An agent-based platform to evaluate V2X routing road traffic scenarios

Abstract

Traffic congestion is a recurrent problem in both urban and non-urban road networks. It impacts several key issues such as higher overall gas consumption, vehicle emissions, and noise. Traffic information available on time to vehicles is a key element for helping to reduce these issues. Nowadays, modern vehicles produce information via its own sensors that can be communicated to other vehicles on the road. For example, average speed or fuel consumption or if it was applied the ABS due to slipping in the previous segment road. This information could be exchanged between vehicles on road to help them in their driving decisions. This is known as V2V communication capability. When this information can be exchanged also with Infrastructure elements of the road, it is known as V2X communication. Current approaches for simulators in the context of V2X communication are devoted to the design and evaluation of the wireless technologies suitable for the efficient exchange of information, they are not designed to deal with the usage that drivers can do with the traffic information exchanged. In this paper, an agent based model is presented to test the importance of traffic information exchange for reducing traffic congestion. In this model, vehicles can use no communication, vehicles to vehicle (V2V) or vehicle to infrastructure (V2I) communications. The functional architecture of the proposed model is structured in several layers including the road network knowledge model, the road traffic model and the interaction protocols. The model allows the creation of different traffic scenarios, based on traffic flow, type of vehicles, etc. Results drawn from the executions of diverse traffic scenarios show the relevance that information exchange (via V2I and V2V communications) has to calculate efficient itineraries in real-time, and thus, reducing the overall consequences of traffic congestion.