Multi-objective PID and fuzzy PID controller design and implementation in cruise control system.

Modern cars must have cruise control because it keeps drivers comfortable and safe on long journeys. The most difficult driving conditions for Adaptive Cruise Control (ACC) are curved and hilly roads, changing highway lanes, and experiencing slow and heavy traffic. The traditional cruise control systems that rely on fixed speed control can be dangerous in circumstances like slow and congested traffic, which is the driving force behind this work. The ACC system can use Multi-objective controllers to regulate comfort, relative distance, and speed. Multi-objective controllers are essential to ACC to keep a safe gap between vehicles ahead of you. A Multi-objective control strategy incorporating PID (Proportional Integral Derivative), Fuzzy-PID, and PID with Kalman Filter is proposed to maintain a safe distance between two cars. The novelty in the proposed approach is using a Multi-objective controller with three PID controllers for speed control in different speed regions. The approach automatically switches between the PID controllers based on the distance between the cars, and each Controller can be tuned according to the situation at hand, resulting in a better response. The Multi-objective Controller provides accurate and efficient speed control. At the same time, the Kalman Filter estimates the system's state, including the lead vehicle's speed and position, and reduces measurement noise to increase precision in the control signal. The Multi-objective Controller with three PID controllers for speed control in different speed regions was simulated in Matlab Simulink. It effectively maintains a safer distance between lead (leading) and Cruise/Ego (trailing) cars. Simulation studies show that the advantage of the proposed approach is its ability to operate over a large range of conditions, including different speeds. [ABSTRACT FROM AUTHOR]