• Convergence Security Journal
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• v.10 no.1
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• pp.41-48
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• 2010

Greedy protocols show good performance in Vehicular Ad-hoc Networks (VANETs) environment in general. But they make longer routes causing by surroundings or turn out routing failures in some cases when there are many traffic signals which generate empty streets temporary, or there is no merge roads after a road divide into two roads. When a node selects the next node simply using the distance to the destination node, the longer route is made by traditional greedy protocols in some cases and sometimes the route ends up routing failure. Most of traditional greedy protocols just take into account the distance to the destination to select a next node. Each node needs to consider not only the distance to the destination node but also the direction to the destination while routing a packet because of geographical environment. The proposed routing scheme considers both of the distance and the direction for forwarding packets to make a stable route. And the protocol can configure as the surrounding environment. We evaluate the performance of the protocol using two mobility models and network simulations. Most of network performances are improved rather than in compared with traditional greedy protocols.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.113-122
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• 2018

In level 3 automated vehicles, drivers are expected to encounter transition of control when the system reaches its limit. Drivers need to refocus their attention on the road ahead and gain situational awareness. Appropriate information should be conveyed during this period in order to prevent human errors. In this paper, we defined the takeover process as 'in-the-middle-of-the-loop' and conducted Task Analysis and Work Domain Analysis to find out information requirements. As a result, we specified required information types and interface considerations. Moreover, we conducted an experimental study to find how the information types affect drivers on situation awareness, cognitive load and reaction time. Consequently, we found different information on system transparency should be conveyed depending on the urgency of takeover situation and driver guidance could help drivers with better situation awareness after the takeover.

• Journal of Korean Tunnelling and Underground Space Association
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• v.4 no.1
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• pp.37-43
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• 2002

Recently, the construction of tunnels longer than one kilometer has increased rapidly. Considering characteristic of limiting structure of longer tunnel, if fires inside tunnel broke out because of vehicle incidents, the catastroph would have high possibility to take place due to toxic smoke and heat of fire. In case of highway tunnel, safety facilities which can cope with tunnel fire are installed in the tunnel but according to rapid increase of heavy good traffic, dangerous goods and enlargement of tunnel magnitude, the research has to carry out about heat fluxes and smoke behaviour during tunnel fire. Therefore, through full-sized fire experiment the paper analyzed temperature distribution, wind velocity, smoke behaviour during tunnel fire.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.21-30
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• 2005

In this paper, we propose lane detection and trackinB algerian using B-Snake as robust algorithm. One of chief virtues of Lane detection algorithm using B-Snake is that it is possible to specify a wider range of lane structure because B-Spline conform an arbitrary shape by control point set and that it doesn't use any camera parameter. Using a robust algorithm called CHVEP, we find the vanishing point, width of lane and mid-line of lane because of the perspective parallel line and then we can detect the both side of lane mark using B-snake. To demonstrate that this algorithm is robust against noise, shadow and illumination variations in road image, we tested this algorithm about various image divided by weather-fine, rainy and cloudy day. The percentage of correct lane detection is over 95$\%$.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.66-77
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• 2014

UTIS(Urban Traffic Information System) directly collects link travel time in urban area by using probe vehicles. Therefore it can estimate more accurate link travel speed compared to other traffic detection systems. However, UTIS includes some missing data caused by the lack of probe vehicles and RSEs on road network, system failures, and other factors. In this study, we suggest a new model, based on k-NN algorithm, for imputing missing data to provide more accurate travel time information. New imputation model is an adaptive k-NN which can flexibly adjust the number of nearest neighbors(NN) depending on the distribution of candidate objects. The evaluation result indicates that the new model successfully imputed missing speed data and significantly reduced the imputation error as compared with other models(ARIMA and etc). We have a plan to use the new imputation model improving traffic information service by applying UTIS Central Traffic Information Center.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.4
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• pp.460-471
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• 2011

