ULTRACEPT | University of Lincoln

Ultra-layers of brain-inspired information processing for vehicle collision avoidance (ULTRACEPT)

Although in their early stages, autonomous vehicles have demonstrated huge potential in shaping our future lifestyles. However, to be accepted by ordinary users, autonomous vehicles have a critical issue to solve – this is trustworthy collision detection. 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 a 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 needed.

The ULTRACEPT consortium proposes an innovative solution with brain-inspired multiple layered and multiple modalities information processing for trustworthy vehicle collision detection. It takes the advantage 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 from complex weather and lighting conditions.

Learn more about ULTRACEPT on the project website https://ultracept.blogs.lincoln.ac.uk/

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement number no 778062. https://cordis.europa.eu/project/id/7...