An Indian Roads Dataset for Supported and Suspended Traffic Lights Detection
This provides a new dataset for autonomous vehicle research in developing regions, but it is incremental as it builds on existing data collection methods.
The authors tackled the lack of datasets for traffic light detection in developing nations like India by creating the Indian Roads Dataset (IRD), which includes over 8000 annotations from 3000+ images and exceeds previous Indian datasets in size, annotations, and variance.
Autonomous vehicles are growing rapidly, in well-developed nations like America, Europe, and China. Tech giants like Google, Tesla, Audi, BMW, and Mercedes are building highly efficient self-driving vehicles. However, the technology is still not mainstream for developing nations like India, Thailand, Africa, etc., In this paper, we present a thorough comparison of the existing datasets based on well-developed nations as well as Indian roads. We then developed a new dataset "Indian Roads Dataset" (IRD) having more than 8000 annotations extracted from 3000+ images shot using a 64 (megapixel) camera. All the annotations are manually labelled adhering to the strict rules of annotations. Real-time video sequences have been captured from two different cities in India namely New Delhi and Chandigarh during the day and night-light conditions. Our dataset exceeds previous Indian traffic light datasets in size, annotations, and variance. We prove the amelioration of our dataset by providing an extensive comparison with existing Indian datasets. Various dataset criteria like size, capturing device, a number of cities, and variations of traffic light orientations are considered. The dataset can be downloaded from here https://sites.google.com/view/ird-dataset/home