Vehicle Positioning Based on Road-side Features and Matching Techniques

Sheng Lun Wang, Jyh-Chin Juang, Hung Yih Tsai

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

Abstract

The accuracy and reliability of the vehicle positioning system are important performance indices of advanced driver assisted systems and the autonomous driving systems. The paper focuses on the development and verification of vehicle positioning techniques by using Lidar and GPS/IMU sensors. To this end, the techniques for feature extraction, map building, and point cloud matching are investigated. The techniques are then integrated and implemented in a robotic operating system (ROS) platform. Experimental results verify the feasibility of the proposed sensor fusion technique with roadside feature extraction characteristics in rendering high accuracy and reliability vehicle positioning.

Original languageEnglish
Title of host publication2018 International Automatic Control Conference, CACS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538662786
DOIs
Publication statusPublished - 2019 Jan 9
Event2018 International Automatic Control Conference, CACS 2018 - Taoyuan, Taiwan
Duration: 2018 Nov 42018 Nov 7

Publication series

Name2018 International Automatic Control Conference, CACS 2018

Conference

Conference2018 International Automatic Control Conference, CACS 2018
CountryTaiwan
CityTaoyuan
Period18-11-0418-11-07

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Modelling and Simulation

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  • Cite this

    Wang, S. L., Juang, J-C., & Tsai, H. Y. (2019). Vehicle Positioning Based on Road-side Features and Matching Techniques. In 2018 International Automatic Control Conference, CACS 2018 [8606772] (2018 International Automatic Control Conference, CACS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CACS.2018.8606772