Real-Time Urban Traffic State Estimation with A-GPS Mobile Phones as Probes

Sha Tao, Vasileios Manolopoulos, Saul Rodriguez, Ana Rusu

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DOI: 10.4236/jtts.2012.21003                

Abstract

This paper presents a microscopic traffic simulation-based method for urban traffic state estimation using Assisted Global Positioning System (A-GPS) mobile phones. In this approach, real-time location data are collected by A-GPS mobile phones to track vehicles traveling on urban roads. In addition, tracking data obtained from individual mobile probes are aggregated to provide estimations of average road link speeds along rolling time periods. Moreover, the estimated average speeds are classified to different traffic condition levels, which are prepared for displaying a real-time traffic map on mobile phones. Simulation results demonstrate the effectiveness of the proposed method, which are fundamental for the subsequent development of a system demonstrator.

Keywords

Traffic State Estimation; A-GPS Mobile Phones; Microscopic Traffic Simulation; Mobile Tracking

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Google Maps Mobile Users Send Traffic Data. http://googlesystem.blogspot.com/2009/08/google-maps-mobile-users-send-traffic.html
[2]	Y. Wang, M. Papageorgiou and A. Messmer, “Real-Time Freeway Traffic State Estimation Based on Extended Kal- man Filter: Adaptive Capabilities and Real Data Testing,” Transportation Research Part A, Vol. 42, No. 10, 2008, pp. 1340-1358. doi:10.1016/j.tra.2008.06.001
[3]	J. Guo, J. Xia and B. Smith, “Kalman Filter Approach to Speed Estimation Using Single Loop Detector measurements under Congested Conditions,” Journal of Trans- portation Engineering, Vol. 135, No. 12, 2009, pp. 927- 934. doi:10.1061/(ASCE)TE.1943-5436.0000071
[4]	X. J. Ban, Y. Li, A. Skabardonis and J. D. Margulici, “Performance Evaluation of Travel-Time Estimation Me- thods for Real-Time Traffic Applications,” Journal of In- telligent Transportation Systems, Vol. 14, No. 2, 2010, pp. 54-67. doi:10.1080/15472451003719699
[5]	R. L. Cheu, C. Xie and D. H. Lee, “Probe Vehicle Popu- lation and Sample Size for Arterial Speed Estimation,” Computer-Aided Civil and Infrastructure Engineering, Vol. 17, No. 1, 2002, pp. 53-60. doi:10.1111/1467-8667.00252
[6]	C. Nanthawichit, T. Nakatsuji and H. Suzuki, “Applica- tion of Probe-Vehicle Data for Real-Time Traffic-State Estimation and Short-Term Travel-Time Prediction on a Freeway,” Transportation Research Record, 2003, pp. 49-59. doi:10.3141/1855-06
[7]	M. Ferman, D. Blumenfeld and X. Dai, “An Analytical Evaluation of a Real-Time Traffic Information System Using Probe Vehicles,” Journal of Intelligent Transpor- tation Systems, Vol. 9, No. 1, 2005, pp. 23-34. doi:10.1080/15472450590912547
[8]	Y. Chen, L. Gao, Z. Li and Y. Liu, “A New Method for Urban Traffic State Estimation Based on Vehicle Track- ing Algorithm,” Proceedings of IEEE Intelligent Trans- portation Systems Conference, Seattle, 30 September-3 October 2007, pp. 1097-1101. doi:10.1109/ITSC.2007.4357646
[9]	R. Cayford and T. Johnson, “Operational Parameters Af- fecting the Use of Anonymous Cell Phone Tracking for Generating Traffic Information,” Transportation Research Board Annual Meeting, Washington DC, 2003.
[10]	B. Hellinga and P. Izadpanah, “An Opportunity Assess- ment of Wireless Monitoring of Wide-Area Road Traffic Conditions,” Technical Report, 2007, pp. 1-78.
[11]	ITU, “Key Global Telecom Indicators for the World Tele- communication Service Sector.” http://www.itu.int/ITU-D/ict/statistics/at_glance/KeyTelecom.html
[12]	MobiThinking, “Global Mobile Statistics 2011.” http://mobithinking.com/stats-corner/global-mobile-statistics-2011-all-quality-mobile-marketing-research-mobile-web-stats-su
[13]	Y. Yim, “The State of Cellular Probe,” California PATH Research Report, 2003.
[14]	M. Fontaine, B. Smith, A. Hendricks and W. Scherer, “Wireless Location Technology-Based Traffic Monitor- ing: Preliminary Recommendations to Transportation Agen- cies Based on Synthesis of Experience and Simulation Re- sults,” Transportation Research Record, Vol. 1993, 2007, pp. 51-58. doi:10.3141/1993-08
[15]	H. Bar-Gera, “Evaluation of a Cellular Phone-Based Sys- tem for Measurements of Traffic Speeds and Travel Times: A Case Study from Israel,” Transportation Research Re- search Part C, Vol. 15, 2007, pp. 380-391.
[16]	J. C. Herrera, et al., “Evaluation of Traffic Data Obtained via GPS-Enabled Mobile Phones: The Mobile Century Field Experiment,” Transportation Research Part C, Vol. 18, No. 4, 2010, pp. 568-583.
