Automated Traffic Light Signal Violation Detection System Using Convolutional Neural Network

  • Bhavya BordiaEmail author
  • N. Nishanth
  • Shaswat Patel
  • M. Anand Kumar
  • Bhawana Rudra
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1154)


Automated traffic light violation detection system relies on the detection of traffic light color from the video captured with the CCTV camera, detection of the white safety line before the traffic signal and vehicles. Detection of the vehicles crossing traffic signals is generally done with the help of sensors which get triggered when the traffic signal turns red or yellow. Sometimes, these sensors get triggered even when the person crosses the line or some animal crossover or because of some bad weather that gives false results. In this paper, we present a software which will work on image processing and convolutional neural network to detect the traffic signals, vehicles and the white safety line present in front of the traffic signals. We present an efficient way to detect the white safety line in this paper combined with the detection of traffic lights trained on the Bosch dataset and vehicle detection using the TensorFlow object detection SSD model.


Convolutional neural networks Object detection TensorFlow Traffic light detection 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Bhavya Bordia
    • 1
    Email author
  • N. Nishanth
    • 1
  • Shaswat Patel
    • 1
  • M. Anand Kumar
    • 1
  • Bhawana Rudra
    • 1
  1. 1.Department of Information TechnologyNational Institute of Technology SurathkalSurathkalIndia

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