• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.91-97
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• 2023

Ensuring the safe arrival of delivery cargo at its intended destination is of utmost importance. Truck drivers play a crucial role in guaranteeing the secure delivery of cargo without any mishaps. However, there are various factors that may lead to delayed arrival of trucks at their destination, such as late departures or prolonged loading operations. The timely departure of cargo transportation is contingent upon several variables, including the driver's experience, cargo volume, and loading time. If the transportation commencement is delayed, it may increase the risk of accidents due to an elevated operating speed. Consequently, we conducted a study to investigate the correlation between cargo loading time, cargo volume, driving experience, and the likelihood of accidents. Our findings indicate that both cargo volume and driver experience can impact the likelihood of vehicle accidents. Furthermore, all factors can have an interactive effect on the occurrence of accidents. However, extending the loading time may mitigate the impact on the likelihood of accidents.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.513-516
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• 2013

Earthmoving equipment's haul-route has a great influence on the productivity of the earth work operation. Haul-route grade is a critical factor in selecting the haul-route. The route that has low grade resistance contributes to increase machine travel speed and production. This study presents a mathematical model called "Hauling-Unit Optimal Routes Selecting system" (HUORS). The system identifies optimal path that maximize the earth-work productivity. It consists of 3 modules, i.e., (1) Module 1 which inputs site characteristic data and computes site location and elevation using GIS(Geographical Information System); (2) Module 2 which calculates haul time; (3) Module 3 which displays an optimum haul-route by considering the haul-route's gradient resistances (i.e., from the departure to the destination) and hauling time. This paper presents the system prototype in detail. A case study is presented to demonstrate the system and verifies the validity of the model.

• The Korean Journal of Food & Health Convergence
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• v.8 no.6
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• pp.11-17
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• 2022

Emergency transport is directly related to the life of the patient, and rapid transport to the hospital is crucial. However, external environmental factors such as traffic or weather, interfere with hospital transport. In this study, we investigated the external environment affecting hospital transport time. We examined the transfer time and patient treatment time of emergency patients in an area of northern Gyeonggi-do from 2018 to 2020. Diagnosis after arrival at the hospital was used, and on-site treatment time was measured from paramedic arrival time at the scene to departure. Furthermore, we examined whether there was a correlation between the time paramedics left the scene and hospital arrival time through the reason for the delay as recorded in the emergency log. Traffic jams had the greatest impact on patient transport, while transport delays occurred due to heavy rain, but not snow. Among injured patients, electrical accidents were the most problematic in terms of on-site treatment time. This was because a lot of first aid is needed in electrical accidents. It must be necessary to mobilize two ambulances in an emergency through the expansion of infrastructure, prepare a plan for rapid transport in heavy rain, and implement strong laws against transport obstruction.

• Industrial Engineering and Management Systems
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• v.12 no.3
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• pp.281-287
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• 2013

In this paper, we introduce a roots method that uses the roots inside the unit circle of the associated characteristics equation to evaluate the steady-state system-length distribution at three epochs (pre-arrival, arbitrary, and post-departure) and sojourn-time distribution in GI/PH/1 queueing model. It is very important for an air base to inspect airplane oil because low-quality oil leads to drop or breakdown of an airplane. Since airplane oil inspection is composed of several inspection steps, it sometimes causes train congestion and delay of inventory replenishments. We analyzed interarrival time and inspection (service) time of oil supply from the actual data which is given from one of the ROKAF's (Republic of Korea Air Force) bases. We found that interarrival time of oil follows a normal distribution with a small deviation, and the service time follows phase-type distribution, which was first introduced by Neuts to deal with the shortfalls of exponential distributions. Finally, we applied the GI/PH/1 queueing model to the oil train congestion problem and analyzed the distributions of the number of customers (oil trains) in the queue and their mean sojourn-time using the roots method suggested by Chaudhry for the model GI/C-MSP/1.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.189-198
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• 1999

