• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.25-35
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• 2011

Traffic volume increases due to diversification of industry. Also, Automobile ownerships also increase steadily. It is estimated that the registered number of vehicle is expected to be 20 milion in the year 2015. These trends may result in increasing the number of woman drivers and elderly drivers. Therefore, this study aims to identify routes that reflect characteristics of each driver's preferences. A survey was conducted on different routes attributes for variances drivers. Driver types were classified by gender, age, and driving career. Accordingly, a weight for road composition attribute such as number of lanes, number of accidents, slope was estimated by using Swing Weighting technique in Multi-Attribute Utility Theory. In addition, a case study was conducted and identified weights were applied to routes. In result, drivers commonly prefer short route when they considered their routes. Also, male drivers prefer speedy and shorter route than that of female drivers. Elderly drivers prefer safe routes that represent low accidents rate. Moreover driving career under a year drivers prefer safe and easy routes. Therefore, we may conclude that the necessity of diversified route information is essential in the future car navigation system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.55-66
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• 2020

This study developed four algorithms and their associated indices that can quantify and qualify road hazards along roadways. Initially, relevant raw data can be collected from commercial vehicles by camera and DTG. Well-processed data, such as potholes, road freezing, and fog, can be generated from the Integrated management system. Road hazard algorithms combine these data with road inventory data in the Data Sharing Platform. Depending on well-processed data, four different road hazard algorithms and their associated indices were developed. To test the algorithms, an experimental plan based on passive DTG attached in probe vehicles was performed at two different test locations. Selection of the test routes was based on historical data. Although there were limitations using random data for commercial vehicles, hazardous roadways sections, such as fog, road freezing, and potholes, were generated based on actual historical data. As a result, no algorithm error was found in the entire test. Because this study provides road hazard information according to a section, not a point, it can be practically helpful to road users as well as road agencies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.38-48
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• 2010

Adverse weather (e.g. strong winds, snow and ice) will probably appear as a more serious and frequent threat to road traffic than in clear climate. Another consequence of climate change with a natural disastrous on road traffic is respond to traffic accident more the large and high-rise bridge zone, tunnel zone, inclined plane zone and de-icing zone than any other zone, which in turn calls for continuous adaption of monitoring procedures. Accident mitigating measures against this accident category may consist of intense winter maintenance, the use of road weather information systems for data collection and early warnings, road surveillance and traffic control. While hazard from reduced road friction due to snow and ice may be eliminated by snow removal and de-icing measures, the effect of strong winds on road traffic are not easily avoided. The purpose of the study described here, was to design of amber information the relationship between traffic safety, weather, user information on road weather and driving conditions in local-scale Geographic. The most applications are the optimization of the amber information definition, improvements to road surveillance, road weather monitoring and improved accuracy of user information delivery. Also, statistics on wind gust, surface condition, vehicle category and other relevant parameters for wind induced accidents provide basis for traffic control, early warning policies and driver education for improved road safety at bad weather-exposed locations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.105-112
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• 2011

Delay reduction of vehicles at the intersection is highly dependent on the signal operation method. Improper traffic operation causes the violation of the traffic regulations and increasing traffic congestion. Delay because of congestion has contributed to the increase in carbon dioxide in the atmosphere. The focus of this paper is to measure the amount of carbon dioxide when the intersection is changed to roundabout. Even though, Intergovernmental Panel on Climate Change(IPCC) recommends Tier 1 method to measure the amount of greenhouse gas from vehicles, this paper used Tier 3 method because we could use the data of average running distance per each vehicle model. Two signalized intersections were selected as the study area and the delay reductions of roundabout operation were estimated by VISSIM microscopic simulation tool. The control delay for boksu intersection reduced from 28.6 seconds to 4.4 seconds and the KRIBB intersection sharply reduced from 156.4 seconds to 23.6 seconds. In addition, carbon dioxide for two intersections reduced to 646.5 ton/year if the intersection is changed to roundabout. Future research tasks include testing the experiment for networks, as well as for various intersection types.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.5
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• pp.13-21
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• 2013

Super high-rise buildings of combined use such as large shopping malls and multiplex etc. have larger parking facilities than general buildings and are characteristic of an increase in the number of the entrance and the exit connecting internal external space of the parking lot. These features cause a congestion of internal traffic by increasing car driving distance in the parking lot, and vehicle idling increases by drivers wander the parking lot in order to find parking space. In addition, they make drivers suffer from lots of difficulties due to parking including increasing their walking line after parking. Therefore, in this study, we developed individual parking information provision algorithm to specify the optimal parking place for drivers according to the purpose of visiting a building and the drivers' moving path, and selected new construction site for the second lotte world in order to evaluate the algorithm developed and performed evaluation. As a result of the evaluation, it was analyzed that in the case of applying the individual parking information provision algorithm compared to the existing parking information provision algorithm, moving distance in the parking lot decreases around 7.43~83.4%, and that in the case of $CO_2$ emission, it decreased about 47.7% on average, which indicates that the efficiency resulted from application of the individual parking information provision algorithm is very high as the application effects are tested.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.53-63
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• 2003

