Estimation of Average Speed of Road Vehicles by Sound Intensity Analysis

Author:

Kotus Józef,Szwoch GrzegorzORCID

Abstract

Constant monitoring of road traffic is important part of modern smart city systems. The proposed method estimates average speed of road vehicles in the observation period, using a passive acoustic vector sensor. Speed estimation based on sound intensity analysis is a novel approach to the described problem. Sound intensity in two orthogonal axes is measured with a sensor placed alongside the road. Position of the apparent sound source when a vehicle passes by the sensor is estimated by means of sound intensity analysis in three frequency bands: 1 kHz, 2 kHz and 4 kHz. The position signals calculated for each vehicle are averaged in the analysis time frames, and the average speed estimate is calculated using a linear regression. The proposed method was validated in two experiments, one with controlled vehicle speed and another with real, unrestricted traffic. The calculated speed estimates were compared with the reference lidar and radar sensors. Average estimation error from all experiment was 1.4% and the maximum error was 3.2%. The results confirm that the proposed method allow for estimation of time-averaged road traffic speed with accuracy sufficient for gathering traffic statistics, e.g., in a smart city monitoring station.

Funder

Narodowe Centrum Badań i Rozwoju

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Speed Detection System Utilizing Lower Frequency Noise;2024 9th International Conference on Mechatronics Engineering (ICOM);2024-08-13

2. Cyclist Safety Device based on Spectral Audio Processing for Approaching Vehicles Detection;2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC);2024-05-20

3. A Deep Wavelet-Fourier Method for Monaural Vehicle Speed Estimation in Real-Life Settings;IEEE Sensors Journal;2024-05-01

4. Augmentation of Various Speed Data by Controlling Frame Overlap for Acoustic Traffic Monitoring;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

5. Acoustic Traffic Monitoring Based on Deep Neural Network Trained by Stereo-Recorded Sound and Sensor Data;2023 31st European Signal Processing Conference (EUSIPCO);2023-09-04

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