Abstract
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.
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Souza, C.R.C., Santos, P.E. (2011). Probabilistic Logic Reasoning about Traffic Scenes. In: Groß, R., Alboul, L., Melhuish, C., Witkowski, M., Prescott, T.J., Penders, J. (eds) Towards Autonomous Robotic Systems. TAROS 2011. Lecture Notes in Computer Science(), vol 6856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23232-9_20
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DOI: https://doi.org/10.1007/978-3-642-23232-9_20
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