As well known, the mechanical (friction or pneumatic) brake system decelerates trains with the friction force between the brake shoe and wheel tread. It seems to be a very simple mechanism. However, the friction changes in a severe non-linear and irregular form. Such an undesirable property makes brake control difficult. Friction cannot be measured easily on running trains, either. If the changes of the friction coefficient can be estimated on a real time basis by using some other signals such as wheel speed which can be obtained easily from the onboard existing hardware system, it must be useful for brake control. In our approach, the method for this purpose has been treated as a non-linear state estimation problem. Thus, we have been trying to apply the extended Kalman filter as a real time estimation method for the friction coefficient. In this paper, a mathematical model of the friction coefficient is made up by using the stochastic system concept, and the extended Kalman filter algorithm is applied for that purpose. Finally, the efficiency of proposed estimation method is proved by computer simulation and trial estimation using the measured data obtained from our dynamo brake test stand.

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In order to prevent corporate accidents, organizations need to facilitate reporting behavior. The purpose of this paper is to examine the response behavior of employees when they make mistakes. Firstly, we reviewed previous research of reporting behavior. Secondly, we conducted a case analysis of the JR Fukuchiyama Line derailment that occurred in 2005. As a result of the case analysis, we identified an employee action which we labeled “reporting avoidance behavior”. Reporting avoidance behavior is not a violation of the rules. However, the reporting avoidance behavior is an unexpected behavior(unsafe behavior)for the rule maker and may contribute to a major accident.

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安全性や騒音防止の観点から, 鉄道車両の滑走防止制御 (ABS) に対する研究は非常に重要である. しかし, ブレーキというシステムにおいて, 滑走という非常に不確実性の高い現象を防止することは容易ではなく, 一般的な制御方法というものは存在しないのが実状である. ところで, ファジィ推論は, 不確実性の高い制御対象に対して高い有効性を発揮することが知られており, 滑走に対しても, 同様の効果が期待できる. そこで, 本論文では, ファジィ推論を用いたABSと, 最近になって実用が進んだ編成でブレーキを制御するシステムを統合することで, 滑走防止に対して有効な新たなブレーキシステムを提案する. また, このブレーキシステムによって, ファジィ推論を用いたABS単独で制御するよりも, ブレーキ距離の短縮と車輪踏面の損傷低減が実現できることを, 数値シミュレーションおよび実車試験によって示す.

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