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.

26
/ 100
Experimental

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.

traffic-management urban-planning smart-cities congestion-reduction transportation-infrastructure
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 13 / 25

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9

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2

Language

Python

License

Last pushed

May 22, 2023

Commits (30d)

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