akshattrivedi/Automating-Traffic-Signals-Based-on-Traffic-Density-Estimation-using-YOLO
Automating the traffic signal timings using images of vehicles near the crossroads using YOLO (You Only Look Once) which includes Convolutional and Fully Connected Neural Networks which is implemented on Python-Django Web Framework.
This system helps urban planners and traffic management teams dynamically adjust traffic signal timings based on real-time vehicle density. By analyzing live camera feeds of intersections, it identifies and counts different vehicle types. The output is a vehicle count by category, enabling more efficient signal changes to reduce congestion.
No commits in the last 6 months.
Use this if you need to automate traffic signal timings based on the actual number and type of vehicles at an intersection, rather than fixed schedules.
Not ideal if your traffic management system requires advanced predictive modeling for long-term flow optimization or integrates with public transport scheduling.
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Language
Python
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Last pushed
May 22, 2023
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