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Journal Title: Modern Transportation and Metallurgical Materials
Established: July 2021
Governing Authority: Jiangsu Association for Science and Technology
Sponsors: Jiangsu Provincial Comprehensive Transportation Society
Jiangsu Provincial Society for Metals
Publication Frequency: Bimonthly
Tel: 025-58783287
Email: xdjtyyjcl@163.com
CN 32-1895/TF
ISSN 2097-017X
Analysis of evacuation efficiency in urban rail stations considering heterogeneous behavior of partnered passengers
DUAN Liwei;XIA Yi;This study focuses on the optimization of emergency evacuation efficiency in rail transit stations, with an emphasis on exploring the influence of heterogeneous behaviors of partnered passengers on the evacuation process. Based on the theory of social force model, AnyLogic simulation platform is used to construct the evacuation model of a typical urban rail station in Chongqing, and the influence of the partnering ratio and the waiting and turning back behaviors of the partnering pedestrians on the evacuation efficiency is systematically analyzed through the control variable method. It is found that the proportion of companionship is significantly negatively correlated with the evacuation efficiency, and the evacuation time is prolonged by 27.5% under the proportion of 50% companionship. The influence of companion pedestrians' waiting behavior grows significantly with the expansion of evacuation scale. Different spatial locations of the folding back behavior produces differentiated flow conflicts, in which the gate area is narrowed due to the narrow channel, resulting in the reduction of the evacuation efficiency by 37.4%. Targeted recommendations are made based on the station's emergency evacuation plan and facility layout.
Research on identifying port service areas using truck GPS data
YANG Hao;FENG Xuejun;XIAO Fu;HUANG Guangyu;JIANG Liupeng;To accurately delineate the road-based collection and distribution areas within port clusters, a data-driven method is developed using GPS trajectory data from collection and distribution trucks, thereby supporting decision-making for competition and cooperation strategies among ports. After preprocessing large-scale GPS data from collection and distribution trucks and extracting origin –destination(OD) pairs, core logistics nodes are identified through the DBSCAN(Density-Based Spatial Clustering of Applications with Noise)spatial clustering algorithm. Subsequently, OD-based port choice probabilities are determined based on the transport frequency between nodes and ports. Delaunay triangulation is employed to precisely delineate the port service areas under the road transport mode. A case analysis of the Fuzhou – Xiamen – Quanzhou port cluster reveals heterogeneous spatial structures, characterized by overlapping hinterlands and "island" service zones. The most intense competition occurs in inland regions, while overlaps are concentrated at the peripheral boundaries of each port's service area.
A review of research and development in intelligent construction for transportation
CHEN Yao;LI Shaorong;HUANG Rencai;Intelligent construction technology, through the in-depth integration of the internet of things, big data, artificial intelligence, digital twin, and robotics with advanced construction technologies, is systematically revolutionizing the full-life-cycle management model of transportation infrastructure. This paper systematically analyzes its core role in improving construction efficiency, reducing costs, enhancing safety, and optimizing resource allocation, and reveals its application value in the entire process of planning and design, construction, and operation and maintenance. The research points out that the current technology integration faces challenges such as insufficient compatibility of heterogeneous systems, pressure on data security protection, and limitations in the interpretability of artificial intelligence algorithms. Moreover, the collaboration between industrialized construction technologies and intelligent technologies still needs to be deepened. Based on the analysis of domestic and foreign cases, such as the automated production of shield tunnel segments in the Yangtze River Delta, preliminary directions for building a standardized technology integration framework are proposed, including the integration of Service-Oriented Architecture(SOA) with digital twin technology, and the construction of a full-life-cycle data governance system. It also emphasizes the need to address the issue of technology fragmentation through cross-domain collaboration. The research results provide theoretical support and practical path references for the intelligent upgrading of transportation infrastructure.
Research on safety evaluation method of high-speed rail interval structure based on weighted Bayesian network
CHEN Bailin;ZHAO Kai;This paper focuses on the study of interval tunnel structures and track structures by analyzing their structural characteristics and selecting monitoring indicators. This paper also proposes a health monitoring system architecture for high-speed rail interval structures featuring digital and model interaction and virtual-real mapping of models and entities in response to the current demand for digital and intelligent health monitoring of transportation infrastructure. Based on the structural characteristics and monitoring indicators, the safety assessment indicators for the structures are selected. To better reflect the actual state of the structures, the actual operational environment factors of the structures in the assessment indicators are included, improving the existing assessment indicator system. A multi-state Bayesian network safety assessment model for high-speed rail interval structures is established. On the basis of inheriting the existing model framework, a dynamic weight model is used to assign weights to each node of the network, solve the weighted conditional probability table, and then infer the predicted risk level. At the same time, the fuzzy analytic hierarchy process is used to assess the risk of operational high-speed rail interval structures, and the scientificity, feasibility, and correctness of the weighted Bayesian network are verified through comparison.
Optimal selection model for bridge reinforcement methods in oversize transport based on DEA-TOPSIS combined weighting method
QIU Linze;GAO Zhaodong;SONG Weiwei;LI Yongyi;With increasing heavy-haul transportation demands in China's mega-projects, bridge safety risks due to insufficient load capacity require urgent solutions. This study develops a DEA-TOPSIS in‑tegrated model to optimize bridge safety evaluation and reinforcement for oversized vehicles. A fuzzybased evaluation system including safety, technical reliability, timeline, economy, and environmental impact is established with AHP-entropy combined weighting. DEA initially screens efficient schemes, followed by TOPSIS-based optimization. Validated through finite element analysis of a Jiangsu ex‑pressway bridge, the method effectively enhances the load-bearing capacity post-reinforcement, dem‑onstrating practical engineering value.
