Cooperative Control in Eco-Driving of Electric Connected and Autonomous Vehicles in an Un-Signalized Urban Intersection

TL;DR

This paper develops optimal Eco-Driving strategies for electric connected and autonomous vehicles at un-signalized intersections, using cooperation among vehicles to enhance energy efficiency through analytical solutions and simulation evaluation.

Contribution

It introduces a novel optimization framework for Eco-Driving at intersections and compares cooperative and non-cooperative algorithms in simulation.

Findings

Cooperative Eco-Driving reduces energy consumption compared to non-cooperative methods.

Analytical solutions effectively handle intersection conflicts.

Simulation results demonstrate improved efficiency with cooperation.

Abstract

This paper addresses the problem of finding the optimal Eco-Driving (ED) speed profile of an electric Connected and Automated Vehicle (CAV) in an isolated urban un-signalized intersection. The problem is formulated as a single-level optimization and solved using Pontryagin's Minimum Principle (PMP). Analytical solutions are presented for various conflicts that occur at an intersection. Cooperation is introduced amongst CAVs as the ability to share intentions. Two levels of cooperation, namely the Cooperative ED (C-ED) and Non-Cooperative (NC-ED) algorithms are evaluated, in a simulation environment, for energy efficiency with Intelligent Driver Model (IDM) as the baseline.