» Articles » PMID: 29206169

Monitoring Traffic Information with a Developed Acceleration Sensing Node

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2017 Dec 6
PMID 29206169
Citations 8
Authors
Affiliations
Soon will be listed here.
Abstract

In this paper, an acceleration sensing node for pavement vibration was developed to monitor traffic information, including vehicle speed, vehicle types, and traffic flow, where a hardware design with low energy consumption and node encapsulation could be accomplished. The service performance of the sensing node was evaluated, by methods including waterproof test, compression test, sensing performance analysis, and comparison test. The results demonstrate that the sensing node is low in energy consumption, high in strength, IPX8 waterproof, and high in sensitivity and resolution. These characteristics can be applied to practical road environments. Two sensing nodes were spaced apart in the direction of travelling. In the experiment, three types of vehicles passed by the monitoring points at several different speeds and values of (the distance between the sensor and the nearest tire center line). Based on cross-correlation with kernel pre-smoothing, a calculation method was applied to process the raw data. New algorithms for traffic flow, speed, and axle length were proposed. Finally, the effects of vehicle speed, vehicle weight, and value on acceleration amplitude were statistically evaluated. It was found that the acceleration sensing node can be used for traffic flow, vehicle speed, and other types of monitoring.

Citing Articles

Image processing and artificial neural network based determination of surface mean texture depth on lab-controlled chip seal pavement samples.

Gokalp I, Uz V, Barstugan M, Balci M Sci Rep. 2024; 14(1):27885.

PMID: 39537667 PMC: 11561359. DOI: 10.1038/s41598-024-78346-x.


Novel Weigh-in-Motion Pavement Sensor Based on Self-Sensing Nanocomposites for Vehicle Load Identification: Development, Performance Testing, and Validation.

Liang M, Zhang Y, Jiao Y, Wang J, Su L, Yao Z Sensors (Basel). 2023; 23(10).

PMID: 37430671 PMC: 10221636. DOI: 10.3390/s23104758.


Performance Testing of Micro-Electromechanical Acceleration Sensors for Pavement Vibration Monitoring.

Ye Z, Wei Y, Yang B, Wang L Micromachines (Basel). 2023; 14(1).

PMID: 36677214 PMC: 9860821. DOI: 10.3390/mi14010153.


Real-Time and Efficient Traffic Information Acquisition via Pavement Vibration IoT Monitoring System.

Ye Z, Yan G, Wei Y, Zhou B, Li N, Shen S Sensors (Basel). 2021; 21(8).

PMID: 33920249 PMC: 8069318. DOI: 10.3390/s21082679.


GeSi Nanocrystals Photo-Sensors for Optical Detection of Slippery Road Conditions Combining Two Classification Algorithms.

Palade C, Stavarache I, Stoica T, Ciurea M Sensors (Basel). 2020; 20(21).

PMID: 33182467 PMC: 7665139. DOI: 10.3390/s20216395.


References
1.
Jian A, Wei C, Guo L, Hu J, Tang J, Liu J . Theoretical Analysis of an Optical Accelerometer Based on Resonant Optical Tunneling Effect. Sensors (Basel). 2017; 17(2). PMC: 5335941. DOI: 10.3390/s17020389. View

2.
Zhang B, Wang C, Zhang H, Wu F, Tang Y . Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring. Sensors (Basel). 2017; 17(2). PMC: 5336039. DOI: 10.3390/s17020298. View

3.
Zhao H, Feng H . A Novel Permanent Magnetic Angular Acceleration Sensor. Sensors (Basel). 2015; 15(7):16136-52. PMC: 4541871. DOI: 10.3390/s150716136. View

4.
Xiong C, Lu H, Zhu J . Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements. Sensors (Basel). 2017; 17(3). PMC: 5375722. DOI: 10.3390/s17030436. View

5.
Losilla F, Garcia-Sanchez A, Garcia-Sanchez F, Garcia-Haro J, Haas Z . A Comprehensive approach to WSN-based ITS applications: a survey. Sensors (Basel). 2012; 11(11):10220-65. PMC: 3274282. DOI: 10.3390/s111110220. View