• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.400-403
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• 2021

Algorithms for predicting the optimal route of vehicles are being actively sudied with the recent development of autonomous driving technology. Companies such as SK, Kakao, and Naver provide services that navigate the optimal route. They predicts the optimal path with information from the users in real time. However, they can predict the optimal route, but not optimal lane route. We proposes a system that navigates the optimal lane path with coordinates data from vehicles using Lidar sensor. The proposed method is a system that guides smooth lanes by acquiring time series coordinate data of a vehicle after performing the Lidar-based object detection method. we demonstrates the performance using actual acquired data from the experimental results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.813-819
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• 2006

Skid Resistance is a index to represent the friction between tire and road surface, which influences driving safety. Skid resistance varies with the conditions of tire, abrasion of road surface, vehicle speed, drying, wet and freezing condition of road surfaces. Especially, freezing occurs when temperature drops below $0^{\circ}C$ followed by snow or rain causes decrease of skid resistance. To recover the decreased skid resistance deicing work is applied. As a results of deicing works, freezing condition is changed into wet condition. However the wet road surfaces containing the remaining deicings agents may not show the skid resistance of normal wet condition. In this study, skid resistances in the condition of freezing, deicing process and deicing agents remained after snow-removal are evaluated. The test results, skid resistance recover quickly when Pre-wetted salt spreading and NaCl was used as deicing method. Skid resistance of Deicing agents remained on the road surface showed that concrete is higher than asphalt. superior effect. Recovery rate of skid resistance by comparison wet condition is 54~80%.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.55-61
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• 2024

In response to the COVID-19 pandemic, the logistics industry in Korea has rapidly been expanding, with offline demand concentrating on online platforms owing to the development of digital infrastructure. This has increased the workload of courier drivers considerably, along with labor intensity. A delivery driver died recently from overwork due to the continuous increase in delivery volume, which raises social concerns. Delivery drivers work long hours, (over 12 hours) and are greatly affected by weather conditions, such as snow, rain, heat waves, and cold waves. In addition, they lack a fixed workplace; perform atypical work handling workpieces of various sizes, weights, and shapes; and spend a large amount of time driving as part of their work. This work involves a high level of tension and requires attention and concentration. Despite the frequency of industrial accidents in the courier industry, studies on safety and health to quantitatively analyze and systematize the work of courier workers are very scarce. Therefore, to define the work process necessary for investigating the harmful factors in delivery service and the work analysis, this study conducted interviews and on-site surveys to analyze the unit work of the delivery service by targeting delivery workers. In other words, a framework of unit work for work analysis was presented to enable research and analysis by considering the aforementioned characteristics of the courier industry. The process was broadly divided into work, transport, storage, delay, and inspection. Work was divided into loading, sorting, unloading, and door subcategories, and transportation was divided into vehicle, cart, and walking subcategories as well as 10 small processes. Moreover, 22 unit works were again drawn by conducting field surveys and interviews. The risk of unit work derived from this study was ergonomically evaluated, and the ergonomic analysis revealed that uploading and transportation were the most dangerous. The results of this study could be used as basic data for preventing industrial accidents among courier workers, whose work has increased with the logistics volume and the development of the logistics industry.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.102-113
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• 2023

With the increasing use of E-scooters, there is an urgent need for research into their driving risks because of the rising number of related accidents. Existing theoretical analysis methods are primarily vehicle-centered and do not adequately reflect the lightweight and compact characteristics of E-scooters. This study was conducted on real roads to analyze the risk and stable speeds of drivers on longitudinal slopes, considering the unique attributes of E-scooters. The risk speed on slopes was, on average, 21 km/h, with the initial risk speed decreasing as the slope became steeper. The stable speed was determined to be an average of 17 km/h, except on slopes of 1-2%, which presented a relatively low risk. These results are expected to contribute to the academic foundation for policies aimed at reducing the top speed of personal mobility, as is currently being promoted in Korea.

• Transactions of Materials Processing
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• v.33 no.2
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• pp.103-111
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• 2024

With the increasing global interest in carbon neutrality, the automotive industry is also transitioning to the production of eco-friendly cars, specifically electric vehicles. In order to achieve comparable driving distances to internal combustion engine vehicles, the application of high-capacity battery packs has led to an increase in vehicle weight. To achieve light-weighting and durability requirements of automotive components simultaneously, there is a demand for research on the application of Ultra-High Strength Steel (UHSS). However, when manufacturing chassis components using UHSS, there are challenges related to fracture defects due to lower elongation compared to regular steel sheets, as well as spring-back issues caused by high tensile strength. In this study, a simulated specimen that is not affected by the property changes of four materials was designed to improve formability of the rear cross member, which is the most challenging automotive chassis component. The influence and correlation of material-specific variables were analyzed through finite element analysis (FEA) for each material with tensile strength of 440, 590, 780, and 980 MPa grades, resulting in the development of a predictive equation. To validate the equation, the simulated specimens of 980 MPa grade were produced from the test molds. Then the reliability of the FEA and predictive equation was verified with measured specimen data using a 3D scanner. The results of this study can be proposed to improve the formability of UHSS chassis components in future researches.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.97-104
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• 2016

