Title: GeoTNavi - smart navigation using geo-temporal traffic information

Authors: Shawn Wang; Susamma Barua; Kunal Desai; Swaroop Deshmukh

Addresses: Department of Computer Science, California State University, Fullerton, P.O. Box 6870, Fullerton, CA, 92834-6870, USA ' Department of Computer Science, California State University, Fullerton, P.O. Box 6870, Fullerton, CA, 92834-6870, USA ' Department of Computer Science, California State University, Fullerton, P.O. Box 6870, Fullerton, CA, 92834-6870, USA ' Department of Computer Science, California State University, Fullerton, P.O. Box 6870, Fullerton, CA, 92834-6870, USA

Abstract: We introduce a software system GeoTNavi that utilises geo-temporal traffic information in suggesting an optimal route for drivers. GeoTNavi aids the driver in two phases. In the first phase, historical traffic information is studied to reveal patterns on any segment of the highway at a specific day and time. This information is utilised to suggest an optimal route for the driver. In the second phase, the real time traffic information will be used to adjust the optimal route along the way. State-of-the-art data warehousing and data mining techniques are applied to ensure efficiency of the system.

Keywords: urban commute; commuting; smart navigation; intelligent navigation; geo-temporal traffic information; data warehousing; data mining; optimal routes; route optimisation; traffic patterns; traffic congestion; traffic jams; congestion prediction; traffic flow estimation; trip planning; web-based applications.

DOI: 10.1504/IJDMMM.2013.051922

International Journal of Data Mining, Modelling and Management, 2013 Vol.5 No.1, pp.20 - 36

Available online: 07 Feb 2013 *

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