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The next generation of driver assistance systems and highly automated driving functions are based on digital maps. In order to meet the high requirements on the correctness and up-to-dateness of this information, this work presents new automated methods to extract up-to-date map information from fle...
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| Superior document: | Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie |
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| Year of Publication: | 2017 |
| Language: | German |
| Series: | Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
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| Physical Description: | 1 electronic resource (XIX, 171 p. p.) |
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| Summary: | The next generation of driver assistance systems and highly automated driving functions are based on digital maps. In order to meet the high requirements on the correctness and up-to-dateness of this information, this work presents new automated methods to extract up-to-date map information from fleet data. The focus is on the inference of static intersection information from fleet data through machine learning and statistical methods. |
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| ISBN: | 1000073704 |
| Hierarchical level: | Monograph |