• Title/Summary/Keyword: Intelligent transportation

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A Study of Hazard Analysis and Monitoring Concepts of Autonomous Vehicles Based on V2V Communication System at Non-signalized Intersections (비신호 교차로 상황에서 V2V 기반 자율주행차의 위험성 분석 및 모니터링 컨셉 연구)

  • Baek, Yun-soek;Shin, Seong-geun;Ahn, Dae-ryong;Lee, Hyuck-kee;Moon, Byoung-joon;Kim, Sung-sub;Cho, Seong-woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.222-234
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    • 2020
  • Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

Analysis of PM (Personal Mobility) Traffic Accident Caracteristics and Cause of Death (PM (Personal Mobility) 교통사고 특성 및 사망사고 발생 요인 분석)

  • Han, Sangyeou;Lee, Chulgi;Yun, Ilsoo;Yoon, Yeoil;Na, Jaepil
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.1
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    • pp.100-118
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    • 2021
  • In this study, PM accidents (1,603case) and bicycle accidents (14,672case) that occurred in the last three years were analyzed to determine the characteristics of PM traffic accidents. In particular, PM traffic accidents were divided into perpetrators and victims to determine the characteristics in detail. For PM accidents, the analysis was conducted on the status of each road grade, road type, weather condition, accident type, day and night occurrence, and vehicle type. The number of PM accidents that occurred in 2019 increased by 129%, and deaths increased by more than 200% compared to the previous year. The proportion of pedestrian accidents among PM traffic accidents was higher than that of bicycle accidents. Therefore, regulations on PM traffic are necessary. For the 20 deaths of PM, a detailed analysis was conducted to analyze the factors of traffic accidents. PM fatalities occurred in 50% of vehicle accidents, and 7 out of 10 vehicle accidents occurred at night. This is believed to have been caused by falling or overturning due to an obstacle, such as a depression in the road pavement or a speed bump.

Study on the Development of Methodology for Evaluation of Driving Safety of Automated Vehicles on Real Roads (실도로 기반 자율주행자동차 주행안전성 평가 방법론 개발 연구)

  • Lee, Youngtaek;Kim, Yejin;Jeong, Harim;Yoo, Hosik;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.280-298
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    • 2021
  • As the development automated vehicles(AV) actively progresses around the world, the demand for a reasonable and systematic evaluation method for AVs is increasing. Research on scenarios, evaluation procedures, and methods for evaluating AVs conducted in simulations and proving ground(PG) is actively conducted internationally. In contrast, methods and procedures for evaluations on real roads are still in their infancy internationally. Therefore, it is necessary to conduct research on evaluating AVs on real roads in preparation for future use of AVs. This study aims to define the basic direction for evaluating the driving safety of AVs on real roads. To this end, the evaluation direction and process of AVs were presented on the real roads, and qualitative and quantitative evaluation indicators were selected to evaluate driving safety. A total of 38 items were selected based on the Road Traffic Act as qualitative evaluation items for evaluating the driving safety of AVs on real roads.

A Study on the Analysis of Dangerous Driving Behavior and Traffic Accident Risk according to the Operation Characteristics of Commercial Freight Vehicles (사업용 화물자동차 운행특성에 따른 위험운전행동 및 교통사고 위험도 분석 연구)

  • Park, Jin soo;Lee, Soo beom;Park, Jun tae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.2
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    • pp.152-166
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    • 2022
  • This study analyzed the causal relationship among operating characteristics of commercial freight vehicles, dangerous driving behaviors, and traffic accident risk. The study applied the existing accident cause and prevention theory to arrive at this relationship. Data related to working characteristics of driver, driving experience, driving ability, driving psychology, vehicle characteristics (size), dangerous driving behavior, and traffic accidents were collected from 303 commercial freight vehicle drivers. Working characteristics and dangerous driving behavior data are based on the driver's digital driving record. The traffic accident data is based on the insurance accident data reflecting actual traffic accidents. First, a structural equation model was built and verified using the model fitness index. Then, the developed model was used to analyze the causal relationship between multiple independent and dependent variables simultaneously. Four dangerous driving behaviors (sudden deceleration, sudden acceleration, sudden passing, and sudden stop) were found to be highly related to traffic accidents. The results further indicate that it is necessary to establish a safety management policy and intensive management for small-sized freight vehicles, drivers with insufficient driving ability, and drivers with dangerous driving behaviors. Such policy and management are expected to reduce traffic accidents effectively.

Research on Longitudinal Slope Estimation Using Digital Elevation Model (수치표고모델 정보를 활용한 도로 종단경사 산출 연구)

  • Han, Yohee;Jung, Yeonghun;Chun, Uibum;Kim, Youngchan;Park, Shin Hyoung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.84-99
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    • 2021
  • As the micro-mobility market grows, the demand for route guidance, that includes uphill information as well, is increasing. Since the climbing angle depends on the electric motor uesed, it is necessary to establish an uphill road DB according to the threshold standard. Although road alignment information is a very important element in the basic information of the roads, there is no information currently on the longitudinal slope in the road digital map. The High Definition(HD) map which is being built as a preparation for the era of autonomous vehicles has the altitude value, unlike the existing standard node link system. However, the HD map is very insufficient because it has the altitude value only for some sections of the road network. This paper, hence, intends to propose a method to generate the road longitudinal slope using currently available data. We developed a method of computing the longitudinal slope by combining the digital elevation model and the standard link system. After creating an altitude at the road link point divided by 4m based on the Seoul road network, we calculated individual slope per unit distance of the road. After designating a representative slope for each road link, we have extracted the very steep road that cannot be climbed with personal mobility and the slippery roads that cannot be used during heavy snowfall. We additionally described errors in the altitude values due to surrounding terrain and the issues related to the slope calculation method. In the future, we expect that the road longitudinal slope information will be used as basic data that can be used for various convergence analyses.

A Study on the Influencing Factors of the Sales and Surplus Companies of the Townbuses in Seoul (서울시 마을버스 매출액 및 흑자업체의 영향요인에 대한 연구)

  • Jang, Jae-min;Shin, Sung-il;YI, Yong-ju
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.4
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    • pp.115-124
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    • 2022
  • Unlike the semi-public system of city buses, Seoul's townbus are operated on a private operating system, which is poor condition to the changes in the environment. Sales decreased due to a decrease in the number of passengers due to COVID-19 and a demand for conversion due to the advent of competitive transportation methods, and the financial support of Seoul Metropolitan Government is continuously increasing. In this study, to analyze the characteristics of townbus operated by a private operating system, the townbus sales and surplus companies were analyzed by what factors were affected. For the analysis data, townbus financial statements of Seoul in 2018 were used, and townbus sales and surplus companies were applied as dependent variables, and townbus operation system, satisfaction survey, humanities and social variables, and subway and public bicycle characteristics were applied as independent variables. As a result of the analysis, the sales is affected by operating hours per vehicle, in-vehicle safety, the number of households, the number of elderly people, and public bicycle variables, and surplus companies are affected by in-vehicle safety, reliability, and public bicycle variables. In particular, public bicycles, a competitive means of transportation, had an impact on industry sales, and the townbus business environment is expected to become more difficult as time goes by. The industry is seeking self-rescue measures, and Seoul is required to strengthen financial support so that townbus can operate stably.

