Scalable reactive vehicle-to-vehicle congestion avoidance mechanism

Abstract

The increasing popularity and acceptance of VANETs will make the deployment of autonomous vehicles easier and faster since the VANET will reduce dependence on expensive sensors. Many useful applications will be possible with the usage of VANETs, which will improve the safety and quality of trips for the owners of these vehicles. One of these applications is the avoidance of traffic congestion by smart dynamic rerouting. For scalability, current cloud-based solutions, like Google Maps traffic, update congestion levels after a time interval rather than providing real-time measurements. In this paper, we introduce a vehicle-to-vehicle congestion avoidance mechanism, which detects real-time congestion levels and reroutes vehicles accordingly to minimize their trip times. Our system is highly distributed and is, therefore, not subjected to the limitations of centralized congestion avoidance mechanisms. We show via simulation that our system can significantly decrease the trip times of vehicles as well as the average car density on the map. Our proposed system, with its checkpoint and offline path generation approaches, is more responsive to local congestion level changes and computationally less complex for least congested route calculations than state-of-the-art congestion avoidance mechanisms.