• 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.

• 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.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.54-66
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• 2024

Various new ITS Services to support autonomous vehicles. Infra-guidance service is also one of the new ITS services that have emerged to harmonize the traffic flow in mixed traffic by assisting autonomous vehicles. As a verification procedure to introduce a new ITS service, use cases and scenarios will be established for various spatial and situational ranges that may occur on the road, and limited test operations and living lab pilot operations will be performed. On the other hand, numerous cases occur depending on environmental factors such as the traffic volume at the time of service operation, weather and road geometric characteristics. This study presents a test scenario design method for verifying new ITS services, focusing on the infra-guidance service that is being researched as an emerging autonomous driving-supported technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.51-56
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• 2020

This study examines the strategies employed by GM, who experienced bankruptcy in 2008. Specifically, we explore the autonomous driving-related technologies and execution, which GM began developing later than other car manufacturing companies. This study found that GM implemented aggressive M&A in search of vertical industrial integration for the development and production of autonomous vehicles. GM selected candidate firms to complement its technological gaps for the development and implementation of the autonomous vehicle. Secondly, GM achieved executive capacity by attempting to build a vertical integration in the wider scope of components, solution, service, and sales. Thirdly, the consistent governmental support and policies, such as the connected car project, M-City, and NCHRP Program expedited the development process. This study provides practical and policy implications for Korean companies and policymakers related to the automotive industry.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.330-340
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• 1998

자율주행 반송차가 주어진 경로를 따라 주행 할 때 주행면의 불균일성과 같은 외란요인과 자율반송차 시스템 자체의 비선형성 등으로 인하여 원치 않는 경로추종오차가 발생하게 되는데 본 연구에서는 이러한 경로추종오차를 최소화하기 위해서 신경회로망을 이용한 경로추종 오차 보상방법을 제안한다. 본 방법에서는 신경회로망을 통하여 조향각 보상량을 제공하므로써 경로추종오차를 보상한다. 신경망은 다층 퍼셉트론을 채용하였으며 역전파 알고리즘의 최급강하규칙(Gradient descent rule)을 이용하여 학습을 수행하였다. 본 제안에서는 학습오차를 경로추종오차로부터 정의하므로써 경로추종오차가 최소화되록 신경회로망을 학습시켰다. 제안된 방법의 타당성은 다양한 경로에 대한 모의실험 및 실제 실험을 통하여 검증하였다.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.545-556
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• 2017

Various assessment indexes have been developed and utilized to evaluate the driver workload. However, existing workload assessment indexes do not fully reflect driving habits and driving patterns of individual drivers. In addition, there exists significant differences in the amount of workload experienced by a driver and the ability to overcome the driver's workload. To overcome these limitations associated with existing indexes, this study has developed a novel workload assessment index to reflect an individual driver's driving pattern. An average of the absolute values of the steering velocity for each driver are set as a threshold value in order to reflect the driving patterns of individual drivers. Further, the sum of the areas of the steering velocities exceeding the threshold value, which is defined as erratic steering area (ESA) in this study, was quantified. The developed ESA index is applied in evaluating the driver workload of manually driven vehicles in automated vehicle platooning environments. Driving simulation experiments are conducted to collect drivers' responsive behavior data which are used for exploring the relationship between the NASA-TLX score and the ESA by the correlation analysis. As a result, ESA is found to have the greatest correlation with the NASA-TLX score among the various driver workload evaluation indexes in the lane change scenario, confirming the usefulness of ESA.

• 한국정책학회보
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• v.21 no.2
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• pp.91-122
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• 2012

국가 재정사업을 평가하는 재정사업 자율평가제도는 2005년에 도입되어 2010년까지 두 번의 평가주기가 완료되었다. 본 연구는 이러한 시점에서 2차 평가주기(2008년~2010년) 동안 평가된 재정사업을 대상으로 평가결과에 영향을 미치는 요인들을 검토하였다. 본 연구는 1차 평가주기(2005년~2007년)의 평가결과를 분석한 기존 연구의 확장연구로서, 이전 연구결과를 재확인하고 일반화 가능성을 보다 제고할 수 있을 뿐만 아니라 이전 연구결과와의 비교를 통해서 평가제도의 변화가 평가결과의 변화를 가져왔는지를 검토할 수 있다는 점에서 의의가 있다. 또한 2차 평가주기가 완료된 시점에서, 향후 제도 개선을 위한 정책적 시사점을 줄 수 있다는 점에서 의의가 있다. 본 연구의 주요 분석결과 및 정책적 함의는 다음과 같다. 첫째, 1차 평가주기에 비해서 2차 평가주기의 평가결과가 향상되었다는 점에서 사업의 성과향상 또는 제도에 대한 실무자들의 이해가 보다 증진된 것으로 해석할 수 있다. 둘째, 성과계획항목이 평가결과에 지나치게 강한 영향력을 준다는 측면에서, 이에 대한 제도적 보완이 요구된다. 성과지표의 설정 및 목표치의 결정은 집행 이전에 적절히 이루어져야 할 부문이기에 이를 계획수립 시 사전적으로 지도할 필요가 있다. 셋째, 집행항목과 성과항목 간 부(-)의 관계를 가지므로 이에 대한 적절한 제도적 보완이 필요하다. 넷째, 제도의 타당성을 저해할 수 있는 비평가요인이 총점에 영향을 미치고 있다는 점을 감안할 때, 이에 대한 제도적 보완이 필요하다.