Taxi Origin-Destination Areas of Interest Discovering Based on Functional Region Division
Xuejin Wan, Mengdan Gao, Jianchu Kang, Jianling Zhao
Journal of Networking Technology, Vol. 8, No. 1, 2017.
DOI: 
Link: http://www.dline.info/jnt/fulltext/v8n1/jntv8n1_1.pdf
Abstract:
This paper introduced a new method to discover the taxi Origin-Destination areas of interest based on functional region division to resolve the problem that taxis distribution is unreasonable. The problem occurs due to dispatching t axis
is not in line with the taxi demand in different functional regions during different time periods. The method proposed in this 
paper clustered t axi Origin-Destination data points of the functional region with the improved DB-SCAN algorithm and
yielded the areas of interest with the statistical method named Chi-square distribution. The accuracy and credibility of the
method was evaluated through two indicators called coverage and hit ratio and a comparison analysis on situations of
different regions. The experiment proved that the proposed method can effectively discover and predicted the taxi Origin-
Destination areas of interest in different functional regions in different time periods.