• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.112-123
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• 2018

The C-ARS(Cooperative Automated Roadway System) refers to a road infrastructure system that links automated vehicles with road infrastructure and communicates with each other via V2X communication to support automated vehicles. The purpose of this study is to suggest a performance evaluation method of C-ARS service. This study exemplifies the 'Work zone information service' among I2V service that provide information to automated vehicles in road infrastructure. First, we define the requirements and service scope needed to check the use case analysis and service performance of the service, and propose an evaluation system for performance evaluation of these services. In addition, the evaluation system was used to verify the feasibility of evaluation through the field test of 'Work zone information service'.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.91-104
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• 2022

The operational design domain (ODD) of autonomous vehicles needs to be expanded on highways and urban roads in light of the substantial commercialization of Level 3 autonomous vehicles. Therefore, this study developed a specific infrastructure autonomous vehicle-based cooperative driving service to ensure the driving safety of autonomous vehicles on city roads. The traffic operation efficiency, safety evaluation, and core evaluation indices for each service were selected and analyzed to study the effect of each service. The result of the analysis confirmed that the traffic operation efficiency and safety of autonomous vehicles were improved through the V2X communication-based autonomous cooperative driving service. On the whole, the significance of this study is in deriving the effect of the autonomous cooperative driving service based on V2X communication on urban roads with interrupting traffic flow.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1007-1010
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• 2019

주행 중인 자율주행차의 탑승자는 차량의 거동을 예측할 수 없기 때문에 불안함을 느낄 수 있으므로 차량의 거동 정보를 사전에 탑승자에게 전달하여 심리적 안정을 제공하는 것은 중요하다. 본 논문에서는 완전 자율주행 상황을 가정하여 자율주행 시스템이 발생시키는 주행 의도를 탑승자에게 전달하는 하드웨어 시스템을 제안한다. 제안하는 시스템은 자율주행차량이 사전에 생성된 경로를 따라 주행하면서 출발, 정지, 방향 전환 등과 같은 총 5 가지 상황에 대한 시각, 청각 및 촉각 알림을 통한 자율주행 의도 전달하는 것을 고려한다. 차량용 시트에 모터를 부착하여 촉각 알림을 통해 자율주행 의도를 전달 하였으며, 모니터를 통해 시각 및 청각 알림을 통해 자율주행 의도를 전달하였다. PC 에서 개발에 필요한 시뮬레이션 데이터를 처리하였으며, 시뮬레이션 환경에서 개발, 실험 및 평가가 진행되었다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.221-239
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• 2022

Various elements such as geometry, traffic safety facilities, congestion level, weather, etc., need to be appropriately reflected in the assessment scenario evaluating the driving safety of automated vehicles. Therefore, this study first established a scenario structure and defined the layer of elements, to derive the elements to be reflected in the automated driving safety evaluation. After that, all elemental candidates that can be reflected in each layer were derived by reviewing the relevant literature. Finally, as a result of an expert survey, 77 items were selected to be reflected in the automated driving safety evaluation. The selected elements are expected to be actively utilized in developing scenarios for the driving safety evaluation of automated vehicles in simulation, proving ground, and real road assessments.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.541-543
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• 2018

자율주행 소프트웨어는 주변 상황을 인식 및 판단하여, 스스로 동작을 제어하는 소프트웨어를 의미한다. 최근 세계적으로 자율주행 자동차에 대한 관심이 높아지고 있고, 이에 따른 자율주행 소프트웨어의 개발 또한 활발하게 진행되고 있다. 그러나 자율주행의 특성상 테스팅 과정에서 물리적인 손상을 일으킬 가능성이 높으며, 테스팅를 위한 시간적, 인력적 비용이 많이 들어가기 때문에 여러 차례 테스팅을 하기 쉽지 않다. 이러한 점은 자율주행 소프트웨어의 안전성을 높일 수 없는 요인으로 평가된다. 따라서 본 논문에서는 OpenDS를 활용한 가상 시뮬레이터 시스템과 이를 바탕으로 한 규격화 된 자율주행 소프트웨어의 테스팅 방법을 제안하며 그 실용 가능성을 평가한다.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.38-50
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• 2018

Emerging automated driving environments will lead to a mixed traffic flow depending on the interaction between automated vehicles (AVs) and manually driven vehicles (MVs) because the market penetration rate (MPR) of AVs will gradually increase over time. Understanding the characteristics of mixed traffic conditions, and developing a method to control both AV and MV maneuverings smoothly is a backbone of the traffic management in the era of automated driving. To facilitate smooth vehicle interactions, the maneuvering of AVs should be properly determined by various traffic and road conditions, which motivates this study. This study investigated whether the aggressiveness of AV maneuvering, defined as automated driving aggressiveness (ADA), affect the performance of mixed traffic flow. VISSIM microscopic simulation experiments were conducted to derive proper ADAs for satisfying both the traffic safety and the operational efficiency. Traffic conflict rates and average travel speeds were used as indicators for the performance of safety and operations. While conducting simulations, level of service(LOS) and market penetration rate(MPR) of AVs were also taken into considerations. Results implies that an effective guideline to manage the ADA under various traffic and road conditions needs to be developed from the perspective of traffic operations to optimize traffic performances.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.641-652
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• 2021

Drivers have willing to do secondary tasks in situations deemed safe autonomous driving. I studied that positive notifications for secure areas could improve situation awareness and driving performance after TOR(Take over request) in autonomous driving. Comparing TOR alert only and monitoring alert conditions, participants in the positive notification condition showed higher situation awareness and driving performance. Also, in emotional assessment, the positive notification condition showed higher positive evaluation than other conditions. Due to Covid-19, I designed experiments separate online with driving videos in experiment 1 and offline using a driving simulator in experiment 2. This study has implications that presented a different perspective on autonomous driving notification design.