Knowledge-based driver assistance systems [electronic resource] : traffic situation description and situation feature relevance / Michael Huelsen.
2014
TL272.57
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Details
Title
Knowledge-based driver assistance systems [electronic resource] : traffic situation description and situation feature relevance / Michael Huelsen.
Author
Huelsen, Michael, author.
ISBN
9783658057503 electronic book
3658057505 electronic book
9783658057497
3658057505 electronic book
9783658057497
Published
Wiesbaden : Springer Vieweg, 2014.
Language
English
Language Note
Abstract in English and German.
Description
1 online resource (xvii, 176 pages) : illustrations (some color)
Item Number
10.1007/978-3-658-05750-3 doi
Call Number
TL272.57
Dewey Decimal Classification
629.2/72
Summary
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.
Note
"Also PhD thesis Karlsruhe Institute of Technology (KIT), Germany, 2013."
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Description based on online resource; title from PDF title page (SpringerLink, viewed May 2, 2014).
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Table of Contents
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.
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.