Advanced Vehicle Dynamics Control for High-Performance Autonomous Vehicles
The emergence of autonomous vehicle technology has significantly impacted the automotive sector, leading to advancements in Advanced Driver Assistance Systems (ADAS) and propelling the industry towards the realization of fully autonomous vehicles. These developments are set to enhance vehicular safety by reducing accidents caused by human error, improve traffic efficiency, and contribute to environmental sustainability through optimized driving patterns and potential integration with electric vehicles.
A critical aspect in the evolution of autonomous vehicles is the control of vehicle dynamics at the limit of handling, especially in high-speed and complex driving conditions that exceed the capabilities of average drivers.
Several algorithms for the control of vehicle dynamics exist in the literature. Nevertheless, limited progress has been made towards the development of controllers that are reliable at very high speeds and at the limit of handling, when both the lateral and longitudinal dynamics of the vehicle are excited at the same time.
This research focuses on the exploration of optimal control techniques for the lateral and longitudinal dynamics of high-performance autonomous vehicles. All the developed algorithms should account for complex vehicle dynamics and road-tire interactions, as well as relevant effects at high speed, such as aerodynamics and load transfer effects. A key aspect of this work is ensuring that the control strategies are applicable to real-world scenarios, including ease of tuning across different vehicle platforms and operating conditions. Additionally, ensuring the feasibility of real-time implementation is essential, particularly for optimization-based techniques, where high computational demands can hinder practical deployment.
In doing so, this research contributes to the broader goal of making autonomous vehicles a reliable and trusted mobility solution.
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