Data-driven development and optimization approach using the example of autonomous driving
Research has been carried out for many years on highly automated and autonomous vehicles; so far with modest results. The reason: Many technical hurdles are still to be overcome, and numerous legal specifications that strongly influence further technical development must be taken into consideration. Many experts are therefore already speaking of the end of the hype around autonomous driving. For example, at the last Consumer Electronic Show (CES), or according to the findings from the Gartner Hype Cycle. The result in 2019: Before autonomous driving becomes reality at development stage 4, another ten years will pass; the hype is currently going through the valley of disillusionment.
All this, of course, does not mean the end of development. It is merely becoming clear that an awareness of the challenges has emerged, and the main focuses are being shifted. Thus, at the present time the focus is on the further development of automated driving functions such as the "Highway Pilot", which consists of a highly intelligent network of assistance and connectivity systems. But here too, there are limits to the evolution, which is why data-driven development is indispensable.
In our MHPDeepDive "Data-Driven Engineering", we will highlight the potential of the new development approach. For this purpose, we will use the example of a value chain that we have created with the help of the MHP Demonstrator. We will present the results and analyze further challenges within the context of the digital transformation that can be mastered with this solution approach.
Dr. Nadja Peterseim
Manager | Engineering Performance and Strategy
Beginn: 11:00 (CEST)
Ende: 11:30 (CEST)