This paper explores robust control strategies for autonomous vehicles operating in complex urban environments. The objective is to ensure the safety, efficiency, and reliability of autonomous vehicles (AVs) while navigating through diverse urban scenarios. The study begins by analyzing the challenges posed by urban environments, including variable traffic conditions, limited road space, and unpredictable human behavior. To address these challenges, we propose a comprehensive framework that integrates several control strategies, including adaptive cruise control, predictive path planning, and collision avoidance algorithms. The proposed control strategies are designed to be robust against uncertainties and disturbances, which are prevalent in urban settings. Simulation-based experiments are conducted to evaluate the performance of these strategies under varying environmental conditions. The results demonstrate that the proposed control strategies effectively enhance the stability, responsiveness, and safety of autonomous vehicles in urban environments. Furthermore, the analysis reveals that the integration of multiple control strategies contributes to a more robust and adaptable AV system. This study thereby paves the way for the development of advanced control technologies that can significantly improve the performance of autonomous vehicles in urban settings.
Brown, D. Robust Control Strategies for Autonomous Vehicles in Urban Environments. Transactions on Engineering and Technology, 2023, 5, 40. https://doi.org/10.69610/j.tet.20230613
AMA Style
Brown D. Robust Control Strategies for Autonomous Vehicles in Urban Environments. Transactions on Engineering and Technology; 2023, 5(1):40. https://doi.org/10.69610/j.tet.20230613
Chicago/Turabian Style
Brown, Daniel 2023. "Robust Control Strategies for Autonomous Vehicles in Urban Environments" Transactions on Engineering and Technology 5, no.1:40. https://doi.org/10.69610/j.tet.20230613
APA style
Brown, D. (2023). Robust Control Strategies for Autonomous Vehicles in Urban Environments. Transactions on Engineering and Technology, 5(1), 40. https://doi.org/10.69610/j.tet.20230613
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