Evaluating the Performance of Fuzzy-PID Control for Lane Recognition and Lane-Keeping in Vehicle Simulations
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Date
2023Author
Moveh, SamuelYahya, Khalid O. Moh.
Attar, Hani
Amer, Ayman
Mohamed, Mahmoud
Badmos, Tajudeen Adeleke
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This study presents the use of a vision-based fuzzy-PID lane-keeping control system for
the simulation of a single-track bicycle model. The lane-keeping system (LKS) processes images to
identify the lateral deviation of the vehicle from the desired reference track and generates a steering
control command to correct the deviation. The LKS was compared to other lane-keeping control
methods, such as Ziegler–Nichols proportional derivative (PD) and model predictive control (MPC),
in terms of response time and settling time. The fuzzy-PID controller had the best performance, with
fewer oscillations and a faster response time compared to the other methods. The PD controller was
not as robust under various conditions due to changing parameters, while the MPC was not accurate
enough due to similar reasons. However, the fuzzy-PID controller showed the best performance,
with a maximum lateral deviation of 2 cm, a settling time of 12 s, and Kp and Kd values of 0.01
and 0.06, respectively. Overall, this work demonstrates the potential of using fuzzy-PID control for
effective lane recognition and lane-keeping in vehicles.
Volume
12Issue
3Collections
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