Legendre pseudospectral computation of optimal speed profiles for vehicle eco-driving system

Abstract

This paper presents a computational framework to solve optimal control problems (OCPs) using Legendre Pseudospectral (PS) method and its application to obtain eco-driving strategies for ground vehicles. Both control and state variables of OCPs are approximated by Lagrange interpolating polynomials at the Legendre-Gauss-Lobatto (LGL) collocation points. The OCP is converted into a nonlinear programming (NLP) problem, and numerically solved by matured optimization algorithms. To implement the PS method, we developed a computational package, called Pseudospectral Optimal control Problem Solver (POPS) in Matlab environment. Further, the POPS is applied to obtain fuel-optimized driving strategies for automated vehicles in hilly road conditions.