The automotive market is subject to different major societal challenges such as reduction of pollutant emissions, reduction of traffic fatalities, or increase mobility for ageing population and disabled people. These societal challenges are addressed by technology trends strongly supported and enabled by Big Data to generate meaningful information and knowledge. As a result, a shift of the value creation in the automotive domain toward ICT has led to vehicles that have already become computers-on-wheels and are now rapidly evolving towards data-on-wheels.
In this context, the challenge is to appropriately manage and use all the local and global information from vehicle fleets to evaluate and validate correct operation in all possible situations. This is especially challenging for embedded diagnosis functions taking into account information from multiple vehicles, and over long periods of time.
The use of the EVOLVE testbed will allow to enrich integrated developments relevant for testing of autonomous driving functionalities with novel scenarios captured by a fleet of vehicles operated in daily traffic.