The open source simulation platform OCTANEwhich 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.
In the context of 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 serve as partners for future automated cooperative vehicles. The pooling of competences enables a holistic evaluation from a technological, social and economic perspective.
In the BMVI-funded project RELAI - Risk Estimation with a Learning AI a data-driven, AI-based approach is used to generate a wide variety of synthetic test scenarios that reflect real, challenging traffic situations in road traffic. The synthetic test scenarios can be used to test automated driving functions in different simulation environments or in real test fields by displaying them on a tablet. The test scenarios are made available to the general public in an open standardized format via a web portal and the mCLOUD. New test scenarios can be automatically generated based on the measured data and used for the evaluation of situation-adaptive, expectation-conform driving behavior.