Xinhao Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Xinhao Liu has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Haowen Tao
School of Civil Engineering, Central South University (CSU), Changsha 410075, China
1 shared publication - Lixiang Zhou
Department of Fire Protection Engineering, Southwest Jiaotong University, Chengdu 611756, China
1 shared publication - Min Yu
China Railway Liu Yuan Group Co., Ltd., Tianjin 300308, China
1 shared publication - Qixiang Yan
State Key Laboratory of Intelligent Geotechnics and Tunnelling, Southwest Jiaotong University, Chengdu, China
1 shared publication - Tao Deng
Institute of Smart City and Intelligent Transportation, Southwest Jiaotong University, Chengdu 611756, China
1 shared publication - Wenqi Gong
Department of Fire Protection Engineering, Southwest Jiaotong University, Chengdu 611756, China
1 shared publication
Latest Publications
- Open Access
Experimental Investigation on the Personnel Recognition Time of Dynamic Evacuation Signage Under Low Visibility
Due to the confined geometry of buildings, restricted smoke extraction leads to rapid accumulation and a sharp decline in visibility, severely impeding evacuation and rescue operations. Evacuation signage can help people quickly find the evacuation routes and achieve rapid evacuation in buildings. However, people’s recognition of the evacuation signage would be affected by the environmental visibility. But how the recognition time of evacuation signs changes under low visibility has not been studied in detail by any scholars yet. A experimental platform was developed to investigate the effects of smoke color, visibility, signage luminance, and flashing modes on recognition time under various smoke conditions. Analysis reveals that as visibility diminishes, the mean recognition time for dynamic evacuation signs increases significantly. At visibilities below 10 m, a luminance of 300 cd/m2 is insufficient for rapid discernment of evacuation directions. However, under the low-visibility conditions in this study, when the luminance of the signage reaches a certain level, further increases in luminance did not significantly affect participants’ recognition time. The integration of the guidance strips significantly reduces mean recognition time and enhances accuracy as the strip luminance increases. Notably, under black smoke conditions, strip luminance exerts a more pronounced impact on recognition time. Furthermore, at a constant signage luminance, the flashing mode of guidance strips also effectively reduces recognition time. This study provides an experimental basis for optimizing the visual design and operating parameters of dynamic evacuation signage under low-visibility conditions, thereby supporting more effective evacuation guidance in fire emergencies.
Open AccessExperimental Investigation on the Personnel Recognition Time of Dynamic Evacuation Signage Under Low Visibility
Due to the confined geometry of buildings, restricted smoke extraction leads to rapid accumulation and a sharp decline in visibility, severely impeding evacuation and rescue operations. Evacuation signage can help people quickly find the evacuation routes and achieve rapid evacuation in buildings. However, people’s recognition of the evacuation signage would be affected by the environmental visibility. But how the recognition time of evacuation signs changes under low visibility has not been studied in detail by any scholars yet. A experimental platform was developed to investigate the effects of smoke color, visibility, signage luminance, and flashing modes on recognition time under various smoke conditions. Analysis reveals that as visibility diminishes, the mean recognition time for dynamic evacuation signs increases significantly. At visibilities below 10 m, a luminance of 300 cd/m2 is insufficient for rapid discernment of evacuation directions. However, under the low-visibility conditions in this study, when the luminance of the signage reaches a certain level, further increases in luminance did not significantly affect participants’ recognition time. The integration of the guidance strips significantly reduces mean recognition time and enhances accuracy as the strip luminance increases. Notably, under black smoke conditions, strip luminance exerts a more pronounced impact on recognition time. Furthermore, at a constant signage luminance, the flashing mode of guidance strips also effectively reduces recognition time. This study provides an experimental basis for optimizing the visual design and operating parameters of dynamic evacuation signage under low-visibility conditions, thereby supporting more effective evacuation guidance in fire emergencies.