• Proceedings of the Korean Society of Marine Engineers Conference
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• 2012.06a
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• pp.214-214
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• 2012

본 논문 만타형 무인잠수정을 이용한 실해역 자율주행 성능시험에 관한 내용을 다룬다. 만타형의 개발을 위해서 6자유도 운동방정식에 대한 시뮬레이션을 실시하였으며, 시뮬레이션 결과를 바탕으로 만타형 무인잠수정을 개발하여 실해역에서 성능시험을 실시하였다. 실해역 자율주행 시험은 가시선 방법(LOS, Line of Sight)방법을 이용하였으며, 제어에는 PD 제어기를 사용하였다. 목표반경을 10m로 하였을 때, 설정된 좌표로 이동하는 것을 확인하였다.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.332-347
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• 2017

Analysis of the interaction between the automated vehicles and manual vehicles is very important in analyzing the performance of automated cooperative driving environments. In particular, the automated vehicle platooning can affect the driving behavior of adjacent manual vehicles. The purpose of this study is to analyze the lane change behavior of the manual vehicles in automated vehicle platonning environment and to conduct the experiment and questionnaire surveys in three stages. In the first stage, a video questionnaire survey was conducted, and responsive behaviors of manual vehicles were investigated. In second stage, the driving simulator experiments were conducted to investigate the lane change behaviors of in automated vehicle platonning environments. To analyze the lane change behavior of the manual vehicles, lane change durations and acceleration noise, which are indicators of traffic flow stability, were used. The driving behavior of manual vehicles were compared across different market penetration rates (MPR) of automated vehicles and human factors. Lastly, NASA-TLX (NASA Task Load Index) was used to evaluate the workload of the manual vehicle drivers. As a result of the analysis, it was identified that manual vehicle drivers had psychological burdens while driving in automated vehicle platonning environments. Lane change durations were longer when the MPR of the automated vehicles increased, and acceleration noise were increased in the case of 30-40 years old or female drivers. The results from this study can be used as a fundamental for more realistic traffic simulations reflecting the interaction between the automated vehicles and manual vehicles. It is also expected to effectively support the establishment of valuable transportation management strategy in automated vehicle environments.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.867-878
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• 2018

As the era of AVs (Automated Vehicles) comes to a close, many researches related to AVs have been conducted. Up until now, research on traffic flow impact of AVs has been the main topic, and research on traffic management for AVs is still in beginning stage. This study analyzed the effect of Dynamic Merge Control (DMC) in manual vehicle (MV) and AV environment at work zone. Dynamic Late Merge (DLM) and DLM with Dynamic Early Merge (DEM) are compared by simulation. Simulation results showed that DLM improves travel time and work zone throughput compared to no merge control case in both MV and AV environment. In the case of additional operation of DEM, the improvement effect was not observed in MV environment, but it was improved in AV environment. As a result, DMC operation in AV environment was as effective as the improvement in transition from MV to AV environment. Therefore congestion reduction at freeway work zone by DMC will be possible in future AV environment, and the improvement of DMC can be suggested.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.14-28
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• 2018

Thanks to technical improvement on the vehicle to vehicle communication and the intelligent transportation system, gradual introduction of the autonomous vehicles is expected soon in the market. The study analyzes the autonomous vehicles' impacts on the network efficiencies. In order to measure the network efficiencies, the study applies the sequential procedures that combines the microscopic and macroscopic simulations. The microscopic simulation attends to the capacity changes due to the autonomous vehicles' proportions on the roadway while the macroscopic simulation utilizes the simulation results in order to identify the network-wide improvement. As expected, the autonomous vehicles efficiently utilizes the existing capacity of the roadway than the human driving does. Particularly, the maximum capacity improvements are expected by the 190.5% on the expressway. The significant capacity change is observed when the autonomous vehicles' proportions are about 80% or more. These improvements are translated into the macroscopic model, which also yields overall network efficiency improvement by the autonomous vehicles' penetration. However, the study identifies that the market debut of the autonomous vehicles does not promise the free flow condition, which implies the possible needs of the system optimal routing scheme for the era of the autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.107-121
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• 2017

