Improving location of vehicles in rural roads

In the last years, the industry of autonomous and assisted driving has been emerging considerably. There are many aspects that should be considered to provide a secure and accurate system. One of them is the location mechanism, which should be able to work in any location and under any weather condi...

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Detalles Bibliográficos
Autor: Igual Nevot, Julia
Tipo de recurso: tesis de maestría
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/340252
Acceso en línea:https://hdl.handle.net/2117/340252
Access Level:acceso abierto
Palabra clave:Autonomous vehicles
Kalman filtering
Ultra wideband
Vehicle localization
Kalman Filter
Inertial Navigation System
Vehicles autònoms
Kalman, Filtratge de
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
Descripción
Sumario:In the last years, the industry of autonomous and assisted driving has been emerging considerably. There are many aspects that should be considered to provide a secure and accurate system. One of them is the location mechanism, which should be able to work in any location and under any weather condition. There are many location solutions but the most traditional and globally used are the ones based on GNSS or image recognition. However, those methods have points of failure that can result in an accident. In certain conditions, to obtain a precise and reliable localization, further information is needed. Nowadays we can construct reference systems based on ultra-wideband (UWB) signals or based disturbances found on the road that can provide additional sources of information, enough to support an autonomous driving. In this thesis, an evaluation of a hybrid solution integrating UWB distance measurements and Inertial Navigation System (INS) for positioning a vehicle in a rural road is performed.