Oleksandr Horobchenko

Improving the process of driving a locomotive of Decision Support Systems

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© Oleksandr Horobchenko, 2017

The training system is implemented with the use of the fuzzy classifier that represents fuzzy knowledge base, the input of which receives signals about current state of the traction rolling stock and of the environment. The results of the work allow implementing intelligent DSS in modern locomotives. This will enhance the level of safety and efficiency of driving a train.

ISBN 978-5-4485-3313-6

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Contents

1. Improving the process of driving a locomotive of Decision Support Systems
2. 1. Introduction
3. 2. Literature review and problem statement
4. 3. The aim and tasks of the study
5. 4. Methods and tools for designing locomotive decision support systems
   1. 4. 1. Structure and architectural hierarchy of DSS for locomotive crews
   2. 4. 2. Formalization of fuzzy situations in the process of train driving
   3. 4.3. The models that simulate decision making processes
   4. 4.4. Methods of decision making of locomotive DSS under conditions of uncertainty of the input data
   5. 4. 5. Determining a current state of train as a control object
   6. 4. 6. The basics of the system of self– learning of intelligent locomotive DSS
   7. 4. 7. Development of mathematical model of dynamic knowledge base
6. 5. Discussion of results of research into intelligent locomotive DSS
7. 6. Conclusions

1. Introduction

The functioning of the ergatic system “train — locomotive driver” is conditioned by a number of factors, the main of which are the quality and timeliness of decision-making. Gradually the systems of driving a locomotive are developing in the direction of decreasing the role of locomotive crews in the process of driving the train, which allows reducing harmful influence of the human factor on the safety and effectiveness of the operation of rolling stock. The final stage of this development will be a transition to a fully automated control of trains.

At present, “the human factor” in operating a locomotive still plays a significant role and reduces transportation safety. This is illustrated by the accident that happened in Spain in 2013, where the accident involving a high-speed train occurred as a result of exceeding the speed by the driver, 80 people died and more than 140 were injured. Over the period from 2011 to 2015, 130 people throughout the world were killed as a result of the railway accidents caused by locomotive brigades [1]. Thus, the problem of improving the quality of driving decisions that a driver takes is relevant and requires further development of theoretical principles of its solution.

2. Literature review and problem statement

Nowadays a number of systems of automatic driving both long – distance trains [2] and local trains have been implemented [3]. For the automation of local trains and subway trains, the company Bombardier designed a new generation of train control systems CITYFLO 650 [4], which currently operates in thirteen cities around the world. In the subways of Santiago, Paris, Hong Kong and Beijing, Alstom company is implementing its design for automated train control [5]. The project Urbalis is supposed to increase the train frequency, at the same time ensuring high safety and increased comfort for passengers. An analysis of these foreign designs allows us to conclude that the use of automated train driving systems is a promising area of research that allows us either to reduce significantly or eliminate completely the negative impact of the human factor on traffic safety. However, a common drawback of these systems is the existence of limited number of parameters that are monitored, the increase in which leads to making the algorithms of automated systems operation even more complicated, which is the cause of a considerable rise in their price. On the other hand, the readjustment, when it is necessary to take into account specific conditions of a particular section, is very difficult in such systems. The projects lack the capacity to accumulate experience and to control the traffic independently in terms