Measurements of road traffic parameters using inductive loops and piezoelectric sensors

• Autorzy: Burnos P. , Gajda J. , Piwowar P. , Sroka R. , Stencel M. , Żegleń T.
• Języki publikacji: EN

Abstrakty

EN

The basic problems corresponding to traffic measurements have been presented in the paper. The Authors gave a general overview of the parameters and characteristics describing the vehicles and traffic flow. The current sensor technologies used in measuring systems have been presented. Moreover the measuring systems used in traffic measurements have been described. Special at tention has been paid to the more sophisticated problems like a vehicle's classification based on the analysis of its magnetic signature and to vehicle's weigh-in-motion technique. The presented results base on the Authors' experience in designing and exploitation of the measuring systems equipped with inductive loops and piezoelectric sensors.

Słowa kluczowe

EN

traffic parameter measurements; single loop detectors; WIM systems; multi sensor WIM systems; vehicle classification; vehicle's magnetic signature

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2007
• Tom: Vol. 14, nr 2
• Strony: 187--203
• Opis fizyczny: Bibliogr. 42 poz., rys., wykr., tab.

Twórcy

autor

Burnos P.

autor

Gajda J.

autor

Piwowar P.

autor

Sroka R.

autor

Stencel M.

autor

Żegleń T.

• AGH - University of Science and Technology, Department of Measurement and Instrumentation, Kraków, Poland,

Bibliografia

• 1. Athol P.: Interdependence of Certain Operational Characteristics Within a Moving Traffic Stream, Highway Research Record, vol. 72, 1965.
• 2. Cebon D.: Handbook of Vehicle-Road Interaction, Swets&Zeitlinger B. V., Lisse, the Netherlands 1999.
• 3. Cebon D.: Design of multiple-sensor weigh-in-motion systems, Journal of Automobile Engineering, Proc. I. Mech. E., 204, pp. 133–144, 1990.
• 4. Cebon D., Winkler C. B.: Multiple-Sensor WIM: Theory and experiments, Transportation Research Record, TRB, 1311, pp. 70–78, 1991.
• 5. Dailey D. J.: Travel Time Estimates Using a Series of Single Loop Volume and Occupancy Measurements, Transport Research Board 76th Annual Meeting, Washington, D.C., 1997.
• 6. Dailey D. J., Harn P., Lin P.: ITS Data Fusion, Final research report, Research project T9903, Department of Transportation, Washington State Transportation Commission, April 1996.
• 7. Dolcemascolo V., Jacob B.: Multiple sensor Weigh-In-Motion: Optimal Design and Experimental Study, Pre-proc. of 2nd European Conference of Weigh in Motion of Road Vehicles, Lisbon, 14/16 September 1998, pp. 129–138.
• 8. Dukkipati R. V.: Vehicle Dynamics, Alpha Science International Ltd. 2000.
• 9. Gajda J., Sroka R., Stencel M., Żegleń T.: Measurement of Road Traffic Parameters Using an Inductive Single-Loop Detector, 9th International Symposium on Electrical Instruments in Industry, Glasgow 1997.
• 10. Gajda J., Stencel M.: Determination of Road Vehicle Types Using an Inductive Loop Detector, XIV IMEKO World Congress, Tampere, Finland, 1997.
• 11. Gajda J., Sroka R.: Vehicle classification by parametric identification of the measured signals, Proc. of XVI IMEKO World Congress, Vienna 2000, vol. IX, pp. 199–204.
• 12. Gajda J., Sroka R., Stencel M., Wajda A., Zeglen T.: A vehicle classification based on inductive loop detectors, Proc. of the 18th IEEE, IMTC, Budapest 2001, pp. 460–464.
• 13. Gajda J.: Statistical calibration of WIM systems, Scientific Series of Rzeszów Politechnic, Electrotechnic, no. 27, Rzeszów, 2004. (in Polish)
• 14. Gajda J., Burnos P.: Self-calibration of the weigh-in-motion systems. Proc. of XV Symposium Modelling and Simulation of Measurement Systems, Krynica 2005. (in Polish)
• 15. Gonzales A., Papagiannakis A. T., O’Brien E.: Evaluation of an Artificial Neural Network Technique Applied to Multiple Sensor Weigh-in-Motion Systems, University College Dublin, Ireland.
• 16. Huhtala M.: Factors Affecting Calibration Effectiveness, Proc. of the Final Symposium of the Project WAVE, Paris 1999.
• 17. Klein L. A.: Sensor Technologies and Data Requirements for ITS, Artech House, London 2001.
• 18. Karlsson B.: Fuzzy Measures for Sensor Data Fusion in Industrial Recycling, Measurement Science and Technology, vol. 9, pp. 907–912, 1998.
• 19. Ki Y. K., Baik D. K.: Vehicle Classification Algorithm for Loop Detectors using Neural Network, IEEE Transactions on Vehicular Technology, vol. 55, no. 6, pp. 1704–1711, 2006.
• 20. Mangeas M., Glaser S., Dolcemascolo V.: Neural networks estimation of truck static weights by fusing weight-in-motion data, Proc. of Eurofusion 2000.
• 21. Maerivoet S., De Moor B.: Traffic Flow Theory, internet paper, 2006.
• 22. Stanczyk D.: New Calibration Procedure by Axle Rank, Proc. of the Final Symposium of the Project WAVE, Paris 1999, pp. 307–316.
• 23. Sun C., Ritchie G., Tsai K., Jayakrishnan R.: Use of vehicle signature analysis and lexicographic optimisation for vehicle reidentification on freeways. Transportation Research Part C 7, pp. 167–185, 1999.
• 24. Wang Y., Nihan N.: Can Single-Loop Detectors Do the Work of Dual-Loop Detectors?, internet paper.
• 25. Weigh-in Motion of Road Vehicle, Final Report of COST 323 action, Ver. 3.0, 1999.
• 26. Weigh-In-Motion of Axles and Vehicles for Europe (WAVE), General Report of 4th Programme Transport, Laboratoire Central des Pontes et Chaussees, 2001.
• 27. Zhang X., Wang Y., Nihan N.: Monitoring a Freeway Network in Real Time Using Single – Loop Detectors, Int. J. Vehicle Information and Communication Systems, vol. 1, no. 1/2, 2005.
• 28. Gibson D., Tweedy C.: An Advanced Preformed Inductive Loop Sensor, NATMEC, Charlotte, USA, 1998.
• 29. www.rtms-by-eis.com
• 30. www.agd-systems.com
• 31. www.rtms-by-eis.com
• 32. www.wavetronix.com
• 33. www.crs-vision.com
• 34. www.iteris.com
• 35. www.traffipax.com
• 36. www.autoscope.com
• 37. www.imagesensing.com
• 38. www.smarteksys.com
• 39. www.orincon.com/itms
• 40. Caruso M. J., Withanawasam L. S.: Vehicle Detection and Compass Application using AMR Magnetic Sensors, Honeywell (internet paper).
• 41. Song K., Chen C., Huang C. C.: Design and Experimental Study of an Ultrasonic Sensor System for Lateral Collision Avoidance at Low Speeds, IEEE Intelligent Vehicles Symposium, Parma, 2004.
• 42. Mustafa H. T.: Infrared Vehicle Sensor for Traffic Control, Ph.D. Thesis – City University of New York, 1994.