Road Lane Semantic Segmentation for High Definition Map

Wonje Jang, Jhonghyun An, Sangyun Lee, Minho Cho, Myungki Sun, Euntai Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)


High Definition map (HD Map) is an important part of autonomous driving vehicle. Most conventional method to generate HD map requires expensive system and postprocessing of observed data. In this paper, we propose automatic HD map generating algorithm using just monocular camera without further human labors. The proposed algorithm detects road lane from image and classifies the type of road lane at pixel-level with Fully Convolutional Network (FCN) which outperforms the other semantic segmentation methods. The segmentation results are used to extract lane features, and the features are used for loop-closure detection. Final map is generated with graph-based Simultaneous Localization and Mapping (SLAM) algorithm. The experiment is done with monocular camera mounted on mobile vehicle. In this paper, final map generated by proposed method is compared with aerial view data. The results show that the proposed method can generate reliable map that is comparable to real roads even only the low-cost sensor is used.

Original languageEnglish
Title of host publication2018 IEEE Intelligent Vehicles Symposium, IV 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538644522
Publication statusPublished - 2018 Oct 18
Event2018 IEEE Intelligent Vehicles Symposium, IV 2018 - Changshu, Suzhou, China
Duration: 2018 Sept 262018 Sept 30

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings


Other2018 IEEE Intelligent Vehicles Symposium, IV 2018
CityChangshu, Suzhou

Bibliographical note

Funding Information:
W. Jang, J. An, S. Lee, M. Cho and E. Kim* is in the School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea (email: [jangwj1256; jhonghyen; hello072; minho8849; etkim] M. Sun is in Hyundai Mnsoft, Hyundai Motor bldg., 74, Wonhyo-ro, Yongsan-gu, Seoul 04365, Korea (email: This research was supported by ‘Machine Learning-based Development of Lane Extraction Algorithm from Mobile Mapping System(MMS)' project funded by the HYUNDAI-MnSOFT Corporation. *Corresponding author

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Automotive Engineering
  • Modelling and Simulation


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