Probabilistic Logic Reasoning about Traffic Scenes

This paper describes a probabilistic logic reasoning system for traffic scenes based on Markov logic network, whose goal is to provide a high-level interpretation of localisation and behaviour of a vehicle on the road. This information can be used by a lane assistant agent within driver assistance systems. This work adopted an egocentric viewpoint for the vision and the reasoning tasks of the vehicle and a qualitative approach to spatial representation. Results with real data indicate good performance compared to the common sense interpretation of traffic situations.