Abstract
Although train control system (TCS) is regarded relatively safe, accidents still happened from time to time. In this paper, we propose a simulation based approach to elicit new requirements from accidents and then modify the TCS to provide a more reliable and safer system. A Modelica system model is constructed to describe the structure and interactions of TCS according to the continuous behavior and discrete fault event of TCS devices. A Modelica accident model is also defined based on the system model in order to predict accidents. These Modelica models are simulated in Open Modelica until all scenarios (paths) are covered. By analyzing the simulation results which indicate the causes of accidents, we elicit new requirements, and modify the original system model. Simulation is used again to show that these modifications could effectively avoid such accidents. A case study is provided to validate our approach.
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This paper is partially supported by the projects funded by the NSFC No. 61472140, 61572195 and, NSFC Key Project 61332008, and SHEITC160306.
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Zhong, W., Wang, Y., Chen, X. (2018). New Requirements Elicited from Accidents of Train Control System Simulated by Modelica. In: Kamalrudin, M., Ahmad, S., Ikram, N. (eds) Requirements Engineering for Internet of Things. APRES 2017. Communications in Computer and Information Science, vol 809. Springer, Singapore. https://doi.org/10.1007/978-981-10-7796-8_15
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DOI: https://doi.org/10.1007/978-981-10-7796-8_15
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