A multi-agent architecture for a driver model for autonomous road vehicles

A look at the current state of driver models and driver related activities (parking, avoiding collisions, path selection, etc.) shows that driving is broken up in a series of small tasks. These must be executed in a coordinated manner by the driver, Their different nature suggest that each could be implemented by an artificial intelligence paradigm (for example: fuzzy logic, neural nets and knowledge based systems). We think that a multi-agent system integrating autonomous agents and enabling them to cooperate to solve problems that are beyond their individual capabilities is the architecture for a more complete driver model. In the long run, the driver model must integrate all characteristics of driver and vehicle, but for the moment current driver models are dedicated to some specific tasks executed by the driver, lateral and longitudinal control, parking and collision avoidance are examples. In this paper we propose an architecture for a generic multi-agent system used to develop the driver model.