• Spatial Information Research
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• v.22 no.1
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• pp.9-17
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• 2014

This study was intended to reliably predict the traffic green house gas emission in Daegu with the use of spatial statistical technique and calculate the traffic green house gas emission of each administrative district on the basis of the accurately predicted emission. First, with the use of the traffic actually surveyed at a traffic observation point, and traffic green house gas emission was calculated. Secondly, on the basis of the calculation, and with the use of Universal Kriging technique, this researcher set a suitable variogram modeling to accurately and reliably predict the green house gas emission at non-observation point suitable through spatial correlation, and then performed cross validation to prove the validity of the proper variogram modeling and Kriging technique. Thirdly, with the use of the validated kriging technique, traffic green gas emission was visualized, and its distribution features were analyzed to predict and calculate the traffic green house gas emission of each administrative district. As a result, regarding the traffic green house gas emission of each administration, it was found that Bukgu had the highest green house gas emission of $291,878,020kgCO_2eq/yr$.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.1-10
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• 2011

According to the worldwide efforts to reduce greenhouse gases consequent upon climatic change, the field of road traffic is also making diverse efforts to reduce the emissions of greenhouse gases. Among these, the exhaust gases from vehicles, the so-called main culprit of the greenhouse gases will take place the more as delay and tie-up of vehicles ever take place. Accordingly, as a scheme for reducing the delay & tie-up of vehicles, it's possible to bring up the idea of supply of new facilities and management of the existing facilities; recently, a lot more focus is being put on the management of the existing facilities due to enormous amounts of construction cost. In the midst of growing concern for traffic demand management policy, it's about the time we should do research on the tollbooth metering on the expressway whose research is almost non-existent home and abroad. As a traffic demand management policy coming to happen in case of the management of pay expressway like Japan and Korea, this research analyzed the contents of tollbooth metering, its effect and its subsequent convenience. Especially as a tool for effect analysis, this research made an analysis using VISSIM-a micro-simulation tool. As the tollbooth metering promoted, as a part of green traffic promotion strategy, is expected to contribute to improvement in traffic flow and reduction in carbon emissions, etc. It seems that there needs to be continuous research work on the management plan & revitalization plan for maximization of its effect later as well.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.79-88
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• 2024

We used actual field data to analyze from a traffic engineering perspective how AI and edge computing technologies affect the reduction of traffic accidents. By providing object information from 20m behind with AI object recognition, the driver secures a response time of about 3.6 seconds, and with edge technology, information is displayed in 0.5 to 0.8 seconds, giving the driver time to respond to intersection situations. In addition, it was analyzed that stopping before entering the intersection is possible when speed is controlled at 11-12km at the 10m point of the intersection approach and 20km/h at the 20m point. As a result, it was shown that traffic accidents can be reduced when the high object recognition rate of AI technology, provision of real-time information by edge technology, and the appropriate speed management at intersection approaches are executed simultaneously.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.149-158
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• 2002

For the purpose of preciously describing real time traffic pattern in urban road network, dynamic network loading(DNL) models able to simulate traffic behavior are required. A number of different methods are available, including macroscopic, microscopic dynamic network models, as well as analytical model. Equivalency minimization problem and Variation inequality problem are the analytical models, which include explicit mathematical travel cost function for describing traffic behaviors on the network. While microscopic simulation models move vehicles according to behavioral car-following and cell-transmission. However, DNL models embedding such travel time function have some limitations ; analytical model has lacking of describing traffic characteristics such as relations between flow and speed, between speed and density Microscopic simulation models are the most detailed and realistic, but they are difficult to calibrate and may not be the most practical tools for large-scale networks. To cope with such problems, this paper develops a new DNL model appropriate for dynamic traffic assignment(DTA), The model is combined with vertical queue model representing vehicles as vertical queues at the end of links. In order to compare and to assess the model, we use a contrived example network. From the numerical results, we found that the DNL model presented in the paper were able to describe traffic characteristics with reasonable amount of computing time. The model also showed good relationship between travel time and traffic flow and expressed the feature of backward turn at near capacity.

• Horticultural Science & Technology
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• v.34 no.1
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• pp.195-205
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• 2016

Sugar beet cyst nematode, Heterodera schachtii, causes serious economic losses worldwide in Brassicaceae crops. In 2011, this nematode was first found in highland vegetable cultivation areas in Korea, and thereafter spread to the surrounding healthy Chinese cabbage fields. However, little has been documented on the biological and ecological characteristics of the sugar beet nematode in highland vegetable cultivation areas. In this study the dispersal of the sugar beet cyst nematode was examined, focusing on spreading through soil and/or water infested with the nematode. When farmers with work boots trampled on Chinese cabbage fields for 10 minutes, the number of cysts recovered from the soil attached to the working differed depending on the research sites. Under irrigation conditions of 2, 4, and 8 liters of water per $m^2$, the amounts of soils attached on the bottom of the work boots and the number of healthy cysts in the soils increased significantly with the increase in soil moisture, although the total number of cysts, eggs, and juveniles did not increase significantly. After driving on the farm road adjacent to cabbage fields infested with the sugar beet cyst nematode, cysts were also recovered from the soil attached to the vehicle's tires, suggesting that the sugar beet cyst nematode can spread to new fields through soil carried by vehicles and by farmers. An excavator and a motor truck could deliver 41 kg and 224 g, respectively, of soil on the shovel shoes and the wheels to other locations during the Chinese cabbage harvest, suggesting that farming equipment and transportation vehicles may be vital means by which the cyst nematode spreads to non-infested fields in the highland area of Korea. Runoff water also contained cysts, whose amounts increased after water irrigation onto the ridges to simulate rainy conditions, with no significant difference in the number of cysts with increasing amounts of irrigation water. All of these results confirmed that the sugar beet cyst nematode spreads through soil attached to work boots, harvesting tools, and transportation vehicles, especially during the harvest time, and through runoff water on rainy days. These observations suggest that personal sanitization and cleaning of working tools and vehicles are one of the most important means to prevent the dispersal of the sugar beet cyst nematode in fields.