• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.337-351
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• 2018

This paper discusses 5G IOT, Augmented Reality, Cloud Computing, Big Data, Future Autonomous Driving Vehicle technology, and presents 5G utilization of Pyeongchang Winter Olympic Games and Jeju Smart City model. The reason is that 5G is the main artery of the 4th industry.5G is the fourth industrial aorta because 5G is the core infrastructure of the fourth industrial revolution. In order for the AI, autonomous vehicle, VR / AR, and Internet (IoT) era to take off, data must be transmitted several times faster and more securely than before. For example, if you send a stop signal to LTE, which is a communication technology, to a remote autonomous vehicle, it takes a hundredth of a second. It seems to be fairly fast, but if you run at 100km / h, you can not guarantee safety because the car moves 30cm until it stops. 5G is more than 20 gigabits per second (Gbps), about 40 times faster than current LTE. Theoretically, the vehicle can be set up within 1 cm. 5G not only connects 1 million Internet (IoT) devices within a radius of 1 kilometer, but also has a speed delay of less than 0.001 sec. Steve Mollenkov, chief executive officer of Qualcomm, the world's largest maker of smartphones, said, "5G is a key element and innovative technology that will connect the future." With 5G commercialization, there will be an economic effect of 12 trillion dollars in 2035 and 22 million new jobs We can expect to see the effect of creation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.96-106
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• 2014

Necessarily traffic policies have been biased in car than pedestrian, so pedestrian's environment is getting worse. Result of this situation our accident rate is high as 36.4%, compared to OECD member countries with average rate of 17.8%(in 2009). Increasing interest for pedestrians environment improvement, and it make an effort to build environment to guarantee walk and safety of pedestrians. Analysis on the binary logistic regression(BLR) was used. The dependent variable is occurring from the road width of less than 9m accident, and independent variable extracted can be obtained from the traffic accident data. Traffic accident on roads having width of less than 9 meters affecting variables is when the driver is straight, when the driver is female, when the pedestrian is walk driveway, and so on. To prevent it, efforts is demanded to protect handicapped, to build safe pedestrians environment using C-ITS and to decrease speed of going straight vehicle on roads having width of less than 9 meters.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.61-69
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• 2020

This study examined the braking characteristics of a heavy haul freight train with P4a distribution valves applied to domestic high-speed freight trains. A freight train was composed of 50 cars, which is twice the normal operation. A braking test was performed to confirm the characteristics of the braking of a heavy haul. The brake cylinder pressures were measured for emergency and service braking on the 1st, 10th, 20th, 30th, and 50th cars. Because the brake signal is transmitted to the pressure through the braking tube connected to the end of the train, the rear vehicle is braking later than the vehicle ahead. Therefore, it is necessary to predict the brake pressures in all cars in a train to supplement the results of the limited tests and calculate the braking distance. The pressure in each car was determined using empirical models of linear interpolation, stepwise, and exponential models, which provided reliable information. The predictive results of the empirical models were compared with the measured results, and the exponential model was predicted relatively accurately. These results are expected to contribute to the safe operation of heavy haul freight trains and can be used to predict the braking distance and calculate the level of impact between vehicles during braking.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.29-42
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• 2012

Recently, traffic congestion has become serious due to increase of private car usages. Carsharing or other innovative public transportation systems were developed to alleviate traffic congestion and carbon emissions. These measures can make the traffic environment more comfortable, and efficient. Cloud Transportation System (CTS) is a recent carsharing model. User can rent an electronic vehicles with various traffic information through the CTS. In this study, a concept, vision and scenarios of CTS are introduced. And, authors analyzed the location of CTS rental stations and estimated CTS demands. Firstly, we analyze the number of the population, employees, students and traffic volume in study areas. Secondly, the frequency and utilization time are examined. Demand for CTS in each traffic zone was estimated. Lastly, the CTS rental station location is determined based on the analyzed data of the study areas. Evaluation standard of the determined location includes accessibility and density of population. And, the number of vehicles and that of parking zone at the rental station are estimated. The result suggests that Haewoondae Square parking lot would be assigned 11 vehicles and 14.23 parking spaces and that Dongbac parking lot be assigned 7.9 vehicles and 10.29 parking spaces. Further study requires additional real-time data for CTS to increase accuracy of the demand estimation. And network design would be developed for redistribution of vehicles.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.27 no.1
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• pp.13-22
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• 2017

Objectives: The objective of this study was to evaluate the exposure levels of door-to-door deliverers to fine particulate matter (PM2.5). Another objective was to confirm the general working patterns of door-to-door deliverers via survey. Methods: In the city of Daegu, ten door-to-door deliverers who wished to join the study were recruited. The general working characteristics of door-to-door deliverers were surveyed using self-reported questionnaires. In the cabin of each car driven by a deliverer, a real-time PM2.5 sampler (Sidepak, Model AM510, TSI Inc., MN, USA) and a GPS device (GPS 741, Ascen, Korea) were installed. Each deliverer was monitored for four days per week so that each day could be monitored at least four times. Results: A total of 40 measurements of PM2.5 concentrations were taken during delivery of parcels. The average exposure levels of door-to-door deliverers to PM2.5 was $44.62{\mu}g/m^3$ ($7-9443{\mu}g/m^3$. Exposure levels to PM2.5 according to the day of the week and coverage areas were not significantly different (p>0.05). Door-to-door deliverers using trucks with older diesel engines manufactured before 2006 had significantly higher exposure levels to PM2.5 than in the case of trucks with diesel engines manufactured after 2006 (p<0.05). Many of the door-to-door deliverers reported the status of having windows open during the delivery task. During delivery services, the working hours spent in residential areas were higher than on roadsides, but exposure levels to PM2.5 in residential areas and on roadsides were $46.17{\mu}g/m^3$ and $49.90{\mu}g/m^3$, respectively. Real-time PM2.5 exposure levels were significantly different between roadways and residential areas (p<0.001). Conclusions: PM2.5 exposure levels of door-to-door deliverers were found to be affected by higher vehicle emissions from the roadsides near their vehicle during deliveries and while driving to other locations compared to by PM2.5 from the diesel engines of their own trucks. Particle concentrations from roadsides and emissions from nearby vehicles through open windows were the main source of PM2.5.

• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.384-397
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• 2021

Background: With volatile organic compounds (VOCs) containing aromatic and halogenated hydrocarbons such as benzene, toluene, and xylene that can adversely affect the respiratory and cardiovascular systems when a certain concentration is reached, it is important to accurately evaluate the source and the corresponding health risk effects. Objectives: The purpose of this study is to provide scientific evidence for the city of Seoul's VOC reduction measures by confirming the risk of each VOC emission source. Methods: In 2020, 56 VOCs were measured and analyzed at one-hour intervals using an online flame ionization detector system (GC-FID) at two measuring stations in Seoul (Gangseo: GS, Bukhansan: BHS). The dominant emission source was identified using the Positive Matrix Factorization (PMF) model, and health risk assessment was performed on the main components of VOCs related to the emission source. Results: Gasoline vapor and vehicle combustion gas are the main sources of emissions in GS, a residential area in the city center, and the main sources are solvent usage and aged VOCs in BHS, a greenbelt area. The risk index ranged from 0.01 to 0.02, which is lower than the standard of 1 for both GS and BHS, and was an acceptable level of 5.71×10^-7 to 2.58×10^-6 for carcinogenic risk. Conclusions: In order to reduce the level of carcinogenic risk to an acceptable safe level, it is necessary to improve and reduce the emission sources of vehicle combustion and solvent usage, and eco-car policies are judged to contribute to the reduction of combustion gas as well as providing a response to climate change.

• Journal of Climate Change Research
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• v.3 no.2
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• pp.153-159
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• 2012

CFC-12 used in mobile air conditioning(MAC) system has been replaced by R-134a, a type of HFC refrigerant, from 1991 to 1994. R-134a has since been widely used as a refrigerant of a mobile air conditioner. However, it is one of the six main green house gases listed in Kyoto Protocol, which makes it imperative to regulate its emission and develop alternative refrigerants. In this study, the concentration of leaked R-134a was measured using VT(Variable Temperature) shed and Running loss test shed to analyze the level of air conditioner refrigerant leaked in a vehicle. According to the analysis of the concentration of R-134a leaked from a vehicle parked, annual leakage amount of R-134a was in the range of 6.46~13.28 g/yr. The figure was similar with the leakage from the mobile air conditioning system currently used. In a study using the same vehicle model, a vehicle equipped with dual evaporation system had a higher leakage rate of refrigerant than a vehicle with a single evaporation system. It appears that the added fittings and joints of the dual evaporator system led to higher leakage rate. Besides, the analysis of the change in R-134a concentration under various car speed found that more refrigerant leaked under high speed(100km/hr) and but the volume of the wind did not affect to the variation of refrigerant leakage.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• Journal of Service Research and Studies
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• v.11 no.3
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• pp.43-54
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• 2021

This study focused on indoor spaces and convenience devices among vehicle interior designs suitable for the autonomous driving era, and presented an interior design model for future automobiles by applying the STEEP analysis method. The service design methodology is applied to deal with changes in display devices installed for the purpose of rearranging layouts and providing driver-centered information. Changes in types and installation locations of displays for various purposes such as connected and infotainment are expected. In particular, through this analysis, trends and experiences through indoor interior research in future self-driving cars will be studied, and subsequent studies will be used as basic data for actual development and application. Key drivers were extracted after deriving future trends linking the research project conducted in five stages to STEEP and consulting experts through FGI. Through this, it was later presented as a direction for indoor design. Through user-centered participatory design methods, emotional keyword derivation methods were used, summarized the derived drivers in five major trends in the future society, and each derived drivers were grouped to consider the relevant technology fields, and added elements to the autonomous driving level. This is an indoor ray viewed from the perspective of various social issues as well as personal tendencies in the future self-driving car industry.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.709-716
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• 2006

The rapid changes of family structure such as singles, working couples and so on have effects on a travel behaviour. One of the characteristics from this is the increasing portion of trip-chain, in which plural activities were conducted in a "single outgoing" travel. Therefore travel must be considered as location change to conduct various activities instead of pursuing single travel purpose. This paper specifies a behavioral homogeneous person group by a job, a possession of cars. Based on this classification of person groups and their activity diary, the sequence, time and travel mode of activities in a day can be verified. As a case study household survey was conducted in city Kongju. The survey result shows that the classification of behavioral homogeneous person group based on criteria like employment status and car ownership bring a good result to forecast trip generation in traffic zone.