Smart Traffic Vehicle monitoring and Signal Allocation using YOLO
DOI:
https://doi.org/10.47392/irjash.2023.S028Keywords:
Traffic Control system, Vehicle monitoring, YOLO object classification, Image segmentation, CountingAbstract
The traffic control system in India is now inflexible to the continuously increasing number of vehicles on the road. Fixed traffic light timing systems are a poor method of controlling traffic flow. Traffic lights are the fundamental component in traffic flow control through predetermined waiting and going times. A smart approach to adjust traffic light timing based on the number of vehicles in each lane is part of an intelligent traffic system. The average journey and waiting time for passengers will be reduced while the safety, dependability, and speed of the traffic flow is all increased. Designing an effective automated Traffic Time Saving system is the goal. The system is used for traffic management. In this proposed application first takes a picture of the car. Images are first converted from RGB to grayscale, then the vehicle picture is retrieved using image segmentation. After applying segmentation to the ready image, neural networks determine whether or not individual section contains a car. The successful parts will be counted by a counter. Lastly, a Graphical User Interface (GUI) will show the appropriate times for each light color.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.