Design and optimization of a Type-2 fuzzy logic-based lateral control system for enhancing trajectory stability in autonomous vehicles
DOI:
https://doi.org/10.15587/1729-4061.2025.326193Keywords:
autonomous vehicle, type-2 FLC, PID control, steering angle, membership function, maneuversAbstract
The focus of this study is the lateral control system of autonomous vehicles using steering control. The main objective is to ensure the vehicle consistently stays on the correct path. Existing methods remain limited, as they often assume ideal road conditions without obstacles or dynamic objects. To address this limitation, this study investigates steering angle control for autonomous vehicles in unstructured environments with potential obstacles. It specifically analyzes the application of a type-2 fuzzy logic controller (type-2 FLC) for steering control, using input values in the form of error and delta error. These values are calculated from the difference between the output generated and the steering angle measured by a pulse encoder mounted on the steering wheel. The type-2 FLC demonstrated high accuracy in obstacle avoidance tests: 1.54% (human), 4.28% (one car), 1.2% (two objects on the left), and 2.13% (two on the left, one on the right). In contrast, the PID controller produced higher error rates: 2.19%, 3.49%, 1.12%, and 3.49%, respectively. Full-route testing showed average forward-route errors of 8.87% for the type-2 FLC and 12.35% for the PID controller. On the return route, the type-2 FLC recorded a 4.52% error, while the PID controller showed 7.57%. Overall, the type-2 FLC achieved lower error rates and better accuracy than the PID controller, particularly in dynamic conditions. These results highlight the effectiveness of the type-2 FLC in enhancing autonomous vehicle performance and steering accuracy. Its low error values indicate superior path-tracking capabilities, effectively addressing the research objective
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