Enable the future mobility developments following the electrification, standardisation, automatisation and digitalisation implementation strategy by providing new AI-enabled electronic component and systems for ECAS vehicles for advanced perception, efficient propulsion and batteries, advanced connectivity, new integration and platform concepts and intelligent components based on trustworthy AI.
Charging network infrastructures are expanding, reducing “range anxiety” for consumers and reducing the time it takes to recharge a vehicle. Existing manufacturers must support new software-based architectures capable of driving needed chemistry efficiencies. More than ten automakers have promised a full range of EV’s by 2030.
The vision that all cars will leverage built-in two-way connectivity capabilities. These capabilities will provide services to the driver, send data back to the cloud and provide over-the-air software updates. The need to improve cybersecurity also rises, increasing the need for more sophisticated in-vehicle and cloud-based security controls.
In the picture, some fundamental aspects of the AI4CSM project trends related to the green deal 2050 are identified. Sharing of services, products, personal skills, and time is seen as the essential feature of the development of sharing economy, whose popularity has grown rapidly in recent years, leading to the success of digital platforms for mobility. Sharing economies have the potential to encourage the distribution and use of underutilized assets and to promote a more sustainable consumption, with economic, social, and environmental consequences.
The automated and autonomous driving functions support reducing the risk of crashes through alerts and discrete system actuation, alerting drivers of approaching pedestrians and allowing intermittent “hands-off” control for brief periods of time. Full autonomous in defined geographic spaces will provide greater productivity to engage in secondary tasks and will enable new business models via lowering the cost of operational human drivers