Inferenz von Kreuzungsinformationen aus Flottendaten
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 |
|---|---|
| : | |
| 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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| 520 | |a 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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| 653 | |a Lichtsignalanlage | ||
| 653 | |a Automated Map Creation | ||
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| 653 | |a Traffic Light | ||
| 653 | |a Automatisierte Kartenerstellung | ||
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