On Evaluating Floating Car Data Quality for Knowledge Discovery

Vitor Cerqueira, Luis Moreira-Matias, Jihed Khiari, Hans van Lint

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)
31 Downloads (Pure)


Floating car data (FCD) denotes the type of data (location, speed, and destination) produced and broadcasted periodically by running vehicles. Increasingly, intelligent transportation systems take advantage of such data for prediction purposes as input to road and transit control and to discover useful mobility patterns with applications to transport service design and planning, to name just a few applications. However, there are considerable quality issues that affect the usefulness and efficacy of FCD in these many applications. In this paper, we propose a methodology to compute such quality indicators automatically for large FCD sets. It leverages on a set of statistical indicators (named Yuki-san) covering multiple dimensions of FCD such as spatio-temporal coverage, accuracy, and reliability. As such, the Yuki-san indicators provide a quick and intuitive means to assess the potential ``value'' and ``veracity'' characteristics of the data. Experimental results with two mobility-related data mining and supervised learning tasks on the basis of two real-world FCD sources show that the Yuki-san indicators are indeed consistent with how well the applications perform using the data. With a wider variety of FCD (e.g., from navigation systems and CAN buses) becoming available, further research and validation into the dimensions covered and the efficacy of the Yuki-San indicators is needed.

Original languageEnglish
Pages (from-to)3749 - 3760
Number of pages12
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number11
Publication statusPublished - 1 Jan 2018


  • Automobiles
  • Data mining
  • data quality
  • Estimation
  • Floating car data
  • Global Positioning System
  • GPS
  • origin-destination matrix
  • Planning
  • Roads
  • traffic control
  • Trajectory
  • trajectory mining.
  • travel time estimation

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