Road Condition Estimation with Data Mining Methods using Vehicle Based Sensors
Abstract:
The work provides novel methods to process inertial sensor and acoustic sensor data for road condition estimation and monitoring with application in vehicles, which serve as sensor platforms. Furthermore, methods are introduced to combine the results from various vehicles for a more reliable estimation.
| Zugehörige Institution(en) am KIT | Institut für Fahrzeugsystemtechnik (FAST) |
| Publikationstyp | Hochschulschrift |
| Publikationsjahr | 2020 |
| Sprache | Englisch |
| Identifikator | ISBN: 978-3-7315-1004-8 ISSN: 1869-6058 KITopen-ID: 1000104538 |
| Verlag | KIT Scientific Publishing |
| Umfang | XVI, 195 S. |
| Serie | Karlsruher Schriftenreihe Fahrzeugsystemtechnik / Institut für Fahrzeugsystemtechnik ; 82 |
| Art der Arbeit | Dissertation |
| Prüfungsdaten | 15.11.2019 |
| Schlagwörter | Maschinelles Lernen, Fahrzeugtechnik, Straßenschäden, Fahrzeugsensorik, Maschine Learning, Vehicle Technology, Road Condition, Vehicle Sensors |
| Relationen in KITopen |