Knowledge-Based Driver Assistance Systems: Traffic Situation Description and Situation Feature Relevance - Softcover

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Michael Huelsen completed his doctoral thesis in a co-operation between the Karlsruhe Institute of Technology (KIT) and the Robert Bosch GmbH. After working in automotive development he is now working in a leading position in purchasing and value engineering at a renowned company manufacturing electrical traction systems.

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The comprehension of a traffic situation plays a major role in driving a vehicle. Interpretable information forms a basis for future projection, decision making and action performing, such as navigating, maneuvering and driving control.

Michael Huelsen provides an ontology-based generic traffic situation description capable of supplying various advanced driver assistance systems with relevant information about the current traffic situation of a vehicle and its environment. These systems are enabled to perform reasonable actions and approach visionary goals such as injury and accident free driving, substantial assistance in arbitrary situations up to even autonomous driving.

Content

• Situation Feature Relevance on Vehicle Measurement Data
• Relevance of Historical Measurement Values
• Knowledge-Based Traffic Situation Description and Simulation
• Relevance by Mutual Information on Ontology Features

Target Groups

• Researchers, lecturers and students in the fields of automotive engineering, mechatronics, computer science and artificial intelligence
• Engineers and developers in the automotive industry, specifically areas of driver assistance systems, vehicle control and mechatronics

The Author

Michael Huelsencompleted his doctoral thesis in a cooperation between the Karlsruhe Institute of Technology (KIT) and the Robert Bosch GmbH. After working in automotive development he is now working in a leading position in purchasing and value engineering at a renowned company manufacturing electrical traction systems.