Using ego-centered affordances in multi-agent traffic simulation

To improve the validity of traffic simulations in urban and suburban areas, we propose to consider the driving context and the driver behavior in terms of space occupation. We endow agent driver with an ego-centered representation of the environment. This representation permits the agent to take a decision in terms of space occupation. Our agent driver model is based on the concept of affordances the ways in which an agent can interact with its environment. First, we use the concept of affordances to identify the possible actions, in terms of space occupation, afforded by the environment. Second, we use an ego-centered representation of the situation around the agent, composed by the identified affordances. The proposed driver model was implemented with ArchiSim and the experiments show that this model makes traffic more fluid.