CF-Pursuit: A Pursuit Method with a Clothoid Fitting and a Fuzzy Controller for Autonomous Vehicles

Abstract

Simple and efficient geometric controllers, like PurePursuit, have been widely used in various types of autonomous vehicles to solve tracking problems. In this paper, we have developed a new pursuit method, named CFPursuit, which has been based on Pure-Pursuit but with certain differences. In CF-Pursuit, in order to reduce fitting errors, we used a clothoid C 1 curve to replace the circle employed in Pure-Pursuit. This improvement to the fitting method helps the Pursuit method to decrease tracking errors. As regards the selection of look-ahead distance, we employed a fuzzy system to directly consider the path's curvature. There are three input variables in this fuzzy system, 6mcurvature, 9mcurvature and 12mcurvature, calculated from the clothoid fit with the current position and the goal position on the defined path. A Sugeno fuzzy model was adapted to output a reasonable look-ahead distance using the experiences of human drivers as well as our own tests. Compared with some other geometric controllers, CF-Pursuit performs better in robustness, cross track errors and stability. The results from field tests have proven the CF-Pursuit is a practical and efficient geometric method for the path tracking problems of autonomous vehicles.

A path-tracking algorithm using predictive Stanley lateral controller

“…9 Ollero et al 10 introduced a supervisory controller (fuzzy controller) for the online tuning of the pure pursuit parameters, which have the ability to automatically tune the look-ahead distance based on path characteristics, velocity, and tracking errors. Shan et al 11 introduced a new method for pursuit technique called clothoid fitting (CF) pursuit, which replaces the circles employed in pure pursuit with a clothoid C curve, which reduces the fitting error. Moreover, they used a fuzzy system to determine the suitable look-ahead distance corresponding to the path's curvature.…”

A Review of some Pure-Pursuit based Path Tracking Techniques for Control of Autonomous Vehicle

“…In summary, which so much attention that has been given to pure-pursuit tracking of explicit path by so many researchers, very little interest has been given to tracking of implicit path since the method was introduced into mobile robots [26], except for the work done on a person following with a rotary sonar [27] and a 2D laser scanner where Morales et al [1] investigated pure-pursuit path tracking for reactive tracking of an implicit path with a non-holonomic vehicle, there method was developed to follow obstacles like; walls, persons and corridors based on onboard 2D laser scanner for each. However, since their basic idea of reactive tracking was essentially that, the path to be followed would be read from the camera, which reduces complexity of data processing greatly.…”

“…It is very important in carrying out mobile robot mission. Path tracking controllers are used to carry out the path following operations and minimal lateral distance as well as the heading between the vehicle and defined path is achieved by a good path-tracking controller [1]. Their goal basically is to autonomously navigate and drive the robot along the path by continually generating speed and steering commands which compensate for the tracking errors, which mainly consist of vehicle's deviations in distance and heading from the path.…”

A Model Predictive Controller with Longitudinal Speed Compensation for Autonomous Vehicle Path Tracking

“…Ref. [7] proposed a path tracking fuzzy controller based on the clothoid curve-fitting reference path. A preview Stanley path tracking controller was designed in [8].…”