• The Journal of Bigdata
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• v.5 no.1
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• pp.155-180
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• 2020

It takes the most important role the problem of assigining vehicles and desigining optimal routes for each vehicle in order to enhance the logistics service level. While solving the problem, various cost factors such as number of vehicles, the capacity of vehicles, total travelling distance, should be considered at the same time. Although most of logistics service providers introduced the Transportation Management System (TMS), the system has the limitation which can not consider the practical constraints. In order to make the solution of TMS applicable, it is required experts revised the solution of TMS based on their own experience and intuition. In this research, different from previous research which have focused on minimizing the total cost, it has been proposed the methodology which can enhance the efficiency and fairness of asset utilization, simultaneously. First of all, it has been adopted the Cluster-First Route-Second (CFRS) approach. Based on the location of customers, we have grouped customers as clusters by using four different clustering algorithm such as K-Means, K-Medoids, DBSCAN, Model-based clustering and a procedural approach, Fisher & Jaikumar algorithm. After getting the result of clustering, it has been developed the optiamal vehicle routes within clusters. Based on the result of numerical experiments, it can be said that the propsed approach based on CFRS may guarantee the better performance in terms of total travelling time and distance. At the same time, the variance of travelling distance and number of visiting customers among vehicles, it can be concluded that the proposed approach can guarantee the better performance of assigning tasks in terms of fairness.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.83-106
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• 2021

Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.

• Journal of Navigation and Port Research
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• v.38 no.5
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• pp.549-559
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• 2014

The increasing demand of maritime transportation and port development especially due to increased international trade resulted in a strengthening of regulating the greenhouse gas emissions mainly from ships by International Maritime Organization (IMO). Responding to these international environmental regulation and enforcement, the United States and the European seaports have expanded their Green Port Policy, which can promote the public welfare by reducing pollution caused by ships and ports. Accordingly, in 2010, Korean government enacted "The Framework Act on Low Carbon, Green Growth" and had pushed for all Korean ports to establish and implement their own green port policies. Therefore, the objective of this study is to establish the Green Port Policy Plan for sustainable and environmental friendly operations and developments of Ulsan port, which plans to be the oil hub port of Northeast Asia. To this end, we studied the current status of the environmental policy issues in Ulsan Port and international-&-domestic case studies on establishment of green port policy. With these studies, Ulsan green policy alternatives were identified that through the experts advice, and then were prioritized by adopting AHP survey analysis. As the result of this study, it was notified that LED lights replacement and AMP establishment as the hardware policy and the port environmental management department as the software policy were equally important policy options for the implementation of sustainable Ulsan Green Port Policy to meet port's characteristics.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.83-101
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• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.113-132
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• 2018

Mokpo port marked the $131^{st}$ anniversary of its opening in 2018. while the Mokpo has taken the new port development initiatives, it is limited by inefficient port functioning due to the lack of maritime port policy and government investment. Hence, port logistics has not been activated. Additionally, studies on Mokpo port have not been conducted, and knowledge available on the port is declarative in nature. On the other hand, research on port competitiveness focuses on how to analyze the factors that determine port competitiveness. Therefore, this study was intended to expand the existing research on Mokpo port and conduct an analysis of non-competitiveness factors and suggested improvements by considering the operational aspect of Mokpo port. In this regard the importance of non-competitiveness factors was assessed through an analytic hierarchy process(AHP) analysis and the influence of the non-competitiveness factors was analyzed through an fuzzy structural modeling(FSM) analysis. The result of the AHP analysis show ed the important non-competitiveness factors included the deactivation of industrial complexes around Mokpo port, the number of liner route, the cost of the pilot and tug. Accor ding to the FSM analysis, the top level included the non-competitive factors at Mokpo port; the intermediate level included the number of liner routes, cost of pilot and tug, enrance and clearance fee, costs of inland transportation, fee for port facilities, and loading and unloading costs; and the bottom level comprised the most non-competitive factors including the deactivation of industrial complexes around Mokpo port, hinterland connectivity, access to international port, incentives, and cost of transportation and storage. Based on the results of analysis, improvements were suggested for non-competitive factors of Mokpo.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.7-20
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• 2012

