Overtaking Characteristic Analysis and High-Risk Overtaking Recognition on Urban Roads

Abstract:

To take proper measures to manage the overtaking behavior on urban roads， a method is proposed to recognize high-risk overtaking vehicles online based on quantitative indicators. First， the traffic wave theory is employed to classify overtaking on urban roads. Enlightened by the types， a multi-dimensional index system is constructed to illustrate the essential features of urban-road overtaking. Then， based on license plate recognition data， a method is introduced to calculate these indexes online. Finally， with the real data， the effectiveness of the index system and its calculation are verified to recognize high-risk overtaking. According to the analysis results， both the correlations between the overtaking number and volume and the overtaken number and volume can be fitted by the polynomial， which would help identify volume-sensitive segments. The K-means algorithm is used to cluster the overtaking vehicles into three types according to the difference between the planning speed and the overtaking speed. Given the type， the actual speed and the overtaking speed difference are suitable for evaluating the overtaking risk. It is found that high-risk overtaking frequently occurs in the unfavorable phases resulting from inappropriate signal control coordination between adjacent intersections. Moreover， overtaking with high risk is also prone to be found among the vehicles passing by the end of green light at downstream intersections and the first vehicles passing during green light at upstream intersections.