Choice of Lane-Changing Point in an Urban Intertunnel Weaving Section Based on Random Forest and Support Vector Machine

Chuwei Zhao; Yi Zhao; Zhiqi Wang; Jianxiao Ma; Minghao Li

doi:10.7307/ptt.v35i2.60

Authors

Chuwei Zhao College of Automobile and Traffic Engineering, Nanjing Forestry University
Yi Zhao College of Automobile and Traffic Engineering, Nanjing Forestry University
Zhiqi Wang College of Automobile and Traffic Engineering, Nanjing Forestry University
Jianxiao Ma College of Automobile and Traffic Engineering, Nanjing Forestry University
Minghao Li College of Automobile and Traffic Engineering, Nanjing Forestry University

DOI:

https://doi.org/10.7307/ptt.v35i2.60

Keywords:

urban intertunnel weaving section, choice of lane-changing point, random forest, support vector machine

Abstract

Urban intertunnel weaving (UIW) section is a special type of weaving section, where various lane-changing behaviours occur. To gain insight into the lane-changing behaviour in the UIW section, in this paper we attempt to analyse the decision feature and model the behaviour from the lane-changing point selection perspective. Based on field-collected lane-changing trajectory data, the lane-changing behaviours are divided into four types. Random forest method is applied to analyse the influencing factors of choice of lane-changing point. Moreover, a support vector machine model is adopted to perform decision behaviour modelling. Results reveal that there are significant differences in the influencing factors for different lane-changing types and different positions in the UIW segment. The three most important factor types are object vehicle status, current-lane rear vehicle status and target-lane rear vehicle status. The precision of the choice of lane-changing point models is at least 82%. The proposed method could reveal the detailed features of the lane-changing point selection behaviour in the UIW section and also provide a feasible choice of lane-changing point model.

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