Weijun Liu

Timely and efficient evacuation is crucial for tunnel fire safety. Previous studies often assumed fixed vehicle spacing and vehicle type ratios, which did not reflect real traffic conditions. Based on high-resolution satellite imagery of congested scenarios nationwide, 1703 sets of static vehicle spacing data were obtained. Descriptive statistical analysis and the K–S test were conducted. As a result, a log-normal distribution model of vehicle spacing was established, with an average spacing of 2.23 m, a logarithmic mean of 0.707, and a logarithmic standard deviation of 0.439. Analysis of 11,211 vehicle samples further revealed an uneven distribution of vehicle types across lanes. Based on the statistical data, a random vehicle arrangement algorithm was developed for highway tunnels, incorporating the log-normal characteristics of vehicle spacing. Using this algorithm, non-uniform vehicle layouts were generated for tunnel evacuation modeling. A total of 120 simulations across 12 different scenarios were then conducted to analyze the impact of log-normal vehicle spacing on evacuation time. Results showed that evacuation time was 2–5% longer under a log-normal distribution than under a uniform distribution. Therefore, future tunnel evacuation simulations should account for the log-normal distribution of vehicle spacing and the actual vehicle type ratio.

Traditional cognitive practices in the Engineering Management Major (EMM) are often constrained by safety risks, high costs, and geographical limitations. This study proposes a novel Virtual Cognitive Practice (VCP) mode that integrates ubiquitous learning (U-learning) with web-based panoramic maps to overcome these challenges. We developed a VCP system leveraging panoramic data of roads, bridges, and tunnels from commercial web mapping platforms to provide high-fidelity, interactive observation environments. To evaluate its effectiveness, 147 undergraduate students participated in a virtual practice course and subsequently completed a structured questionnaire. The results demonstrate that the accuracy on objective knowledge tests exceeded 80%, alongside a high mean score of 4.27/5 for visualization satisfaction. Statistical analysis using Chi-square tests indicates that students with prior on-site experience are significantly more confident in the VCP mode’s potential as a pedagogical alternative. This research bridges the technical gap in EMM practical education by providing a flexible, ubiquitous learning ecosystem.

The effective delineation of fire station response zones is critical for urban public safety planning, yet traditional methods often fail to account for dynamic traffic conditions, leading to suboptimal resource allocation. This study proposes a novel block-unit-based method that incorporates real-time traffic data to delineate fire station response zones, improving the scientificity of response time estimation. The method was validated using data from Daxiang District, China, a typical urban–rural mixed region, encompassing 2230 block units, 4 fire stations, and 13,097 demand points. Analysis of 1,225,047 data samples revealed an average travel time of 960.7 s, highlighting significant accessibility challenges. The re-delineated response zones cover areas ranging from 1.07 to 156.24 km², with significant variations. It is attributed to the concentration of fire stations in urban areas, insufficient coverage of vast rural regions, and the proximity of one station to a river and regional boundary. These findings underscore the spatial inequities in fire service provision and the need for a more balanced resource allocation strategy. Recommendations include establishing rural fire stations, improving urban traffic conditions, and relocating certain fire stations. This approach can enhance regional accessibility and provides a scientific basis for fire service planning.

The authors would like to make the following corrections in the published paper [1]: (1)Add the Institutional Review Board Statement:Ethical review and approval were waived for this study by Changsha University of Science and Technology as this research falls under social science research conducted through anonymous surveys/interviews

In the context of global sustainable development strategies and the rise of intelligent construction, it has become increasingly urgent for universities to adapt construction management curricula to meet the demands of this new era. However, prior education-reform-based studies rarely offer a systematic, educator-centered prioritization of knowledge areas, limiting actionable guidance for course sequencing and credit-hour allocation. To address this gap, this study identifies eight essential knowledge categories for construction management education through a comprehensive literature review and a survey of faculty members with strong theoretical and practical experience. An improved Analytic Hierarchy Process (AHP) model, weighted by the Consistency Ratio (CR), is applied to prioritize these areas. Results show that Fundamentals of Construction (18.50%), BIM (18.08%), and AI and Big Data (17.07%) received the highest importance values. These findings emphasize the need for curriculum reorientation to align with intelligent construction. This study contributes to modernizing construction management education and offers practical insights for curriculum development, ensuring alignment with industry trends and technological advancements.

