On the Dempster-Shafer framework and new combination rules
Information Sciences: an International Journal
Artificial Intelligence
Mass distributions on L-fuzzy sets and families of frames of discernment
Advances in the Dempster-Shafer theory of evidence
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Decision making in the TBM: the necessity of the pignistic transformation
International Journal of Approximate Reasoning
Hierarchical and conditional combination of belief functions induced by visual tracking
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Singular sources mining using evidential conflict analysis
International Journal of Approximate Reasoning
Belief functions contextual discounting and canonical decompositions
International Journal of Approximate Reasoning
Virtual 3D City Model for Navigation in Urban Areas
Journal of Intelligent and Robotic Systems
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This article proposes a perception scheme in the field of intelligent vehicles. The method exploits prior map knowledge and makes use of evidential grids constructed from the sensor data. Evidential grids are based on occupancy grids and the formalism of the Dempster-Shafer theory. Prior knowledge is obtained from a geographic map which is considered as an additional source of information and combined with a grid representing sensor data. Since the vehicle environment is dynamic, stationary and mobile objects have to be distinguished. In order to achieve this objective, evidential conflict information is used for mobile cell detection. As well, an accumulator is introduced and used as a factor for mass function specialisation in order to detect static cells. data recorded in urban conditions illustrate the benefits of the presented approach.