• Title/Summary/Keyword: Intelligent Transportation Systems (ITS)

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Development of a Model for Calculating the Negligence Ratio Using Traffic Accident Information (교통사고 정보를 이용한 과실비율 산정 모델 개발)

  • Eum Han;Giok Park;Heejin Kang;Yoseph Lee;Ilsoo Yun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.6
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    • pp.36-56
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    • 2022
  • Traffic accidents occur in Korea are calculated with the 「Automobile Accident Negligence Ratio Certification Standard」 prepared by the 'General Insurance Association of Korea' and the insurance company's agreement or judgment is made. However, disputes are frequently occurring in calculating the negligence ratio. Therefore, it is thought that a more effective response would be possible if accident type according to the standard could be quickly identified using traffic accident information prepared by police. Therefore, this study aims to develop a model that learns the accident information prepared by the police and classifies it to match the accident type in the standard. In particular, through data mining, keywords necessary to classify the accident types of the standard were extracted from the accident data of the police. Then, models were developed to derive the types of accidents by learning the extracted keywords through decision trees and random forest models.

Issue-Tree and QFD Analysis of Transportation Safety Policy with Autonomous Vehicle (Issue-Tree기법과 QFD를 이용한 자율주행자동차 교통안전정책과제 분석)

  • Nam, Doohee;Lee, Sangsoo;Kim, Namsun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.4
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    • pp.26-32
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    • 2016
  • An autonomous car(driverless car, self-driving car, robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars can detect surroundings using a variety of techniques such as radar, lidar, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Autonomous cars have control systems that are capable of analyzing sensory data to distinguish between different cars on the road, which is very useful in planning a path to the desired destination. An issue tree, also called a logic tree, is a graphical breakdown of a question that dissects it into its different components vertically and that progresses into details as it reads to the right.Issue trees are useful in problem solving to identify the root causes of a problem as well as to identify its potential solutions. They also provide a reference point to see how each piece fits into the whole picture of a problem. Using Issue-Tree menthods, transportation safety policies were developed with autonompus vehicle in mind.

A Component Design for Advanced Traveler Information System (여행자 정보 고급화 시스템을 위한 컴포넌트 설계)

  • Kim, Jin-Hwan;Jang, Jae-Yeong;Lee, Bong-Gyu
    • The KIPS Transactions:PartD
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    • v.8D no.6
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    • pp.789-798
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    • 2001
  • ITS (Intelligent Transport Systems) is comprised of a number of advanced technologies, including information processing, communications, control, and electronics. Joining these technologies to the transportation system will save lives more safely, save time, and save money more efficiently. The National ITS Architecture provides a common framework for planning, defining, and integrating intelligent transportation systems. Most ITS projects are being designed and implemented in accordance with the National ITS Architecture, a reference framework that spans all of standards activities. Recently, as software technology is rapidly improved and stabilized, there are some needs to reuse pre-developed and powerful ITS technology. ITS standardization based on components and open interfaces becomes a way to solve these reusability of current ITS technology. This paper focuses on how could we design and implement the ITS component based on the National ITS Architecture. Furthermore, design and analysis of UML (Unified Modeling Language) was made through the ATIS (Advanced Traveller Information System) component development task and this UML methodology is expected to provide a standardized model for newly developed ITS components.

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Analysis of Driving and Environmental Impacts by Providing Warning Information in C-ITS Vehicles Using PVD (PVD를 활용한 C-ITS 차량 내 경고정보 제공에 따른 주행 및 환경영향 분석)

  • Yoonmi Kim;Ho Seon Kim;Kyeong-Pyo Kang;Seoung Bum Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.224-239
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    • 2023
  • C-ITS (Cooperative-Intelligent Transportation System) refers to user safety-oriented technology and systems that provide forward traffic situation information based on a two-way wireless communication technology between vehicles or between vehicles and infrastructure. Since the Daejeon-Sejong pilot project in 2016, the C-ITS infrastructure has been installed at various locations to provide C-ITS safety services through highway and local government demonstration projects. In this study, a methodology was developed to verify the effectiveness of the warning information using individual vehicle data collected through the Gwangju Metropolitan City C-ITS demonstration project. The analysis of the effectiveness was largely divided into driving behavior impact analysis and environmental analysis. Compliance analysis and driving safety evaluation were performed for the driving impact analysis. In addition, to supplement the inadequate collection of Probe Vehicle Data (PVD) collected during the C-ITS demonstration project, Digital Tacho Graph ( DTG ) data was additionally collected and used for effect analysis. The results of the compliance analysis showed that drivers displayed reduced driving behavior in response to warning information based on a sufficient number of valid samples. Also, the results of calculating and analyzing driving safety indicators, such as jerk and acceleration noise, revealed that driving safety was improved due to the provision of warning information.

