By:
Traffic congestion is a ubiquitous challenge in urban areas, necessitating innovative solutions to improve transportation efficiency and alleviate gridlock. Traditional traffic signal control methods often prove inadequate in dynamically adapting to fluctuating traffic conditions, leading to increased travel times, fuel consumption, and emissions. In response, adaptive traffic control systems have emerged as a promising approach to mitigate congestion and enhance traffic flow in urban environments. These systems use real-time data from cameras, sensors, and other sources to dynamically modify the timing of signals in response to environmental conditions and traffic demand. By continuously optimizing signal phasing and timing plans, adaptive control strategies aim to maximize intersection throughput, minimize delays, and enhance overall traffic safety. This paper provides a comprehensive review of adaptive traffic control systems, exploring their underlying principles, key components, and applications in urban transportation. Through a synthesis of existing literature, empirical analysis, and case studies, we identify the strengths and limitations of adaptive control strategies, examine emerging trends and technologies in the field, and discuss the challenges and opportunities associated with the implementation of adaptive traffic management solutions. Our findings highlight the potential of adaptive traffic control systems to transform traffic management practices, improve mobility outcomes, and create more sustainable and resilient transportation networks in the future.
Keywords:Â traffic control, signal, Wireless Sensors, Networks, Microcontroller
Citation:
