• Title/Summary/Keyword: Vehicle safety information

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Road Patrol Strategy based on Pothole Occurrence Characteristics considering Rainfall Effects (우천에 따른 포트홀 발생 특성을 고려한 도로순찰 전략)

  • Han, Daeseok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.603-611
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    • 2020
  • Potholes on the road directly affect drivers' safety, satisfaction, and vehicle damage. Thus, real-time detection and response are required. Increasing frequency of patrols allows for potholes to be detected and responded to quickly, but this takes much manpower, money, and time. In addition, potholes have different occurrence characteristics depending on the rain conditions, so it is necessary to consider the optimal frequency from an economic and road-service perspective. Therefore, a quantitative analysis was done on the effects of rainfall on the occurrence characteristics of potholes. Information on the persistence, impact of rainfall intensity, and weather information was collected over a long period. Based on the results, a risk-based, optimized, and changeable road-patrol strategy is presented. The analysis results show that the probability of pothole occurrence increases by 2.4 times in rainy weather. Furthermore, the impact continues for 3 days even after the rain stops. The probability of pothole occurrence increases by 0.46% per 1 mm of rainfall, and the occurrence characteristics react sensitively to even a small amount of rain of around 1 mm. It was concluded that road patrol is required at least once every three days for an effect-free period, while twice a day is needed for the "sphere of influence" period to achieve a 95% reliability level.ys for effect-free period, while twice a day for sphere of influence period to satisfy 95% reliability level.

A Study on the Analysis of the Walking Environment in the Residential Area for the Elderly in Busan Using Spatial Analysis (공간 분석 기법을 적용한 부산 노인 주거지의 보행환경 분석에 대한 연구)

  • Whiho LEE;Jihyun KIM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.251-265
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    • 2023
  • The purpose of this study is to deduce key indicators in evaluating the pedestrian environment for the elderly in Busan, which has entered an aging society, and to propose policy improvement measures. The key indicators were selected based on prior research and surveys, and the effectiveness of those indicators were measured through evaluations conducted on three places which have the highest proportion of the elderly population in Busan. The summaries of analysis are as follow. First, the three places are hillslide residential areas, and areas of activity that the elderly have were very narrow due to the restrictions on their movement caused by slope. Second, the areas were filled with a number of illegally parked vehicles. And the degree of segregation of pedestrian and vehicle and the level of safety were very low. Third, the streets with steep slopes of the target site force the elderly to move vertically, and for this reason, the elderly are expressing difficulties in outdoor activities. Fourth, it was found that the target site lacked a space for relaxation during outdoor activities. The poor walking environment not only limit the essential and social activities of the elderly, but also adversely affects the health and quality of life of the elderly. In order to maintain the health of the elderly and improve the quality of life, actions should be taken to improve the walking factors that affect the movement and external activities of the elderly.

Unsupervised Learning-Based Threat Detection System Using Radio Frequency Signal Characteristic Data (무선 주파수 신호 특성 데이터를 사용한 비지도 학습 기반의 위협 탐지 시스템)

  • Dae-kyeong Park;Woo-jin Lee;Byeong-jin Kim;Jae-yeon Lee
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.147-155
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    • 2024
  • Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.

Optimizing Clustering and Predictive Modelling for 3-D Road Network Analysis Using Explainable AI

  • Rotsnarani Sethy;Soumya Ranjan Mahanta;Mrutyunjaya Panda
    • International Journal of Computer Science & Network Security
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    • v.24 no.9
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    • pp.30-40
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    • 2024
  • Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO2 emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

A Study on the Improvement of Airspace Legislation in Korea (우리나라 공역 법제의 개선방안)

