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Due to safety issues when passengers get on and off the subway and spend a lot of time on the subway, this makes subway station signs very important. Moreover, in case of fire and other dangerous situations and emergency evacuation, the guiding signs must be able to guide passengers to leave the station and dangerous areas efficiently and orderly,...
Citations
... This encompasses aspects including sign location, color, graphics, flashing frequency, etc. Furthermore, they have examined attention distribution at different types of intersection, changes in heart rate and skin conductivity [37], as well as significant changes in electroencephalographic signals [38]. Their findings can serve as a foundation for the design of exit signage in complex structures. ...
... In our study, most participants noticed the guidance signs for emergency shelters, but we also observed that 17% of participants struggled to understand the content of these guidance signs due to poor alignment between the sign direction and complex intersections. Numerous studies have investigated the effective distance, direction compliance, design, location, and content of directing signs in buildings [28,33,[35][36][37][38][39]. Our findings are consistent with previous research, which emphasizes the significant impact of the angle of interaction and arrow direction on the evacuees' confidence level. ...
A fast evacuation from buildings to emergency shelters is necessary and important after the occurrence of a disaster. We investigated the variations in physical behaviors and cognition processes while finding emergency shelter. The on-site emergency-shelter-finding experiments were conducted in Beijing, China. Participants performed the task by using a wearable eye-tracking device. We aimed to assess three eye metrics: fixation counts, mean fixation duration, and visual attention index, to perform cognitive searching analysis for the environmental elements. The results showed that most people spend more fixation time on digital maps (297.77 ± 195.90 ms) and road conditions (239.43 ± 114.91 ms) than signs (150.90 ± 81.70 ms), buildings (153.44 ± 41.15 ms), and plants (170.11 ± 47.60 ms). Furthermore, most participants exhibit hesitation and retracing behaviors throughout the wayfinding process. The participants with relatively rich disaster experience and a proactive personality exhibit better performance in the shelter-finding task, such as a shorter retracing distance (p = 0.007) and nearer destination (p = 0.037). Eye metrics, together with the questionnaire, can mirror the complexity and heterogeneity of evacuation behavior during emergency shelter-finding. In addition, this also provides insights for the optimization of guidance sign systems and improvements in emergency management.
... The evacuation guidance methods commonly used in subway stations can be divided into substance guidance [9] and human guidance [10] . Substance guidance is to lead passengers to evacuate by the aid of fixed signage [11] . Human guidance is to guide the evacuation direction or lead passengers to evacuate directly. ...
... where a c represents the adjustment coefficient between labor cost investment and different safety needs. The balance degree of passenger quantity led by each guide y 4 is given by Eq. (11) . The smaller the difference in the number of guided passengers per guide, the smaller the y 4 value. ...
The reasonable setting of guides can directly improve the evacuation capacity in the subway station. The important role of guide assignment scheme and evacuation path planning of guided passengers is particularly prominent. Considering the distribution of passengers in the station, one contribution is that an assignment scheme of the initial number and location of guides is firstly established based on Gaussian mixture model and cost function method, so as to increase the guidance range and reduce the waste of human resources. Another contribution is that a multi-objective optimization model is developed for guide path planning and NSGA-II method is used to find the optimal solution, which could help avoiding the evacuation bottlenecks in advance. Massmotion embedded with social force model and minimum cost model is adopted to simulate the movement of people, which is verified by the independent sample t-test in this paper. Evacuation experiments under the random distribution of passengers are carried out to demonstrate the significance of the proposed guidance method. The results indicate that the total evacuation efficiency can be improved by about 13% in the scenario with guides, and the passengers’ choice of stairs/escalators is more balanced. Moreover, passengers induced by different guides can avoid reaching the same evacuation node at the same time window, which alleviates the pressure of nodes. The results could provide theoretical support for passenger safety management and even improve the service level of stations.
... The system is mainly used to solve these problems: location problems, condition problems, model problems, simulation problems, and forecast changes [18,19]. The realization of GIS technology is based on data collection technology, communication technology, software technology, information security technology, virtual reality technology, etc. GIS technology can not only effectively manage various resource and environmental information with spatial attributes, conduct rapid and repeated analysis and testing of resource and environmental management and practice models, facilitate decision-making, and conduct scientific and policy standard evaluations but also can effectively dynamic monitoring, analysis, and comparison of resource and environmental conditions, and changes in production activities during the period, data collection, spatial analysis, and decisionmaking processes can also be integrated into a common information flow, which can significantly improve work efficiency and economic benefits and provide technical support to ensure sustainable development [20,21]. ...
In recent years, with the continuous expansion and development of cities, urban population has become more and more dense. At present, there are few researches on community emergency evacuation management system in China. Therefore, the establishment of community emergency evacuation management system based on mobile big data can not only meet the efficient, fast, smooth, and orderly evacuation and settlement needs of the masses but also minimize emergencies. All kinds of losses and influences caused by accidents have very important practical significance. In this paper, an emergency evacuation management system is developed and designed on smart community platform based on mobile big data technology. In the process of development, it is found that the service integration method of mobile big data and application model is the best combination of this system. The construction process of community emergency evacuation management system framework is introduced in detail. Through the research and design of the system, and then test and analysis of the experiment, the sixth grade teachers and students of a primary school group experiment, there are 50 people in each group. The experimental group is familiar with the system operation in advance, and the knowledge of emergency evacuation management is previewed in advance. It is concluded that the class with emergency evacuation management system has much faster response time and decision-making time to emergencies than the class without emergency evacuation management system, and the injury situation of the class is much better. The study shows that the emergency evacuation management system plays an important role in dealing with emergencies, improving the escape rate and reducing the number of injured. I believe it will be further promoted in the future.
... Lou [5] uses the Gaussian mixture model of machine vision to build the mapping relationship between the observed variables of the object and the robot joint variables. Huang and Cao [6] was to analyze the decision response of subway evacuation signs using the characteristics of the brain components. Huang et al. [7] propose the application of research of FFR based on deep learning in the diagnosis of coronary heart disease complicated with diabetes mellitus. ...
