A Novel Independent Train Localization Method Based on Multi-Sensor Fusion

Author(s):  
Datian Zhou ◽  
Tao Tang

Train localization system is a vital part of train control system. A novel independent train localization method based on multi-sensor fusion is proposed in this paper. In conventional train localization system, the position determination is dependent on the reference information source controlled by rail operator, such as track circuit and so on. In some new train localization systems on test[1][2][3][4], the localization methods based on Satellite Navigation are very popular, so that the system’s reliability and safety are put outside of the rail operators’ control actually. The localization method proposed in this paper uses inertial sensor gyrometer and conventional odometer, which is mounted on the locomotive’s driven axle. Gyrometer is used to measure train’s heading angular rate. And odometer is used to measure train’s velocity. Usually, the dead reckoning method independent of outside reference information is selected for these two sensors’ fusion. But an obvious disadvantage of this method is the position error is increasing linearly according to time, so that this method can not work independently. Therefore Satellite Navigation system is often used to restrict the increasing error to an acceptable range. The method proposed in this paper overcomes the disadvantage of dead reckoning. Because the rail route or train’s moving track is fixed, the route’s curvature-mile curve can be obtained. According to this curve it is obvious, in the area where route is straight, the curvature value is zero; in the area existing a turning, the value is not zero. DGPS equipment is mounted on the test train to get and record the position data on the test route. Then the curvature-mile curve can be calculated from these data. We use Hurst coefficient to get the characters of train track such as turning from the gyrometer and odometer’s data. By matching these characters and the known route’s curvature-mile curve, the train’s real-time position can be calculated. If the dual-direction communication channel such as GSM-R is available, virtual block or moving automatic block in train control system could be achieved. Details of this process are presented in this paper with some results to illustrate the effectiveness of the methods.




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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