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浮动车信息处理技术研究 被引量:11

A Study on Floating Car Based Information Processing Technology
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摘要 概括了浮动车技术的基本原理,重点介绍了浮动车信息处理系统的处理流程及地图匹配、路径推测和路况信息计算方法。针对GPS数据精度差、路网结构复杂等影响浮动车信息处理准确性提升的问题,给出了一系列改进型研究工作。最后,给出了评估浮动车信息处理准确性的方法,并指出了浮动车信息处理技术的后续工作。 The floating car technique is one of the key technologies in ITS ( intelligent transportation system) to acquire the traffic information in recent years. In this paper, firstly, the fundamental principle of floating car technique is introduced. Then, the enhanced processing procedures of floating car information system, and some important approaches including map matching, path deriving and traffic information calculating are emphasized. To review the key issues affecting information processing accuracy, such as poor GPS data precision and complex road network, a serious of enhanced approaches are presented. Finally, some experiments are given to evaluate information processing accuracy and future work is pointed out.
出处 《中国图象图形学报》 CSCD 北大核心 2009年第7期1230-1237,共8页 Journal of Image and Graphics
关键词 浮动车 信息处理 地图匹配 路径推测 信息融合 floating car, information processing, map matching, path deriving, information fusion
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  • 1Wu D D, Zhu T Y, Lu W F, et al. A heuristic map-matching algorithm by using vector-based recognition [ C ]// Proc of the International Multi-Conference on Computing in the Global Information Technology ( ICCGI' 07 ). Piscataway : IEEE, 2007 : 18 - 24
  • 2Vapnik V N. The nature of statistical learning theory[ M]. New York : Springer-Verlag, 1995 : 138 - 141
  • 3Langley P. Selection of relevant features in machine learning [ C ]//Proc AAAI Fall Symposium on Relevance. New Orleans : AAAI Press, 1994 : 140 - 144
  • 4Lee H M, Chen C M, Chen J M, et al. An efficient fuzzy classifier with feature selection based on fuzzy entropy [ J ]. IEEE Trans on Systems Man Cybernet, Part B, 2001, 31 ( 3 ) : 426 - 432
  • 5Uncu O, Turksen I B. Two step feature selection: approximate functional dependency approach using membership values[ C ]// Proceedings 2004 IEEE International Conference on Fuzzy System. Piscataway: IEEE, 2004 : 1643 - 1648
  • 6Connon R L, Dave J V, Bezdek J C. Efficient implementation of the fuzzy c-means clustering algorithms[ J]. IEEE Trans on Patten Analysis and Machine Intelligence, 1986, 8 (2) :248 -255
  • 7Han J W, Kamber M. Data mining concepts and techniques [ M ]. Los Altos: Morgan Kaufmann, 2001 : 132 - 136
  • 8Kuehne R,,Schaefer R P,Mikat J, et al.New approaches for traffic management in metropolitan areas[].IFAC CTS.2003
  • 9Marchal F,Hackney J K,Axhausen K W.Efficient map-matching of large GPS data sets-test on a speed monitoringex- periment in Zurich[].Transport Res Rec.2004
  • 10Pfoser D,Jensen C S.Capturing the uncertainty of moving-object representations[]..1999

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