  • Kim, Jong-Dae
    • The Korean Journal of Air & Space Law and Policy
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    • v.33 no.2
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    • pp.61-114
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    • 2018
  • Recently airspace became a hot issue considering today's international relations. However, there was no data that could be fully explained about a legal system of korean airspace, so I looked at law and practice about korean airspace together. The nation's aviation law sector is comletely separate from those related to civil and military aircraft, at least in legal terms. The Minister of Land, Infrastructure and Transport shall carry out his/her duties with various authority granted by the "Aviation Safety Act". The nation's aviation-related content is being regulated too much by the Ministry of Land, Infrastructure and Transport's notice or regulation, and there are many things that are not well known about which clauses of the upper law are associated with. The notice should be clearly described only in detail on delegated matters. As for the airspace system, the airspace system is too complex for the public to understand, and there seems to be a gap between law and practice. Therefore, I think it would be good to reestablish a simple and practical airspace system. Airspace and aviation related tasks in the military need to be clearly understood by distinguishing between those entrusted by the Minister of Land, Infrastructure and Transport and those inherent in the military. Regarding matters entrusted by the Minister of Land, Infrastructure and Transpor, it is necessary to work closely with the Minister of Land, Infrastructure and Transport when preparing related work guidelines, and to clarify who should prepare the guidelines. Regarding airspace control as a military operation, policies or guidelines that are faithful to military doctrine on airspace control are needed.

Intelligent Railway Detection Algorithm Fusing Image Processing and Deep Learning for the Prevent of Unusual Events (철도 궤도의 이상상황 예방을 위한 영상처리와 딥러닝을 융합한 지능형 철도 레일 탐지 알고리즘)

  • Jung, Ju-ho;Kim, Da-hyeon;Kim, Chul-su;Oh, Ryum-duck;Ahn, Jun-ho
    • Journal of Internet Computing and Services
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    • v.21 no.4
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    • pp.109-116
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    • 2020
  • With the advent of high-speed railways, railways are one of the most frequently used means of transportation at home and abroad. In addition, in terms of environment, carbon dioxide emissions are lower and energy efficiency is higher than other transportation. As the interest in railways increases, the issue related to railway safety is one of the important concerns. Among them, visual abnormalities occur when various obstacles such as animals and people suddenly appear in front of the railroad. To prevent these accidents, detecting rail tracks is one of the areas that must basically be detected. Images can be collected through cameras installed on railways, and the method of detecting railway rails has a traditional method and a method using deep learning algorithm. The traditional method is difficult to detect accurately due to the various noise around the rail, and using the deep learning algorithm, it can detect accurately, and it combines the two algorithms to detect the exact rail. The proposed algorithm determines the accuracy of railway rail detection based on the data collected.

Electrode bonding method and characteristic of high density rechargeable battery using induction heating system (유도 가열 접합 시스템을 이용한 대용량 이차전지 전극의 접합 방법 및 특성)

  • Kim, Eun-Min;Kim, Shin-Hyo;Hong, Won-Hee;Cho, Dae-Kweon
    • Journal of Advanced Marine Engineering and Technology
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    • v.38 no.6
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    • pp.688-697
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    • 2014
  • In this study, electrode bonding technology needed for high density of rechargeable battery is studied, which is recently researched for electric vehicle, the small leisure vessel. For the alternative overcoming the limit of stacking amount able to be stacked by conventional ultrasonic welding, the low temperature bonding method, eligible for minimum of degeneration of chemical activator on the electrode surface which is generated by thermal effect as well as the increase of conductivity and tension strength caused by electrode bonding using filler metal, not using conventional direct heating on the electrode material method, is studied. Specifically to say, recently used more generally the ultrasonic welding and spot welding method are not usable for satisfying stable electric conductivity and bonding strength when much electrode is stacking bonded. If the electrical power is unreasonably increased for the welding, due to the effect of welding temperature, deformation of electrode and activating material degeneration are caused, and after the last packaging, decline of electrical output and generating heat cause to reduce stability of battery. Therefore, in this study, induction heating system bonding method using high frequency heating and differentiated electrode method using filler metal pre-treatment of hot dipping are introduced.

