Multi-Agent Traffic Simulation for Development and Validation of Autonomic Car-to-Car Systems

In this chapter, we present the concept of an integrated multi-agent simulation platform to support the development and validation of autonomic cooperative car-to-car systems. The simulation allows to validate the car-to-car coordination strategies in various traffic scenarios in variable technology penetration levels (i.e. mixing different strategies) and user acceptance of such system as an external observer and/or as a part of the traffic (human in the loop with intelligent cooperative guidance system). The platform combines features of realistic driving simulation, traffic simulation with flexible level of detail and AI controlled vehicles. The principal idea of the platform is to allow the development and study of complex autonomic distributed car-to-car systems for vehicles coordination. The platform provides a development environment and a tool chain that is necessary for the validation of such complex systems. Autonomic car-to-car systems are based on coordination mechanisms between agents, where an agent represents a reasoning unit of a single vehicle. The road traffic is modelled as a multi-agent system of cooperative agents. The interaction between the agents brings autonomic properties into the emerged system (e.g. the traffic adapts to a blockage of a lane and vehicles merge into a second lane). The system also exhibits autonomic properties from a single user perspective. The driver approaches the system in a form of a driver assistance system—we can refer it as an autonomic driver assistance system. The driver is interacting only with the assistance system via a human-machine interface (HMI). The autonomic driver assistance system is hiding the complexity of multi-agent interactions from the user. The related agent of the single vehicle is responsible for an interaction with other agents in the system without any user’s intervention.