TRADER:Traffic Light Phases Aware Driving for Reduced Traffic Congestion in Smart Cities

Despite the significant research efforts and resources spent to alleviate the impact of road traffic congestion on economy, environment and road safety, it is still one of the major unsolved problems of the 21st century. The emergence of smart self-driving vehicles promises a dramatic change in the way road traffic congestion is controlled and mitigated. This can be achieved by enabling efficient communication between these vehicles and modern road infrastructure such as smart traffic lights controllers. This paper, therefore, proposes a simple yet efficient mechanism named (TRADER: TRaffic Light Phases Aware Driving for REduced tRaffic Congestion) in order to reduce the overall vehicles' travel time in smart cities. TRADER has been implemented and extensively evaluated under several scenarios using SUMO and TraCI. The obtained simulation results, using a set of typical road networks, have demonstrated the effectiveness of TRADER in terms of the significant reduction of travel time, up to 31.44% in a random road network topology.