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Methodology for Developing a Predictive Model for Highway Traffic Information Using LSTM (LSTM을 활용한 고속도로 교통정보 예측 모델 개발 방법론)

  • Yoseph Lee;Hyoung-suk Jin;Yejin Kim;Sung-ho Park;Ilsoo Yun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.1-18
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    • 2023
  • With the recent developments in big data and deep learning, a variety of traffic information is collected widely and used for traffic operations. In particular, long short-term memory (LSTM) is used in the field of traffic information prediction with time series characteristics. Since trends, seasons, and cycles differ due to the nature of time series data input for an LSTM, a trial-and-error method based on characteristics of the data is essential for prediction models based on time series data in order to find hyperparameters. If a methodology is established to find suitable hyperparameters, it is possible to reduce the time spent in constructing high-accuracy models. Therefore, in this study, a traffic information prediction model is developed based on highway vehicle detection system (VDS) data and LSTM, and an impact assessment is conducted through changes in the LSTM evaluation indicators for each hyperparameter. In addition, a methodology for finding hyperparameters suitable for predicting highway traffic information in the transportation field is presented.

The Influences of Speed desire frustration on Driving Stress (운전자의 속도 욕구좌절이 운전 스트레스에 미치는 영향)

  • Soon yeol Lee ;Soon chul Lee
    • Korean Journal of Culture and Social Issue
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    • v.15 no.2
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    • pp.319-338
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    • 2009
  • This study was intended to recognize whether speed desire frustration influences in driving stress. Stress desire frustration is the difference between prefer speed and normal speed. As a result, driver's the prefer speed is higher than the normal speed on 4 road condition(high-way, urban-way, residential-way, rural-way). Also, driver's speed desire frustration caused statistical effect in driving stress on 4 road condition. speed desire frustration effect Driving Stress Scale(DSS) 5 sub-scale factors(progress obstacle, traffic circumstance, accident & regulation, regulation obedience, time pressure). This is that driver who experience much speed desire frustration creates high driving stress. Speed desire frustration analyzed high driver and low driver's Driving Stress Scale(DSS) score and overspeed regulation and traffic accident experience difference. As analysis result, speed desire frustration high driver driving stress high appear. However, difference of overspeed regulation experience or traffic accident experience by speed desire frustration did not appear.

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Accident Risk Consequences Analysis for Operating a Hydrogen Refueling Station in Urban Railway Site (도심 내 철도부지 수소충전소 운영을 위한 사고 위험 영향 분석)

  • Jae Yong Lee;Deokkyu Youn;Chul-Ho Lee;Jaeyoung Lee
    • Journal of the Korean Institute of Gas
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    • v.27 no.4
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    • pp.70-77
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    • 2023
  • In response to climate change, each country is proposing a goal to reduce greenhouse gases in its energy supply and demand plan, and the use of hydrogen gas is a topic that is always prioritized as an energy resource for implementation. A popular way to use this hydrogen gas is the use of hydrogen fuel cell vehicles, and expansion of hydrogen charging stations is essential for using these hydrogen fuel cell vehicles. However, there are several limitations to the expansion of hydrogen refueling stations, the most representative of which is resident acceptance. Most of the hydrogen charging stations currently built in Korea are located in the outskirts with low population density, so the inconvenience to hydrogen fuel cell vehicle users has not been resolved, and as a result, there has been no progress in the spread of hydrogen fuel cell vehicles. In this paper, we analyzed the consequences of accident damage to determine the risks of constructing a hydrogen charging station on a railroad site frequently used by citizens. The target hydrogen charging station site was a railroad depot in Busan, and there are trains, national highways, and commercial facilities around this site. Assuming the worst-case scenario, we would like to consider the safety of the hydrogen refueling station site by analyzing the area affected by the accident and its consequence.

Effect of Compensation for Thickness Reduction by Chemical Degradation of PEMFC Membrane on Performance and Durability (PEMFC 고분자막의 화학적인 열화에 의한 두께 감소 보정이 성능 및 내구성에 미치는 영향)

  • Sohyeong Oh;Yoojin Kim;Seungtae Lee;Donggeun Yoo;Kwonpil Park
    • Korean Chemical Engineering Research
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    • v.62 no.1
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    • pp.1-6
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    • 2024
  • As the demand for hydrogen electric vehicles for commercial vehicles increases, the durability of PEMFCs must increase more than five times that of passenger cars, so research and development to improve durability is urgent. When the PEMFC membrane electrode assembly (MEA) undergoes chemical degradation, the MEA thickness decreases and pinholes occur. In this study, changes in the performance and durability of the MEA were measured while increasing the clamping pressure of the unit cell after open circuit voltage (OCV) holding, an accelerated chemical degradation experiment. As the clamping pressure increased, the resistance of the polymer membrane and the membrane/electrode contact resistance decreased, improving the I-V performance and reducing the hydrogen permeability. As the hydrogen permeability decreased, the OCV increased. When the pinhole area was removed and the MEA clamping pressure was increased, the hydrogen permeability decreased sharply, confirming that the local degradation has a large effect on the performance and durability of the entire cell. When the pinhole was removed and re-clamping and OCV holding was evaluated, it was confirmed that the durability improved according to the decrease in membrane resistance and hydrogen permeability.

Research on Overheating Prediction Methods for Truck Braking Systems (화물차의 제동장치에서 발생하는 과열 예측방안 연구)

  • Beom Seok Chae;Young Jin Kim;Hyung Jin Kim
    • Smart Media Journal
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    • v.13 no.6
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    • pp.54-61
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    • 2024
  • Recently, due to the increase in domestic and international online e-commerce platforms and the increase in container traffic at domestic ports, the operating ratio of large trucks has increased, and the number of truck fires is continuously increasing. In particular, spontaneous combustion is the most common cause of truck fires. Various academic approaches have been attempted to prevent truck fires, but due to the lack of research on the spontaneous tire ignition phenomenon that occurs during braking, this research directly designed and manufactured an experimental device to establish an environment similar to the braking system of a truck. A non-contact temperature sensor was installed on the brake device of the experimental device to collect temperature data generated from the brake device. Based on the data collected from the temperature sensor of the brake device and the temperature sensor on the tire surface, the ARIMA model among the time series prediction models was used to Appropriate parameters were selected to suit the temperature change trend, and as a result of comparing and analyzing the measured and predicted data, an accuracy of over 90% was obtained. Based on this, a plan was proposed to reduce the rate of fires in trucks by providing real-time warnings and support for truck drivers to respond to overheating phenomena occurring in the braking system.

Analyzing the Effects of Low Emission Bus Zones Using Bus Information System Data (버스정보시스템 데이터를 활용한 Low Emission Bus Zone 도입의 탄소배출 저감 효과 분석)

  • Hye Inn Song;Kangwon Shin
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.6
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    • pp.196-207
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    • 2023
  • As part of measures to address the climate crisis, buses are also being converted to electric and hydrogen buses. Local authorities need to prioritize carbon emissions when allocating newly introduced and converted electric and hydrogen buses, and as a method, consider the introduction of Low Emission Bus Zones (LEBZ) to propose the reduction of pollution from specific links. To introduce LEBZ, it is necessary to compare the carbon emissions before and after its implementation, yet there is a shortage of studies that focus solely on buses or analyze the effects of introducing LEBZ to specific links. In this paper, we utilized bus information system data to calculate and compare the effects of introducing LEBZ to bus priority lanes in Jeju. We categorized scenarios into five groups, with scenarios 1 through 4 involving the introduction of LEBZ, and scenario 5 designating cases where LEBZ was not introduced. Comparative results confirmed that in scenarios with LEBZ introduction, the reduction per km reached a maximum of 0.097t per km, whereas in cases without LEBZ, it amounted to 0.022t per km, demonstrating higher efficiency. It underscores the significance of conducting carbon emission calculations and comparing the effects of LEBZ introduction using bus information system data, which can be directly applied by local authorities to make informed and rational decisions.

Open Innovation in Car-Sharing Industry: Focusing on the Cooperation Case between Gongcar and Rental Car Company (카셰어링 산업의 개방형 혁신: (주)공카와 렌터카 업체간 개방형 혁신 사례를 중심으로)

  • Kiyeon Hwang;Jaehong Park;Youngwoo Sohn;Woosung Nam;Yeonhwa Cho
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.1
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    • pp.93-105
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    • 2024
  • Car-sharing is a representative model of the sharing economy, and it is a service that rents or uses a car for the necessary time without owning a car. This industry is growing due to various factors such as technological advances, increasing awareness of environmental protection, and increasing demand for solving traffic congestion problems in cities. Accordingly, there is a need for a strategic approach for companies providing car-sharing services to respond quickly to market changes in order to expand market share and differentiate services. Accordingly, this study conducted a case study on open innovation activities between Gongcar and existing rental car companies, focusing on the research question "What effects do open innovation activities between car-sharing companies and existing rental car companies cause?" As a result of the study, it was confirmed that Gongcar have (1) the ability to actively respond to market fluctuations by establishing a flexible vehicle supply chain based on demand, (2) have significantly reduced growth capital expenditure (Growth Capex), and both cafe and rental car companies have (3) performed successful open innovation by improving key KPI indicators and recording financial performance. This study reveals how open innovation acts as a key business growth engine in the car-sharing industry, and its significance is found in that it empirically confirmed the successful implementation conditions of open innovation based on resource dependence theory.

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Full-waveform Inversion of Ground-penetrating Radar Data for Deterioration Assessment of Reinforced Concrete Bridge (철근 콘크리트 교량의 열화 평가를 위한 지표투과레이더 자료의 완전파형역산)

  • Youngdon Ahn;Yongkyu Choi;Hannuree Jang;Dongkweon Lee;Hangilro Jang;Changsoo Shin
    • Journal of the Korean GEO-environmental Society
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    • v.25 no.2
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    • pp.5-14
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    • 2024
  • Reinforced concrete bridge decks are the first to be damaged by vehicle loads and rain infiltration. Concrete deterioration primarily occurs owing to the corrosion of rebars and other metal components by chlorides used for snow and ice melting. The structural condition and concrete deterioration of the bridge decks within the pavement were evaluated using ground-penetrating radar (GPR) survey data. To evaluate concrete deterioration in bridges, it is necessary to develop GPR data analysis techniques to accurately identify deteriorated locations and rebar positions. GPR exploration involves the acquisition of reflection and diffraction wave signals due to differences in radar wave propagation velocity in geotechnical media. Therefore, a full-waveform inversion (FWI) method was developed to evaluate the deterioration of reinforced concrete bridge decks by estimating the radar wave propagation velocity in geotechnical media using GPR data. Numerical experiments using a GPR velocity model confirmed the deterioration phenomena of bridge decks, such as concrete delamination and rebar corrosion, verifying the applicability of the developed technology. Moreover, using the synthetic GPR data, FWI facilitates the determination of rebar positions and concrete deterioration locations using inverted velocity images.

Selection of Evaluation Metrics for Grading Autonomous Driving Car Judgment Abilities Based on Driving Simulator (드라이빙 시뮬레이터 기반 자율주행차 판단능력 등급화를 위한 평가지표 선정)

  • Oh, Min Jong;Jin, Eun Ju;Han, Mi Seon;Park, Je Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.44 no.1
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    • pp.63-73
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    • 2024
  • Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.

Assessment of the Non-point Source Pollution Control Strategies for Water Quality Improvement in the Haeban Stream of West Nakdong River Watershed (서낙동강 유역 해반천의 수질 개선을 위한 비점오염관리대책 효과 분석)

  • Yejin Kim
    • Journal of Wetlands Research
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    • v.26 no.1
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    • pp.1-9
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    • 2024
  • In this study, a HSPF model was developed to simulate runoff and water quality in the Haebancheon watershed, which has a high land area ratio and population density among the West Nakdong River watersheds. Various non-point source pollution control strategies were applied, and the reduction in pollutant loads and the exceedance rate of water quality standards were analyzed. The scenarios included basic road cleaning for reducing pollutant loads, runoff reduction measures considering extensive low-impact development techniques, and inflow reduction measures to mitigate non-point source pollution entering the river. In the first step, practical conditions such as the number of vehicles for road cleaning in Kimhae City were considered, while for the second and third steps, it was assumed that 50% of the applicable land use area was used to be applicable for the LID techniques. As a result of applying all three measures, it was analyzed that the BOD pollutant load could be reduced by 58.28%, T-N by 58.49%, and T-P by 51.56%. Furthermore, the 60th percentile of water quality measurements accumulated over 5 years was set as the target water quality, and a flow-duration curve was constructed. The exceedance rate of the flow-duration curve before and after applying non-point source pollution reduction measures was analyzed. As a result, for BOD, the exceedance rate decreased from 41.57% before applying the measures to 16.32% after, showing a 25.25% reduction in the exceedance rate. For T-N, the exceedance rate decreased significantly from 40.31% before the measures to 22.84% after, and for T-P, it decreased significantly from 62.43% to 27.22%.