Sicheng Zhu

In recent years, frequent fire disasters have led to enormous damage in China. Effective firefighting rescues can minimize the losses caused by fires. During the rescue processes, the travel time of fire trucks can be severely affected by traffic conditions, changing the effective coverage of fire stations. However, it is still challenging to determine the effective coverage of fire stations considering dynamic traffic conditions. This paper addresses this issue by combining the traveling time calculation model with the effective coverage simulation model. In addition, it proposes a new index of total effective coverage area (TECA) based on the time-weighted average of the effective coverage area (ECA) to evaluate the urban fire services. It also selects China as the case study to validate the feasibility of the models, a fire station (FS-JX) in Changsha. FS-JX station and its surrounding 9,117 fire risk points are selected as the fire service supply and demand points, respectively. A total of 196 simulation scenarios throughout a consecutive week are analyzed. Eventually, 1,933,815 sets of valid sample data are obtained. The results showed that the TECA of FS-JX is 3.27 km², which is far below the standard requirement of 7.00 km² due to the traffic conditions. The visualization results showed that three rivers around FS-JX interrupt the continuity of its effective coverage. The proposed method can provide data support to optimize the locations of fire stations by accurately and dynamically determining the effective coverage of fire stations.

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.