Distributed Signal-Free Intersection Optimization via Iterative Time Slots Adjustment for Connected and Automated Vehicles

We propose a novel control strategy for signal-free intersection management through trajectory optimization for connected and automated vehicles. Such methodology is designed to be employed in a distributed manner, hence with no need for central units or specific tasks for leading vehicles, while only a limited amount of information needs to be exchanged and processed. The approach relies on an iterative distributed allocation and subsequent optimization of the time slots to cross the intersection. The distributed allocation aims to identify the constraints for the optimization problem to be solved, which enables the formulation of uncoupled subproblems that can be solved by each vehicle independently. The iterative algorithm initially allows the allocated time slots to overlap via a violation function that gradually decreases to zero as the algorithm progresses. This provides the optimization problem with enough flexibility to allow vehicles to resize their time slots and make them more suitable to meet their own requirements of trajectory smoothness and error minimization. We include simulation results and sensitivity analyses to demonstrate the effectiveness of our approach.