Autonomous Vehicle
Autonomous Vehicle
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Autonomous vehicle control programs that can perform tasks such as basic navigation, follow traffic signs and lights and parallel park a Tesla Model X in Webots simulated environment
Autonomous vehicle control programs that can perform tasks such as basic navigation, follow traffic signs and lights and parallel park a Tesla Model X in Webots simulated environment
Skills developed:
Software: OpenCV, Sensor Integration (GPS, Lidar, Camera, Gyro)
Algorithms: RRT star
Reinforcement Learning: Markov Decision Process
Features of the project
Features of the project
Parallel parking
Parallel parking
Uses lidar and camera feedback to develop a control logic to parallel park the car. The control logic is implemented in stages. Details on the stages are shown in the points below
Stage 1: Backup if started at middle
Stage 2: Identify side of parking and distance
Stage 3 : Identify stretch for close up
Stage 4: Close up
Stage 5 : Find park spot and initiate parallel park
Follow traffic rules
Follow traffic rules
Traffic lights
Computer vision libraries utilized to detect the traffic lights and control actuators to perform tasks based on the color of the traffic lights.
Stop signs
Trained a pattern recognition model to detect a stop sign and stop the vehicle for 3 seconds before the white line
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