• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.745-756
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• 2022

The road tunnel is a semi-closed space that is blocked on all sides except the entrance and exit, and in the event of a fire, the smoke of the fire spreads longitudinally due to heat buoyancy caused by the fire and air currents that always exist in the tunnel. To solve this problem, smoke removal facilities are installed in road tunnels to secure a safe evacuation environment by controlling the direction of movement of smoke or directly smoking at fire points. In urban areas, the service level of urban roads decreases due to the increase in traffic due to the increase in population, and as a solution, the construction of underground roads in urban areas is increasing. When a fire occurs during hydrogen leakage through TPRD of a hydrogen fuel cell vehicle (FCEV), the fire intensity depends on the amount of leakage, and the maximum fire intensity depends on the orifice diameter of the TPRD. Considering the TPRD orifice diameter of 1.8 mm, this study analyzed the diffusion distance of fire smoke according to the wind speed of the roadway and the opening interval of the large exhaust port when the maximum fire intensity was 15 MW. As a result, it was analyzed that air flow in the tunnel could be controlled if the wind speed of the road in the tunnel was less than 1.25 m/s, and smoke could be controlled within 200 m from the fire if the damper interval was 50 m and 100 m.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.153-163
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• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.3
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• pp.298-306
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• 2014

The railway signalling system for safe train operation regulates the train speed to ensure the safety distance between consecutive trains by using wayside facilities such as track circuits and interlocking systems. In addition, this signalling system controls the trackside equipment such as a railway point along the train line. This ground-equipment-based train control systems require high CAPEX and OPEX. To deal with these problems, the train control system using the on-board controller has been recently proposed and its related technologies have been widely studied. The on-board-controller-based train control system is that the on-board controller can directly control the trackside equipment on the train line. In addition, if this system is used, the wayside facilities can be simplified, and as a result, the efficient and cost-effective train control system can be realized. To this end, we have developed the prototypes of the on-board controller and wayside object control units which control the point and crossing gate and performed the integrated operation simulation in a testbed. In this paper, before the field test of the on-board-controller-based train control system, we perform the preliminary field trial including the installation test, wireless access test, interface test with other on-board devices, and normal operation test.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.133-144
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• 2004

A model and a measure which can evaluate the risk of rear end collision are developed. Most traffic accidents involve multiple causes such as the human factor, the vehicle factor, and the highway element at any given time. Thus, these factors should be considered in analyzing the risk of an accident and in developing safety models. Although most risky situations and accidents on the roads result from the poor response of a driver to various stimuli, many researchers have modeled the risk or accident by analyzing only the stimuli without considering the response of a driver. Hence, the reliabilities of those models turned out to be low. Thus in developing the model behaviors of a driver, such as reaction time and deceleration rate, are considered. In the past, most studies tried to analyze the relationships between a risk and an accident directly but they, due to the difficulty of finding out the directional relationships between these factors, developed a model by considering these factors, developed a model by considering indirect factors such as volume, speed, etc. However, if the relationships between risk and accidents are looked into in detail, it can be seen that they are linked by the behaviors of a driver, and depending on drivers the risk as it is on the road-vehicle system may be ignored or call drivers' attention. Therefore, an accident depends on how a driver handles risk, so that the more related risk to and accident occurrence is not the risk itself but the risk responded by a driver. Thus, in this study, the behaviors of a driver are considered in the model and to reflect these behaviors three concepts related to accidents are introduced. And safe stopping distance and accident occurrence probability were used for better understanding and for more reliable modeling of the risk. The index which can represent the risk is also developed based on measures used in evaluating noise level, and for the risk comparison between various situations, the equivalent risk level, considering the intensity and duration time, is developed by means of the weighted average. Validation is performed with field surveys on the expressway of Seoul, and the test vehicle was made to collect the traffic flow data, such as deceleration rate, speed and spacing. Based on this data, the risk by section, lane and traffic flow conditions are evaluated and compared with the accident data and traffic conditions. The evaluated risk level corresponds closely to the patterns of actual traffic conditions and counts of accident. The model and the method developed in this study can be applied to various fields, such as safety test of traffic flow, establishment of operation & management strategy for reliable traffic flow, and the safety test for the control algorithm in the advanced safety vehicles and many others.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.339-350
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• 2024

Purpose: This study analyzes accessibility of 10 hydrogen charging stations in Seoul and identifies areas that were difficult to access. The purpose is to re-analyze accessibility by adding a new location in terms of equity and safety of location placement, and then draw implications by comparing the improvement effects. Method: By applying the location-allocation model and the service area model based on network analysis of the ArcGIS program, areas with weak access were identified. The location selection method applied the 'Minimize Facilities' method in consideration of the need for rapid arrival to insufficient hydrogen charging stations. The limit distance for arrival within a specific time was analyzed by applying the average vehicle traffic speed(23.1km/h, Seoul Open Data Square) in 2022 to three categories: 3,850m(10minutes), 5,775m(15minutes), 7,700m(20minutes). In order to minimize conflicts over the installation of hydrogen charging stations, special standards of the Ministry of Trade, Industry and Energy applied to derive candidate sites for additional installation of hydrogen charging stations among existing gas stations and LPG/CNG charging stations. Result: As a result of the analysis, it was confirmed that accessibility was significantly improved by installing 5 new hydrogen charging stations at relatively safe gas stations and LPG/CNG charging stations in areas where access to the existing 10 hydrogen charging stations is weak within 20 minutes. Nevertheless, it was found that there are still areas where access remains difficult. Conclusion: The location allocation model is used to identify areas where access to hydrogen charging stations is difficult and prioritize installation, decision-making to select locations for hydrogen charging stations based on scientific evidence can be supported.