Research Engineer
Aniket Salvi has been working as a research engineer at Fraunhofer IKS since November 2017. Previously, he graduated with a master of science degree in electrical engineering and information technology from Otto von Guericke University Magdeburg. His main research area is model-driven engineering in the fields of automotive and industrial automation. Currently, his work focuses on the development of methods for dependable environment perception and context awareness for dynamic safety management.
by Aniket Salvi
In our previous article, we introduced some standardized terminology related to Autonomous Driving and Operational Design Domain (ODD). In this article, we look at the safety implications of transitioning through multiple ODDs while executing the Dynamic Driving Task (DDT).
The Operational Design Domain (ODD) precisely defines the area in which automated driving functions may be used. As such, they represent a fundamental prerequisite for safe automated driving. Part 1 of a three-part series on the importance of ODD.
Artificial intelligence (AI) has to be able to handle uncertainty before we can trust it to deliver in safety-critical use cases, for example, autonomous cars. The Fraunhofer Institute for Cognitive Systems IKS is investigating ways to help AI reason with uncertainty, one being the operational design domain.
