Research on Enhanced Situation Awareness Model with DMI Visualization Cues for High-Speed Train Driving

被引:2
|
作者
Wang, Aobo [1 ]
Guo, Beiyuan [1 ]
Yi, Ziwang [1 ]
Fang, Weining [1 ]
机构
[1] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
High-speed train driving; SA enhancement; Human in the loop; Interface design; Adaptive automation; PERFORMANCE; DRIVER; AUTOMATION; RAILWAY; WORKLOAD; OPTIMIZATION; SYSTEMS; IMPACT; FUTURE; SAFETY;
D O I
10.1080/10447318.2023.2247613
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
With the rapid increase of high-speed train driving automation, the human-computer interaction of high-speed train driving is changing. It is a major dilemma to maintain a well-interactive process between the driver and the driving system for the intelligent train operation. Nevertheless, the enhancement of the driver's situation awareness (SA) is an effective way to promote the process of driver-driving system interaction. To achieve this purpose, we proposed an enhanced SA model based on the perceptual cycle model (PCM). The model helps to identify the high-speed train DMI interface elements that affect the different SA level of drivers and provides theoretical support for describing the SA change pattern of driving tasks. We proposed a new display mode (ESA mode) for enhancing driver SA according to this model, and conducted driving simulator experiments to explore the differences of SA change patterns between the ESA mode and the normal mode (NSA mode) for 16 subjects. The experimental results showed that the ESA mode successfully overcame the subjects' SA recession in the NSA mode. The interaction with enhanced SA can help the driver remain vigilant and further improve the general driving performance during monotonous process of automated high-speed train driving.
引用
收藏
页码:6185 / 6199
页数:15
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