Data acquisition and pre-processing are important steps in any traffic data collection, analysis or simulation project. In this paper the authors present the results of a case study they have done on traffic simulation for a stretch of the E17 highway near Antwerp, Belgium. They will especially focus on the data collection and processing part. The objective of the work presented here is to illustrate how traffic data can be collected and processed in such a way that it can be used for modeling and prediction purposes. The data collection and processing process consists of three steps: data acquisition, interfacing, and pre-processing. During this process a central database with raw sensor data is created. In general the raw sensor data will contain errors or missing values due to sensor failures, data link errors, biases, and other measurement errors. Therefore, the authors introduce a pre-processing step in order to deal with data that is known to be corrupt or for which the value is temporarily not available (many simulation packages require data records that are complete and contain no gaps). After the three steps have been carried out, they have a database of "clean and complete" traffic data that can be used for further analysis or that can be used in other applications such as highway traffic simulation or traffic forecasts. (A) For the covering abstract see ITRD E106484.


  • English

Media Info

  • Features: References;
  • Pagination: p. 4/1-4/7

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Filing Info

  • Accession Number: 00801614
  • Record Type: Publication
  • Source Agency: Transport Research Laboratory
  • Files: ITRD
  • Created Date: Nov 8 2000 12:00AM