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Publication Detail
Urban traffic data fusion
  • Publication Type:
  • Authors:
    Chow AHF, Tsapakis I, Tanaksaranond G, Cheng T, Heydecker B, Emmonds A
  • Publication date:
  • Pagination:
    177, 184
  • Published proceedings:
    Proceedings of the 17th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2012: Transportation and Logistics Management
  • ISBN-13:
  • Status:
This paper analyses the use of different type of data for retrieving the underlying traffic pattern. We present and investigate a data fusion algorithm for integrating heterogeneous traffic data in urban networks. The fusion algorithm is developed based upon the adaptive smoothing method (ASM) proposed by Treiber and Helbing. The objective is to produce a more refined picture of urban traffic through processing and integrating data from different sources in urban network. The filtering and fusion algorithm can work with data collected in different spatio-temporal granularity, with different level of accuracy, and from different kinds of sensors. The accuracy of the fusion algorithm is evaluated on a VISSIM microscopic simulation test-bed. This paper contributes to urban traffic analysis and management.
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