This paper explores the application of fuzzy control systems in the realm of autonomous vehicles navigating through urban environments. As urban landscapes become increasingly complex with diverse traffic conditions, the challenge lies in developing intelligent control algorithms that can effectively manage the dynamic and unpredictable nature of city streets. Fuzzy control systems, which utilize heuristic rules and linguistic variables to handle uncertainty, offer a promising approach to this challenge. The paper begins by introducing the fundamentals of fuzzy logic and control theory, followed by a detailed analysis of the specific requirements for autonomous vehicles in urban settings. It then discusses the integration of fuzzy control techniques into vehicle control systems, focusing on obstacle avoidance, traffic management, and predictive behavior. Case studies and simulations are presented to demonstrate the feasibility and effectiveness of fuzzy control in enhancing the autonomy and safety of vehicles operating in urban environments. The results indicate that fuzzy control systems can significantly improve the decision-making capabilities of autonomous vehicles, making them more adaptable to the complexities of city traffic.
Smith, D. Fuzzy Control Systems for Autonomous Vehicles in Urban Environments. Transactions on Applied Soft Computing, 2022, 4, 26. https://doi.org/10.69610/j.tasc.20220216
AMA Style
Smith D. Fuzzy Control Systems for Autonomous Vehicles in Urban Environments. Transactions on Applied Soft Computing; 2022, 4(1):26. https://doi.org/10.69610/j.tasc.20220216
Chicago/Turabian Style
Smith, Daniel 2022. "Fuzzy Control Systems for Autonomous Vehicles in Urban Environments" Transactions on Applied Soft Computing 4, no.1:26. https://doi.org/10.69610/j.tasc.20220216
APA style
Smith, D. (2022). Fuzzy Control Systems for Autonomous Vehicles in Urban Environments. Transactions on Applied Soft Computing, 4(1), 26. https://doi.org/10.69610/j.tasc.20220216
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