• International Journal of Highway Engineering
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• v.4 no.2 s.12
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• pp.33-42
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• 2002

The cracks in the pavements result from drying shrinkage, temperature change, repeated traffic loadings and so on. The reduction of soil support, spatting and many local failures are caused by water and incompressible foreign materials infiltrated into the cracks. In order to reduce this kind of problems the crack width must be controlled and managed by the accurate measurement. The current method is a visual survey using a microscope, which requires traffic blocking. The purpose of this study is to find the best condition to measure accurate crack width using automated pavement condition survey equipment running at the similar speed as other vehicles. In this study pavement surfaces are filmed on an enlarged scale by the camera with a zoom lens, and then the proper focal distance is determined according to the crack width through a pilot survey. The conditions for measurement of the accurate crack width using the image processing technique are suggested by comparing crack widths surveyed using a microscope in the field with those computed by various factors in the image processing program, STADI-2. In conclusion, the camera with a focal distance of 75m could detect crack range of 0.5mm$\sim$1.2mm In width with an accuracy of 80% for CRCP. The camera with a focal distance of 12.5mm could detect crack range of 1.8mm$\sim$3.3mm in width with an accuracy of 90% for asphalt pavement.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.4
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• pp.39-48
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• 2016

An information management system for a solid waste landfill site was developed, in this study, to optimize the operation and management of solid waste landfill in real time in addition to provide the information of landfill status to the landfill operator, public official concerned and local residents. The landfill information management system is composed of two systems (Solid waste landfill history management system and landfill operation and performance management system). The solid waste landfill history management system based on automated RFID/LPR system allows landfill operators to provide information of waste collection vehicles and received waste. In addition, the system aids in the identification of 3-dimensional (3D) position for landfilled solid wastes. Using the landfill operation and performance management system based on 3D laser scanner delivers information about landfill volume, settlement, landfill density, and current landfill capacity to landfill operators in real time, resulting in optimum space utilization. Ultimately, this system would dramatically reduce exposure of landfill operators to hazardous materials and improve the productivity of landfill operations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.63-68
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• 2017

Although automated metro subway systems have the advantage of operating a train without a train driver, it is difficult to detect an immediate fault condition and take countermeasures when an unusual situation occurs. Therefore, it is important to construct a maintenance information system (MIS) that detects the vehicle failure/status information in real time and maintains it efficiently in the depot of the railway's vehicles. This paper proposes a conceptual design method that realizes the interface between the train control system (TCS), the operation control center train control monitoring system (OCC-TCMS) console, and the MIS using wireless communication network in real-time. To transmit a large amount of information on 800,000 occurrences per day during operation, data was collected in a 56 byte data table using a data processing algorithm. This state information was classified into 4 hexadecimal codes and transmitted to the MIS by mapping the status and the fault information on the vehicle during the main line operation. Furthermore, the transmission and reception data were examined in real time between the TCS and MIS, and the implementation of the failure information screen was then displayed.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.545-556
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• 2017

Various assessment indexes have been developed and utilized to evaluate the driver workload. However, existing workload assessment indexes do not fully reflect driving habits and driving patterns of individual drivers. In addition, there exists significant differences in the amount of workload experienced by a driver and the ability to overcome the driver's workload. To overcome these limitations associated with existing indexes, this study has developed a novel workload assessment index to reflect an individual driver's driving pattern. An average of the absolute values of the steering velocity for each driver are set as a threshold value in order to reflect the driving patterns of individual drivers. Further, the sum of the areas of the steering velocities exceeding the threshold value, which is defined as erratic steering area (ESA) in this study, was quantified. The developed ESA index is applied in evaluating the driver workload of manually driven vehicles in automated vehicle platooning environments. Driving simulation experiments are conducted to collect drivers' responsive behavior data which are used for exploring the relationship between the NASA-TLX score and the ESA by the correlation analysis. As a result, ESA is found to have the greatest correlation with the NASA-TLX score among the various driver workload evaluation indexes in the lane change scenario, confirming the usefulness of ESA.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.105-117
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• 2020

