Controlling a Longitudinal Autonomous Vehicle Using Modified Particle Swarm Optimization

Abstract This paper presents two optimization algorithms for selecting the optimal Proportional Integral Derivative (PID) controller’s coefficients for a longitudinal dynamics vehicle system. The suggested optimization algorithms are the Particle Swarm Optimization (PSO) and Modified PSO (MPSO) algorithms, which use the Integral Absolute value Error (IAE) as a cost function to find the PID controller's coefficients. The optimal proposed controllers are compared in terms of optimized PID controller’s response specifications expressed in standards of maximum Overshoot (OS), Steady-State Error (SSE), Settling Time (ts) (2%), and Rise Time (tr). The obtained results show that a combined PID controller with the MPSO algorithm is more effective than an combined PID controller with the traditional PSO algorithm at controlling the vehicle's longitudinal dynamics system with an enhanced percentage of 2.5%.