• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.97-100
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• 2023

차량 인터넷은 목적지까지 스스로 주행하는 자율 주행 자동차의 최적 경로 설정을 도와주는 차세대 네트워크이다. 자율 주행 자동차의 원활한 자율 주행을 위해서는 도로 위 객체 인지뿐만 아니라 실시간 교통 정보가 수신되어야 한다. 공격자는 자동차로 전달되는 메시지를 탈취하여 내용을 변경하거나 메시지를 제거하는 중간자 공격을 시도할 수 있다. 중간자 공격을 탐지하기 위해 MARINE 기법이 제안되었지만, 주행하는 자동차가 적은 환경에서 중간자 공격을 탐지하기 어렵다. 제안 방법은 이러한 문제를 해결하기 위해 교통 정보 센터에 축적된 교통 정보를 이용하여 자동차에 전달되는 메시지를 분석하고 중간자 공격을 탐지하는 방법을 제안한다.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.450-455
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• 2021

In this paper, we introduce the contents of research on the establishment of an evaluation environment for autonomous cooperative driving platform for commercial vehicles based on V2X communication. For the evaluation of the autonomous cooperative driving platform based on V2X communication, various standards, standards, and guidelines for test evaluation should be developed and provided to the test subject, along with the establishment of test beds such as roads and V2X infrastructure that can apply various driving scenarios. do. In addition, based on this, various reference equipment and test equipment for actual test and evaluation should be developed. In this paper, various technologies, standards, equipment, and construction infrastructure developed to construct the evaluation environment for autonomous cooperative driving platform for commercial vehicles based on V2X communication are introduced.

• TTA Journal
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• s.173
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• pp.52-57
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• 2017

• TTA Journal
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• s.173
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• pp.16-22
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• 2017

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.62-73
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• 2022

As the competition among the autonomous vehicle (AV, here after) developers are getting fierce, Korean government has been supporting developers by deregulating safety standards and providing financial subsidies. Recently, some OEMs announced their plans to market Lv3 and Lv4 automated driving systems. However, these market changes raised concern among public road management sectors for monitoring road conditions and alleviating hazardous conditions for AVs and human drivers. In this regards, the authors proposed a methodology for monitoring road infrastructure to identify hazardous factors for AVs and categorizing the hazards based on their level of impact. To evaluate the degrees of the harm on AVs, the authors suggested a methodology for managing road hazard factors based on vehicle performance features including vehicle body, sensors, and algorithms. Furthermore, they proposed a method providing AVs and road management authorities with potential risk information on road by delivering them on the monitoring map with node and link structure.

• Journal of IKEEE
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• v.22 no.4
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• pp.1099-1103
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• 2018

Platooning of vehicles is an efficient traffic management model that improves traffic flow and fuel consumption. Especially, it is necessary to reduce computational load and networking overhead in automated connected vehicle systems. Because it is important to maintain the size of the platoon group appropriately for efficient platoon operation, this study proposed a dynamic grouping scheme for platooning in an automated vehicle system. The proposed scheme is analyzed by a mathematical model based on Markov chain. From the performance evaluation, it was confirmed that the proposed scheme appropriately controls the size of the platoon group.

• 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.20 no.2
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• pp.15-29
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• 2021

The signal intersection is the most challenging space for autonomous vehicles. To promote the safe driving of autonomous vehicles on urban roads with traffic signals, autonomous vehicles need to receive traffic signal information from infrastructure through V2I communication. Thus, a protocol for providing traffic signal information was added to the standard traffic signal controller specification of the National Police Agency. On the other hand, there are technical limitations when applying this to digital traffic signal controllers because the protocols are defined mainly for analog traffic signal controllers. Therefore, this study proposes developing a signal information linkage module to provide traffic signal information from a digital traffic signal controller to an autonomous vehicle and an algorithm improvement method that can provide accurate traffic signal information at the time of traffic signal transition.

• Journal of Auto-vehicle Safety Association
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• v.16 no.1
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• pp.35-41
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• 2024

In order to verify autonomous driving scenarios and safety, a lot of driving and accident data is needed, so various organizations are conducting classification and analysis of traffic accident types. In this study, it was determined that accident recording devices such as EDR (Event Data Recorder) and DSSAD (Data Storage System for Automated Driving) would become an objective standard for analyzing the causes of autonomous vehicle accidents, and traffic accidents that occurred from 2015 to 2020 were analyzed. Using the database system of IGLAD (Initiative for the Global Harmonization of Accident Data), approximately 360 accident data of EDR-equipped vehicles were classified and their characteristics were analyzed by comparing them with accident types of ADAS (Advanced Driver Assistance System)-equipped vehicles. It will be used to develop autonomous vehicle accident investigation guidelines in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.13-27
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• 2021

In this study, the impact of traffic flow on the market penetration rate of autonomous vehicles(AV) was analyzed using the data for the year 2020 of the Yongin IC~Yangji IC section of Yeongdong Expressway. For this analysis, a microscopic traffic simulation model VISSIM was utilized. To construct the longitudinal control of the AV, the Intelligent Driver Model(IDM) was built and applied, and the driving behavior was verified by comparison with a normal vehicle. An examination of the study results of mobility and safety according to the market penetration rate of the AV, showed that the network's mobility improves as the market penetration rate increases. However, from the point of view of safety, the network becomes unstable when normal vehicles and AVs are mixed, so there should be a focus on traffic management for ensuring safety in mixed traffic situations.