Proposal for a Compressive Measurement-Based Acoustic Vehicle Detection and Identification System

Billy Dawton, Shigemi Ishida, Yuki Hori, Masato Uchino, Yutaka Arakawa

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

Abstract

As society becomes increasingly interconnected, the need for sophisticated signal processing and data analysis techniques becomes increasingly apparent, particularly in the field of Intelligent Transportation Systems (ITS) where various sensing applications generate data at an exponential rate. In this paper, we put a forward a compressive sensing-based system to extract information from passing vehicle sounds sampled at sub-Nyquist rates for Acoustic Vehicle Detection and Identification (AVDI) applications. The obtained compressive measurements are used to detect and identify passing vehicles. Initial evaluation performed using data obtained from roads on a university campus presents an accuracy of 86.2 % with a back-end ADC sample rate of 3 kHz.

Original languageEnglish
Title of host publication2020 IEEE 92nd Vehicular Technology Conference, VTC 2020-Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728194844
DOIs
Publication statusPublished - Nov 2020
Event92nd IEEE Vehicular Technology Conference, VTC 2020-Fall - Virtual, Victoria, Canada
Duration: Nov 18 2020 → …

Publication series

NameIEEE Vehicular Technology Conference
Volume2020-November
ISSN (Print)1550-2252

Conference

Conference92nd IEEE Vehicular Technology Conference, VTC 2020-Fall
CountryCanada
CityVirtual, Victoria
Period11/18/20 → …

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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