The Analysis Correlation Subway and Bike Sharing Ridership before and during COVID-19 Pandemic in Seoul (코로나19(COVID-19)로 인한 지하철과 공유자전거 통행량 변화의 상관성 연구)

  • Lee, Sangjun;Shin, Seongil;Nam, Doohee;Kim, Jiho;Park, Juntae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.14-25
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    • 2021
  • With the spread of COVID-19 and the government policy of social distancing, the demand for subways and buses is decreasing, whereas the demand for public bicycles and personal transportation is increasing. Hence, research is needed to understand the characteristics of this phenomenon and to prove the statistical reliability of the correlation between the subway and shared bicycle demands. In this study, the correlation between the number of confirmed COVID-19 cases and the replacement rate of subway and public bicycle demands was examined, but the statistical significance was not significant. However, during the period of September to December 2020, in which the number of confirmed COVID-19 cases in Seoul started to increase rapidly, there was a correlation between the number of confirmed COVID-19 cases and the replacement ratio. If the number of confirmed COVID-19 cases increases by more than a certain number, public bicycles are expected to play a significant role as alternates to the subways. It is expected that the role of public bicycles will increase, and that it is possible to suggest the direction of transportation operation and policy establishment for the continuation of COVID-19 countermeasures in field demonstration after elementary technology development. It is also expected that this study will suggest a direction for future development and policymaking.

A Safety Analysis Based on Evaluation Indicators of Mixed Traffic Flow (혼합 교통류의 적정 평가지표 기반 안전성 분석)

  • Hanbin Lee;Shin Hyoung Park;Minji Kang
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.1
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    • pp.42-60
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    • 2024
  • This study analyzed the characteristics of mixed traffic flows with autonomous vehicles on highway weaving sections and assessed the safety of vehicle-following pairs based on surrogate safety indicators. The intelligent driver model (IDM) was utilized to emulate the driving behavior of autonomous vehicles, and the weaving sections were divided into lengths of 300 and 600 meters for analysis within a micro-traffic simulation (VISSIM). Although significant differences were found in the average speed, density, and headway between the two sections through t-test results, no significant differences were observed when comparing the number of conflicts per indicator and the vehicle-following pair. Four safety indicators were selected for the mixed traffic evaluation based on their ability to represent risk levels similar to those perceived by drivers. The safety analysis, based on the selected four indicators, determined that autonomous vehicles following other autonomous vehicles were the safest pairing. Future research should focus on integrating these indicators into a single comprehensive index for analysis.

Queue Detection using Fuzzy-Based Neural Network Model (퍼지기반 신경망모형을 이용한 대기행렬 검지)

  • KIM, Daehyon
    • Journal of Korean Society of Transportation
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    • v.21 no.2
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    • pp.63-70
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    • 2003
  • Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

Research on Driving Pattern Analysis Techniques Using Contrastive Learning Methods (대조학습 방법을 이용한 주행패턴 분석 기법 연구)

  • Hoe Jun Jeong;Seung Ha Kim;Joon Hee Kim;Jang Woo Kwon
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.1
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    • pp.182-196
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    • 2024
  • This study introduces driving pattern analysis and change detection methods using smartphone sensors, based on contrastive learning. These methods characterize driving patterns without labeled data, allowing accurate classification with minimal labeling. In addition, they are robust to domain changes, such as different vehicle types. The study also examined the applicability of these methods to smartphones by comparing them with six lightweight deep-learning models. This comparison supported the development of smartphone-based driving pattern analysis and assistance systems, utilizing smartphone sensors and contrastive learning to enhance driving safety and efficiency while reducing the need for extensive labeled data. This research offers a promising avenue for addressing contemporary transportation challenges and advancing intelligent transportation systems.

Analysis of the Transport Characteristics of Bulk Cargo in Freight Stations Located Behind Trade Ports (무역항 배후 화물철도역의 벌크화물 운송특성 분석)

  • Choi, Chang-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.6
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    • pp.47-61
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    • 2016
  • The present study analyzed the railway transport characteristics of bulk cargo flowing in and out of trade ports in South Korea. Bulk cargo transport in freight stations located behind trade ports was examined using actual flow data, and new implications were drawn accordingly. The results showed that bulk cargo volume in freight stations located behind trade ports is gradually decreasing, and it is also failing to secure a competitive edge against road transport. This downfall can be mainly attributed to the decrease in competitiveness of railway transport as well as the emergence of new trade ports that do not have lead-in track for port. Therefore, greater effort is required to strengthen the connection between new trade ports and railway freight stations.

Evaluation and Model Development of Transfer Resistance Factors for Bulk Freight Transportation (벌크화물운송의 환적저항요인 평가 및 모형 개발)

  • Choi, Chang-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.3
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    • pp.1-11
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    • 2016
  • The present study aims to evaluate transfer resistance factors in railway stations and draw new implications. The data used for the model estimation are RP (revealed preference) data and SP (stated preference) data. Two types of models were used for the analysis: integration model which combined line-haul stage, transfer stage and shuttle stage and separation model which assessed the three stages separately. The results revealed that while bulk freight shippers mainly focused on line-haul stage, they put emphasis on transfer stage as well. It's especially notable that transfer stage was considered more important than shuttle stage. Therefore, in future transportation policies concerning rail freight, it would be crucial not only to enhance the competitiveness of line-haul stage but also make improvements in transfer stage regarding railway stations.