Analysis of combat effectiveness is required to consider the concept of tactical cooperative engagement between manned-unmanned weapon systems, in order to predict the required operational capabilities of future weapon systems that meets the concept of 'effect-based synchronized operations.' However, analytical methods such as mathematical and statistical models make it difficult to analyze the effects of complex systems under nonlinear warfare. In this paper, we propose a combat simulation model that can simulate the concept of cooperative engagement between manned-unmanned combat entities based on wireless communications. First, we model unmanned combat entities, e.g., unmanned ground vehicles and drones, and manned combat entities, e.g., combatants and artillery, considering the capabilities required by the future ground system. We also simulate tactical behavior in which all entities perform their mission while sharing battlefield situation information through wireless communications. Finally we explore the feasibility of the proposed model by analyzing combat effectiveness such as target acquisition rate, remote control success rate, reconnaissance lead time, survival rate, and enemy's loss rate under a small-unit armor reconnaissance scenario. The proposed model is expected to be used in war-game combat experiments as well as analysis of the effects of manned-unmanned ground weapons.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.101-111
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• 2022

Conditional autonomous vehicles should hand over control to the driver according on driving situations. However, if the driver is immersed in a non-driving task, the driver may not be able to make suitable decisions. Previous studies have confirmed that the cues enhance take-over performance with a directional information on driving. However, studies on the effect of take-over cues on the driver's brain activities are rigorously investigated yet. Therefore, this study we evaluates the driver's brain activity according to the take-over cue. A total of 25 participants evaluated the take-over performance using a driving simulator. Brain activity was evaluated by functional near-infrared spectroscopy, which measures brain activity through changes in oxidized hemoglobin concentration in the blood. It evaluates the activation of the prefrontal cortex (PFC) in the brain region. As a result, it was confirmed that the driver's PFC was activated in the presence of the cue so that the driver could stably control the vehicle. Since this study results confirmed that the effect of the cue on the driver's brain activity, and it is expected to contribute to the study of take-over performance on biomakers in conditional autonomous driving in future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

• Food Science of Animal Resources
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• v.29 no.4
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• pp.506-512
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• 2009

Salmonellosis is an important worldwide foodborne infectious disease that is transmitted by many food vehicles including raw and processed animal products and fresh produce. In this study, the effectiveness of automated ELISA ($VIDAS^{(R)}$) and realtime PCR in the detection of Salmonella spp. in steamed pork and raw broccoli sprouts was evaluated by comparing their results with those of a conventional culture method. Bulk samples (500 g) of steamed pork and raw broccoli sprouts were inoculated with various levels of Salmonella and divided into 20 samples (25 g each). All the samples, including the controls, were analyzed using a conventional culture method, $VIDAS^{(R)}$, and real-time PCR to detect the presence of Salmonella. In addition, the levels of background flora in the steamed pork and the raw broccoli sprouts were determined. In the steamed pork that contained less than 100 CFU/g of aerobic bacteria, all three methods detected low levels of Salmonella without a statistical difference in their performance. In the broccoli sprouts with high quantities of background flora (ca. $6.7{\times}10^7$ CFU/g), however, all three methods were unable to detect low levels of Salmonella, and real-time PCR and $VIDAS^{(R)}$ more sensitively detected Salmonella than the culture method, with significant statistical differences. In conclusion, $VIDAS^{(R)}$ and real-time PCR could be superior to conventional culture methods in detecting Salmonella in food with high levels of background flora.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.180-185
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• 2003

The increase of traffic over a bridge has been emerged as one of the most severe problems in view of bridge maintenance, since the load effect caused by the vehicle passage over the bridge has brought out a long-term damage to bridge structure, and it is nearly impossible to maintain operational serviceability of bridge to user's satisfactory level without any concern on bridge maintenance at the phase of completion. Moreover, bridge maintenance operation should be performed by regular inspection over the bridge to prevent structural malfunction or unexpected accidents front breaking out by monitoring on cracks or deformations during service. Therefore, technical breakthrough related to this uninterested field of bridge maintenance leading the public to the turning point of recognition is desperately needed. This study has the aim of development on automated inspection system to lower surface of bridge superstructures to replace the conventional system of bridge inspection with the naked eye, where the monitoring staff is directly on board to refractive or other type of maintenance .vehicles, with which it is expected that we can solve the problems essentially where the results of inspection are varied to change with subjective manlier from monitoring staff, increase stabilities in safety during the inspection, and make contribution to construct data base by providing objective and quantitative data and materials through image processing method over data captured by cameras. By this system it is also expected that objective estimation over the right time of maintenance and reinforcement work will lead enormous decrease in maintenance cost.