• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.173-173
• /
• 2017

드론의 시장규모가 커짐에 따라 초창기 군사 목적에서 현재 민간부문으로 확대되고 있다. 현재 드론은 실외에서 사용될 목적으로 제작된 것이 많으나 실내에서도 드론의 활용 여부가 증가할 것으로 예상된다. 본 연구에서는 실외에서만 사용 가능한 GPS를 대신하여 영상 촬영으로 획득한 이미지를 CNN으로 학습을 시켜 자율고도제어비행을 하도록 한다. 첫 번째로 수동 조작하는 드론에 IMU센서를 부착하여 획득한 고도 데이터를 표로 제시함으로써 GPS를 사용하지 않는 드론의 실내주행에서 일정한 고도 유지는 다소 무리가 있음을 보여준다. 두 번째로 드론의 수동 조작은 일정하지 않은 고도 때문에 CNN의 학습할 영상 획득이 어렵다. 일정한 고도의 영상 획득을 위한 실험용 높이 조절 Base를 제작하여 고도별 영상을 획득한다. 획득한 영상을 통해 얻은 이미지를 CNN 학습을 시킨 후, 학습에 사용되지 않은 이미지를 사용하여 고도 판별을 확인한다. 대조군으로 실내장소를 바꾸어 미리 학습된 CNN으로 고도 판별을 확인한다. 학습에 사용된 이미지의 환경(생명공학관)과 대조군(제 2 공학관)이 촬영된 장소의 환경요소의 차이로 오차가 발생한다. 오차는 실내 장소의 총 높이의 차이 및 서로 상이한 천장 구조물에 따른 것으로 사료되며 Data crop을 통해 획득한 이미지의 천정 부분을 제거하여 노이즈를 줄여 고도 판별의 정확도를 높일 수 있을 것으로 예상한다. 세 번째, CNN으로 학습을 통해 Model을 도출하여 자율 고도 제어 프로세스를 제시한다. 그리고 해당 프로세스를 이용한 자율고도제어 주행과 수동조작을 통한 주행에서의 Z축 가속도 데이터의 표준편차를 비교하여 본 연구의 실효성을 보여준다

• Broadcasting and Media Magazine
• /
• v.24 no.1
• /
• pp.63-72
• /
• 2019

고령인구의 증대 및 출생 인구의 감소로 과소지와 대중교통 취약지역이 확산되고 있다. 이러한 인구구조의 변화는 교통약자의 독립적 이동이 더욱 불편해지고, 물류의 수송이 어려워 진다. 한편, 도심은 차량의 포화상태로 대기환경의 질이 나빠지고 도심도로는 주차장으로 변질될 뿐만 아니라, 운전자와 보행자 모두에게 안전의 위협이 되고 있다. 이러한 환경과 이동의 효율성을 극대화 하는 방안으로 친환경자동차와 자율주행기술의 접목이 연구개발 중이다. 자율주행기술은 자율주행차와 도로 인프라에 ICT가 융 복합되어 이동과 수송분야의 새로운 산업과 서비스 창출이 가능하다. 본 고에서는 교통약자의 이동과 물류의 수송을 지원하는 자율주행기술의 개발 동향을 살펴본다. 특히 광화문, K-City 등의 도심 자율주행서비스 테스트 경험을 통해 해결해야 하는 복잡한 도심 주행 환경의 인지와 교차로 및 합류로, 비정형 도로환경에서의 주행협상기술의 필요성을 소개한다. 도심의 주행 환경은 고속도로와 같은 자동차 전용도로와 달리, 신호등과 교차로, 2륜 이동체 및 버스 등이 다양하게 혼재된 것으로 인지 및 판단 기능의 고도화가 적극적으로 요구된다. 그리고, 다양한 자율주행서비스 시장을 확산하기 위해 요구되는 이동하는 공간과 시간을 메꿔 줄 미디어 콘텐츠의 역할에 대해 설명하고자 한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.4
• /
• pp.28-46
• /
• 2021

85-90% of the causes of traffic accidents are human factors, and autonomous vehicles with little free running distance can be an alternative to prevent traffic accidents caused by human factors. However, securing safety of autonomous vehicles should be preceded in order to reduce traffic accident damage through the introduction of autonomous vehicles. Therefore, it is necessary to verify whether the vehicle can respond appropriately to changes in the road and traffic environment through repeated and reproduced test runs in an environment similar to the actual road. In this study, K-City's development strategies for upgrading, differentiating, and systematic development were established by comparing and analyzing the current status of domestic and foreign testbeds and business environment analysis. Furthermore, we derive challenge tasks to achieve each strategy.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.70-86
• /
• 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
• /
• v.22 no.1
• /
• pp.172-191
• /
• 2023

