• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.183-196
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• 2022

Public transportation accessibility has been evaluated through minimum level of service for public transportation. However it is evaluated based operators rather than users. This study analyzed the users' accessibility(first-mile, last-mile) to public transportation using altteul transport card data. As a result of user's accessibility of public transportation, rural areas was lower than that in the urban areas. This study calssified type 1 and 2 based average approach time, and average approach time of Type 1 and 2 were more than average approach time of total area. We propsed an efficient introduction of autonomous public transportation on-demand service using delphi survey. As a result of delphi survey, experts agreed on 9 items regarding function, service item, route operation, approach distance, route mileage, punctuality.

• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.5
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• pp.495-503
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• 2016

Regulation for the testing and operation of autonomous vehicles on public roadways has been recently developed all over the world. For example, the licensing standards and the evaluation technology for autonomous vehicles have been proposed in California, Nevada and EU. But specific safety evaluation scenarios for autonomous vehicles have not been proposed yet. This paper presents safety evaluation scenarios for extraordinary service permission of autonomous vehicles on highways. A total of five scenarios are selected in consideration of safety priority and real traffic situation. These scenarios are developed based on existing ADAS evaluation and simulation of autonomous vehicle algorithm. Also, Safety evaluation factors are developed based on ISO requirements, other papers and the current traffic regulations. These scenarios are investigated via computer simulation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.104-115
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• 2023

User-centered public transportation services such as DRT, Autonomous Transit etc. have been provied but current minimum level of service for public transportation has been evaluated by the operator because there is no data on user's accessibility to use public transportation. This study was performed GRID analysis using altteul transport card data including user's accessibility to use public transportation. The analysis result showed that user's accessibility to use public transportation was different within a same dong area. We proposed improving minimum level of service for public transportation considered by the user. The result of applying the proposed method showed that many area was changed to unsatisfied area for minimum level of service for public transportation

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.5
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• pp.137-146
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• 2024

Demand-responsive transit (DRT) is a concept introduced to provide appropriate service to areas with insufficient public transit services. Since the focus has been on regional expansion, a service evaluation and feedback system has not yet been established. In the context of recent research to combine DRT service and autonomous driving technology, this study examines domestic and overseas-related evaluation systems and research cases to discover indicators that meet demand-response autonomous mobility service evaluation. This study proposes a method for evaluating demand-responsive autonomous mobility services using an analytic hierarchy process (AHP) technique based on the investigated indicators. It is expected that the results will be used as primary data for building an evaluation system, contributing to enhanced service competitiveness and secure sustainability.

• 한국ITS학회:학술대회논문집
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• 2005.11a
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• pp.83-88
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• 2005

A transportation problem in Korea is a serious issue that has to be solved urgently in the motor era of 15 million vehicles. Recently ITS has been introduced to improve efficiency of the current roads because an excessive budget and a long term construction are needed to build new roads. Therefore the government enacted the law as of ITS and the in architecture. However, these ITS information services were oriented to mainly vehicles and drivers, not public entities such as bus driver, passengers and so on. Nowadays lots of local autonomous city introduced a public transportation information system (PTIS), and providing useful information for the public. For this PTIS, important design issues are to be focused on detecting and tracking technology of moving bus, and a wireless communication link to transmit the location information. This paper presents design models using several wireless communication methods, and an implementation case using a Wireless packet Data communication Network (WDN) to transmit bus location information at Seoul, Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.80-96
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• 2024

This study conducted over two rounds Delphi survey targeting experts in the fields of roads, transportation, automobiles, intelligent transport systems(ITS), and communications to analyze the direction of change in road design, operation, and systems in the Lv.4/4+ autonomous driving era. To construct the Delphi survey items, a basic survey was conducted. The first and second Delphi surveys targeted experts in fields closely related to autonomous driving. The results of the survey revealed an expectation that in the future, transportation operations would change focus to shared autonomous vehicle(AV) and public transportation transfers, and there would be corresponding changes in the cross-sectional configuration. Exclusive lanes for AV are expected to be introduced commencing from highways and general national roads, and there was a consensus that they should be installed in the center of the road rather than on the sides and would use the same lane width as that of the existing road. In terms of facilities for AVs, it was found that it would be necessary to expand pedestrian-vehicle separation facilities, insert communication chips into facilities for location recognition, advance precision maps, and expand roadside communication facilities.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.493-498
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• 2017

Recently, traffic data is analyzed for efficiency of bus operation, D2D(: Door to Door) service, and self-driving of public transportation. However, various studies have been carried out to predict the delay time of public transportation, especially buses, but the research to date has been insufficient due to limitations of simple analysis and data acquisition. In this study, delay time estimation is performed by collecting and processing data such as day of the week, weather, and time of day based on bus operation information. The proposed method in this paper can be applied to autonomous public transport and public traffic control system by improving the accuracy by adding variables in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.94-109
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• 2024

As autonomous vehicles are allowed to drive on public roads, there is an increasing amount of on-road data available for research. It has therefore become possible to analyze impacts of autonomous vehicles on traffic safety using real-world data. It is necessary to use indicators that are well-representative of the driving behavior of autonomous vehicles to understand the implications of them on traffic safety. This study aims to derive indicators that effectively reflect the driving stability of autonomous vehicles by analyzing the driving behavior using the Waymo Open Dataset. Principal component analysis was adopted to derive indicators with high explanatory capability for the dataset. Driving stability indicators were separated into longitudinal and lateral ones. The road segments on the dataset were divided into four based on the characteristics of each, which were signalized and unsignalized intersections, tangent road section, and curved road section. The longitudinal driving stability was 35.48% higher in the curved road sections compared to the unsignalized intersections. With regard to the lateral driving stability, the driving stability was 76.08% higher in the signalized intersections than in the unsignalized intersections. The comparison between curved and tangent road segments showed that tangent roads are 146.87% higher regarding lateral driving stability. The results of this study are valuable for the further research to analyze the impact of autonomous vehicles on traffic safety using real-world data.