Group cycling in urban environments: Analyzing visual attention and riding performance for enhanced road safety

被引:0
作者
Li, Meng [1 ,2 ]
Zhang, Yan [1 ,2 ]
Chen, Tao [1 ,2 ,3 ,4 ]
Du, Hao [5 ]
Deng, Kaifeng [1 ,2 ]
机构
[1] Tsinghua Univ, Sch Safety Sci, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Inst Publ Safety Res, Dept Engn Phys, Beijing 100084, Peoples R China
[3] Anhui Prov Key Lab Human Safety, Hefei 230601, Anhui, Peoples R China
[4] Beijing Key Lab Comprehens Emergency Response Sci, Beijing, Peoples R China
[5] Natl Univ Def Technol, Coll Elect Sci & Technol, Changsha 410073, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金; 国家重点研发计划;
关键词
Riding groups; Visual attention; Riding performance; Steering entropy; QUALITY BICYCLE PATHS; GAZE BEHAVIOR; MODEL;
D O I
10.1016/j.aap.2024.107804
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
China is a major cycling nation with nearly 400 million bicycles, significantly alleviating urban traffic congestion. However, safety concerns are prominent, with approximately 35% of cyclists forming groups with family, friends, or colleagues, exerting a significant impact on the traffic system. This study focuses on group cycling, employing urban cycling experiments, GPS trajectory tracking, and eye-tracking to analyze the visual search, and cycling control of both groups and individuals. Findings reveal that group cyclists tend to focus more on companions, leading to a dispersed gaze pattern compared to individual riders who focus more on the direct path and surroundings. Group riders also exhibit shorter fixation times on traffic signs, potentially indicating decreased attention to traffic regulations. Despite similar lateral position deviation, group cyclists exhibit higher steering entropy, indicating greater variability in their steering choices. Additionally, group riders demonstrate varied passing times, suggesting a collective advantage in navigating complex traffic conditions. This study enhances our understanding of bicycles within traffic dynamics, offering valuable insights for traffic management systems.
引用
收藏
页数:12
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