Mahmoud, Yara Hazem Mohamed (Western Michigan University), Brown, Nick (Western michigan university), Motallebiaraghi, Farhang (Western Michigan university), Koelling, Melinda (Western Michigan University), Meyer, Richard (western Michigan university), Asher, Zachary D. (Western Michigan University), Dontchev, Asen (American Mathematical Society), Kolmanovsky, Ilya V. (University of Michigan)

Autonomous Eco-Driving with Traffic Light and Lead Vehicle Constraints: An Application of Best Constrained Interpolation

Scheduled for presentation during the Regular session "Vehicle control technology" (MoAT2), Monday, August 23, 2021, 14:40−15:00, Room T2

6th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, August 23-25, 2021, Tokyo, Japan

This information is tentative and subject to change. Compiled on April 19, 2024

Abstract

Eco-Driving is a critical technology for improving automotive transportation efficiency. It is achieved by modifying the driving trajectory over a particular route to minimize required propulsion energy. Eco-Driving can be approached as an optimal control problem subject to driving constraints such as traffic lights and positions of other vehicles. In this paper, we demonstrate the connection between Eco-Driving and best interpolation in the strip which is a problem in approximation theory and optimal control. By exploiting this connection, we are able to generate optimal Eco-Driving trajectories that can be driven with an autonomous system and evaluate them using conventional, hybrid electric and fully electric vehicle models from FASTSim software. Our results quantify the fuel economy improvements that can be achieved with the proposed approach.