This study was undertaken to strategize the mixed traffic operation of autonomous vehicles in the pilot zone. This was achieved by analyzing the changes expected when autonomous vehicles are mixed in the autonomous vehicle pilot zone. Although finding a safe and efficient traffic operation strategy is required for the pilot zone to serve as a test bed for autonomous vehicles, there is no available operation strategy based on the mixture of autonomous vehicles. In order to presents a traffic operation strategies for each period of autonomous vehicle introduction, traffic efficiency and safety analysis was performed according to the autonomous vehicle market percentage rate. Based on the analysis results, the introduction stage was divided into introductory stage, transition period, and stable period based on the autonomous vehicle market share of 30% and 70%. This study presents the following traffic operation strategies. Considering the traffic flow operation strategy, we suggest the advancement of the existing road infrastructure at the introductory stage, and operating an autonomous driving lane and the mileage system during the transition period. We also propose expanding the operation of autonomous driving lanes and easing the speed limit during the stable period. In the traffic safety strategy, we present a manual and legal system for responding to autonomous vehicle accidents in the introductory stage, an analysis of the causes of autonomous vehicle accidents and the implementation of preventive policies in the transition period, and the advancement of the autonomous system and the reinforcement of the security system during the stable period. Through the traffic operation strategy presented in this study, we foresee the possibility of preemptively responding to the changes of traffic flow and traffic safety expected due to the mixture of autonomous vehicles in the autonomous vehicle pilot zone in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.5
• /
• pp.200-215
• /
• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.1
• /
• pp.6-13
• /
• 2022

The Ministry of Land, Infrastructure and Transport (MoLIT) and the Korean Automobile Testing and Research Institute (KATRI) are supporting the development of Lv.3 automated vehicle (hereinafter, AV) technology by constructing an automated driving pilot city (as known as K-City) equipped with total 5 evaluation environments (urban, motorway, suburban, community road, and autonomous parking facility) which is a test bed exclusively for AV (2017~2018). An upgrade project is in a progress to materialize harsh environments such as bad weather (rain, fog, etc.) and reproduction of communication jamming (GPS blocking, etc.) with the purpose of supporting the development of Lv.4 connected & automated vehicle (hereinafter, CAV) technology (2019~2022). We intend to proactively establish a national level standard for CAV test-bed and test road requirements, test method, etc. for establishment of a road map for the construction of the test bed which is being promoted step by step and analyze and, when required, benchmark the case of China that has announced and is utilizing it. Through this, we plan to define standardized requirements (evaluation facility, evaluation system, etc.) on the test bed for the development of Lv.4/4+ CAV technology and utilize the same for the design and construction of a test bed, establishment of a road map for the construction of a real car-based test environment related to the support for autonomous driving service substantiation, etc. through provision of an evaluation environment utilizing K-City, and the establishment of a K-City upgrade strategies, etc.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.4
• /
• pp.60-69
• /
• 2022

Recently, the importance of simulation validation in a virtual environment for autonomous driving system validation is increasing. At the same time, interest in the advancement of the virtual driving environment is also increasing. To develop autonomous driving technology, a simulation environment similar to the real-world environment is needed. For this reason, not only the road model is configured in the virtual driving environment, but also the driving environment configuration that includes the surrounding environments -traffic, object, etc- is necessary. In this article, FMTC, which is a test bed for autonomous vehicles, is implemented in a virtual environment and advanced to form a virtual driving environment similar to that of real FMTC. In addition, the similarity of the virtual driving environment is verified through comparative analysis with the real FMTC.

• Journal of Auto-vehicle Safety Association
• /
• v.15 no.1
• /
• pp.16-26
• /
• 2023

Recently, the importance of simulation in a virtual driving environment as well as real road-based tests for autonomous vehicle testing is increasing. Real road tests are being actively conducted at K-City, an autonomous driving test bed located at the Korea Automobile Safety Test & Research Institute of the Transportation Safety Authority. In addition, the need to advance the K-City virtual driving environment and build a virtual environment similar to the autonomous driving system test environment in real road tests is increasing. In this study, for K-City of Korea Automobile Safety Test & Research Institute, using detailed drawings and actual field data, K-City virtual driving environment was advanced, and similarity verification was verified through comparative analysis with actual K-City.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.3
• /
• pp.18-29
• /
• 2022

Recently, cooperative intelligent transport systems (C-ITS) testbeds have been deployed in great numbers, and advanced autonomous driving research using V2X communication technology has been conducted actively worldwide. In particular, the broadcasting services in their beginning days, giving warning messages, basic safety messages, traffic information, etc., gradually developed into advanced network services, such as platooning, remote driving, and sensor sharing, that need to perform real-time. In addition, technologies improving these advanced network services' throughput and latency are being developed on many fronts to support these services. Notably, this research analyzed the network latency requirements of the advanced network services to develop a remote driving service for the droid type low-speed robot based on the 3GPP C-V2X communication technology. Subsequently, this remote driving service's performance was evaluated using system modeling (that included the operator behavior) and simulation. This evaluation showed that a respective core and access network latency of less than 30 ms was required to meet more than 90 % of the remote driving service's performance requirements under the given test conditions.