Exploiting Map Information for Driver Intention Estimation at Road Intersections

Abstract : Safety applications at road intersections require algorithms that can estimate the manoeuvre intention of all the drivers in the scene. In this paper, the use of contextual information extracted from a digital map of the road network is explored. We propose a Bayesian network which combines probabilistically uncertain observations on the vehicle's behaviour and information about the geometrical and topological characteristics of the road intersection in order to infer a driver's manoeuvre intention. The approach is evaluated on trajectories recorded from real traffic, including complex scenarios where the behaviour of the vehicle is inconsistent. We define an evaluation method that accounts for the impossibility to make reliable predictions in some situations, and show that the system is able to reliably combine vehicle state information and map information to infer a driver's intended manoeuvre.
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Communication dans un congrès
2011 IEEE Intelligent Vehicle Symposium, Jun 2011, Baden-Baden, Germany. pp.583-588, 2011
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Stéphanie Lefèvre, Christian Laugier, Javier Ibañez-Guzmán. Exploiting Map Information for Driver Intention Estimation at Road Intersections. 2011 IEEE Intelligent Vehicle Symposium, Jun 2011, Baden-Baden, Germany. pp.583-588, 2011. 〈inria-00588743〉

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