Abstract: In today's cities, effective traffic management systems play an important role in ensuring traffic balance and reducing congestion at intersections. This article presents a new hardware-based traffic management system (STMS) designed to adjust traffic signals in response to oncoming traffic. STMS leverages advances in Internet of Things (IoT) technology to integrate sensor networks and control systems into critical interfaces to achieve real-time monitoring and signal updates.
The main function of STMS is the ability to adjust the set time according to the proximity of the vehicle. When the vehicle approaches the signal, sensors detect their presence and send this information to the central control. The system then uses advanced algorithms to intelligently prioritize oncoming traffic by turning the traffic light green, thus encouraging traffic flow and reducing the potential for collisions.
In fact, STMS uses a responsive approach to signal control, ensuring that the signal returns to normal operation after the vehicle has passed through the intersection. This ensures a fair distribution of green time in transit and prevents unnecessary disruption of all traffic. STMS seamlessly integrates with the existing transport system, providing the best solution for efficient signal operation and improving overall operation.
The use of STMS represents a significant advance in traffic management, providing large-scale and flexible solutions for different types of urban environments. In addition to the direct benefits of easing traffic, STMS should improve road safety, reduce travel times and reduce environmental impact by reducing traffic-related vehicle emissions. As cities continue to experience urban growth and traffic congestion, innovative solutions such as STMS will play a key role in shaping the future of transportation in the city and beyond.
Keywords: Traffic management, IoT, Smart cities, Emergency vehicle prioritization, Traffic signal control, Proximity sensors, Adaptive signal timing, Urban mobility, Vehicle detection, Intersection management.
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DOI:
10.17148/IJARCCE.2024.134162
