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Sensors 2016, 16(9), 1340; doi:10.3390/s16091340

Querying and Extracting Timeline Information from Road Traffic Sensor Data

1
Department of Big Data, Pusan National University, Busan 46241, Korea
2
Department of Computer Science & Electrical Engineering, University of Missouri-Kansas City, Kansas City, MO 64110, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 16 June 2016 / Revised: 28 July 2016 / Accepted: 15 August 2016 / Published: 23 August 2016

Abstract

The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset. View Full-Text
Keywords: traffic sensor data; timeline model; historical traffic sensor data; TQ-index; traffic data query processing traffic sensor data; timeline model; historical traffic sensor data; TQ-index; traffic data query processing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Imawan, A.; Indikawati, F.I.; Kwon, J.; Rao, P. Querying and Extracting Timeline Information from Road Traffic Sensor Data. Sensors 2016, 16, 1340.

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