Autonomous vehicle navigation with semantical modelling: A project overview

• Published in: 2022 IEEE/SICE International Symposium on System Integration (SII)
• Main Authors: Corrêa Victorino, Alessandro, Abel, Marie-Hélène
• Other Authors: Heuristique et Diagnostic des Systèmes Complexes Compiègne (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2022
• Subjects: [SCCO.COMP]Cognitive science/Computer science; [SPI.AUTO]Engineering Sciences [physics]/Automatic; Narvik; Norway
• Online Access: https://hal.science/hal-03523324; https://hal.science/hal-03523324/document; https://hal.science/hal-03523324/file/Autonomous_vehicle_navigation_semantic_modelling_fv.pdf; https://doi.org/10.1109/SII52469.2022.9708871

International audience In this paper we consider the problem related to the autonomous navigation of a robotic vehicle by modeling and describing the semantics of the context associated to the navigation. Considering the semantical modelling of the navigation context, as obstacles, pedestrians, roundabouts, information on the vehicle itself (load, power, etc.), on the robotic vehicle, it is integrating to add this symbolic artificial intelligence to a classical navigation control scheme. This semantic modeling generates an additional degree of abstraction by "reasoning" about the information collected by the various sensors of the autonomous vehicle in order to build a navigation context. This navigation context is able to provide decision support for the autonomous or semi-autonomous vehicle (interaction to the driver). In this paper, we present a project developed at