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Conference Papers Year : 2022

Localization Integrity for Intelligent Vehicles: How and for what?


In theory, a vehicle could navigate with only a perception system that would understand everything about its surroundings. Moreover, we often navigate more efficiently on roads we have already traveled thanks to the geospatial knowledge of the environment.Localization and maps are a way to simplify navigation tasks, for autonomous vehicles or advanced driving assistance. Indeed, localization associated with a High Definition (HD) map facilitates the understanding of the driving situation, allowing to focus attention on areas of interest, to identify interacting road users and to anticipate the situation based on prediction mechanisms. Global localization is also a way to increase perception beyond the sensors' field of view, in hidden areas or in degraded conditions thanks to the real-time exchange of data between road users in a cooperative system. Localization being used in many autonomous navigation tasks, it has to be non-misleading. Integrity monitoring in real-time becomes a key issue as well as defining its requirements which are task-dependent (and very diverse). This is a challenge that the scientific community faces when it comes to defining the different levels of requirements. In this talk, I will present a multi-sensor localization system studied in the lab using GNSS, odometry and exteroceptive sensors (Lidar and camera) able of detecting and associating geo-referenced features in HD maps such as road markings or traffic signs.I will also present results we have recently obtained in the lab regarding the management of events that can lead to integrity losses and misleading localization information for autonomous vehicles. A particular focus will be on the management of erroneous sensor data, map errors, and association problems. Finally, the question of the choice of a TIR (Target Integrity Risk) for the calculation of a Protection Level (PL) will be addressed in order to initiate discussions with the workshop participants.
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hal-03691244 , version 1 (08-06-2022)


  • HAL Id : hal-03691244 , version 1


Philippe Bonnifait. Localization Integrity for Intelligent Vehicles: How and for what?. 33rd IEEE Intelligent Vehicles Symposium (IV 2022), Jun 2022, Aachen, Germany. ⟨hal-03691244⟩
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