Efficiently detecting intrusions on a railway perimeter is crucial for ensuring the safety of railway transportation. With the development of computer vision, researchers have been actively exploring methods for detecting foreign object intrusion via image recognition technology. This article reviews the background and importance of detecting railway perimeter intrusion, summarizes the limitations of traditional detection methods, and emphasizes the potential of improving detection accuracy and efficiency in image recognition with deep learning models. Further, it introduces the development of deep learning in image recognition, focusing on the principles and progress of key technologies such as convolutional neural networks (CNNs) and vision transformers (ViTs). In addition, the application status of semantic segmentation and object detection algorithms based on deep learning in detecting railway perimeter intrusion is explored, including the classification, principles, and performance of the algorithms in practical applications. Finally, it highlights the primary challenges faced in railway perimeter intrusion detection and projects future research directions to resolve these challenges, including multisource data fusion, large-scale dataset construction, model compression, and end-to-end multitask learning networks. These studies support the accuracy and real-time detection of railway perimeter intrusion, and provide technical guarantees for railway transportation monitoring tasks.

The paper proposes an analytical framework for evaluating, in the case of interrupted conditions, the effect of bus bridging services on the degree of connectivity of rail networks. The average travel time is used to compare a normal network and an interrupted rail network. Different situations in interrupted rail network are compared with a normal network, namely, making passengers wait for troubleshooting, detouring them to other routes, and the bus bridging service strategy. The study uses ratios of average travel time under various situations to assess the connectivity of interrupted rail transit. The approach is applied to a case study based on the Beijing public transit system and actual travel data. It found that bus bridging is a relatively effective method of enhancing the connectivity of metro network and minimizing delays. In particular, key factors such as the behavior of affected passengers, the willingness to use bus bridging service, and transfer passenger, which influence connectivity of interrupted rail networks with bus bridging services, are provided.

This paper aims to clarify the current status, hotspots, historical evolution and development trend of the research on funding and management of basic research in China. Firstly, 736 relevant papers indexed during 1992-2019 in the core journal database of China National Knowledge Infrastructure (CNKI) were analyzed in details. Using the information visualization software CiteSpaceV5.6.R3, the institutional cooperation co-occurrence map, author cooperation co-occurrence map, keyword co-occurrence map, and keyword timeline view maps were plotted through content mining. The results show that: the research institutions in the research field of basic research funding and management have formed three core cooperation networks, and the institutions in Beijing attract the most attention; most of the prolific and active authors choose teamwork over independent research; the research topics mainly fall into four aspects of basic research: input, subjects, results, and talents; the research hotspots are in line with policies and demands, and evolve through three stages: exploration and gradual progress, adjustment and development, and expansion and acceleration. The research results open up a new direction for relevant studies, and provide a reference for innovative parties to implement basic research.

The special driving environment of highway extra-long tunnels causes high operational risks and difficult escape. The establishment of a sound emergency escape support system is essential for drivers to escape safely in risky accidents. Based on the factors such as the type and severity of tunnel operation risks, this paper studies and puts forward the level of extra-long tunnel operation risk management and the requirements for safe emergency escape of relevant personnel under different levels, and establishes and improves the composition of the extra-long tunnel emergency support system and the function, location and spacing of each facility in the subsystems. Considering the condition of extra-long tunnels, the research conclusions provide a scientific basis for emergency escape management and establishment technology, and proposes a safer support system for emergency escapes.