• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.1-14
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• 2019

In order to minimize problems related to the performance and safety of automobiles, the "Age Limit for Vehicles System" which restricts the age of buses, taxis, and trucks, was implemented in 1973. This contributed to the reduction of accidents and increase of user's service satisfaction. However, the restriction system for trucks was abolished in August 1997 as it was deemed restrictive to economic growth. It is found that one of main causes of traffic accidents such as Changwon Tunnel accident occurred in recent years, is the aging of trucks. Thus, There is a growing need for the management of the age of trucks. In this study, the time when cargo vehicles need to be managed is suggested, by analyzing the safety of cargo vehicles using vehicles inspection data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.84-95
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• 2018

A mathematical model of responsibility-sensitive safety (RSS) has been proposed as a way to determine whether an autonomous driving accident has occurred. Autonomous vehicles related industry and academia have shown great interest in this model. However, this mathematical model lacks a comprehensive review on whether the model can be used to clarify responsibilities of autonomous vehicles in the event of a traffic accident. In this study, we analyzed the issues that need to be solved in order to apply the RSS model. In conclusion, there is a limit in the equation and the social acceptability of the RSS model. To use the RSS model practically, it is necessary to define the response time of the autonomous vehicle and to measure and control the reaction time value according to the appropriate technology level for each autonomous vehicle.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.160-173
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• 2021

Recently, research on the development of autonomous vehicles has increased worldwide. Moreover, a means to identify and analyze the characteristics of traffic accidents of autonomous vehicles is needed. Accordingly, traffic accident data of autonomous vehicles are being collected in California, USA. This research examined the characteristics of traffic accidents of autonomous vehicles. Primarily, traffic accident data for autonomous vehicles were analyzed, and the text data used text-embedding techniques to derive major keywords and four topics. The methodology of this study is expected to be used in the analysis of traffic accidents in autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.132-145
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• 2021

This study analyzes the main road network for road users to manage roads efficiently and derives problematic road sections to be improved. Traditional road management has been operated by manager-oriented view and a diversified road management system based on congestion. Therefore, in this research, the mail road Network was selected from the viewpoint of passenger-oriented, logistics-oriented and tourism-oriented, and the problematic road sections were derived through Level Of Service (LOS) analysis, safety analysis using EPDO accident rate, and network service analysis. This study emphasizes the efficient user-oriented road construction and management system and the need of constructing a mail road network, and it suggests the improvement strategies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.134-143
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• 2020

With the worldwide spread of African swine fever, interest in livestock epidemics is growing. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted livestock-related vehicles' trajectory by utilizing the facility visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority and presented them as exposure indexes aggregating the link-time occupancy of each vehicle. As a result, a total of 274,519 livestock-related vehicle trajectories were extracted, and exposure values by link and zone were quantitatively derived. Through this study, it is expected that prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies would be provided.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.167-189
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• 2022

In the case of SAE autonomous driving levels 2 and 3, since complete autonomous driving is impossible, the take-over process is essential, and take-over time(TOT) is the most important factor in determining the safety of the autonomous driving system. Accordingly, research on TOT is being actively conducted, but each research is independently conducted and general conclusions that integrate various research results are required. Therefore, in this study, the factors affecting TOT were analyzed using meta-analysis, which integrates the results of individual studies and presents an integrated opinion. As a result of meta-analysis, a total of 10 influencing factors were selected, and most of them were related to the non-driving related task(NDRT) type. In addition, implications for the future research direction of take-over and NDRT were presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.70-86
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• 2022

An autonomous demand-responsive bus with mobility-on-demand service is an innovative transport compensating for the disadvantages of an autonomous bus and a demand-responsive bus with mobility-on-demand service. However, less attention has been paid to the quantitative impact assessment of the autonomous demand-responsive bus due to the technological complexity of the autonomous demand-responsive bus. This study simulates autonomous demand-responsive bus trips by reinforcement learning on a microscopic traffic simulation to quantify the impact of the autonomous demand-responsive bus. The Chungju campus of the Korea National University of Transportation is selected as a testbed. Simulation results show that the introduction of the autonomous demand-responsive bus can reduce the wait time of passengers, average control delay, and increase the traffic speed compared to the results with fixed route bus service. This study contributes to the quantitative evaluation of the autonomous demand-responsive bus.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.117-132
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• 2023

Mobility as a Service(MaaS) is an integrated mobility service that enables flexible reservation and payments for various transportation services on one platform, including existing public transportation. To popularize MaaS, users need to be satisfied with the service, and the factors that lower satisfaction need to be improved. In this study, the structural equation model was used to identify the influence of factors on the overall satisfaction level. Improvement plans to increase user satisfaction were derived based on importance-satisfaction analysis and the decision tree model. The analysis revealed the level of connectivity in MaaS apps to be a significant factor that needs to be improved for a higher user satisfaction level of MaaS

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.1-15
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• 2023

In this study, the number of truck traffic accidents was predicted by using Poisson and negative binomial regression analysis to understand what factors affect accidents using expressway data. Significant variables in the truck traffic accident prediction model were continuous driving time, link length, truck traffic volume. number of bridges and number of drowsy shelters. The calculated LOSS rating was expressed on the national expressway network to diagnose the risk of truck accidents. This is expected to be used as basic data for policy establishment to reduce truck accidents on expressways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.65-80
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• 2023

In this study, a classification analysis was performed based on the type of traffic situation. The purpose was to derive the major variable factors that could represent the traffic situation. The TTI(Travel Time Index) was used as a criterion for determining traffic conditions, and analysis was performed using data generally detected by the Vehicle Detecting System(VDS). First, the major factors influencing the traffic situation were selected through factor analysis, and traffic conditions were clustered through a cluster analysis of the major factors. After that, variance analysis for each cluster was performed based on the TTI, and similar clusters were merged to categorize the type of traffic situation. The analysis derived, the maximum queue length and occupancy as major factors that could represent the traffic situation. Through this study, it is expected that efficient management of traffic congestion would be possible by just concentrating on the main variable factors that affect the traffic situation.