Model Predictive Control of Autonomous Vehicles to Enhance Driving Performance and Safety.

The paper explores the potential benefits of using Model Predictive Control (MPC) algorithm to enhance the driving performance and safety of autonomous vehicles. MPC is a control strategy that uses a mathematical model of the vehicle and its environment to predict future behavior and make optimal control decisions. The paper first provides an overview of MPC and its applications in the control of autonomous vehicles and then discusses the benefits of MPC, including improved vehicle handling, increased fuel efficiency and enhanced safety. It also examines some of the challenges associated with implementing MPC in autonomous vehicles, such as computational complexity and model uncertainty. Finally, the paper concludes with a discussion on future research directions, including the need for more accurate models and improved computational algorithms to make MPC more practical for real-world applications. [ABSTRACT FROM AUTHOR]