Efficient Traffic Signal Management using AI
Among the emerging problems of modern cities, urban traffic congestion takes the lead. It causes increased travel times, higher fuel consumption, and greater environmental pollution. The conventional traffic signal system operates at fixed time intervals, which fail to account for dynamic traffic patterns. The proposed work discussed here is AI-based smart traffic signal management. It dynamically modifies the timings of the signals in real-time that maximizes real-time data captured through cameras placed strategically, with the help of machine learning and computer vision algorithms that achieve dramatic reduction in congestion, improved fuel consumption, and higher reduction in emissions. The system creates an intelligent infrastructure which makes traffic management responsive, hence ensuring sustainable urban environments.
Authors
- T. Kavitha
- M. Thanga Subha Devi
- K. Veeraj
- H. M. Vinay
- R. S. Abhijit
- Nithin Shiva Vanka
Institutions
- Horizon College and Seminary (CA)
Publication Details
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1109/icoeca66273.2025.00119
- Citations
- 1
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.01