Research of Dynamic Vehicle Positioning in Different Driving Scenarios

  • 鄒 達文

Student thesis: Master's Thesis


Autonomous vehicles are becoming popular in modern society so navigation of autonomous vehicles is now an important issue The traditional positioning system is satellite navigation The accuracy of satellite navigation depends on the environment and the quality of the signal Perceptual sensors such as camera Lidar and inertial sensors may also assist navigation Similarly information from the external environment is subject to uncertainties Using an inertial sensor integrated with the Global Navigation Satellite System is a common approach to solving this problem The general method used to integrate two systems is the extended Kalman filter However there are some assumptions and approximations in the process that may not satisfy a complex vehicle dynamic system This thesis discusses the positioning accuracy in multi driving scenarios where different fusion algorithms are used to compare the positioning performance
Date of Award2017 Aug 25
Original languageEnglish
SupervisorJyh-Chin Juang (Supervisor)

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