Cooperative Eco-Driving Control of Connected Multi-Vehicles With Spatio-Temporal Constraints

In this article, we propose a novel time-energy optimal control approach with applications in cooperative eco-driving of connected and automated vehicles (CAVs) in urban traffic networks. Safely approaching and departing signalized intersections requires the satisfaction of both spatial equality constraints determined by intersection locations and temporal inequality constraints in compliance with the green light phases. To generate time- and energy-optimal trajectories, the optimal crossing times at intersections are firstly treated as characteristic time constraints, which makes the problem tractable. Then the direct multiple shooting method and time transformation technique are applied to find a numerical solution. The contribution of this article is twofold. The first one is the development of a novel time- and energy-optimal control approach that ensures a trade-off between minimizing energy and time for a general class of optimal control problems with multiple characteristic times. The second contribution is the application of the proposed method to the challenging problem of multi-CAVs' cooperative eco-driving control, in which multiple vehicles must simultaneously minimize travel time and energy consumption in the presence of spatio-temporal constraints. Simulation analysis over real-world urban route scenarios shows that the proposed eco-driving control strategy can save up to 8.2% of energy or reduce up to 6.7% of travel time compared to a baseline method. Furthermore, hardware-in-the-loop (HiL) experimental results indicate that the proposed strategy can be implemented in real-time.