Layer Model to abstract Functions of Complex Intervening Driver Assistance System

Jochen Kramer
ASAM International Conference 2015 - Big Data in Future Car Development
Well established intervening driver assistance systems are based on information, which can be directly derived from the powertrain (cruise control, ABS, ESP, etc). On the other hand, the introduction of e.g. Adaptive Cruise Control (ACC) also requires data from the vehicle surrounding as rule base. Future driver assistance systems as well as autonomous driving functionalities require the recording and interpretation of data from the vehicle surrounding. While conventional control systems were so far realized by a controller with a fix number of physical values, the new systems require complex information streams (e.g. continuous camera recordings) and situational decisions on how to drive the vehicle. The recognition of the vehicle surrounding is already possible with the help of different sensors like cameras, radar and ultrasound. Complex driver assistance tasks (like automated lane change on the highway) require consistent processing of environment data and information. One important challenge with regards to development and validation of current and future driver assistance systems is therefore to cope with the quantity and complexity of the available data. This requires an abstraction of information and functions that are needed for carrying out the driving task.
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