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Vehicles often face congestion at airport curbsides because private vehicles, taxis, and ride-hailing vehicles compete for limited space while dropping off passengers. This competition may lead to blockages and long dwell times, thus worsening the congestion. To solve this issue, management strategies such as first-in-first-out queuing or fines for excessive dwell times have been suggested. However, there is a lack of reliable video data and analysis of drop-off behavior at airport curbsides. In this study, we empirically analyzed the key characteristics of passenger drop-off behavior at the Airport T2 terminal in Guangxi Province, China, which handles approximately 18 million passengers per year. First, we extracted the relevant features of both passengers and vehicles by deep learning algorithm, such as the direction of passenger movement, vehicle type, vehicle location, trunk state, and passenger drop-off time. Subsequently, we constructed new features, such as driver behavior and passenger behavioral complexity, based on the original features. We used least-squares regression and logistic regression to analyze the data. Our analysis reveals that the drop-off time of passengers primarily depends on the complexity of their behavior during the drop-off process. Additionally, we observed that specific features, such as driver behavior and vehicle type, could be employed to estimate passenger drop-off behavior. These findings have practical implications in providing valuable insights into the design and management of airport curbside areas and future strategies for connected vehicles.

For the engineering structure in case of fire, a fire hydrant is generally used for extinguishing the fire. This paper presents an experimental investigation on interfacial bond behavior of high-strength concrete-filled steel tube (HSCFST) after exposure to elevated temperatures and cooled by fire hydrant using the pull-out test of 22 specimens. According to the experimental study, the failure mechanism of HSCFST exposed to elevated temperatures and water-cooling (ETWC) was revealed, the influence of various parameters on the bond behavior was analyzed, and the calculation formula of the bond strength of HSCFST subjected to ETWC was put forward. The results show that the load-slip curves of the loading end and the free end of the specimen are basically similar, and can be divided into three types of typical curves. In the push out test, the strain on the outer surface of the steel tube is exponentially distributed with its distance from the loading end. After ETWC exposure, the bond strength of the specimen is less affected by the concrete strength, which is inversely proportional to the anchorage length, and it is basically stable after the constant temperature duration is longer than 60 min. With the increase of the maximum temperature, the ultimate bond strength increases first, then decreases and then increases, and the residual bond strength increases first and then decreases. Besides, the study indicate that cooling method has significant influence on the bond behavior, compared with natural cooling specimens, the ultimate bond strength, residual bond strength, and shear bond stiffness of water-cooling specimens are smaller, and the interfacial energy dissipation capacity is larger. [ABSTRACT FROM AUTHOR]