FhG-Co-Driver - from map-guided automatic driving by machine vision to a cooperative driver support

A digital road map provides partial knowledge about the operating environment for a road vehicle. If a road vehicle is equipped with a video camera, machine vision approaches can provide knowledge about the actual traffic environment around the vehicle. Experiences with a combination of two such approaches during the commissioning of a van for automatic driving on a private road network are reported, including experiences gathered during subsequent driving experiments on public roads and several improvement cycles for hardware and software. Based on these experiences, a second generation vehicle for automatic driving - a sedan - has been designed and commissioned. It is currently evaluated on public roads. This equipment provides an experimental platform for studying drivervehicle interactions with the option to automatically evaluate actual traffic situations around the vehicle in real-time. Our equipment thus offers an approach to record and disentangle the multitude of factors which influence the - often subconscious - reactions of a driver. It is our working hypothesis that only an automatic, in-depth understanding of the actual traffic situation facilitates the design of a driver support system which is competent and flexible enough to win acceptance by a wide spectrum of users.