University of Mary Washington
Traffic congestion has become a daily problem that most people suffer. This not only impacts the productivity of the population but also poses a safety risk. Most of the technologies for intelligent highways focus on safety measures and increased driver awareness, and expect a centralized management for the traffic flow. This paper presents a new approach for enabling autonomous and adaptive traffic management through vehicular networks. By allowing data exchange between vehicles about route choices, congestions and traffic alerts, a vehicle makes a decision on the best course of action. Unlike centralized schemes that provide recommendations, the VANET-based Autonomous Management (VAM) approach factors in the destination and routes of nearby vehicles in deciding on whether rerouting is advisable.