The Origin-Destination(OD) matrix is very important in describing transport movements in a region. The OD matrix can be estimated using traffic counts on links in the transport network and other available information. This information on the travel is often contained in a target OD matrix and traffic counts in links. To estimate an OD matrix from traffic counts, they are the major input data which obviously affects the accuracy of the OD matrix estimated, Generally, the quality of an estimated OD matrix depends much on the reliability of the input data, and the number and locations of traffic counting points in the network. Any Process regarding the traffic counts such as the amount and their location has to be carefully studied. The objective of this study is to select of the optimal location of traffic counting points for the OD matrix estimation. The model was tested in nationwide network. The network consists of 224 zones, 3,125 nodes and 6,725 links except to inner city road links. The OD matrix applied for selection of traffic counting points was estimated to 3-constrained entropy maximizing model. The results of this study follow that : the selected alternative to the best optimal counting points of six alternatives is the alternative using common links of OD matrix and vehicle-km and traffic density(13.0% of 6,725 links), however the worst alternative is alternative of all available traffic counting points(44.9% of 6,725 links) in the network. Finally, it should be concluded that the accuracy of reproduced OD matrix using traffic counts related much to the number of traffic counting points and locations.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.458-467
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• 2017

The expressway of the Korea has an important role in freight movement because 76 percent of the commodity is transported by trucks. However, there has been few indices on the role of expressways regarding freight transportation and truck traffic. The objective of this study is to propose four freight transportation related indices using ITS-related system such as TCS and HS-Wim: total truck's travel miles ($veh{\cdot}km/year$), total freight transport miles ($ton{\cdot}km/year$). efficiency of truck's travel ($veh{\cdot}km/km$), and efficiency of freight movement ($ton{\cdot}km/km$). These truck and freight related indices were estimated and compared by two different data sources: traffic volume data using VDS and OD data using TCS. These indices were designed to estimated on real time and updated every day and month.

• Korean Journal of Community Nutrition
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• v.12 no.5
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• pp.617-629
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• 2007

To ensure the microbiological safety of food items prepared after cooking process, this study was aimed to identify the hazards related with cooked foods donated to foodbanks through quantitative microbial analysis. Five foodbanks located in Incheon and Gyeonggi area among government-dominant foodbanks were surveyed from February to June, 2007. Manager, recipient, donator, type and quantity of donated foot and facility and equipment were examined for the general characteristics of foodbank. The time and temperature of food md environment were measured at steps from after-production to before-distribution, and the microbial analysis was performed mainly with indicator organism and major pathogens. The amount of cooked foods donated to each foodbank was about 20 to 30 servings and consisted of 80% of total donated foods. Only three foodbanks had separate offices for foodbank operation and four institutions had at least one temperature-controlled vehicle. The flow of donated foods was gone through the steps; production, meal service and holding at donator, collection by foodbank, transport (or holding after transport) and distribution to recipients. It took about 3.8 to 6.5 hours at room temperature from after-production to before-distribution. Only aerobic plate counts (APC) and coliforms were found in microbial analysis. The APC after production were relatively high in $8.2{\times}10^5,\;7.4{\times}10^5,\;6.9{\times}10^5$ and $4.2{\times}10^5 CFU/g$ while $2.8{\times}10^6, \;9.4{\times}10^5,\;1.0{\times}10^6$ and $5.4{\times}10^5CFU/g$ before distribution in mixed Pimpinella brachycarpa, mixed chard mixed amaranth and mixed spinach, respectively. The levels of coliforms in mixed chard and mixed spinach were complied with the standards of the Ministry of Education and Human Resources Management The level of APC in boiled pork was increased from $< 1.0{\times}10 CFU/g$ to $4.0{\times}10^2 CFU/g$. One of delivery vessels was shown $6.2{\times}10^3 CFU/100 cm^2$ in APC, which was over the standards for environment. One of serving tables also showed the high level of $1.2{\times}10^3 CFU/100 cm^2$ in APC and $6.6{\times}10^2 CFU/100 cm^2$ in coliforms. These results suggest the sanitary management of holding at donator and the time-temperature control are key factors to ensure the safety of cooked foods donated to foodbank.

• 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 The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.162-177
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• 2020

The perception of traffic environment based on various sensors in autonomous driving system has a direct relationship with driving safety. Recently, as the perception model based on deep neural network is used due to the development of machine learning/in-depth neural network technology, a the perception model training and high quality of a training dataset are required. However, there are several realistic difficulties to collect data on all situations that may occur in self-driving. The performance of the perception model may be deteriorated due to the difference between the overseas and domestic traffic environments, and data on bad weather where the sensors can not operate normally can not guarantee the qualitative part. Therefore, it is necessary to build a virtual road environment in the simulator rather than the actual road to collect the traning data. In this paper, a training dataset collection process is suggested by diversifying the weather, illumination, sensor position, type and counts of vehicles in the simulator environment that simulates the domestic road situation according to the domestic situation. In order to achieve better performance, the authors changed the domain of image to be closer to due diligence and diversified. And the performance evaluation was conducted on the test data collected in the actual road environment, and the performance was similar to that of the model learned only by the actual environmental data.