[17]	B. R. Hellinga and L. Fu, “Reducing Bias in Probe-Based Arterial Link Travel Time Estimates,” Transportation Research Part C, Vol. 10, No. 4, 2002, pp. 257-273.
[18]	Transport Canada, “Development and Demonstration of a System for Using Cell Phones as Traffic Probes.” http://www.tc.gc.ca/eng/innovation/tdc-summary-14300-14359e-1430.htm
[19]	Mobile Millennium, “The Mobile Century Field Test.” http://traffic.berkeley.edu/project/mobilecentury
[20]	G. Rose, “Mobile Phones as Traffic Probes: Practices, Pro- spects and Issues,” Transport Reviews, Vol. 26, No. 3, 2006, pp. 275-291. doi:10.1080/01441640500361108
[21]	X. Dai, M. Ferman and R. Roesser, “A Simulation Eva- luation of a Real-Time Traffic Information System Using Probe Vehicles,” Proceedings of IEEE Intelligent Transportation Systems Conference, 12-15 October 2003, pp. 475-480.
[22]	V. Manolopoulos, S. Tao, S. Rodriguez, M. Ismail and A. Rusu, “MobiTraS: A Mobile Application for a Smart Traf- fic System,” Proceedings of IEEE International NEWCAS conference, Montrea, 20-23 June 2010, pp. 365-368.
[23]	SUMO. http://sumo.sourceforge.net/
[24]	eWorld. http://eworld.sourceforge.net/
[25]	OpenStreetMap. http://www.openstreetmap.org/
[26]	J. Ygnace, C. Drane, Y. B. Yim and R. D. Lacvivier, “Travel Time Estimation on the San Francisco Bay Area Network Using Cellular Phones as Probes,” California PATH Re- search Report, 2000, pp. 1-47.
[27]	K. Srinivasan and P. Jovanis, “Determination of Number of Probe Vehicles Required for Reliable Travel Time Mea- surement in Urban Network,” Transportation Research Record, 1996, pp. 15-22. doi:10.3141/1537-03
[28]	M. Chen and S. I. J. Chien, “Determining the Number of Probe Vehicles for Freeway Travel Time Estimation by Microscopic Simulation,” Transportation Research Record, 2000, pp. 61-68. doi:10.3141/1719-08
[29]	S. M. Turner and D. J. Holdener, “Probe Vehicle Sample Size for Real-Time Information: The Houston Experience,” Proceedings of the Annual Meeting of ITS America, Vol. 1, Houston, 1996, pp. 287-295.
[30]	M. Fontaine and B. L. Smith, “Probe-Based Traffic Mo- nitoring Systems with Wireless Location Technology: An Investigation of the Relationship between System Design and Effectiveness,” Transportation Research Record, 2005, pp. 3-11. doi:10.1049/iet-its.2009.0053
[31]	W. Shi and Y. Liu, “Real-Time Urban Traffic Monitoring with Global Positioning System-Equipped Vehicles,” IET Intelligent Transport Systems, Vol. 4, No. 2, 2010, pp. 113- 120.
[32]	World Geodetic System, 1984. http://en.wikipedia.org/wiki/World_Geodetic_System
[33]	SUMOPlayer. http://sourceforge.net/apps/mediawiki/sumo/index.php?title=SUMOPlayer
[34]	F. Gustafsson and F. Gunnarsson, “Mobile Positioning Using Wireless Networks,” IEEE Signal Processing Maga- zine, Vol. 22, No. 4, 2005, pp. 41-53.
[35]	Y. Yim and R. Cayford, “Investigation of Vehicles as Probes Using Global Positioning System and Cellular Phone Tracking: Field Operational Test,” 2001.
[36]	http://escholarship.org/uc/item/0378c1wc.pdf
[37]	Universal Transverse Mercator Coordinate System. http://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system
[38]	Y. Bar-Shalom, X. R. Li and T. Kirubarajan, “Estimation with Applications to Tracking and Navigation,” Wiley- Interscience, Hoboken, 2001. doi:10.1002/0471221279
[39]	D. Simon, “Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches,” John Wiley & Sons, Hobo- ken, 2006. doi:10.1002/0470045345
[40]	N. Caceres, J. Wideberg and F. Benitez, “Review of Traf- fic Data Estimations Extracted from Cellular Networks,” IET Intelligent Transport Systems, Vol. 2, No. 3, 2008, pp. 179-192. doi:10.1049/iet-its:20080003
[41]	Driving and Speed Limits in Stockholm. http://carrentalscout.com/driving-speed-limits-stockholm
[42]	Y. Zhao “Vehicle Location and Navigation Systems,” Ar- tech House, London, 1997.
[43]	D. Bernstein and A. Kornhauser, “An Introduction to Map Matching for Personal Navigation Assistants,” New Jer- sey TIDE Center Technical Report, 1996.
[44]	M. Weserman, R. Litjens and J. Linnartz, “Integration of Probe Vehicle and Induction Loop Data-estimation of Travel Times and Automatic Incident Detection,” Cali- fornia PATH Research Report, 1996.
[45]	Java OSM Editor. http://josm.openstreetmap.de/
[46]	D. J. Lovell, “Accuracy of Speed Measurements from Cel- lular Phone Vehicle Location Systems,” Journal of Intel- ligent Transportation Systems, Vol. 6, No. 4, 2001, pp. 303-325. doi:10.1080/10248070108903698