| Citation: | LONG Yan, HUANG Jianling1, ZHAO Xiaohua, LI Zhenlong. Development and Classification of Lane-changing Graph Based on Multi-view Collaborative and Interactive Techniques[J]. Journal of Transport Information and Safety, 2022, 40(1): 106-115. doi: 10.3963/j.jssn.1674-4861.2022.01.013
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This paper aims to intuitively display the details of drivers' visual perception and related driving behavior in the lane-changing process by developing a multi-view collaborative visualization-based lane-changing graph. Specifically, driving behavior data related to lane-changing process are extracted from a simulated expressway, which is carried out by a driving simulator. The lane-changing graph is developed by coordinating parallel coordinates, count diagram, and bar chart with lane-changing trajectory. Following the analysis of 40 data sets of lane-changing behavior using the multi-view technique and the criteria for qualified lane-changing area, the lane-changing behavior is then classified into"Qualified""Barely Qualified", and"Unqualified". Meanwhile, the reasons of the unqualified lane-changing processes are also studied. The results show that the proportions of"Qualified""Barely Qualified", and"Unqualified"processes are 10.00%, 12.50%, and 77.50% respectively. The average standard deviations of the turning speed of the steering wheel, acceleration, and lateral acceleration observed over the unqualified processes (6.57°; 0.91 m/s2;0.41 m/s2) are larger than those observed over the qualified processes (4.55°; 0.34 m/s2;0.17 m/s2). The reasons for showing unqualified processes are mainly twofold: excessive lateral acceleration due to a large turning angle of the steering wheel and excessive change of longitudinal acceleration due to inappropriate operation of the gas panel. In general, the lane-changing graph can analyze and diagnose the lane-changing process accurately, which can provide supports for optimizing driver behavior in the lane-changing process.
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