Abstract

Different algorithms for path tracking have been described and implemented for autonomous vehicles. Traditional geometric algorithms like Pure Pursuit use position information to compute vehicle’s steering angle to follow a predefined path. The main issue of these algorithms resides in cutting corners since no curvature information is taken into account. In order to overcome this problem, we present a sub-system for path tracking where an algorithm that analyzes GPS information off-line classifies high curvature segments and estimates the ideal speed for each one. Additionally since the evaluation of our sub-system is performed through a simulation of an adaptive Pure Pursuit algorithm, we propose a method to estimate dynamically its look-ahead distance based on the vehicle speed and lateral error. As it will be shown through experimental results, our sub-system introduces improvements in comfort and safety due to the extracted geometry information and speed control, stabilizing the vehicle and minimizing the lateral error.