Design of Acoustic Vehicle Detector with Steady-Noise Suppression

Shigemi Ishida, Masato Uchino, Chengyu Li, Shigeaki Tagashira, Akira Fukuda

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

7 Citations (Scopus)

Abstract

Vehicle detection is a basic component for many applications in intelligent transportation system (ITS). We are developing a low-cost vehicle detector relying on sound arrival time difference on two microphones. Our previous paper presented that our acoustic vehicle detector successfully detected vehicles with an F-measure of 83 %. However, the acoustic detector has difficulties in vehicle detection in an environment with steady noise such as rain noise.This paper presents a steady-noise suppression method for the acoustic vehicle detector. Our key idea is to exclude the influence of steady noise in a sound delay estimation. The acoustic vehicle detector estimates vehicle sound delay by finding a peak on a cross-correlation function. We theoretically analyze the influence of steady noise and remove a peak caused by the noise to minimize the influence. Experimental evaluations revealed that the steady-noise suppression method effectively reduced the noise influence and resulted in F-measures of 0.92 and 0.90 in normal and heavy rain conditions, respectively.

Original languageEnglish
Title of host publication2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2848-2853
Number of pages6
ISBN (Electronic)9781538670248
DOIs
Publication statusPublished - Oct 2019
Event2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand
Duration: Oct 27 2019Oct 30 2019

Publication series

Name2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

Conference

Conference2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Country/TerritoryNew Zealand
CityAuckland
Period10/27/1910/30/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Management Science and Operations Research
  • Instrumentation
  • Transportation

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