This paper deals with an eco-driving control problem for autonomous electric vehicles in urban traffic networks with signalized intersections. Specifically, a novel control scheme is proposed to make the vehicle travel through a sequence of signalized intersections while always catching green lights with minimum energy consumption. The proposal includes a speed reference generator, a sliding mode local controller and an event-triggered decision maker whose intelligence is provided by a pre-specified condition. This mechanism enables to determine when it is necessary to re-plan a new optimal velocity profile by the speed planner, which solves a sub-optimal version of the non-convex eco-driving optimal control problem due to the traffic lights constraints. The sliding mode controller instead enables a finite time tracking of the optimized speed reference and plays the role of compensator of the uncertainties affecting the vehicle dynamics. Such a robustness property in turn allows to limit the triggering events when a new optimization is solved to update the speed reference profile. The performance of the whole control scheme are finally assessed in simulation.

Event-triggered eco-driving with sliding mode control for an electric vehicle in urban traffic networks

Incremona, Gian Paolo;
2022

Abstract

This paper deals with an eco-driving control problem for autonomous electric vehicles in urban traffic networks with signalized intersections. Specifically, a novel control scheme is proposed to make the vehicle travel through a sequence of signalized intersections while always catching green lights with minimum energy consumption. The proposal includes a speed reference generator, a sliding mode local controller and an event-triggered decision maker whose intelligence is provided by a pre-specified condition. This mechanism enables to determine when it is necessary to re-plan a new optimal velocity profile by the speed planner, which solves a sub-optimal version of the non-convex eco-driving optimal control problem due to the traffic lights constraints. The sliding mode controller instead enables a finite time tracking of the optimized speed reference and plays the role of compensator of the uncertainties affecting the vehicle dynamics. Such a robustness property in turn allows to limit the triggering events when a new optimization is solved to update the speed reference profile. The performance of the whole control scheme are finally assessed in simulation.
2022 European Control Conference, ECC 2022
978-3-9071-4407-7
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1219569
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