Suggestion of Evaluation Elements Based on ODD for Automated Vehicles Safety Verification : Case of K-City (자율주행자동차 안전성 검증을 위한 ODD 기반 평가요소 제시 : K-City를 중심으로)

  • Kim, Inyoung;Ko, Hangeom;Yun, Jae-Woong;Lee, Yoseph;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.5
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    • pp.197-217
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    • 2022
  • As automated vehicle(AV) accidents continue to occur, the importance of safety verification to ensure the safety and reliability of automated driving system(ADS) is being emphasized. In order to encure safety and reliability, it is necessary to define an operational design domain(ODD) of the ADS and verify the safety of the ADS while evaluating its ability to respond in situations outside of the ODD. To this, international associations such as SAE, BSI, NHTSA, ISO, etc. stipulate ODD standards. However, in Korea, there is no standard for the ODD, so automated vehicles's ODD expression method and safety verification and evaluation are not properly conducted. Therefore, this study analyzed overseas ODD standards and selected suitable ODD for safety verification and evaluation, and presented evaluation elements for ADS safety verification and evaluation. In particular, evaluation elements were selected by analyzing the evaluation environment of the automated driving experimental city (K-City) that supports the development of ADS technology.

An Investigation of Rider Behavior to Transfer Seoul Metropolitan Transit Using Public Transport Card Data (교통카드 데이터를 이용한 수도권 광역급행철도 환승행태에 관한 연구)

  • Gun ki Jung;Dong min Lee;Sun hoon Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.6
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    • pp.146-164
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    • 2022
  • Recently, the Korean government promoted the construction of metropolitan express subway to connect major transportation hub in the metropolitan area within 30 minutes. Most stations of the metropolitan express subway are connected to existing subway stations, so the importance of transfer increased. Although many studies have been conducted on the effect of transfer penalty on route choice, there are few studies on the transfer behavior of the metropolitan express subway. Therefore, in this study, a transfer behavior analysis was conducted on the Shinbundang Line, a representative metropolitan express subway. To analyze the transfer behavior according to the degree of traffic congestion and the presence of fare payment, route choice models were made using transport card data divided according to week, time, and user characteristics. As a result of the analysis, users of the metropolitan express subway had greater disutility to the transfer waiting time compared to the transfer moving time. Furthermore, especially during the peak time, EIVM(Equivalent in-vehicle minutes) of the transfer waiting time was 3.51. In this study, EIVM for metropolitan express subway users were analyzed to be 2.6 minutes, which is significantly lower than the results of previous studies on subways. This suggests that there is a difference in the transfer penalty between subways and metropolitan express subway, and that it is necessary to apply the transfer penalty between subways and express subway differently when forecasting subway traffic demand.

User Benefit Analysis By Transfer Fare Policy : Focuses on the case of Gyeonggi-do (지역별 대중교통 환승혜택 형평성 개선방안에 관한 연구 : 경기도를 중심으로)

  • Eunyoung Kim;Donghyung Yook;Seungneo Son
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.6
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    • pp.225-240
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    • 2022
  • Gyeonggi-do comprises several types of areas, including urban, semi-urban, and rural areas. The availability of public transportation services varies depending on the area types, but the fare structure is based on a simple transfer rule, i.e., a transfer is free when completed within 30 minutes. As a result, users in non-urban areas with a poor frequency of public transportation services do not receive transfer discounts because most of the bus routes in these areas have a gap of more than 30 minutes between services. In terms of equality of opportunity, the transfer rule is being applied unfavorably and, as a result, equality of opportunity of the non-urban commuter is severely affected. Therefore, this study analyzed the user benefits mainly stemming from transfer fares using the smart card data of commuters using public transportation in Gyeonggi-do. An index called the beneficiary rate of the free transfer was developed and a scenario analysis was conducted based on the various levels of the rate. The results of this analysis proved that the users of public transportation services in non-urban areas in Gyeonggi-do can only receive transfer benefits by the extended time for free transfer and not by the implementation of a uniform policy irrespective of the type of area. The study also suggested an equitable fare transfer system and policy alternatives.

A Study on Estimating the Crossing Speed of Mobility Handicapped for the Activation of the Smart Crossing System (스마트횡단시스템 활성화를 위한 교통약자의 횡단속도 추정)

  • Hyung Kyu Kim;Sang Cheal Byun;Yeo Hwan Yoon;Jae Seok Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.6
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    • pp.87-96
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    • 2022
  • The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.