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Financement de l’UE (1 894 500 €) : Perception ultra-stratifiée avec traitement de l’information inspiré par le cerveau pour éviter les collisions avec les véhicules Hor11/07/2018 Programme de recherche et d'innovation de l'UE « Horizon »
Texte
Perception ultra-stratifiée avec traitement de l’information inspiré par le cerveau pour éviter les collisions avec les véhicules
Autonomous vehicles, although in its early stage, have demonstrated huge potential in shaping future life styles to many of us. However, to be accepted by ordinary users, autonomous vehicles have a critical issue to solve – this is trustworthy collision detection. No one likes an autonomous car that is doomed to a collision accident once every few years or months. In the real world, collision does happen at every second - more than 1.3 million people are killed by road accidents every single year. The current approaches for vehicle collision detection such as vehicle to vehicle communication, radar, laser based Lidar and GPS are far from acceptable in terms of reliability, cost, energy consumption and size. For example, radar is too sensitive to metallic material, Lidar is too expensive and it does not work well on absorbing/reflective surfaces, GPS based methods are difficult in cities with high buildings, vehicle to vehicle communication cannot detect pedestrians or any objects unconnected, segmentation based vision methods are too computing power thirsty to be miniaturized, and normal vision sensors cannot cope with fog, rain and dim environment at night. To save people’s lives and to make autonomous vehicles safer to serve human society, a new type of trustworthy, robust, low cost, and low energy consumption vehicle collision detection and avoidance systems are badly needed. This consortium proposes an innovative solution with brain-inspired multiple layered and multiple modalities information processing for trustworthy vehicle collision detection. It takes the advantages of low cost spatial-temporal and parallel computing capacity of bio-inspired visual neural systems and multiple modalities data inputs in extracting potential collision cues at complex weather and lighting conditions.
| Guangzhou University | ? |
| AGILE ROBOTS AG | 279 000 € |
| DINO ROBOTICS GmbH | 9 000,00 € |
| UNIVERSITAET MUENSTER | 225 000 € |
| UNIVERSITY OF HAMBURG | 162 000 € |
| University of Leicester | 148 500 € |
| University of Lincoln | 765 000 € |
| University of Newcastle Upon Tyne | 247 500 € |
| Visomorphic Technology Ltd. | 58 500 € |
https://cordis.europa.eu/project/id/778062
Cette annonce se réfère à une date antérieure et ne reflète pas nécessairement l’état actuel. L’état actuel est présenté à la page suivante : Guangzhou University, Guangzhou, Chine.