• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1132-1137
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• 2008

Automatic Operation based on ATO (Automatic Train Operation) is necessary for driverless Light Rail Transit business. When this kind of driverless LRT operation plan is made, TPS (Train Performance Simulation) is traditionally simulated at all-out mode and coasting mode based on manual operation. Commercial schedule speed equals to all-out speed minus $9{\sim}15%$ make-up margin. Coasting mode TPS simulation is also run at commercial schedule speed to calculate run time and energy consumption. But TPS based on manual operation should make an improvement on accuracy in case of driverless LRT operation Plan. In this paper, new fast mode TPS simulation using ATO pattern is proposed and show near actual ATO result. The actual ATO pattern can be accurately simulated with the introduction of 4 parameters such as commercial braking rate, jerk, station stop profile and grade converted distance. Normal mode TPS simulation for commercial schedule speed can be designed to have fast mode trip time plus 3 seconds/km margin recommended by korean standard LRT specification.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.1
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• pp.11-22
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• 2018

The safety of tunnels is quantified by quantitative risk assessment when planning the disaster prevention facilities of railway tunnels, and it is decided whether they are appropriate. The purpose of this study is to estimate the probability of the train stopping in the tunnels at train fire, which has a significant effect on the results of quantitative risk assessment for tunnel fires. For this purpose, a model was developed to calculate the coasting distance of the train considering the coefficient of train running resistance. The probability of stopping in case of train fire in the tunnel is predicted by the Monte Carlo simulation method with the coasting distance and the emergency braking distance as parameters of the tunnel lengths and slopes, train initial driving speeds. The kinetic equations for predicting the coasting distance were analyzed by reflecting the coefficient train running resistance of KTX II. In the case of KTX II trains, the coasting distance is reduced as the slope increases in a tunnel with an upward slope, but it is possible to continue driving without stopping in a slope downward. The probability of the train stopping in the case of train fire in tunnel decreases as the train speed increases and the slope of the tunnel decreases. If human error is not taken into account, the probability that a high-speed train traveling at a speed of 250 km/h or above will stop in a tunnel due to a fire is 0% when the slope of the tunnel is 0.5% or less, and the probability of stopping increases rapidly as the tunnel slope increases and the tunnel length increases.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.878-886
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• 2009

This paper proposes an optimal algorithm for generating a train speed profile giving optimal energy efficiency based on GA (Genetic Algorithm) and shows its effectiveness with simulations. After simplifying the train operation mode to a maximum traction, a coasting and a maximum breaking, adjusting the coasting point to minimize the train consuming energy is the basic scheme. Satisfying the two constraints, running distance and running time between two stations, a coasting point is determined by GA with a fitness function consisting of a target running time. Simulation results have shown that multiple coasting points could exist satisfying both of the two constraints. After figuring out consumed energies according to the multiple coasting points, an optimal train speed profile with a coasting point giving the smallest consumed energy has been selected. Simulation blocks for the train performance simulation and GA have been designed with the Simulink.

• Journal of the Korean Society of Safety
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• v.27 no.6
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• pp.31-42
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• 2012

Urban transit vehicle that uses electrical energy, is faster, safer and energy-efficient public transit than other means. As a Research method, the Matlab/Simulink are used to modeling a regenerative brake-capable train, and actual parameters such as powering and braking characteristics, all kinds of resistance, passenger load, velocity, gradient, radius of curve etc and powering and breaking commands per time or distance are inputted to train's dynamic equation, then a simulation program is made and used to yield train driving pattern and driving time and the amount of driving energy used thereby at auto and manual operation and at all sector.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.174-183
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• 2005

A train driving requires to n the fixed distance within given time, and it is desirable to consume low energy if necessary. Reducing energy consumption depends on the train operation modes by either manual or automatic operation. In this article, an operation to reduce energy consumption by changing modes of train operation by a driver without changing the train operation requirement is investigated. The powering model, braking model and consumed energy calculation model are developed, then simulated by using a Matlab software. The accuracy of the train dynamic model established by the simulations is verified by comparing with the real experimental data. Several simulations by various operations in the real track are executed, then the desirable pattern of train driving is found.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1878-1884
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• 2010

Currently in Korea, neutral sections in front of substations and sectioning posts are greatly divided into AC/DC sections and AC/AC sections. Considering catenary damage and safety issues trains pass crossover by coasting driving at notch-off. However in cases of Japan, China, or Taiwan, the usage of automatic crossover system makes it possible to pass at notch-on, enhancing high-speed railway operation for efficiency, and stability. These are the purposes of developing automatic power crossover system in neutral sections. This paper introduces two methods to detect the position of a train required to activate automatic crossover systems in neutral sections. The optimal method is expected in terms of the distance of neutral section.