Outlier Detection of Handover Data for Inner-Suburban Freeway Traffic Information Estimation Using Mobile Probes

Mobile probes provide a supplementary means of traffic information estimation for inner-suburban freeways in the major big cities in China. Lack of sufficient participants with GPS-based smart phones at the moment, handover-based location solution, one of GSM-based location solutions, was tentatively employed in this paper. Since handover data currently cannot have the same location performance with GPS data, low location accuracy has been a great challenge for traffic information estimation. To improve the estimated accuracy of travelling speed using mobile probes, an outlier detection algorithm of handover data is developed for identifying those handover links with large estimated errors. The developed outlier detection algorithm contains two steps, outlier detection of individual handover link and outlier detection of linked handover links. LS-SVM ensemble classifier is employed in the first step and a statistical-based algorithm is employed in the second step. Evaluations of the developed algorithm were finally studied using field data collected in a preliminary field test in a stretch of inner suburban freeway in Beijing, China.