Resilience quantitative evaluation framework and performance improvement for train control system on-board equipment

Author(s):  
Wei ShangGuan ◽  
Fuwei Hu ◽  
Min Yuan ◽  
Baigen Cai ◽  
Jian Wang
Author(s):  
Scott Gage ◽  
Alan Polivka ◽  
Shad Pate ◽  
W. David Mauger

For the last several years, the railroad industry has been developing various elements for typical Positive Train Control (PTC) systems and has been demonstrating their functionality. In order to test the capabilities of these systems, Transportation Technology Center, Inc. (TTCI), the industry, and Federal Railroad Administration (FRA) have guided and funded the development of the PTC Test Bed located at the Transportation Technology Center (TTC) in Pueblo, Colorado. Recent upgrades to the PTC Test Bed at TTC have enhanced the capabilities to support on-track testing of Interoperable Train Control (ITC aka I-ETMS®) system/subsystem functionality (including radio communications), interoperability, and performance/stress characterization. Now, onboard, wayside, and office additions have been made for the PTC Test Bed to support testing associated with Advanced Civil Speed Enforcement System (ACSES) II systems and equipment. In support of train control objectives, TTCI has also implemented a broken rail detection test bed, which has produced some interesting results.


Author(s):  
Lei Jiang ◽  
Yiliu Liu ◽  
Xiaomin Wang ◽  
Mary Ann Lundteigen

The reliability and availability of the onboard high-speed train control system are important to guarantee operational efficiency and railway safety. Failures occurring in the onboard system may result in serious accidents. In the analysis of the effects of failure, it is significant to consider the operation of an onboard system. This article presents a systemic approach to evaluate the reliability and availability for the onboard system based on dynamic Bayesian network, with taking into account dynamic failure behaviors, imperfect coverage factors, and temporal effects in the operational phase. The case studies are presented and compared for onboard systems with different redundant strategies, that is, the triple modular redundancy, hot spare double dual, and cold spare double dual. Dynamic fault trees of the three kinds of onboard system are constructed and mapped into dynamic Bayesian networks. The forward and backward inferences are conducted not only to evaluate the reliability and availability but also to recognize the vulnerabilities of the onboard systems. A sensitivity analysis is carried out for evaluating the effects of failure rates subject to uncertainties. To improve the reliability and availability, the recovery mechanism should be paid more attention. Finally, the proposed approach is validated with the field data from one railway bureau in China and some industrial impacts are provided.


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