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基于多视图协同交互技术的换道图谱构建与分类
引用本文:龙彦,黄建玲,赵晓华,李振龙.基于多视图协同交互技术的换道图谱构建与分类[J].交通信息与安全,2022,40(1):106-115.
作者姓名:龙彦  黄建玲  赵晓华  李振龙
作者单位:1.北京工业大学城市交通学院 北京 100124
摘    要:为直观展示换道过程中驾驶人视觉感知与手脚操作的细节特征,研究了多视图协同可视化的换道图谱.采用驾驶模拟舱进行高速公路驾驶实验,提取换道过程相关指标数据.将平行坐标、计数图、柱状图与换道轨迹协同可视化以构建换道图谱.采用多视图交互技术对提取的40个换道过程进行分析,提出换道过程的合格区范围并以此将换道图谱分为合格、临界合...

关 键 词:智能交通  换道过程  换道图谱  多视图协同
收稿时间:2021-09-20

Development and Classification of Lane-changing Graph Based on Multi-view Collaborative and Interactive Techniques
LONG Yan,HUANG Jianling,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.
Authors:LONG Yan  HUANG Jianling  ZHAO Xiaohua  LI Zhenlong
Affiliation:1.College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China2.Beijing Transportation Information Center, Beijing 100073, China
Abstract: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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