SAVeD: Acoustic Vehicle Detector with Speed Estimation capable of Sequential Vehicle Detection

Shigemi Ishida, Jumpei Kajimura, Masato Uchino, Shigeaki Tagashira, Akira Fukuda

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

2 Citations (Scopus)

Abstract

In the ITS (intelligent transportation system), vehicle detection is one of the core technologies. We are developing an acoustic vehicle detector that detects vehicles using a sound map, which is a map of sound arrival time difference on two microphones. We developed vehicle detection algorithms based on state machine and DTW (dynamic time warping) to detect S-curves on a sound map drawn by passing vehicles. However, the detection algorithms often fail to detect simultaneous and sequential passing vehicles. This paper presents SAVeD, a sequential acoustic vehicle detector. The SAVeD fits an S-curve model to sound map points using a RANSAC (random sample consensus) robust estimation method to detect each vehicle. The SAVeD then removes sound map points corresponding to the detected vehicle and continues vehicle detection process for the following vehicles. Experimental evaluations demonstrated that the SAVeD improves detection accuracy by more than 10 points compared to the state-machine based algorithm.

Original languageEnglish
Title of host publication2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages906-912
Number of pages7
ISBN (Electronic)9781728103235
DOIs
Publication statusPublished - Dec 7 2018
Event21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 - Maui, United States
Duration: Nov 4 2018Nov 7 2018

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2018-November

Other

Other21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
CountryUnited States
CityMaui
Period11/4/1811/7/18

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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  • Cite this

    Ishida, S., Kajimura, J., Uchino, M., Tagashira, S., & Fukuda, A. (2018). SAVeD: Acoustic Vehicle Detector with Speed Estimation capable of Sequential Vehicle Detection. In 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018 (pp. 906-912). [8569727] (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC; Vol. 2018-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2018.8569727