AI-Driven Automatic Speed Control: A Technological Solution for Road Safety

Abstract

The proliferation of speeding-related fatalities on global roadways demands innovative technological interventions that transcend traditional enforcement methods and human behavioral modifications. This article presents a comprehensive analysis of AI-driven automatic speed control systems as a transformative solution to road safety challenges, examining the technological framework, implementation strategies, and potential impacts of these advanced systems. The article delves into the multi-level architecture of computer vision, GPS, digital maps, and integration of vehicle control, illustrating how current convolutional neural networks and machine learning techniques allow real-time speed limit detection and automatic speed adjustment of the vehicle. The progression from rudimentary cruise control to intelligent speed adaptation systems indicates an underlying change in car safety thinking, from driver support to forward-looking automation. Urban and rural deployment problems are addressed, including sensor reliability, GPS precision, and human-machine interface issues, while commercial fleet operations in real-world applications offer empirical evidence of system performance. The article demonstrates that AI-based speed control systems provide multifaceted benefits including primary safety enhancements, environmental benefits through decreased emissions, economic gains through lower operational expenditures, and wellbeing improvements for drivers through decreased cognitive load Successful deployment is shown in the study to require careful attention to technical robustness factors, regulatory adherence, infrastructure preparedness, and user acceptance, with behavioral adaptation studies showing positive reaction by drivers towards well-designed systems. This technology intervention is not an incremental improvement but a paradigm shift in managing road safety, offering a scalable solution, eliminates the human error factor and will facilitate broader acceptance of autonomous vehicle technologies.