Automotive

Artificial intelligence, the low cost of sensors and the development of new communications technologies (4G/5G, V2X…) have created a boom in advanced driver assistance systems (ADAS) and self-driving vehicles.

Challenges:

• Allow the autonomous driving algorithm to cover as many situations as possible
• Prepare the individual for use based on a rethought ergonomics
• Prioritize new services related to autonomous transport

Collecting data will make it possible to develop new services (insurance, parking etc.), optimize R&D and production costs based on actual use by car drivers, or even implement predictive maintenance.

Challenges:

• Protect personal data and car manufacturer data
• Exploit a large quantity of unstructured data
• Innovate in distribution and services in the automotive sector

The software scope in a modern car is up to 100 million lines of code and by this 50 times higher compared to a modern smart phone. In the near future the automotive industry foresees, that installed software solutions along with its associated innovations will make the difference in the global competition. The selling value of the software on a premium vehicle in 2013 was about 10% and increases up to 40% in 2023. The volume of software doubles every 18 months and the risk of software errors increases exponentially.

Challenges:

• Enable future innovations in vehicle networking, car/driver communication, infotainment, driver assistance
• Secure errorfreee and robust software solutions under the specific security aspects of i.e. driver assistance systems
• Develop modular software platforms for cost efficiency and controllable vehicle prices