• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.112-119
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• 2005

In road tunnel, in order to prevents an accident and minimize the damage of an accident in the case of fire, safety facilities and equipments are integral parts. The type and amount of safety facilities are based on tunnel type and length, traffic flow rate, etc. Therefore many countries use a tunnel classification system that categories tunnel into groups, and specifies the necessary emergency equipment for each group. In this study, for the purpose of classifying tunnel based on tunnel ist investigated the domestic and foreign standards and regulations for safety of road tunnel. As a results, we suggest the method of classification of tunnel by traffic performance, tunnel grade, the volume of traffic, fraction of HGV, rules or regulations for transports of dangerous good through tunnel.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.157-162
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• 2004

Recently, Life Cycle Cost (LCC) for civil infrastructures, such as pavements, bridges, and dams, has been emphasized. However there are few cost models for road tunnel especially for maintenance phase. The road network is composed of highways, bridges, and road tunnels. Thus it is as important as for road tunnels to keep safe for traffic. The maintenance strategies for road tunnels can be achieved based on the minimization of LCC in maintenance phase. For this purpose, in this paper, cost model and cost classification for road tunnel in maintenance phase are suggested.

• Fire Science and Engineering
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• v.31 no.5
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• pp.107-116
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• 2017

Fires in tunnels are an international concern and fatal accidental fires in tunnels seem to occur on annual. They have the potential to become much worse int the future as more and longer tunnels are constructed and as traffic densities increase. This is a serious problem. The main purpose of this study is to develop operational procedures for fire brigades in road tunnel fires. This study discussed the past to see what can be learned from the incidents that have already done in tunnels. 73 cases of road tunnel fires domestic and outside of Korea were investigated and classified into 4 incident categories. Among them, 4 tunnel fires are highlighted, focusing on the activities of fire brigades and operation. Regarding the establishment of the strategies for fire fighting, 6 kinds of fire scenario curves have been deducted with regard to the relation between intervention time and heat release rate. It made the choice from the defensive or aggressive fire fighting activities depending on two criteria i.e. response limit and maximum response time. Road Tunnel Classification models can be useful when a fire brigade evaluates fire risk levels in the tunnels under its jurisdiction from the firefighting point of view and sets up preventive measures.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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• pp.313-323
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• 2016

With the development of autonomous vehicle, there has been active research on advanced driver assistance system for road marking detection using vision sensor and 3D Laser scanner. However, vision sensor has the weak points that detection is difficult in situations involving severe illumination variance, such as at night, inside a tunnel or in a shaded area; and that processing time is long because of a large amount of data from both vision sensor and 3D Laser scanner. Accordingly, this paper proposes a road marking detection and classification method using single 2D Laser scanner. This method road marking detection and classification based on accumulation distance data and intensity data acquired through 2D Laser scanner. Experiments using a real autonomous vehicle in a real environment showed that calculation time decreased in comparison with 3D Laser scanner-based method, thus demonstrating the possibility of road marking type classification using single 2D Laser scanner.

• Journal of KIBIM
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• v.6 no.2
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• pp.29-38
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• 2016

Road bridges are deteriorating gradually, and it is forecasted that the number of road bridges aging over 30 years will increase by more than 3 times of the current number. To maintain road bridges in a safe condition, current safety conditions of the bridges must be estimated for repair or reinforcement. However, budget and professional manpower required to perform in-depth inspections of road bridges are limited. This study proposes an estimation model for safety rating of road bridges by analyzing the data from Facility Management System (FMS) and Yearbook of Road Bridges and Tunnel. These data include basic specifications, year of completion, traffic, safety rating, and others. The distribution of safety rating was imbalanced, indicating 91% of road bridges have safety ratings of A or B. To improve classification performance, five safety ratings were integrated into two classes of G (good, A and B) and P (poor ratings under C). This rearrangement was set because facilities with ratings under C are required to be repaired or reinforced to recover their original functionality. 70% of the original data were used as training data, while the other 30% were used for validation. Data of class P in the training data were oversampled by 3 times, and Repeated Incremental Pruning to Produce Error Reduction (RIPPER) algorithm was used to develop the estimation model. The results of estimation model showed overall accuracy of 84.8%, true positive rate of 67.3%, and 29 classification rule. Year of completion was identified as the most critical factor on affecting lower safety ratings of bridges.

• Journal of the Korea institute for structural maintenance and inspection
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• v.4 no.4
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• pp.129-140
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• 2000

Retaining wall is a constructed structure in order to construct road, rail, building for effective use and obtainments of the limited ground. Recently, many kinds of research have been actively developed for a standardization and information to the maintenance and management of bridge, tunnel, road. With the works of database construction of that, many kinds of data with respect to statistics is cumulated. Database work of retaining wall is wholly lacking and lagged behind in the works of database construction. This paper suggests classification system on inspection data. On the basis of that, code work with classification system was practised and DB program of inspection data of retaining wall was developed. And input work for a data of maintenance and management was practised. The purpose of this paper is to suggest a kind of statistics data and investigate a characteristics of inspection using statistic data on retaining wall.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.75-79
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• 2008

Since tunnel construction order was placed one by one, various sensors and actuators installed at the RTU and higher level system in each tunnel maintenance office had their own protocols depending on construction company. The TGMS testbed established on the extended region of Yong-dong Highway, for example, did not have consistent protocol between each automation levels and management levels without considering the functions and/or roles of each level. The management sever in each tunnel was simply networked to the TGMS server. Therefore, it is impossible to implement a new control algorithm as well as to integrate each other since each tunnel was constructed by different company. So, if the construction company is out of business, there is no way to maintain the corresponding tunnel effectively. In order to solve this problem, all the necessary standard protocols was established between automation level and management levels. These interface standards provide the clear classification between individual tunnel system and tunnel management system. So, even if construction company is different, its effect is minimized, so that it is expected to successfully establish PC based TGMS.

• Journal of Korean Tunnelling and Underground Space Association
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• v.3 no.4
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• pp.17-24
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• 2001

Four road tunnels of which the construction conditions were similar were selected in the paper, and laboratory tests and rockmass classification for the tunnels were carried out. And the analysis was performed to find out the correlation between ratio of bit abrasion or drilling parameter and support pattern of tunnel using jumbo drill machine. It was analyzed that there was average abrasion of bit from 11.85% to 3.25% per support patterns of tunnel in four tunnels. Drilling parameter happens to fluctuate according to extent of fracture zone.

• Tunnel and Underground Space
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• v.9 no.3
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• pp.214-220
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• 1999

In this study, the validity of items of RMR system is evaluated and the applicability of this system to the data measured in Korean sites if discussed. Database was constructed from 139 sites, which are composed of subways, railway tunnels and road tunnels. These sites are located nationwide. Analysis shows that original classification of Bieniawski is valid although it was derived empirically. But it has considerable rating difference (error) in the result of Korean application. Thus new classification systems of KRMRI and KRMR2 are suggested, which are deduced from the Korean database. The former includes adjusted ratings and the latter adopts two more items. These are deduced by artificial neural network because it is difficult to select \`characteristic value'to estimate rock quality.

• Proceedings of the SAREK Conference
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• 2006.11a
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• pp.104-104
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• 2006