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Sensors 2014, 14(2), 2892-2910; doi:10.3390/s140202892

Dual Roadside Seismic Sensor for Moving Road Vehicle Detection and Characterization

1
School of Transportation Science and Engineering, Harbin Institute of Technology, No. 73 Huanghe Rd., NanGang Dist., Harbin 150090, China
2
Department of Civil & Environmental Engineering, University of Washington, Box 352700, Seattle, WA 98195-2700, USA
*
Author to whom correspondence should be addressed.
Received: 19 December 2013 / Revised: 11 January 2014 / Accepted: 13 January 2014 / Published: 12 February 2014
(This article belongs to the Section Physical Sensors)
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Abstract

This paper presents a method for using a dual roadside seismic sensor to detect moving vehicles on roadway by installing them on a road shoulder. Seismic signals are split into fixed time intervals in recording. In each interval, the time delay of arrival (TDOA) is estimated using a generalized cross-correlation approach with phase transform (GCC-PHAT). Various kinds of vehicle characterization information, including vehicle speed, axle spacing, detection of both vehicle axles and moving direction, can also be extracted from the collected seismic signals as demonstrated in this paper. The error of both vehicle speed and axle spacing detected by this approach has been shown to be less than 20% through the field tests conducted on an urban street in Seattle. Compared to most existing sensors, this new design of dual seismic sensor is cost effective, easy to install, and effective in gathering information for various traffic management applications.
Keywords: generalized cross correlation; time delay of arrival(TDOA); source localization; axle detection; vehicle detection generalized cross correlation; time delay of arrival(TDOA); source localization; axle detection; vehicle detection
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Wang, H.; Quan, W.; Wang, Y.; Miller, G.R. Dual Roadside Seismic Sensor for Moving Road Vehicle Detection and Characterization. Sensors 2014, 14, 2892-2910.

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