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MODERN TUNNELLING TECHNOLOGY 2024, Vol. 61 Issue (4) :14-27    DOI:
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Information Perception Mechanism and Evaluation Method of Highway Tunnel Lighting Environment
(1. School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074; 2. State Key Laboratory of Mountain Bridge and Tunnel Engineering, Chongqing Jiaotong University, Chongqing 400074; 3. Chengdu Xinzhu Jiaotong Technology Co., Ltd.,Chengdu 611430; 4. College Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074)
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Abstract Current tunnel lighting standards are primarily based on physical evaluation indicators such as luminance in photopic vision, which do not fully consider the actual spatiotemporal variations of the dynamic visual environment during driving in tunnel, and also do not adequately reflect the psychological and physiological perceptions as well as the behavioral responses of drivers. In light of this, a systematic study on tunnel lighting environment and information perception is conducted to reveal the variation trends and relationships between physical information and physiological perception. Consequently, a series of tunnel lighting environment evaluation methods based on information perception are proposed, and validated through extensive static and dynamic information perception tests.The results show that the tunnel lighting environment consists of material information, which is represented by physical quantity information. As a human-vehicle-road coupling environment, information perception involves both the physical quantity information of the tunnel lighting environment and the psychological and physiological responses of humans, i.e., biological perception. By comprehensively analyzing the relationship between physical quantity in? formation and biological perception, the mechanism of information perception is formed, and evaluation methods based on information perception are established. These methods can provide theoretical basis and reference indicators for the design and improvement of tunnel lighting environments.
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KeywordsTunnel lighting environment   Physical quantity information   Biological quantity information   Information perception mechanism   Evaluation method     
Abstract: Current tunnel lighting standards are primarily based on physical evaluation indicators such as luminance in photopic vision, which do not fully consider the actual spatiotemporal variations of the dynamic visual environment during driving in tunnel, and also do not adequately reflect the psychological and physiological perceptions as well as the behavioral responses of drivers. In light of this, a systematic study on tunnel lighting environment and information perception is conducted to reveal the variation trends and relationships between physical information and physiological perception. Consequently, a series of tunnel lighting environment evaluation methods based on information perception are proposed, and validated through extensive static and dynamic information perception tests.The results show that the tunnel lighting environment consists of material information, which is represented by physical quantity information. As a human-vehicle-road coupling environment, information perception involves both the physical quantity information of the tunnel lighting environment and the psychological and physiological responses of humans, i.e., biological perception. By comprehensively analyzing the relationship between physical quantity in? formation and biological perception, the mechanism of information perception is formed, and evaluation methods based on information perception are established. These methods can provide theoretical basis and reference indicators for the design and improvement of tunnel lighting environments.
KeywordsTunnel lighting environment,   Physical quantity information,   Biological quantity information,   Information perception mechanism,   Evaluation method     
Cite this article:   
.Information Perception Mechanism and Evaluation Method of Highway Tunnel Lighting Environment[J]  MODERN TUNNELLING TECHNOLOGY, 2024,V61(4): 14-27
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