A predictive accident-duration based decision-making module for rerouting in environments with V2V communication

Communication for cooperative traffic management increases convenience and efficiency in driving. Intelligent vehicles can collect information about the driving environment, the driver situation and, more importantly, information on other vehicles. While giving this information to the driver can be useful, there is also the possibility of presenting the driver with too much information. Existing vehicles already have some mechanisms to take certain actions if the driver fails to act. Future vehicles will need more complex decision-making modules which receive the raw data from all available sources, process this data and inform the driver about existing or impending situations and suggest, or even take actions. In this work, we explore the use of a decision-making module for accident situations that processes information from VANET communication and advises the driver based on the situation. Our decision-making algorithm is a simple and effective algorithm that can be implemented in each vehicle to assist the driver in situations where rerouting to avoid traffic congestion caused by an accident may be necessary. Our approach estimates accident duration and provides a rerouting for upcoming traffic. Our algorithm has been implemented and evaluated within an elegant traffic simulation system where both city and highway environments are considered, along with various proportions of V2V-equipped vehicles. Overall, the results indicate that using our decision-making module in vehicles shows great potential for improving performance of vehicular systems by reducing both travel and wait times and providing more accurate information on surrounding environments.