Utilizing Decision Tree,SVM And KNN Algorithms For Optimal Speed Detection And Control With Superior Accuracy

Over-speeding is a major contributor to traffic accidents and fatalities worldwide. AI and ML algorithms like decision tree, SVM and KNN can be used within vehicles to automatically detect and control speed limits, thus improving road safety. This paper explores the potential of AI/ML-based systems for vehicle speed limit detection and control, analyzing their functionalities, challenges and future directions. The paper finds that AI/ML-based systems can effectively detect and control speed limits, leading to a significant reduction in traffic accidents and fatalities. Improving algorithm accuracy and ensuring data reliability are fundamental to unlock the full potential of this technology. The paper also discusses some future directions for AI/ML-based speed limit detection and control, such as the use of more sophisticated algorithms and the development of more comprehensive data sets.