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This paper aims to extract traffic rule at intersection from floating car data, traffic rule is the logical connectivity data in road network. Firstly, based on intersection data model, the geometric characteristics of intersection are presented, and the angle of arcs is calculated to get the traffic diversion. Secondly, routes are extracted from floating car data, which represent the number of turning car at intersection. Thirdly, a classification model based on support vector machine is used to classify the connected state of arcs, and the classification feature includes the number of car and traffic diversion. Finally, this method is applied in some intersections of Guangzhou Province using six days’ floating car data. The experiment results reveal the accuracy is about 90 percent.

Extracting Logical Connectivity of Intersection from Floating Car Data Using Support Vector Machine Method