In Korea, the number of crash accident victims per 100,000 population is three times higher than the average of OECD. In particular, 60% of it occurs on the community road. Thus, this study intends to analyze the causes of such accidents through a pedestrian and vehicle traffic survey. The purpose is to establish practical safety enhancement measures for community roads. In recent years, lots of changes have occurred in the pedestrian environment. A traffic survey shows that 65% of pedestrians walk on the right and 17% of people use smart-phones while walking. An eye camera experiment shows that the operation load of drivers on the community roads is more than 4 times higher than those in urban roads. According to a speed survey, 62% of vehicles drive at 30km/h or above. The characteristics of accidents on community roads are as follows. First, the ratio of accidents on the edge of the road is 2.3 times as high as those on other roads. Second, when people walk on the right, the ratio of accidents is 2.5 times as high as that of walking on the left. Third, it becomes more dangerous when people cross the road from the right to the left. The majority of accidents is caused by unsafe driving (84.4%). When a vehicle makes a left turn, the likelihood of accidents is 2.3 times as high as those caused by a right turn. The ratio of accidents caused by vehicles going backwards is 14% among all accidents. In community roads, the focus of drivers should be at least 4 times higher than those on urban roads. Thus, walking in the opposite direction of vehicles and careless behaviors are highly likely lead to accidents.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.287-310
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• 2022

Companies' interest in developing AI-based intelligent new products is increasing. Recently, the main concern of companies is to innovate customer experience and create new values by developing new products through the effective use of Artificial intelligence technology. However, due to the nature of products based on radical technologies such as artificial intelligence, intelligent products differ from existing products and development methods, so it is clear that there is a limitation to applying the existing development methodology as it is. This study proposes a new research method based on KANO-TOPSIS for the successful development of AI-based intelligent new products by using car voice assistants as an example. Using the KANO model, select and evaluate functions that customers think are necessary for new products, and use the TOPSIS method to derives priorities by finding the importance of functions that customers need. For the analysis, major categories such as vehicle condition check and function control elements, driving-related elements, characteristics of voice assistant itself, infotainment elements, and daily life support elements were selected and customer demand attributes were subdivided. As a result of the analysis, high recognition accuracy should be considered as a top priority in the development of car voice assistants. Infotainment elements that provide customized content based on driver's biometric information and usage habits showed lower priorities than expected, while functions related to driver safety such as vehicle condition notification, driving assistance, and security, also showed as the functions that should be developed preferentially. This study is meaningful in that it presented a new product development methodology suitable for the characteristics of AI-based intelligent new products with innovative characteristics through an excellent model combining KANO and TOPSIS.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• 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.22 no.6
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• pp.133-144
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• 2004

A model and a measure which can evaluate the risk of rear end collision are developed. Most traffic accidents involve multiple causes such as the human factor, the vehicle factor, and the highway element at any given time. Thus, these factors should be considered in analyzing the risk of an accident and in developing safety models. Although most risky situations and accidents on the roads result from the poor response of a driver to various stimuli, many researchers have modeled the risk or accident by analyzing only the stimuli without considering the response of a driver. Hence, the reliabilities of those models turned out to be low. Thus in developing the model behaviors of a driver, such as reaction time and deceleration rate, are considered. In the past, most studies tried to analyze the relationships between a risk and an accident directly but they, due to the difficulty of finding out the directional relationships between these factors, developed a model by considering these factors, developed a model by considering indirect factors such as volume, speed, etc. However, if the relationships between risk and accidents are looked into in detail, it can be seen that they are linked by the behaviors of a driver, and depending on drivers the risk as it is on the road-vehicle system may be ignored or call drivers' attention. Therefore, an accident depends on how a driver handles risk, so that the more related risk to and accident occurrence is not the risk itself but the risk responded by a driver. Thus, in this study, the behaviors of a driver are considered in the model and to reflect these behaviors three concepts related to accidents are introduced. And safe stopping distance and accident occurrence probability were used for better understanding and for more reliable modeling of the risk. The index which can represent the risk is also developed based on measures used in evaluating noise level, and for the risk comparison between various situations, the equivalent risk level, considering the intensity and duration time, is developed by means of the weighted average. Validation is performed with field surveys on the expressway of Seoul, and the test vehicle was made to collect the traffic flow data, such as deceleration rate, speed and spacing. Based on this data, the risk by section, lane and traffic flow conditions are evaluated and compared with the accident data and traffic conditions. The evaluated risk level corresponds closely to the patterns of actual traffic conditions and counts of accident. The model and the method developed in this study can be applied to various fields, such as safety test of traffic flow, establishment of operation & management strategy for reliable traffic flow, and the safety test for the control algorithm in the advanced safety vehicles and many others.