Biblio

Train operation is highly influenced by the rail track state and the surrounding environment. An abnormal obstacle on the rail track will pose a severe threat to the safe operation of urban rail transit. The existing general obstacle detection approaches do not consider the specific urban rail environment and requirements. In this paper, we propose an edge intelligence (EI)-based obstacle intrusion detection system to detect accurate obstacle intrusion in real-time. A two-stage lightweight deep learning model is designed to detect obstacle intrusion and obtain the distance from the train to the obstacle. Edge computing (EC) and 5G are used to conduct the detection model and improve the real-time detection performance. A multi-agent reinforcement learning-based offloading and service migration model is formulated to optimize the edge computing resource. Experimental results show that the two-stage intrusion detection model with the reinforcement learning (RL)-based edge resource optimization model can achieve higher detection accuracy and real-time performance compared to traditional methods.

In order to effectively assess the security risks in multimodal transport networks, a security risk assessment method based on WBS-RBS and Pythagorean Fuzzy Weighted Average (PFWA) operator is proposed. The risk matrix 0-1 assignment of WBS-RBS is replaced by the Pythagorean Fuzzy Number (PFLN) scored by experts. The security risk ranking values of multimodal transport network are calculated from two processes of whole-stage and phased, respectively, and the security risk assessment results are obtained. Finally, an example of railway-highway-waterway intermodal transportation process of automobile parts is given to verify the validity of the method, the results show that the railway transportation is more stable than the waterway transportation, and the highway transportation has the greatest security risk, and for different security risk factors, personnel risk has the greatest impact. The risk of goods will change with the change of the attributes of goods, and the security risk of storage facilities is the smallest.