Investigating rear-end collision avoidance behavior under varied foggy weather conditions: A study using advanced driving simulator and survival analysis

被引：0
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作者：
Shangguan, Qiangqiang [1 ,2 ]
Fu, Ting [1 ,2 ]
Liu, Shuo [1 ,2 ]
机构：
[1] The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai,201804, China
[2] College of Transportation Engineering, Tongji University, 4800 Cao'an Highway, Shanghai,201804, China
来源：
Accident Analysis and Prevention | 2020年 / 139卷
关键词：
Previous studies have focused on the impact of visibility level on drivers’ behavior and their safety in foggy weather. However; other important environmental factors such as road alignment have not been considered. This paper aims to propose a methodology in investigating rear-end collision avoidance behavior under varied foggy conditions; with focusing on changes in visibility and road alignment in this study. A driving simulator experiment with a mixed 2 × 4 × 6 factor design was conducted using an advanced high-fidelity driving simulator. The design matrix includes two safety-critical conditions; four visibility conditions; and six road alignment situations (in terms of the road curve and slope). Behavior variables from different dimensions were identified and compared under varied conditions. To estimate the safety of drivers; a time-based measurement; speed reduction time; is selected among the variables as a measure of safety. The survival analysis approach was introduced to model the relationship between environmental factors and driver safety; using speed reduction time as the survival time. Both the Kaplan-Meier method and the COX model were applied and compared. Results generally suggest that reduced visibility leads to more dangerous rear-end collision avoidance behavior from different aspects. Though findings are mixed regarding the road alignment; the impact of the road alignment was found to be significant. Interestingly; conditions of downward slope were found to be safer. Overall; the COX model outperformed the Kaplan-Meier method in understanding the impact of environmental factors; and it can be applied to investigate other contributing factors for freeway safety under foggy weather conditions. © 2020 Elsevier Ltd;
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