Transit Traffic Filtration Algorithm from Cleaned Matched License Plate Data

Abstract

The analysis and planning of suburban traffic flows is an extremely important task to ensure efficient and fluent traffic distribution in existing infrastructure. One of the main sources of this information from existing situations is origin–destination (OD) matrices, usually obtained from traffic CCTV cameras. In this paper, a novel method is proposed for the filtration of transit traffic from the overall traffic through the area. The main feature that differentiates this method from existing outlier (and thus transit traffic) detection methods is that it is focused solely on prolonged trips (which are believed to be caused by vehicles stopping in the investigated area). Initial calibration of the method on training data (sample size of N = 216,159 trips through paired detectors) and verification on test data prove the accuracy of the algorithm on the level of 98% in urban and suburban areas, respectively, in Czech Republic conditions, which gives high hopes for the feasibility of the method.

Keywords

• travel time
• outlier filtering algorithm
• automatic vehicle identification systems
• intelligent transportation systems
• traffic surveillance systems
• automatic number plate recognition