Online velocity trajectory planning for manual energy efficient driving of heavy duty vehicles using model predictive control

This paper presents a novel approach to online velocity trajectory planning for manual energy efficient driving which involves Model Predictive Control (MPC) for map-based anticipatory driving of heavy duty vehicles. The proposed model leads to a Quadratic Programming (QP) optimization problem with sparse matrix structure, allowing to be solved robustly and efficiently. By reducing the optimization problem to a QP standard form, existing and well-proven QP solvers can be used to calculate a reliable solution for a real-time vehicle control application. Evaluations show that the calculation time of the MPC optimization process with a two kilometer long preview horizon is, compared to other literature, significantly reduced to 1.8 milliseconds, while in real-world driving experiments an average fuel consumption reduction of 11.4% compared to normal driving is measured.