Implementation of Lateral and Longitudinal Control in Nebrija Autonomous Vehicle

This paper describes the development and implementation of lateral and longitudinal control algorithms for a low-cost self-driving vehicle within the Nebrija Autonomous Vehicle (NEVA) project. For lateral control, a Pure Pursuit algorithm was implemented using a Python script. This geometric approach leverages GPS data to define a path and calculates the steering angle required to reach a designated goal point along the path. Longitudinal control utilizes a PID controller to achieve a target speed. This target speed is adjusted based on upcoming path curvature data obtained from the Pure Pursuit algorithm. The vehicle can thus modulate its speed for approaching curves or straighter sections. The performance of these algorithms was evaluated through real-world road tests, demonstrating their reliability and effectiveness for the NEVA vehicle.