Vehicle self-localization using 3D building map and stereo camera

Jiali Bao, Yanlei Gu, Li Ta Hsu, Shunsuke Kamijo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

11 Citations (Scopus)


Self-localization is one of the most important part in autonomous driving system. In urban canyon, the multipath and non-line-of-sight effects to GPS receiver decrease the precision of self-localization of the vehicle. More specifically, the lateral error is more serious because of the blockage of the satellites. However, the building on roadside could be the stable reference object for localization. Therefore, this paper proposes to use stereo camera and 3D building map to reduce the lateral error of positioning result. In our proposal, stereo camera is used to detect and reconstruct the building side view. Lateral distance between building and vehicle estimated by stereo camera is compared with 3D building map to rectify the lateral position of vehicle. In addition, this paper employs inertial sensor and GPS receiver to decide the longitudinal position of vehicle. The particle filter is used for the sensor fusion. The experiment is conducted in the center of Tokyo, Japan, which is a typical urban city scene with high density of tall buildings. It demonstrates that the proposed method could achieve sub-meter level accuracy in GPS difficult environments.

Original languageEnglish
Title of host publication2016 IEEE Intelligent Vehicles Symposium, IV 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509018215
Publication statusPublished - 5 Aug 2016
Externally publishedYes
Event2016 IEEE Intelligent Vehicles Symposium, IV 2016 - Gotenburg, Sweden
Duration: 19 Jun 201622 Jun 2016

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings


Conference2016 IEEE Intelligent Vehicles Symposium, IV 2016

ASJC Scopus subject areas

  • Computer Science Applications
  • Automotive Engineering
  • Modelling and Simulation


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