The objective of this paper is to construct pseudo-panel data set and estimate price and income elasticities of car travel demand, using 1995-2007 household income and expenditure survey data, in order to provide quantitative information for analyzing related policy effects in the transport sector. We categorized household survey data into 14 cohorts based on the birth year of the household head. As the result, a total of 133 pseudo-panel data sets was created for estimating price and income elasticities of car travel demand. Especially, price and income elasticities of car travel demand were separately estimated both short-term and long-term. We analyzed the panel model considering fixed effect within cohorts, using explanatory variables such as previous year's fuel consumption, real household income after tax, education level of the household head, the number of children under five, and the share of household type averaged by cohorts. As results, the short-term and long-term price elasticities of car travel demand were calculated as 0.2974-0.4280 and 0.4087-0.6275, respectively. Similarly, the short-term and long-term income elasticities were calculated as 0.3364-0.6281 and 0.7098, respectively.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.29-42
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• 2016

Speeding is an important factor in traffic safety. Speed not only affects crash severity, but is also related to the possibility of crash occurrence. This study presents results from an analysis of 27,968 speed violation cases collected from 36 red light and speed enforcement cameras at signalized intersections in the city of Cheongju. Data included details of their violation history such as speeding tickets within a recent 3-year span and their demographic characteristics. The goal of this analysis is to understand the correlation between speed violations and various factors in terms of humans, vehicles and road environments. This study used descriptive statistics and Binary Logistics Regression(BLR) analysis with SPSS 20.0 software. The major results of this study are as follows. First, speed violations occurred at rural and suburban area. Second, about 25.6% of the violators committed to more than 20km/h over a speed limit. Third, the difference between speed violators and normal drivers clearly appeared in location of intersection(urban/rural/suburban area), gender and age. Finally, a statistically significant model(Hosmer and Lemeshow test: 11.586, p-value: 0.171) was developed through the BLR.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.35-44
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• 2021

In recent times, several studies have been conducted focusing on crashes occurring on the main segment of the highway. However, there is a dearth of research dealing with traffic safety relating to other highway facilities, especially ramp areas. According to the Korea Expressway Corporation's Expressway Information Service, 6,717 crashes have occurred on ramps in the five years from 2015~2019, which accounts for about 15% of all highway accidents. In this study, the simple and full safety performance functions (SPFs) were evaluated and explored using different statistical distributions (i.e., Poisson Gamma (PG) and Poisson Inverse Gaussian (PIG)) and techniques (i.e., fixed effects (FE) and random effects (RE)) to provide more accurate crash prediction models for highway ramp sections. Data on the geometric characteristics of traffic and roadways were collected from various systems and with extensive efforts using a street-view application. The results showed that the PIG models present more accurate crash predictions in general. The results also indicated that the RE models performed better than FE models for simple and full SPFs. The findings from this study offer transportation practitioners using the Korea Expressway Corporation's Expressway a dependable reference to enhance and understand traffic safety in ramp areas based on accurate crash prediction models and empirical evidence.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.121-122
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• 2023

As containerized maritime transport began in earnest, the size of container ships has steadily increased, and recently, the operation of 24,000 TEU-class vessels has become regular. However, concerns about the efficiency and productivity of such mega container ships from a port operational perspective have continued to be raised. The 10^th Busan International Port Conference requested an in-depth study on the trends of container ship enlargement by analyzing the order status of ultra-large container ships from major global liners. Generally, the factor that drives the upsizing of ships is the realization of economies of scale that lowers transportation costs per TEU, which leads to a higher level of cost reduction per unit transportation compared to the increase in fuel consumption due to transporting large amounts of cargo with a single ship. However, it is necessary to examine whether this trend of container vessel enlargement is feasible for port operations. To this end, this study compares and analyzes the productivity and efficeiency of different ship sizes to evaluate the effect of ship size on port operations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.72-73
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• 2023

As containerized maritime transport began in earnest, the size of container ships has steadily increased, and recently, the operation of 24,000 TEU-class vessels has become regular. However, concerns about the efficiency and productivity of such mega container ships from a port operational perspective have continued to be raised. The 10th Busan International Port Conference requested an in-depth study on the trends of container ship enlargement by analyzing the order status of ultra-large container ships from major global liners. Generally, the factor that drives the upsizing of ships is the realization of economies of scale that lowers transportation costs per TEU, which leads to a higher level of cost reduction per unit transportation compared to the increase in fuel consumption due to transporting large amounts of cargo with a single ship. However, it is necessary to examine whether this trend of container vessel enlargement is feasible for port operations. To this end, this study compares and analyzes the productivity and efficeiency of different ship sizes to evaluate the effect of ship size on port operations.