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Safety effect of tunnel environment self-explaining design based on situation awareness

2023; Elsevier BV; Volume: 143; Linguagem: Inglês

10.1016/j.tust.2023.105486

1878-4364

Ying Yan, Yu Zhang, Huazhi Yuan, Wan Li, Hongliang Ding,

Traffic and Road Safety

The aim of this study was to investigate the safety effect of environment self-explaining design from drivers' situation awareness. First, a situation awareness model was developed based on drivers' situation awareness status and the schema proposed in this study. Subsequently, simulation experiment environments were developed using 3D Max software. A total of 30 driver volunteers were recruited to perform driving simulation experiments under different tunnel environment self-explaining design scenes. Notably, the information on drivers' eye movement and driving behaviors was collected using eye trackers and a driving simulator. Last, the situation awareness level of drivers was estimated utilizing the situation awareness model. The results indicated that drivers' situation awareness varied with tunnel environment self-explaining design scenes. The visual illusion marking colored pavement and light-colored decorated sidewall in tunnels provided greater self-explaining performance and significantly enhanced driver cognition of the driving environment. Moreover, the optimal outcomes were achieved, including the scheme of inclined slope pattern, longitudinal marking colored pavement, and blue-white decorated sidewall in tunnels. As revealed by the findings of this study, tunnel environment self-explaining design takes on a critical significance in improving tunnel driving environment and safety.