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Towards Adaptive Sensory Data Fusion for Detecting Highway Traffic Conditions in Real Time

  • Yanling Cui
  • Beihong JinEmail author
  • Fusang Zhang
  • Tingjian Ge
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10828)

Abstract

The key challenge of detecting highway traffic conditions is to achieve it in a fully-covered, high-accuracy, low-cost and real-time manner. We present an approach named Megrez on the basis of treating mobile phones and probe vehicles as roving sensors, loop detectors as static sensors. Megrez can admit one or multiple types of data, including signaling data in a mobile communication network, data from loop detectors, and GPS data from probe vehicles, to carry out the traffic estimation and monitoring. In order to accurately reconstruct traffic conditions with full road segment coverage, Megrez provides a practical way to overcome the sparsity and incoherence of sensory data and recover the missing data in light of recent progresses in compressive sensing. Moreover, Megrez incorporates the characteristics of traffic flows to rectify the estimates. Using large-scale real-world data as input, we conduct extensive experiments to evaluate Megrez. The experimental results show that, in contrast to three other fusion methods, the results from our approach have high precisions and recalls. In addition, Megrez keeps the errors of estimates low even when not all three types of data are available.

Keywords

Data fusion Traffic condition detection Mobile signaling Compressive sensing Adaptation 

Notes

Acknowledgement

This work was supported by the National Natural Science Foundation of China under Grant No. 61472408 and the Ministry of Transportation of China under Grant No. 2015315Q16080. Tingjian Ge was supported in part by the NSF grants IIS-1149417 and IIS-1633271.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Yanling Cui
    • 1
    • 2
  • Beihong Jin
    • 1
    • 2
    Email author
  • Fusang Zhang
    • 1
    • 2
  • Tingjian Ge
    • 3
  1. 1.State Key Laboratory of Computer Sciences, Institute of SoftwareChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.University of MassachusettsLowellUSA

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