. Practical applications have become possible due to recent advances in vehicle local sensors and inter vehicle communications. These advances have opened up many possibilities for active safety systems to be more intelligent and robust. The further enhancement of these technologies can be utilized as a risk assessment system of automated drive. This dissertation presents a risk assessment for improved vehicle safety using Front Vehicle Dynamic States through vehicle-to-vehicle wireless communication. A vehicle-to-vehicle wireless communication (V2V communication) has been implemented and fused with a radar sensor to obtain the prediction of remote vehicles motion. Based on the predicted behavior of remote vehicles, a collision risk and a human reaction time are determined for a better driver acceptance and active safety control intervention. A human-centered risk assessment using the V2V communication has been incorporated into a collision avoidance algorithm to monitor threat vehicles ahead and to find the best intervention point. The performance of the proposed algorithm has been investigated via computer simulations and vehicle tests for application to urban and highway driving situation. It has been shown from both simulations and vehicle tests that the proposed integrated risk assessment algorithm with the V2V communication can be beneficial to active safety systems in decision of controller intervention moment and in control of automated drive for the guaranteed safety.