• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.76-95
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• 2019

An on-board truck scale is an essential technical solution for preventing overload, which makes the driver aware of the commercial vehicle weight. This study analyzed the effects of the driving pattern and transportation efficiency by the IoT Platform service for an on-board truck scale. A comparison of before and after installation using the long-term monitored data confirmed the reduction effects both of the overload ratio and overweight value, and their effects on increasing the transportation efficiency. In addition, the analysis result of the driving route showed that the installation of an on-board truck scale could be a more effective way of preventing overload than increasing the weighing checkpoints.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.153-172
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• 2018

Overloading of Commercial vehicles have been an important area of transportation as one of the main causes of pavement damage, bridge collapse, severe traffic accident, etc. In this study, we analyzed the effects of overweight prevention by analyzing overweight driving patterns and using weight sensors. First, we analyzed relevant literatures of overweight and surveyed the commercial weight sensors. Then we chose the typical type of overweight vehicles based of overweight enforcement data analysis. MEMs inclinometer weight sensor were installed to 10 test vehicles and data was collected by weight sensors and gps in real time. As a result of gross vehicle weight and axle weight analysis, it was found weight sensor could decrease overweight rate. However, since the number of samples of test vehicles is insufficient to represent the whole commercial vehicle, further studies are deemed possible through the extension test.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.287-288
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• 2019

본 논문에서는 대용량 화물 DTG 데이터 분석을 위한 빅데이터 플랫폼을 설계 및 구현한다. DTG(digital tacho graph)는 차량운행기록을 실시간으로 저장하는 장치로서, 차량의 GPS, 속도, RPM, 제동유무, 이동거리 등 차량운행 관련 데이터가 1초 단위로 기록된다. 차량 운행 패턴 및 분석을 하기 위해서는 DTG 데이터의 빠른 처리가 필수적이며, 특히 대용량 DTG 데이터를 가공 및 변환하기 위해서는 별도의 플랫폼이 필요하다. 본 논문에서는 오픈소스 기반의 빅데이터 프레임워크인 스파크(Spark)를 이용하여 대용량 화물 DTG 데이터의 전처리 플랫폼을 구현하였다. 실제 대용량 화물 DTG 데이터를 대상으로 데이터를 변환 및 지도상에 표현해 보인다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.74-87
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• 2020

Overloaded trucks are the main source that threatens road safety and directly affects the reduction of pavement life. The On-board truck scale is the only equipment that could prevent overloading by measuring and adjusting the loading weight before driving. Legislation is needed to encourage its installation so that the driver can prevent overloading. In this study, an on-board truck scale system was installed on 30 dump trucks for transporting construction waste, such as soil and aggregates, which are major loads of 36.55% for overloading, and the trucks were monitored remotely. The overload prevention effect was analyzed by comparing driving data for 1 month before distribution of the weight display app that can recognize the weight to the driver and 1 month after distribution. After installation, overloading could be 6.1% reduced, and the transportation efficiency could be increased by checking the weight provided from the On-board truck scale system.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.4
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• pp.540-552
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• 2011

Freight travel pattern has been less studied comparing with the field of passenger travel. Nonetheless, the importance of the freight travel has been increasing in urban travel sector, and the research needs on the freight travel demand hence is increasing. The current paper aims to identify, by tons of freight trucks and cargos, the characteristics of mean travel pattern, efficiency or performance, and the characteristics of freight trip chain regarding destination location, destination type and freight type. The study analyzed the nation-wide data of freight travel behavior survey. This study intended to set the starting framework of decision-making principle in freight travel, which has already been popular in passenger travel study. Findings suggest that those characteristics are clearly distinguished among trucks and cargos of different sizes of tons. The results are expected to provide important insight to the development of relevant transportation policy measures.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.67-74
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• 2019

In this paper, we design and implement an analytics platform based on bulk cargo DTG data for crackdown on overloaded trucks. DTG(digital tachograph) is a device that stores the driving record in real time; that is, it is a device that records the vehicle driving related data such as GPS, speed, RPM, braking, and moving distance of the vehicle in one second unit. The fast processing of DTG data is essential for finding vehicle driving patterns and analytics. In particular, a big data analytics platform is required for preprocessing and converting large amounts of DTG data. In this paper, we implement a big data analytics framework based on cargo DTG data using Spark, which is an open source-based big data framework for crackdown on overloaded trucks. As the result of implementation, our proposed platform converts real large cargo DTG data sets into GIS data, and these are visualized by a map. It also recommends crackdown points.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.89-97
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• 2004

The Korea Air Force(KAF) has operated freight flights based on the prefixed time and route schedule, which is adjusted once in a month. The major purpose of the operation of freight flights in the KAF is to distribute necessary supplies from the home air base to other air bases. The secondary purpose is to train the young pilots to get more experiences in navigation. Each freight flight starts from and returned to the home air base everyday except holidays, while it visits several other air bases to accomplish its missions. The study aims to forecast freight demand at each base by using time series analysis, and then it tried to optimize the cost of operating flights by solving vehicle routing problem. For more specifically, first, several constraints in operating cargos were defined by reviewing the Korea Air Force manuals and regulation. With such constraints, an integer programming problem was formulated for this specific routing problem allowing several visits in a tour with limitation of maximum number of visits. Then, an algorithm to solve the routing problem was developed. Second, the time series analysis method was applied to find out the freight demand at each air base from the mother air base in the next month. With the forecasted demands and the developed solution algorithm, the oprimum routes are calculated for each flight. Finally, the study compared the solved routing system by the developed algorithm with the existing routing system of the Korea Air Force. Through this comparison, the study proved that the proposed method can provide more (economically) efficient routing system than the existing system in terms of computing and monetary cost. In summary, the study suggested objective criteria for air routing plan in the KAF. It also developed the methods which could forecast properly the freight demands at each bases by using time series analysis and which could find the optimum routing which minimizes number of cargo needed. Finally, the study showed the economical savings with the optimized routing system by using real case example.