• Journal of the Korean Society for Advanced Composite Structures
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• v.6 no.3
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• pp.41-49
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• 2015

The repair of manhole raise has been caused much construction times and disruption of traffic flow, serious environmental pollution from crushed construction wastes, and budget waste due to the repeated repair construction works. In order to overcome such problems, we have developed the new manhole repairing composite structures by using a glass fiber-reinforced polymer (GFRP) pipe, which can raise manhole to the regular height of the overlayed road pavement with rapid construction and minimum traffic jams. This environmental-friendly technology is method completed by the methyl methacrylate monomer (MMA) double wide flanged GFRP pipe composite structures in order to raise manhole to the regular height. In this paper, two kinds of the compressive strength tests of MMA mortar composites were conducted and evaluated by a general compressive strength test, and compressive strength test after freezing-thawing resistance test. It was found that this MMA mortar composites will be used for the application of the double wide flanged GFRP pipe composite structures.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.281-291
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• 2017

Nowadays, as traffic jams are a daily elementary problem in both developed and developing countries, systems to monitor, predict, and detect traffic conditions are playing an important role in research fields. Comparing them, researchers have been trying to solve problems by applying many kinds of technologies, especially roadside sensors, which still have some issues, and for that reason, any one particular method by itself could not generate sufficient traffic prediction results. However, these sensors have some issues that are not useful for research. Therefore, it may not be best to use them as stand-alone methods for a traffic prediction system. On that note, this paper mainly focuses on predicting traffic conditions based on a hybrid prediction approach, which stands on accuracy comparison of three prediction models: multinomial logistic regression, decision trees, and support vector machine (SVM) classifiers. This is aimed at selecting the most suitable approach by means of integrating proficiencies from these approaches. It was also experimentally confirmed, with test cases and simulations that showed the performance of this hybrid method is more effective than individual methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.576-579
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• 1997

In order to repair sewage pipes, it is necessary to dig up the damaged sewage pipes, which results in traffic jams. Since digging up the pipes takes too much time and cost, this method is inefficient. So, in stead of digging up the damaged pipes, a robot is sent down to the pipe to do the repair works. For big pipes, human workers go into the pipe and do to repair works, but for small pipes, it is impossible for human worker to go inside the pipe. In this case, mobile robots have used. The procedures for repairing pipes are as follows : First, the condition of the sewage pipes is observed by a robot. Second, appropriate steps for repair are determined according to the types of the damage. While repairing procedures, a newly-developed packer is sent into the sport to be repaired inside the pipe. Then, the packer is filled with air by a V-shaped wrinkel pipe. This makes the packer inflates uniformly and adhere closely to the inside wall of the pipe in large area. This increases the area that can be repaired. Therefore, the newly-developed packer will be very helpful for sewage pipe repair works.

• Journal of Advanced Navigation Technology
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• v.3 no.1
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• pp.60-68
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• 1999

In this paper, we propose a new background generation method for image detector for traffic information collection. Conventional methods result in bad performance when there are frequent traffic jams due to heavy traffic. To improve on this, we use high level information from vehicle detection. Only part of the image that is not considered as vehicle is used in background generation. The proposed method finds background more robustly than that of the conventional methods even in the presence of heavy traffic.

• Journal of Auto-vehicle Safety Association
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• v.9 no.3
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• pp.24-30
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• 2017

This paper presents the development of laser scanner based static obstacle detection algorithm for vehicle localization on lane lost section. On urban autonomous driving, vehicle localization is based on lane information, GPS and digital map is required to ensure. However, in actual urban roads, the lane data may not come in due to traffic jams, intersections, weather conditions, faint lanes and so on. For lane lost section, lane based localization is limited or impossible. The proposed algorithm is designed to determine the lane existence by using reliability of front vision data and can be utilized on lane lost section. For the localization, the laser scanner is used to distinguish the static object through estimation and fusion process based on the speed information on radar data. Then, the laser scanner data are clustered to determine if the object is a static obstacle such as a fence, pole, curb and traffic light. The road boundary is extracted and localization is performed to determine the location of the ego vehicle by comparing with digital map by detection algorithm. It is shown that the localization using the proposed algorithm can contribute effectively to safe autonomous driving.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.981-983
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• 2013

Damage of the road flooding has recently increased because of torrential rains. However, its prevention is in poor situation. In this study, we propose system expressing an information of flood risk for announcing to drivers to prevent damage of flooding or traffic jams. Our system implements on GUI enviroment that users can easily know the danger of road flooding using C# Language and ArcObjects API. If users use this system, they can know how dangerous of flooding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2355-2373
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• 2011

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

• Korean Journal of Construction Engineering and Management
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• v.5 no.4 s.20
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• pp.139-146
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• 2004

Resent removal work for road signs has been labor intensive and required times since it has been done manually using shaving type equipment. While traditional process is conducting, there are traffic jams caused by the passing control, and happened unexpected accidents to workers working at dangerous road circumstance. Besides, in current shaving method, there are high potentialities on the air pollution as well as the explosive accident occurred by using a propane gas. So, as an alternative, we have studied to develop the automatic erasing equipment made up with a high pressure water-jet system and automatic control system, mobile system; Wate-rjet system consists of an intensifier and nozzles to give a high pressure and spray on the sign, and automatic control system is composed of one axis robot using a hydraulic servo actuator controlled by a lever, And as a mobile system, a truck plays an important role for the transport of equipment and the forward movement in a removal process. In this paper, we have analyzed the characteristics of road signs and have investigated current erasing methods in the field. And we have organized and designed automatic erasing equipment, and we have made a basic experiment to find out the optimal spray condition as like the spray distance, spray angle and injection pressure.

• Journal of Drive and Control
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• v.14 no.3
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• pp.8-17
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• 2017

With automobiles sharply increasing in numbers worldwide, we are faced with critical social issues such as traffic accidents, traffic jams, environmental pollution, and economic inefficiency. In response, research on ITS is promoted mainly by regions with advanced automotive industry such as the U.S., Europe, and Japan. While Korea is working on moving forward in the global market through developing and turning to global standards systems related to ASV (Advanced Safety Vehicle), the country is not fully prepared for such projects. The purpose of ACC (Adaptive Cruise Control) is to control a vehicle's longitudinal speed and distance and minimize driver workload. Such a system should be valuable in preventing accidents, as it reduces driver workload in the 21st-century world of telematics created by development of the automobile culture industry. In this light, the thesis presents a method to test and evaluate ACC system and a mathematical method to assess distance. For the proposed test and evaluation, theoretical values are tested with vehicle test and a database is acquired, by using vehicles equipped with an ACC system. Theoretical evaluation criteria for developing ACC system may be used and scenario-specific evaluation methods may find useful application through testing the formula proposed by comparing the database and mathematical method.