Model Predictive Control for On-Ramp Vehicle Merging to a Platoon on Main Road in Finite Time

Abstract

This paper addresses the longitudinal control problem of an on-ramp vehicle merging into a platoon on the main road. To tackle this challenge, a finite-time model predictive control (MPC) algorithm with a specialized feedback control law is proposed. A constraint set of the state error is designed and based on this, a decision-making scheme is established to allow the on-ramp vehicle to assess the feasibility of the merging operation at the beginning under the designed MPC strategy. If the merging is feasible, the proposed MPC strategy will be applied to drive the on-ramp vehicle towards a small neighborhood around the desired state on the basis of platoon’s velocity and position within a finite time step before joining the platoon. Furthermore, asymptotic convergence towards the desired state is achieved by a co-designed feedback control law. Otherwise, the MPC strategy will not be triggered, instead an alternative method such as slowing down the on-ramp vehicle to create space and allow the vehicles on the main road to proceed ahead. Under the proposed method, the recursive feasibility of the MPC optimization problem is achieved at all time steps and the finite time convergence to the small neighborhood of the desired state can be proved under the MPC algorithm. An upper bound on the convergence time step is also derived, which is used to prove the effectiveness of the decision-making mechanism. In addition, the closed-loop constraints satisfaction and asymptotic stability of the on-ramp vehicle are also guaranteed. The effectiveness of the proposed MPC method is demonstrated through simulation examples.