A distributed trajectory control strategy for the connected automated vehicle in an isolated roundabout

This paper develops a distributed cooperative control strategy (DCCS) to plan and optimize the collision-free trajectory for the connected automated vehicle (CAV) at an isolated roundabout. The representation of the trajectories of CAVs is defined within a roundabout. The central angle and lane radius are used to indicate the location of vehicles, and the corresponding angular velocity is used to describe the vehicle's speed through the roundabout. This trajectory definition method simplifies the proposed problem into two parts: the trajectory optimization of each vehicle in a specific lane and the lane change coordination of CAVs in the roundabout. To solve the trajectory optimization problem, a mixed-integer linear programming (MILP) model is formulated at the vehicle level to minimize the travel time and make the trajectory as smooth as possible. A model predictive control (MPC) framework is designed to coordinate lane-change conflicts and push CAVs' trajectories toward global optimization. The proposed framework integrates the vehicles' trajectory optimization results so that all CAVs reach a consensus. Numerical experiments test the effect of the strategy in terms of traffic efficiency and mobility performance under different demand pattern scenarios. The results show that the proposed RA-DCCS (Roundabout-DCCS) can make all CAVs smooth and conflict-free trajectories and enable vehicles to execute reasonable lane change decisions.