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access icon free Vehicle detection using three-axis AMR sensors deployed along travel lane markings

  • Author(s): Meng Liu 1 ; Wang Hua 2 ; Quan Wei 2
    • View affiliations
  • Source: Volume 11, Issue 9, November 2017, p. 581 – 587
    DOI:  10.1049/iet-its.2017.0100 , Print ISSN 1751-956X, Online ISSN 1751-9578
© The Institution of Engineering and Technology
Received 14/03/2017, Accepted 16/07/2017, Revised 13/06/2017, Published 19/07/2017

A vehicle detection method is developed based on three-axis anisotropic magneto resistive (AMR) sensors along travel lane markings. The method integrates multiple algorithms and uses different geomagnetic waveforms which are disturbed by vehicles passing a single AMR sensor. This method comprehensively analyses X-, Y-, and Z-axis information and applies a double-window algorithm to extract a single vehicle waveform. The vehicle mixed algorithm (VMA) is developed to differentiate vehicles driving by the AMR sensor simultaneously and determine vehicle flow rates. In addition, the vehicle motion-state discrimination algorithm (VMSDA) is developed to distinguish the vehicle operating status (i.e. driving on the left lane, the lane line, or the right lane). The field experimental tests verified the effectiveness of the both algorithms. Results indicate that the average accuracy rates of VMA and VMSDA can, respectively, be up to 98.0 and 96.4%.

Inspec keywords: object detection; motion estimation; road vehicles; traffic engineering computing

Other keywords: vehicle motion state discrimination algorithm; travel lane markings; VMSDA; single AMR sensor; vehicle mixed algorithm; different geomagnetic waveforms; three-axis AMR sensors; single vehicle waveform; double-window algorithm; vehicle detection method; vehicle operating status

Subjects: Optical, image and video signal processing; Computer vision and image processing techniques; Traffic engineering computing

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