Study on Road Traffic Condition Identification Based on Floating Taxi

Abstract:

This paper describes a prototype system based on floating taxi for traffic condition identification. The system consists of in-vehicle hardware units placed in floating taxi and backstage database that process all data send from the report units. The communication between the taxi and the database center is based on a very compact wireless communication protocol. The taxi sample size is decided by the variables: section traffic information update cycle, data sampling interval, section covering ratio. The test in a road section showed that the system is operational which could offer useful reference for urban traffic management and resident trips decision.

• Periodical: Applied Mechanics and Materials (Volumes 105-107)
• Pages: 2250-2254
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.105-107.2250
• Online since: September 2011
• Authors: Xin Sheng Yao, Jian Hua Qu, Ji Lai Ying
• Keywords: Condition Identification, Floating Taxi, Sample Size, Traffic Information

References

[1] G. Leduc. Road traffic data: Collection methods and applications. Technical report, Institute for Prospective Technological Studies, EU, (2008). http://ftp.jrc.es/EURdoc/JRC47967.TN.pdf

[2] "Floating car data methods" are gaining momentum worldwide; http://www.ivsource.net/archivep/2003/nov/031112_FCD.html

[3] Boyce, D., Rouphail, N., and Kirson, A. Estimation and measurement of link travel times in the ADVANCE project. In Proceedings of the IEEE-IEE Vehicle Navigation & Information Systems Conference, Ottawa. Ont. IEEE, Piscataway, N.J. 1993, pp.62-66

DOI: 10.1109/vnis.1993.585586

[4] Laurent B., Sodit. Real-time information on road traffic based on Floating Car Data http://www.pdfxx.com/f1/f1b9147a359bbe3b-download.pdf

[5] Neumann, T. Efficient queue length detection at traffic signals using probe vehicle data and data fusion, 16th ITS World Congress, Stockholm, Sweden (2009)

[6] Green MW, Fontaine MD, Smith BL. Investigation of dynamic probe sample requirements for traffic condition monitoring. Transportation Research Record 1870, pp.55-61, (2004)

DOI: 10.3141/1870-07

[7] Zhang, C., Yang, X., Yan, X., Methods for floating car sampling period optimization, Journal of Transportation Systems Engineering and Information Technology, Vol.7 (3), pp.100-104, (2007) (In Chinese)

DOI: 10.1016/s1570-6672(07)60025-7

[8] Bejan, A., Gibbens, R., Evans, D., etc. Statistical modeling and analysis of sparse bus probe data in urban areas, 13th International IEEE Annual Conference on Intelligent Transportation Systems Madeira Island, Portugal (2010), pp.1256-1263

DOI: 10.1109/itsc.2010.5625144

[9] Travel time data collection handbook, fhwa report, chapter 5, ITS Probe Vehicle Techniques, (1998). http://www.fhwa.dot.gov/ohim/handbook/chap5.pdf