A port has been regarded as a significant contributor to air pollution in the surrounding areas. Port-related air pollutants are released from not only marine vessels, but also various land-side sources at ports, which include cargo handling equipment, vehicles, locomotives, and fugitive dust sources by port activities such as bulk handling and vehicle movements. However, most studies in Korea have only focused on vessel emissions and there is a lack of information on the emissions from other sources at port. In this study, in order to establish the port-related emission inventory and evaluate the relative contribution of these sources to air emissions from the Port of Incheon, the emissions from land-side sources were estimated and the CAPSS (Clean Air Policy Support System) data for vessel emissions were used. In particular, the detailed information and activity data for the cargo handling equipment source were collected and the emission factors and emissions by equipment types were calculated using U.S. EPA methodologies. Total HC, CO, $NO_x$, $PM_{10}$, and $SO_2$ emissions from port-related sources including the vessel in 2007 were calculated as 229 ton/year, 638 ton/year, 4,861 ton/year, 307 ton/year, and 3,995 ton/year, respectively. It was found that the vessel was the largest contributor to air pollutant emissions from the port, the cargo handling equipment was responsible for about from 8% to 13% of HC, CO, and $NO_x$ emissions and the resuspended road dust contributed about 39% for $PM_{10}$ emissions. The results of this study will be used to establish the management and reduction strategies of air pollution in the port.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.3
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• pp.60-68
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• 2017

Since the bridge is the main facility of the road that is the core of the civil infrastructure, the bridge is constructed to ensure stability and serviceability during the traffic use. In order to secure the safety of bridges, evaluating the integrity of bridges at present is an important task in the maintenance work of bridges. In general, to evaluate the load carrying capacity of bridges, it is possible to confirm the superimposed behavior and symmetric behavior of bridges by estimating the lateral load distribution factor of the bridges through vehicle loading tests. However, in order to measure the lateral load distribution factor of a commonly used bridge, a static loading test is performed. There is a difficulty in traffic control. Therefore, in this study, the static displacement component of the bridge measured in the dynamic loading test and the ambient vibration test was extracted by using empirical mode decomposition technique. The lateral load distribution was estimated using the extracted static displacement component and compared with the lateral load distribution factor measured in the static loading test.

• Journal of the Society of Disaster Information
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• v.13 no.4
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• pp.570-576
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• 2017

Trucks take up more portions than cars on highways. Due to this, road use relatively diminish and it serves locally as a threatening factor to nearby drivers. Baggage car accident has distinct characteristics so that it needs the application of different analysis opposed to ordinary accidents. Accident prediction model, one of accident analyses, is used to predict the numbers of accident in certain parts, establish traffic plans as well as accident prevention methods, and diagnose the danger of roads. Thus, this study aims to apply the accident rate of baggage car on highways and calculate the correction factor to be put in the accident prediction models. Accident data based on highway was collected and traffic amounts and accident documents between 2014 and 2016 were utilized. The author developed an accident prediction model based on numbers of annual accidents and set mean annual and daily traffic amounts. This study intends to identify the practical accident prediction model on highway and present an appropriate solution by comparing the prediction model in accords with the accident rate between baggage cars.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.5963-5967
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• 2014

Reducing the impact of collisions of cars is a major issue for reducing the injury and death of passengers. According to the statistical data of the Road Traffic Authority, the deaths from side collision accidents caused by the collision of passenger cars is greater than the deaths from head-on collision accidents. To accommodate this, vehicle designers have added a reinforcing material called the impact frame and impact beam on the inside of the door. Many experiments are needed to develop the door impact beam. These reinforcements to develop a collision experiment is essential. Collision experiments are costly and time consuming. This study used a drop Impactor to obtain the impulse and a strain experimental device was developed for this purpose. The economic costs were reduced and the ideal experiment device configuration was determined. A comparison of the experimental results with numerical value analysis revealed $3.5{\tiimes}10-3sec$ strain ranging from $3.49{\tiimes}10-3$ to $3.99{\tiimes}10-3$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1022-1026
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• 2013

Recently, the waste heat recovery technique using thermoelectric generator (TEG) in automotive engine has emerged to improve thermal efficiency in commercial vehicle. It is not difficult to recognize the numerous attempts that have been made to develop the TEG simulation model, but it is hard to find the model in conjunction with a particular heat engine system. In this study, 1-D commercial software AMESim was used to develop a computational model that can assess waste heat recovery from a diesel engine exhaust using TEG. The developed TEG simulation model can be used for evaluating the TEG performance of various types of TE module, and the diesel engine model can simulate any type of on and off-road diesel engines. The simulation results demonstrated that approximately 544.75W could be recovered from the engine exhaust and 40.4W could be directly converted into electricity using one TE module. The models developed in this study can be easily coupled with each other in the same computational program; thus, the models are expected to provide a viable tool for developing and optimizing a TEG waste heat recovery system in an automotive diesel engine.