Governments often plan multiple fire stations simultaneously to improve firefighting capabilities, but constructing them within limited resources and time remains a challenge. A spatial decision support model is proposed in this study to determine the prioritized construction sequence of urban fire stations. Two simulation environments were established: one with only existing fire stations and another with both existing and proposed stations as fire service supply points (FSSPs). Response times were simulated using real-time traffic data. The construction urgency of the proposed fire stations was assessed using the construction sequence scoring equation. To validate the model, a case study of Shaoyang City, China, was conducted. A total of 30,968 fire service demand points were gathered, with 20 existing fire stations and 13 proposed fire stations designated as FSSPs. Twenty-five evaluation scenarios were established, resulting in 1,297,025 valid simulation results. The scoring results revealed a maximum score of 119,320, a minimum of 23,420, and an average of 61,412. Based on these results, recommendations for the construction sequence of proposed fire stations in Shaoyang City were made, and the improvements in fire protection levels were calculated. By prioritizing the construction of higher-performance fire stations, this model maximizes resource efficiency and enhances public safety.

Over recent decades, the number of high-rise building fires has increased rapidly with urbanization. However, few studies have been conducted from the perspective of fire safety awareness among residents in high-rise buildings. This study investigated the fire safety literacy of people in high-rise buildings. High-rise buildings are an important part of the urban environment, and fires can cause environmental pollution. In this work, online and on-site questionnaire surveys were combined to investigate residents’ evacuation preparation, firefighting skills, and knowledge about firefighting equipment. A total of 3000 questionnaires were collected, of which 2026 were validated. The survey results showed that 27.79% of residents were unaware of the location of evacuation staircases, 55.43% were not aware of the location of refuge floors in super high-rise buildings, and 41.20% were not aware that fire doors should be in a normally closed state. The main findings of this investigation indicate that the fire safety knowledge of residents in high-rise buildings is gravely deficient. Therefore, it is recommended that fire safety awareness campaigns be enhanced in both school education and community activities, and residents in high-rise buildings should be organized to participate in regular fire drills.

In recent years, the number of underwater road tunnels in Chinese cities has increased. However, the current situation of personal fire safety literacy as it pertains to these tunnels remains unclear. To address this gap, a questionnaire survey was conducted to investigate people’s awareness of escape slides, evacuation signs, and the correct evacuation paths for fire escape. A total of 1049 respondents in Changsha, China, were surveyed, with 791 valid questionnaires collected and analyzed. The findings revealed that a significant proportion of respondents (81.80%) were unaware of the presence of escape slides in underwater road tunnels, while 87.86% could not recognize them and 93.05% could not use them. Only 42.04% of respondents could identify evacuation signs in underwater road tunnels. In the event of a fire, just half of the respondents could select the appropriate escape or evacuation path. Additionally, demographic differences among respondents also influenced their level of fire safety literacy. Based on these findings, it is recommended that the government and relevant organizations should enhance the dissemination of knowledge regarding escape slides and evacuation signs in underwater road tunnels.

The number of tunnel fire accidents has increased with the scale of expressway tunnel construction and traffic flow. Due to the severity of tunnel fires, improving tunnel fire safety and reducing fire accident hazards has become a societal concern. It is essential to explore and evaluate tunnel fire safety literacy among the population. In this study, an online and on-site questionnaire survey was conducted in Hunan Province, China. A total of 1990 questionnaires were collected, of which 1573 were valid. Overall statistical analysis, descriptive statistics, and correlation analysis were performed on valid questionnaires. The results show that the overall level score rate of awareness of drivers and passengers regarding tunnel fire safety was only 0.43. In total, 58.42% of people were unaware of the pedestrian cross passages in expressway tunnels, and 68.40% were unable to recognize them. Similarly, 46.47% of people were unable to recognize evacuation signs in expressway tunnels. In addition, 39.29% of people chose the wrong evacuation behavior. The percentage of people who were aware of the correct usage of firefighting facilities in expressway tunnels was below 50.00%. Correlation analysis results show that tunnel users’ demographic characteristics significantly affected their cognition of expressway tunnel escape methods. This study shows that tunnel users’ emergency escape knowledge regarding tunnels is relatively low. Corresponding countermeasures were proposed to guide policy decisions for enhancing tunnel fire safety.