Distributed Model Predictive Control for Highway Maneuvers. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Mohseni, Fatemeh; Frisk, Erik; Åslund, Jan; Nielsen, Lars
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 8531
• Page End: 8536
• Publication Date: 2017-07
• Subjects: Automated vehicles -- Cooperative systems -- MPC -- Optimization; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.1406
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper describes a cooperative control method for autonomous vehicles, in order to perform different traffic maneuvers. The problem is formulated as a distributed optimal control problem for a system of multiple autonomous vehicles with an identified model and then solved using nonlinear Model Predictive Control (MPC). The distributed approach has been used in order to make the problem computationally feasible to be solved in real-time. In the proposed method, each vehicle computes its own control inputs using estimated states of neighboring vehicles. The constraints on the control inputs ensure the comfort of passengers. The method allows us to construct a cost function for several different scenarios in which safety and performing the maneuver constitute two terms of the integrated cost of the finite horizon optimization problem. To provide safety, a potential function is introduced for collision avoidance. Simulation results show that the distributed algorithm scales well with increasing number of vehicles.