Research and Design of Road Traffic Flow Detection System

Abstract:

A road traffic flow detection system is designed based on induction loop, and the control platform is constructed based on the most advanced 32-bit ARM processor and CPLD. The systems hardware framework and software design process are introduced in this paper. The defects of traditional system such as deficient processing capacity and low measurement accuracy are overcome. In this system the data of the frequency change caused by the vehicles through the coil is collected, and the function of vehicles type classification in real-time is added, which is a great improvement compared to traditional induction loop detection system of vehicles.

• Periodical: Advanced Materials Research (Volumes 945-949)
• Pages: 3291-3295
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.945-949.3291
• Online since: June 2014
• Authors: Zan Song*, Qing Ye
• Keywords: Classification of Vehicle Types, Embedded System, Induction Loop, Intelligent Transportation System (ITS), Traffic Flow Detection

References

[1] Henry X, Liu: Uncovering the Contribution of Travel Time Reliability to Dynamic Route Choice Using Real-time Loop Data. (Transportation Research Part A, 2004) p.435.

DOI: 10.1016/j.tra.2004.03.003

[2] Ahmed M, Ei-Geneidy, Robert L. Bertini: Toward Validation of Freeway Loop Detector Speed Measurements Using Transit Probe Data. IEEE Intelligent Transportation Systems Conference. (2004) p.779.

DOI: 10.1109/itsc.2004.1399001

[3] Taek M. Kwon: Route Tracking of Border Crossing Vehicles Using Inductance Signatures of Loop Detectors. Contraband Detection and Personal Safety. (2005) p.103.

DOI: 10.1109/mshs.2005.1502566

[4] Charles Harlow: Automatic Vehicle Classification System With Range Sensors. Transportation Research Part C (2001) p.231.

[5] Benjamin Coifman: Identifying the Onset of Congestion Rapidly with Existing Traffic Detectors. Transportation Research Part A (2003) p.277.

DOI: 10.1016/s0965-8564(02)00016-2

[6] Clustering of Vehicle wave-form based on Principal Component Analysis and ART2 Neural Network. International Conference Measuring Technology and Mechatronics Automation, ICMTMA, V1, (2010) p.792.

DOI: 10.1109/icmtma.2010.776

[7] Herivelton A. Oliveira, Fabio R. Barbosa: A Vehicle Classification Based on Inductive Loop Detectors Using Artificial Neural Networks. 9th IEEE/IAS International Conference on Industry Applications (2010).

DOI: 10.1109/induscon.2010.5740079

[8] J. Gajda, R. Sroka, M. Stencel, A. Wajda, and T. Zeqlen: A vehicle classification based on inductive loop detectors. 18th IEEE Conf. IMTC, vol, 1, (2001) p.460.

DOI: 10.1109/imtc.2001.928860

[9] Korea Institute of Construction Technology. A basic design and analysis for urban traffic management system. Ministry Construction and Transportation, (1997) p.267.