Weight Changing Model Predictive Controller for Adaptive Cruise Control with Multiple Objectives

Abstract

In this work, model predictive control (MPC) problem with multiple objectives was solved to formulate adaptive cruise control of the passenger vehicle, hierarchical control architecture was implemented in which desired acceleration calculated by upper controller was translated to throttle and brake output by the lower controller. To propose the optimum acceleration a vehicle following model was established and constant time headway policy was used to propose safe distance. An optimization problem was formulated whose performance index mathematically included performance, safety, comfort, and economy. Quadratic programming was used to solve and implement receding horizon control. Investigating the impact of choosing different weighing parameters, a changing weights strategy was formulated which can adapt to the driving conditions by changing the weighing parameters within limits to get better results. Simulations were performed for both the constant and changing weights, Results demonstrated considerable improvement in weight changing with conditions.