Prioritization Analysis for Contents Sensibility Evaluation of the Future Mobility (차세대 이동공간 대상의 콘텐츠 감성 평가를 위한 우선순위 도출)

  • Lee, Jung Min;Ju, Da Young
    • Science of Emotion and Sensibility
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    • v.21 no.1
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    • pp.3-16
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    • 2018
  • The emergence of the fourth industrial revolution is rapidly changing the conventional society and the industry, eroding the boundaries among the technology, culture, and finance. In the mobility industry, as the engineering-based industry converges with the information technology, the mobile space is changing from mobility or safety-centric space into space where the passengers can consume infotainment or contents services. The contents evaluation of the future mobility is conducted in terms of usability or technology acceptance aspect, but according to the trend analysis, the mobility industries, such as vehicle OEMs, it is necessary to evaluate the emotional or sensibility factors for the development of their future mobile space design. Herein, this research study evaluates which sensibility factor should be evaluated in priority to develop the contents interaction in the future mobile space. Thus, using Patrick Jordan's Four Pleasure Model, the priority evaluation has been conducted among 116 Korean drivers. As a result of the statistical analysis and AHP (Analytic Hierarchy Process), it has been found that first, it is necessary to evaluate psychological, ideological, social and physical sensibility in the respective order, and second, it is necessary to evaluate based on the contents user type.

Preliminary Design of a Urban Transit Passenger Guidance System Using Congestion Management Model (혼잡관리 모형을 이용한 도시철도 이용객 동선유도시스템 기본설계)

  • Kim, Kwang-Mo;Park, Hee-Won;Kim, Jin-Ho;Park, Yong-Gul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.5
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    • pp.3610-3618
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    • 2015
  • The congestion of railway vehicle and station shows up to 220%. Especially, transfer resistance of passenger increase rapidly by the collision of circulation. So increment of travel time, occurrence of safety accidents act as a factor that inhibits the utilization of urban railway station. In this paper, to improve traveling speed and comfort of urban rail passengers, urban transit passenger guidance system using congestion management model is proposed. The congestion management model that can mitigate a recurring/non-recurring congestion is constructed and the preliminary design of the system (middleware system, control system, guidance drive system) is carried out. Passenger Guidance System is configured by step for changing the external data into a form usable by the algorithm, step to perform the congestion management algorithm using the real-time data and historical data, step to control device based on the value that is calculated by congestion management algorithm, step to drive the device based on the information in the control system and circulation guidance devices. In the future, detail design will be performed based on the preliminary design. A prototype of the various devices according to the station structures and locations will be made. The control module of guidance device will be developed.

Development of Traffic Accident Index Considering Driving Behavior of a Data Based (데이터 기반의 도로구간별 운전자의 통행행태를 고려한 교통사고지표 개발)

  • LEE, Soongbong;CHANG, Hyunho;CHEON, Seunghoon;BAEK, Seungkirl;LEE, Young-Ihn
    • Journal of Korean Society of Transportation
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    • v.34 no.4
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    • pp.341-353
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    • 2016
  • Highway is mainly in charge of middle-long distance of vehicular travel. Trip length has shown a growing trend due to increased commute distances by the relocation of public agencies. For this reason, the proportion of driver-driven accidents, caused by their fatigue or sleepiness, are very high on highways. However, existing studies related to accident prediction have mainly considered external factors, such as road conditions, environmental factors and vehicle factors, without driving behavior. In this study, we suggested an accident index (FDR, Fatigued Driving Rate) based on traffic behavior using large-scale Car Navigation path data, and exlpored the relationship between FDR and traffic accidents. As a result, FDR and traffic accidents showed a high correlation. This confirmed the need for a paradigm shift (from facilities to travel behavior) in traffic accident prediction studies. FDR proposed in this study will be utilized in a variety of fields. For example, in providing information to prevent traffic accidents (sleepiness, reckless driving, etc) in advance, utilization of core technologies in highway safety diagnostics, selection of priority location of rest areas and shelter, and selection of attraction methods (rumble strips, grooving) for attention for fatigued sections.