The purpose of this paper is to develop a knowledge-based real-time decision support system to support decision makers for efficient berth operation of Inchon Port. In these days the berth operation problems have been many studied. The berth operation rules differ from port to port and the problem is highly dependent on natural geographical and operational environment of port. In Inchon Port the ship’s entrance into port and departure from port is extremely affected status of dock. In this paper we analyzed some effects of dock a specific character of Inchon Port with a real data of ship’s in Inchon Port. And reconstruct a previous expert’s knowledge of berth allocating problem in Inchon Port. Also the mechanism for the efficient berth operation has been studied by repeatedly dispatching in order to obtain a best effect of berth allocation, with real-time updated information for delay at service time of a specific berth and changing of a working-berth. The system is developed with graphic user interface(GUI) concept using user interactive approach. And this system will be provide decision support maker with an efficient and fast way to berth allocating and reduce wastes of time space and manpower in Inchon Port operation.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.90-94
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• 2022

In order to minimize the picking time when the products are released from the warehouse, they should be located close to the exit when the products are released. Currently, the warehouse determines the loading location based on the order of the requirement of products, that is, the frequency of arrival and departure. Items with lower requirement ranks are loaded away from the exit, and items with higher requirement ranks are loaded closer from the exit. This is a case in which the delivery time is faster than the products located near the exit, even if the products are loaded far from the exit due to the low requirement ranking. In this case, there is a problem in that the transit time increases when the product is released. In order to solve the problem, we use the idle time of the stocker in the warehouse to rearrange the products according to the order of delivery time. Temporal difference learning method using Q_learning control, which is one of reinforcement learning types, was used when relocating items. The results of rearranging the products using the reinforcement learning method were compared and analyzed with the results of the existing method.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.3
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• pp.487-500
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• 1997

In this paper, we introduce the shortest flow-generating path problem in the generalized network. As the simplest generalized network model, this problem captures many of the most salient core ingredients of the generalized network flows and so it provides both a benchmark and a point of departure for studying more complex generalized network models. We show that the generalized label-correcting algorithm for the shortest flow-generating path problem has O(mn) time complexity if it starts with a good point and also propose an O($n^3m^2$) algorithm for finding a good starting point. Hence, the shortest flow-generating path problem is solved in O($n^3m^2$) time.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.187-192
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• 2017

Autonomous driving vehicle research demands complex road and lane understanding such as lane departure warning, adaptive cruise control, lane keeping and centering, lane change and turn assist, and driving under complex road conditions. A fast and robust road lane detection subsystem is a basic but important building block for this type of research. In this paper, we propose a method that performs road lane detection from black box input. The proposed system applies Random Sample Consensus to find the best model of road lanes passing through divided regions of the input image under HSV color model. HSV color model is chosen since it explicitly separates chromaticity and luminosity and the narrower hue distribution greatly assists in later segmentation of the frames by limiting color saturation. The implemented method was successful in lane detection on real world on-board testing, exhibiting 86.21% accuracy with 4.3% standard deviation in real time.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.9-14
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• 2018

A road recognition system or Lane departure warning system is an early stage technology that has been commercialized as early as 10 years but can be optional and used as an expensive premium vehicle, with a very small number of users. Since the system installed on a vehicle should not be error prone and operate reliably, the introduction of robust feature extraction and tracking techniques requires the development of algorithms that can provide reliable information. In this paper, we investigate and analyze various real-time road detection algorithms based on color information. Through these analyses, we would like to suggest the algorithms that are actually applicable.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.79-103
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• 1995

The elasticity of a model is considered most important. Without showing the proper elasticity any model cannot provide useful information for decision making. This paper demonstrates a macro model which can generate dynamic transport informations every 15 minutes. Without the Wardrop principles and the monotonicity assumptions for the link travel time and link volume relationship, the basic elements of this new modeling approache are composed of link density simulation, stochastic incremental route choice, departure time choice, destination choice and mode choice. The elasticity of the proposed model is examined based on elasticity equations and simulation results. Also the transferability from a mega city like Seoul to a big city like Daejon is demonstrated for the choice model. The issues centering around the dynamic relations among density(k), speed(u), and flow rate(v) are also discussed for the modeling of highly congested situations.