Intelligent fuzzy switching of control strategies in path control for autonomous vehicles

Abstract

Autonomous vehicles often move along rather arbitrary types of path each demanding a different strategy for effective control. While it has been shown in previous papers that basic fuzzy (nonlinear) controllers can perform better than linear optimal controllers, it is desirable to take more fuzzy variables into account in order to cope intelligently with a wider variety of situations. By means of actual examples and using a physical mobile testbed, the application of intelligent fuzzy switching is investigated, which reduces a three-variable problem to a two-level lower-order problem, with reasonably smooth blending of the control strategies according to different path conditions, and with significant reduction of design effort used to generate the fuzzy control law. Experimental results are provided to demonstrate the usefulness of the proposed approach for dealing with vehicle paths characterised by nonlinear shapes and abrupt curvature changes.