This study conducted a 3-stage survey and simulation experiment to identify the impact of vehicle platoons on car-following behavior of manually-driven vehicles. Vehicle maneuvering data obtained from driving simulations was statistically analyzed based on three measures including average speed, acceleration noise, and offset to represent the deviation of lateral movements. Results indicate that MV drivers tended to have psychological burden while driving in automated vehicle platooning environments, which resulted in different vehicle maneuvers. It is expected that the outcome of this study would be useful fundamentals in developing various traffic operations strategies for managing mixed traffic stream consisting of MVs and autonomous vehicles.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.298-298
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• 2022

최최근 자율주행차의 안전한 주행을 보장하기 위한 모델 공식 기반 접근이 제시되고 있으며, 인텔-모빌아이의 RSS(responsibility-sensitive safety) 모델[1, 2]과 엔비디아의 SFF(Safety Force Field) 방법[2]이 주목받고 있다. 자율주행차 시뮬레이터을 이용하여 이러한 안전 주행 모델 적용의 효과와 역효과를 시뮬레이션하는 것은 자율주행 자동차와 제도의 개발에 매우 중요하다. 본 연구에서는 RSS와 SFF 모델을 살펴보고 이를 자율주행에 적용하기 위한 비교 연구 방법을 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.698-701
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• 2020

여러 대의 자율주행 차량이 하나의 그룹을 형성하여 주행하는 군집주행은 미래 고속도로 교통 시스템의 핵심 기술이다. 이러한 군집주행에서 발생할 수 있는 다양한 상황에서의 안전을 고려하는 일은 단독 자율 주행에서의 경우보다 더 어렵다. 다양한 군집주행의 안전 위협 요인 중, 의도하지 않은 동작으로부터 자율주행 차량의 안전성을 향상하는 방법을 가이드하기 위하여 새로운 표준 ISO/PAS 21448이 제정되었다. 본 논문에서는 ISO/PAS 21448 표준이 다루는 시나리오를 통해 군집주행에서 발생할 수 있는 의도하지 않은 상황의 극복을 위한 방법을 제시하였다. 특히 군집주행 시뮬레이터인 VENTOS를 이용하여 본 논문에서 제시하는 방법이 안전한 군집주행이라는 목표를 달성할 수 있음을 확인하였다.

• Journal of Korea Game Society
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• v.15 no.5
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• pp.131-142
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• 2015

A self-driving car is an autonomous vehicle capable of fulfilling the main transportation capabilities of a traditional car. It must be capable of sensing its environment and navigating without human input. In this paper, we design the agent that can simulate these self-driving cars and develop a prototype for it. To do this, we analyze the requirements for the self-driving car, and then the agent is designed to be suitable for traditional multi-agent system. The key point of the design is that agents move along the steering forces only. The prototype of the designed agent was implemented by using Unity 3D. From simulation results using the prototype, movements of the agents were very realistic. However, in the case of increasing the number of the agent the performance was seriously degraded, and so the alternatives of the problem were suggested.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.55-72
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• 2017

Autonomous Vehicles(AV) are considered as an alternative to solve various social problems. Many researches which are related to developing technologies and AV operations have been conducted vastly and on-going. However, there seem to be little studies on various influences of AI algorithm on driving installed in AV. This study aims to examine the impacts of the ethical decisions made by Utilitarianism-based AI in AV when the oncoming car crossed over the central line. It establishes scenarios about situation of encroaching a central line and analyzes traffic impacts of ethical decision made by AV. According to the results of the analyses, as th accident occurs, overall speed of traffic decrease. There is a negative impact on the traffic flow when AV made an Utilitarian-based ethical decision by changing the lane. However, when AV choose to collide head-on, there is a positive effect to relieve traffic flow with an assistance of CACC, equipped.