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…mehr
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.
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.
Inhaltsangabe
Introduction.- The Research Domain of this Thesis and its State of the Art.- Theoretical Foundations Relevant to this Thesis.- Situation Feature Relevance on Measurement Data.- Knowledge-Based Traffic Situation Description.- Relevance by Mutual Information on Ontology Features.- Conclusion.
Introduction.- The Research Domain of this Thesis and its State of the Art.- Theoretical Foundations Relevant to this Thesis.- Situation Feature Relevance on Measurement Data.- Knowledge-Based Traffic Situation Description.- Relevance by Mutual Information on Ontology Features.- Conclusion.
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