PID Controller for A Bearing Angle Control in Self-Driving Vehicles
Abstract
The enhancement of self-driving vehicles has the potential to disrupt traditional transportation systems, Utilizing progress in secure and intelligent mobility. However, control of movement in self-driving vehicles is still difficult to carry out driving duties in a constantly changing road environment. The regulation of bearing angle is an essential component in self-driving vehicles navigation systems, facilitating the secure and efficient operation of vehicles across a range of environments, including urban streets, highways, and off-road terrain. It employs algorithms and sensor fusion to perceive surroundings, compute trajectories, and execute precise steering commands. The bearing angle represents the angle between the vehicle's current and desired directions. By consistently monitoring this angle and implementing appropriate steering inputs, the self-driving vehicle can accurately stay on track and proactively adapt to obstacles or adhere to a designated route. In this context, we explore the advancements in bearing angle control methods for self-driving vehicles. By conducting simulations of a simplified block diagram for a self-guiding vehicle's bearing angle control techniques, the efficacy of the steering system of self-driving cars has been briefly examined. We provide various methods of control, which are considered approaches for controlling the angle of bearings through lag lead compensation and PID auto-tuned controllers. The results show that the auto-tuned PID controller outperforms all other controllers in terms of transient and steady-state responses.
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DOI: https://doi.org/10.18196/jrc.v5i3.21612
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