Automatic Building and Labeling of HD Maps with Deep Learning


  • Mahdi Elhousni Worcester Polytechinic Institue
  • Yecheng Lyu Worcester Polytechinic Institue
  • Ziming Zhang Worcester Polytechinic Institue
  • Xinming Huang Worcester Polytechinic Institue



In a world where autonomous driving cars are becoming increasingly more common, creating an adequate infrastructure for this new technology is essential. This includes building and labeling high-definition (HD) maps accurately and efficiently. Today, the process of creating HD maps requires a lot of human input, which takes time and is prone to errors. In this paper, we propose a novel method capable of generating labelled HD maps from raw sensor data. We implemented and tested our methods on several urban scenarios using data collected from our test vehicle. The results show that the proposed deep learning based method can produce highly accurate HD maps. This approach speeds up the process of building and labeling HD maps, which can make meaningful contribution to the deployment of autonomous vehicles.




How to Cite

Elhousni, M., Lyu, Y., Zhang, Z., & Huang, X. (2020). Automatic Building and Labeling of HD Maps with Deep Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 34(08), 13255-13260.



IAAI Technical Track: Emerging Papers