In the last decade, self-driving cars have witnessed a meteoric rise in popularity due to exceptional research in the fields of Edge Computing and Artificial Intelligence. Nowadays, autonomous vehicles use elaborate mathematical models in tandem with sophisticated Deep Learning techniques to navigate safely. PID Controllers have been used ubiquitously by researchers for autonomous vehicles. Deep Learning techniques like YOLO allow autonomous vehicles to be able to detect a wide range of objects in their surroundings leading to better responses. In this paper, a PID controller has been implemented to navigate a vehicle in CARLA Simulator. A Custom Traffic Light detection model has also been integrated with the controller to respond to traffic lights in the path of the vehicle.
Implementation of a PID Controller for Autonomous Vehicles with Traffic Light Detection in CARLA
Lect. Notes in Networks, Syst.
22.03.2023
13 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Traffic Light Detection , Deep Learning , Object Detection , Autonomous Vehicle , PID Controller , CARLA Simulator Statistics, general , Artificial Intelligence , Computational Intelligence , Computer Systems Organization and Communication Networks , Computer Science , Engineering , Professional Computing
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