A study on using linear microphone array-based acoustic sensing to detect approaching vehicles

Shimada, Naoto; Itai, Akitoshi; Yasuda, Hiroshi

doi:10.1109/iscit.2010.5664832

Cited by 3 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There has been a growing interest in passive acoustic-based systems for vehicle monitoring since the mid 1990s, comprising vehicle detection [4][5][6][7], vehicle classification [8], traffic density estimation [9][10][11][12][13][14], speed estimation [15][16][17][18][19][20] and also energy consumption estimation using sound [21]. In this paper, we investigate a particle filtering-based technique for jointly estimating speed and wheelbase length of two-axle vehicles as they pass by.…”

Section: Introductionmentioning

confidence: 99%

Pass-by noise acoustic sensing for estimating speed and wheelbase length of two-axle vehicles.

Marmaroli¹,

Odobez²,

Falourd³

et al. 2013

Proceedings of Meetings on Acoustics

View full text Add to dashboard Cite

This paper focuses on acoustic road traffic monitoring and looks, more specifically, into the problem of joint speed and wheelbase length estimation of two-axle vehicles as they pass by. It is known that both front and rear axle trajectories may be observed using a cross-correlation based processing in conjunction with a well designed two-element microphone array placed on the roadside. This is mainly due to the broadband nature of the tyre/road noise which makes two peaks appear in, one per axle, in the correlation function. In a former work, we proposed to conduct this double-peak-tracking problem using a specific particle filter that model road vehicles as bimodal sound sources (bimodal particle filter). After a brief theoretical recall of the method, this paper stresses on the recent preliminary results we obtained from simulation and in-situ experiments.

show abstract

Section: Introductionmentioning

confidence: 99%

Pass-by noise acoustic sensing for estimating speed and wheelbase length of two-axle vehicles.

Marmaroli¹,

Odobez²,

Falourd³

et al. 2013

Proceedings of Meetings on Acoustics

View full text Add to dashboard Cite

show abstract

Enhancing Wireless Sensor Networks with Acoustic Sensing Technology: Use Cases, Applications & Experiments

Hollosi

Nagy

Rodigast

et al. 2013

2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical A

View full text Add to dashboard Cite

This paper presents research carried out within the EU FP7 EAR-IT project, which is working on the challenges of bringing acoustic sensing intelligence to large-scale indoor and outdoor wireless sensor networks, i.e. into two existing testbeds out of the EU FP7 FIRE projects SmartSantander and Hobnet. Besides the benefits by integrating machine-learning based acoustic sensing technology, the general deployment approach of the so-called Acoustic Processing Unit, an embedded device whose capabilities go beyond state-of-the-art IoT sensors, as well as the EAR-IT indoor and outdoor use cases are described. This includes hardware qualification for the applications such as energy efficiency of buildings, traffic monitoring and emergency vehicle detection and tracking outdoor as well as acoustic emergency detection for indoor environments and further, a detailed description of the individual Acoustic Processing Unit software components. Latest efforts and simulation results for acoustic source localization using audio sensing technology for wireless sensor networks are presented, indicating that a more intelligent usage of the audio modality enables a wide range of applications and services with high social and technological value.

show abstract

Observation of Vehicle Axles Through Pass-by Noise: A Strategy of Microphone Array Design

Marmaroli

Carmona

Odobez

et al. 2013

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

Abstract-This paper focuses on road traffic monitoring using sounds and proposes, more specifically, a microphone array design methodology for observing vehicle trajectory from acoustic-based correlation functions. In a former work, authors have shown that combining generalized cross correlation (GCC) functions and a particle filter onto the audio signals simultaneously acquired by two sensors placed near the road allows the joint estimation of the speed and the wheelbase length of road vehicles as they pass by. This is mainly due to the broadband nature of the tire/road noise, which makes their spatial dissociation possible by means of an appropriate GCC processor. At the time, nothing has been said about the best distance to chose between the sensors. A methodology is proposed here to find this optimum, which is expected to improve the observation quality and, thus, the tracking performance. Theoretical developments of this paper are partially assessed with preliminary experiments.

show abstract

A study on using linear microphone array-based acoustic sensing to detect approaching vehicles

Cited by 3 publications

References 3 publications

Pass-by noise acoustic sensing for estimating speed and wheelbase length of two-axle vehicles.

Pass-by noise acoustic sensing for estimating speed and wheelbase length of two-axle vehicles.

Enhancing Wireless Sensor Networks with Acoustic Sensing Technology: Use Cases, Applications & Experiments

Observation of Vehicle Axles Through Pass-by Noise: A Strategy of Microphone Array Design

Contact Info

Product

Resources

About