Architecture for Scalable and Distributed Control of Connected and Automated Vehicles With Reconfigurable Path Planning

The control architecture for Connected and Automated Vehicles (CAVs) proposed in this work combines three features: Scalable, Distributed, and Reconfigurable. The term Scalable is used in the sense that the number of CAVs can change in the runtime. The term Distributed is used in the sense that the control is totally embedded in the CAVs, without a central manager/coordinator. And the term Reconfigurable is used in the sense that the CAVs may change their destinations and paths at any time. In this architecture, we assure the nonblocking and collision-free behavior of the system, and also the privacy of the path for each CAV. The control structure is composed of a local plant, a path controller, and a coordination controller, all modeled by automata. The dispute for road occupation between CAVs is handled to avoid collisions, based on a wireless communication where each CAV imposes disablings of events (actions) to other CAVs. We propose an online treatment for deadlock avoidance, with no need to compute a monolithic controller in any phase of the design. The path and coordination controllers are proposed to be embedded and synthesized in the CAV at runtime, which allows scalability and reconfiguration. The architecture is validated through a simulation environment in Robotarium and a practical experimental testbed with Lego Mindstorms robots. Two examples are given, as well as three simulations and three experiments are executed. One of the simulations was run for 54h, varying from 1 to 36 CAVs and the architecture is most efficient at 22.2% of the CAVs occupation rate on the map. Results show that all requirements were met.Note to Practitioners-This paper was motivated by the problem of controlling a large-scale system of CAVs, such as big cities. In these kinds of systems, vehicles are starting and stopping their routes at any time and it is desirable that the control system be scalable. Furthermore, it is unfeasible to implement on central controller/coordinator in such a large system, making it desirable to have a distributed control system, embedded in each vehicle. Finally, due to the dynamics of traffic, such as congestion, it is desirable that the control system be reconfigurable. Existing control techniques have some of these features but not all of them in one methodology. In this paper, we propose one control architecture for CAVs, which comprises all three features at runtime. With these features, a CAV may, for example, start its route at any time (scaling the system) and change it at any time (reconfiguring) without interfering in the control of other CAVs. The proposed architecture supports many solutions for CAVs that can be modeled jointly, such as intersection management, road merging, path planning, and roundabouts. In the article, we develop the mathematics of the control and apply it to simulations and experiments. Results show that the proposed architecture can be applied in practice. Our codes for the simulations and experiments are shared in a public repository.