Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB
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Autonomous systems / robotics

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Automated, cooperative and connected driving

Automation is becoming an integral part of all areas of daily life. In addition to autonomous manipulators and robot systems, which can independently navigate in rough terrain to perform dangerous tasks, we at Fraunhofer IOSB are working on future-oriented innovative mobility solutions. We develop application-oriented driver assistance functions and conduct research on automated and connected driving under consideration of realistic market launch scenarios. This includes both questions of validation through targeted data collection and simulation as well as acceptance considerations through the development of innovative functionalities focused on passengers.

Fields of application

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Two identical “test vehicles for technologyexperiments” (German: Versuchsfahrzeuge für Technologie-Experimente, VERTEX) approved for automated driving with numerous sensors and actuators as variants with electric and combustion engines, offer extensive possibilities for data collection and development of automated driving functions.

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The open source simulation platform OCTANE, which is currently under development, can serve as an arbitrarily extendable simulation platform for a multitude of mobility issues. The system architecture supports the simulation of different abstraction levels of e.g. vehicle dynamics, traffic flow and sensor models with maximum adaptability to the respective application.

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In the “High Performance Center for Mobility Research”, we are dealing with the evolutionary introduction of near-market novel connected driving functions (iFORESEE) with the aim of achieving a high penetration rate of vehicles with connected technologies that may partner with future automated cooperative vehicles. The pooling of competences enables a holistic evaluation from a technological, social and economic perspective.

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In RELAI(text in German language only), a data-driven AI approach is used to generate synthetic test scenarios as a representation of real, challenging traffic situations on the road. The test scenarios are shared with the general public via a web portal and the mCLOUD. New scenarios can be generated automatically from measured data and used to evaluate situation-adaptive driving behavior.