On Evaluating Floating Car Data Quality for Knowledge Discovery

On Evaluating Floating Car Data Quality for Knowledge Discovery

Cerqueira, Vitor (NEC Laboratories Europe)
Moreira Matias, L.A. (TU Delft Transport and Planning; NEC Laboratories Europe)
Khiari, Jihed (NEC Laboratories Europe)
van Lint, J.W.C. (TU Delft Transport and Planning)

2018-01-01

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.

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

http://resolver.tudelft.nl/uuid:37df3832-50e6-43dc-b0f0-d4661da0141a

https://doi.org/10.1109/TITS.2018.2867834

2019-03-26

1524-9050

IEEE Transactions on Intelligent Transportation Systems, 19 (11), 3749 - 3760

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2018 Vitor Cerqueira, L.A. Moreira Matias, Jihed Khiari, J.W.C. van Lint