System Dynamics Approach for Modelling the Variation of Organizational Factors for Risk Control in Automatic Metro

The automatic metro inspires a new way of thinking about the development of urban transportation systems, specifically how the overall system completes the automatic functions. The insights into the potential correlation between safety and system variation are crucial for safe and effective operation management in the automatic metro. Thus, this paper propose a system dynamics (SD)-based model to construct the operational feedback mechanisms of the automatic metro through investigation, interview, and empirical analysis of the Beijing and Shanghai metro systems, covering the aspects of organization resource assignment, organizational experience and avoidance of driver error. From the model, the variation trend of the dynamic processes can be used to analyze the key elements or variables over time. Three key factors (the safety policy, delay time for organizational experience, and resource assignment coefficient), are identified to evaluate the crucial linkage between safety and variation over time. The changing trend of system risk influenced by the combination of these three factors is further analyzed to demonstrate how the functionalities of organization should be synchronized with the transformation of different grades of automation. The paper specifies an explicit framework that recognizes the relationships among the automation degree, organization policy and system risk at the macro level and comprehensively reveals the adaptation process of organization corresponding to the revolution process of the automation degree of the metro.

• Record URL:
  https://doi.org/10.1016/j.ssci.2017.01.002
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0925753517300024
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09257535
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhao, Bobo
  • Tang, Tao
  • Ning, B
• Publication Date: 2017-4

Language

• English

Media Info

• Media Type: Print
• Features: References;
• Pagination: pp 128-142
• Serial:
  • Safety Science
  • Volume: 94
  • Publisher: Elsevier
  • ISSN: 0925-7535
  • Serial URL: http://www.sciencedirect.com/science/journal/09257535

Subject/Index Terms

• TRT Terms: Automated vehicle control; Public transit; Risk assessment; Subways; Vehicle dynamics
• Geographic Terms: Beijing (China); Shanghai (China)
• Subject Areas: Operations and Traffic Management; Public Transportation; Safety and Human Factors;

Filing Info

• Accession Number: 01632356
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 18 2017 11:53AM