Guillaume Trehard

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Either for driver assistance systems or autonomous vehicles, detecting traffic lights (status and pose) is required when Intelligent Transport Systems go downtown. As detection algorithms could still have some misclassification on the traffic light status, this paper proposes a solution to nearly avoid this problem. An Interacting Multiple Model filter is(More)
From the early beginning, the Simultaneous Localization And Mapping (SLAM) problem has been approached using a probabilistic background. A new solution based on the Transferable Belief Model (TBM) framework is proposed in this article. It appears that this representation of knowledge affords numerous advantages over the classic probabilistic ones and leads(More)
Locate a vehicle in an urban environment remains a challenge for the autonomous driving community. By fusing information from a LIDAR, a Global Navigation by Satellite System (GNSS) and the vehicle odometry, this article proposes a solution based on evidential grids and a particle filter to map the static environment and simultaneously estimate the position(More)
Navigation in the Intelligent Transportation Systems (ITS) domain is still divided between reliable solutions that require heavy and costly set-ups and affordable solutions that still lack performances. By proposing a new method for Simultaneous Localisation and Mapping (SLAM) based on Transferable Belief Model (TBM), the authors aimed at finding a(More)
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