Pub. Date | : April, 2023 |
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Product Name | : The IUP Journal of Electrical and Electronics Engineering |
Product Type | : Article |
Product Code | : IJEEE010423 |
Author Name | : Raymond C Ezeoma, Ameze Big-Alabo and Bartholomew Ogbonna |
Availability | : YES |
Subject/Domain | : Engineering |
Download Format | : PDF Format |
No. of Pages | : 18 |
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.
An autonomous vehicle is one that can drive itself from the starting point to a predetermined destination in "autopilot" mode using various in-vehicle technologies and sensors, including adaptive cruise control, active steering (steer by wire), anti-lock braking systems (brake by wire), GPS navigation technology, lasers and RADAR (Paul, 2015). Autonomous vehicles are expected to be the heart of future transportation systems. This is because of safety, economic, productivity and convenience benefits which are the core values anticipated in self-driving vehicles. This technology aims at improving driving safety, comfort, and economy, and reduce traffic accident rate (Yao et al., 2020). While safety is of paramount importance among these values, it is also the feature that presents the biggest concern.
Autonomous Vehicles, Model Predictive Control (MPC) algorithm, Performance, Safety