Self-Driving Car Autonomous System Overview - Industrial Electronics Engineering - Bachelors' Thesis -
Keywords: 
Autonomous vehicles.
SLAM
LIDAR
GPS/GNSS
Issue Date: 
Oct-2020
Defense Date: 
Jun-2020
Publisher: 
Servicio de Publicaciones. Universidad de Navarra
Citation: 
CASADO HERRÁEZ, Daniel "Self-Driving Car Autonomous System Overview - Industrial Electronics Engineering - Bachelors' Thesis -" Días, J. y Medina, A.Trabajo fin de grado. Universidad de Navarra, Pamplona, 2020
Abstract
Research has made possible a continuous development of autonomous vehicles during the past decade. This project will provide an overview of the main technologies involved in autonomous driving, mentioning specific features that will make it suitable for the Formula Student Driverless competition. First, the sensors that capture data from the environment will be studied: LIDAR, camera, radar, GPS, IMU, odometry and their combination using sensor fusion. Second, object identification and localization will be explained with practical examples of classical methods (color thresholding and descriptor extraction), as well as modern techniques using convolutional neural networks. Third, the control components of the car will be analyzed, regarding the car model, path generation and optimization, and the vehicle controller. Finally, Formula Student driverless car examples will be presented with the goal of comparing the studied components with real life cases.

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