Vehicle and Traffic Light Control Through Gradient-Based Coordination and Control Barrier Function Safety Regulation

Abstract

Abstract In this paper, we present a decentralized control framework for the coordination of connected vehicles and traffic lights in urban intersections. The framework uses gradient-based methods to dynamically coordinate, at every time-step, the planned intersection arrival times of vehicles and the planned switching times of traffic lights. Assuming no constraints, vehicles then use analytical optimal control methods to determine a nominal acceleration profile intended to place them at the intersection at the desired arrival time. Finally, using control barrier functions, the agents' accelerations and arrival times are modified to ensure safety and feasibility. The work in this paper builds on existing research on safe-set nonlinear control methods, multi-agent gradient-based methods, and optimal control methods used to tackle the intelligent intersection management problem. Here, we integrate the use of these different approaches to present a comprehensive control architecture that can flexibly coordinate the timing of both vehicles and traffic lights, while maintaining safety and feasibility. Simulations show that the method can save between 4% and 15% in fuel consumption and between 55% and 70% in delay for different traffic conditions.