| 雾环境下高速公路驾驶人跟驰行为研究 |
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| 引用本文： | 张续光,高建平,廖丽,BAJAJ D.雾环境下高速公路驾驶人跟驰行为研究[J].中国公路学报,2022,35(1):275-285. |
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| 作者姓名： | 张续光 高建平 廖丽 BAJAJ D |
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| 作者单位： | 1. 重庆交通大学土木工程学院, 重庆 400074;2. 重庆建筑工程职业学院交通与市政工程学院, 重庆 400072 |
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| 基金项目： | 国家自然科学基金项目（51378520）；重庆市自然科学基金项目（cstc2019jcyj-msxmX0694）；重庆市教委科技项目（KJQN201904302，KJQN202104301） |
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| 摘 要： | 雾环境下驾驶人行车与正常天气相比，在低能见度下视觉参照物较少，驾驶人更倾向于跟驰行驶。为研究雾环境下高速公路驾驶人跟驰行为，以真实雾环境下实车试验方式，选择多条高速公路作为试验路段，以Smart Eye眼动仪获取车辆在雾环境下高速公路驾驶人视觉参数，包含驾驶人注视区域、注视角度、注视持续时间、瞳孔直径、扫视速度以及扫视幅度等，以归一化方法对驾驶人注视重心进行分析，研究不同能见度下驾驶人的跟驰需求，并通过对雾环境下上述视觉参数进行规律总结。对雾环境下驾驶人跟驰特性进行统计及分类，将跟驰行为划分为主动、半主动、半被动以及全被动跟驰；通过分析雾区低能见度下驾驶人跟驰行驶条件，引入多维偏好理论及后悔理论，进行驾驶人跟驰决策模型构建，并基于差分法对模型进行参数标定及验证。研究结果表明：驾驶人在1次跟驰动态过程中，正常车道保持时驾驶人扫视速度较低，而当处于车道调整时，驾驶人扫视速度存在较大波动，且平均扫视速度较高，低能见度下驾驶人注视点转移速度27.0 （°）·s-1明显低于晴好天气的52.0 （°）·s-1；驾驶人在跟驰过程中，能见度对驾驶人跟驰时的视觉特征有显著影响，通过跟驰模型构建可为后续雾环境下车辆跟驰前后车距及车速预测提供理论支撑。
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| 关 键 词： | 交通工程 雾环境 后悔理论 高速公路 跟驰行为 多维偏好 |
| 收稿时间： | 2020-07-15 |
Car Following Behavior of an Expressway Driver in Fog Environment |
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| ZHANG Xu-guang,GAO Jian-ping,LIAO Li,BAJAJ D.Car Following Behavior of an Expressway Driver in Fog Environment[J].China Journal of Highway and Transport,2022,35(1):275-285. |
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| Authors: | ZHANG Xu-guang GAO Jian-ping LIAO Li BAJAJ D |
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| Affiliation: | 1. School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China;2. School of Transportation and Municipal Engineering, Chongqing Jianzhu College, Chongqing 400072, China |
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| Abstract: | Driving in foggy environments provides fewer visual references than that in normal weather, owing to low visibility; thus, drivers are more inclined to car following. To study the car following behavior of expressway drivers in foggy environments, a number of typical mountain expressways were selected as test road sections in a real fog test mode. Smart Eye trackers were used to obtain the visual parameters of the drivers, including the driver's gaze area, gaze angle, gaze duration, pupil diameter, saccade speed, and saccade amplitude. The normalization method was used to analyze the driver's gaze center of gravity; further, the driver's follow-up action under different visibilities was studied. Investigating the regular summary of the abovementioned visual parameters in the fog environment, it was found that the driver's saccade speed is low when the normal lane is maintained during a follow-up dynamic process, and the high when the lane is adjusted with high average saccade speed. The driver's gaze transfer speed under low visibility is 27.0 (°)·s-1, which is significantly lower than that under fine weather (52.0 (°)·s-1). Car following behavior was divided into active, semi-passive, and fully passive following:By analyzing the driver in foggy areas with low visibility driving conditions, the multi-dimensional preference theory and regret theory are introduced to construct the driver's car-following decision model, and the model is calibrated and verified based on the difference method. The research results suggest that the driver's visibility has a significant influence on the visual characteristics during the car-following process. The car-following model can provide theoretical support for the prediction of the distance and speed of the car before and after the car-following process in foggy environments. |
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| Keywords: | traffic engineering fog environment regret theory expressway following behavior multi-dimensional preference |
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