• Korea Trade Review
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• v.45 no.4
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• pp.137-152
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• 2020

The increase in national income, the expansion of transportation network, the increase in leisure time, and the influx of foreign tourists in the era of internationalization, the influx of the outside population of Jeju region increased rapidly until 2020. However, the corona 19 (Covid-19) incident that began in January 2020 has hit the entire industry, and the tourism industry in Jeju has also been greatly damaged. However, in the second half of 2020, with some calming of the Corona 19 situation and difficult to leave overseas, the number of visitors to Jeju Island is increasing again as Koreans choose Jeju Island as their domestic tourism. This study analyzed the capacity of Jeju's external population based on the Contingent Valuation Method, and based on this, attempted to suggest policy recommendations for Jeju. The size of accommodations such as the density of visitors, toilets, and rest areas were excluded from consideration, and the level of securing the parking lot already exceeded the capacity, and the rate of securing the parking lot was 93.4%. In the case of accommodation, the total number of available rooms is 88,691, even if one guest per room is assumed, which is 32,372,215 per year, which is sufficient in terms of visitor capacity. To analyze the aspects of psychological capacity, this study analyzed whether the residents are feeling psychological discomfort through three methods of road congestion, garbage disposal, and sewage treatment through Contingent Valuation Method. However, the inconvenience caused by the increase of visitors and the effect of continuous population influx is working in combination, and it has the limitation that the effects of these independent factors cannot be specifically separated. As a result of the study, discomfort has already been recognized in terms of psychological capacity among the factors of capacity, and it was estimated that a cost of about 45 billion won per year was incurred as a result of deriving psychological costs through Contingent Valuation Method. In the future, a policy review is needed to resolve or maintain the perception of this discomfort through continuous management. Accordingly, it is necessary to recognize that the increase of visitors leads to the psychological discomfort of the residents, and to seek a policy alternative that can simultaneously increase the number of visitors and the comfort of the residence.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.305-316
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• 2013

To find out if modern roundabout is still effective under drivers behavior and driving conditions in Busan Metropolitan City, the effects before and after introduction of roundabout were analyzed. According to analysis on velocity profile at roundabout, velocity deviation decreased, and average vehicle speed was close to design speed. As a result, it has been confirmed that most roundabouts were properly built. In terms of traffic operation, average vehicle speed improved by 87.2% when a traffic intersection was replaced by a roundabout. therefore, it has been found out that the introduction of roundabout has a positive effect on increasing vehicle speed by reducing traffic congestion. In addition, annual benefits expected from the replacement from a traffic intersection to a roundabout were KRW 872 million as follows; KRW 410 million in traffic communication, KRW 39 million in transportation safety, KRW 255 million in energy saving, KRW 95 million in reduction of air pollution and KRW 73 million in reduction of traffic signal installation cost. In other words, if 10% (193 spots) of all traffic intersections (1,926 spots in total) in Busan City are replaced by roundabouts, the municipal authority would be able to save about KRW 168.3 billion. According to analysis on the benefits expected from the installation of roundabouts compared to the investment cost for traffic intersections, about KRW 679 million could be saved per roundabout. Considering 10% of all traffic intersections in the City of Busan, about KRW 131 billion could be saved annually. The traffic accidents in roundabout usually occur because drivers aren't aware of right-of-way rules. Once the right-of-way rules settle, the number of traffic accidents would significantly decrease. In addition, it is urgent to promote education and campaign for drivers, pedestrians and bikers on the roundabout.

• Journal of Korean Society of Transportation
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• v.17 no.4
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• pp.99-110
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• 1999

With a growing awareness, transportation is the maior source of urban air pollution. Planners and policy-makers are strongly urged to care the impacts of transportation management strategies on environment. Since transport-related air Pollution can be regarded as negative externalities of transport, it is indispensable to evaluate chanties in air quality which seems to occur when proposed transport measures are implemented. In addition, transport measures should be integrated in a set of combined Paradigm regarding transport and environment. Based on the integrated Paradigm between transportation demand management(TDM) and environmental planning, the main focus is given to apply environment cost internalizing measures to the short-term congestion management Program(SCMP) in Seoul, that has been developed in 1998 by Seoul Development Institute. Three modules are analyzed: without and/or with ￦500, ￦1000 emission plus gas tax, respectively. From the empirical applications on Seoul city, one of the most exemplary findings in SCMP program is that, emission plus gas tax can be a very useful measure to reduce vehicular emissions by targeting major Pollutants differently, rather than by dealing with pollutants collectively. Further research that provides (1)showing the spatial variation of pollution levels along the intersections, (2)more developing combined Paradigm between transport, land use, and environment, (3)using environmental road capacity rather than Physical-aspects of road capacity, and (4)continuing R&D on air quality constrained TDM, can contribute significantly to applications of the real and efficient environment-constrained transportation planning.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.