• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.329-332
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• 2007

현재 2D기반 내비게이션에서는 다양한 형태로 차량에 부착한 단말기나 핸드폰을 통하여 차량 주행 안내서비스를 제공하고 있으나, 이러한 주행 안내 서비스는 대부분 2차원 평면상에서 정보만을 지원해 줄 뿐 사람의 인식과 일치하는 실감형 정보를 제공하지 못하는 한계가 있다. 또한 차량이 도로를 주행하는 과정에서 다양한 돌발 상황이 발생할 수 있는데 이에 대한 정보의 제공이나, 또는 주행안내에 필수적인 직진, 회전 등 방향 정보와 차선 변경, 교통 표지판 정보 등 필요정보를 운전자에게 가장 효율적으로 제공할 수 있는 실감형 정보 제공의 필요성이 커지고 있는 실정이다. 본 논문에서는 안내 서브시스템, 차선 인식 서브시스템, 신호등/표지판 인식 서브시스템으로부터 정보를 취득하여, 취득된 정보를 표현 서브시스템이 안내 정보를 표현할 수 있도록 정보를 제공하는 주행상태 판단 모듈의 기능을 구현 한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.575-583
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• 2017

This paper describes the design and evaluation of a driving mode decision algorithm for automated driving for merge situations on highways. For the development of a highly automated driving control algorithm for merge situations, the driving mode decision is crucial for merging appropriately. There are two driving modes: lane keeping and lane changing (merging). The merge mode decision is determined based on the state of the surrounding vehicles and the remaining length of the merge lane. In the merge mode decision algorithm, merge possibility and the desired merge position are decided to change the lane safely and quickly. A safety driving envelope is defined based on the desired driving mode using the information on the surrounding vehicles' behaviors. To obtain the desired steering angle and longitudinal acceleration for maintaining the subject vehicle in the safe driving envelope, a motion planning controller is designed using model predictive control (MPC), with constraints that are decided considering the vehicle dynamics, safe driving envelope, and actuator limit. The proposed control algorithm has been evaluated via computer simulation studies.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.409-411
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• 2018

자율주행차에서 경로계획기법은 지도, 목적지 경로와 다른 정적/동적 장애물에 대한 예측 정보를 바탕으로, 안전하고, 합법적이며 효율적으로 차량을 조종하는 목표를 가진다. 고속도로 환경에서, 차량이 차선을 유지하고, 다른 차량들과 충돌을 회피하며, 더 느리게 움직이는 트래픽을 지나쳐 효율적이면서 안전한 경로를 생성하는 기법이 요구된다. 본 연구에서는, 시스템의 행위를 모델링하는 기법 중의 하나인 유한상태기계를 적용하였다. 시뮬레이터를 통해, 급가속/감속과, 충돌 없이, 차선을 유지/변경을 힐 수 있음을 보였다. 자율주행차의 고속도로 주행의 경우, 유한상태기계를 적용하여, 효율적이고 안전한 경로계획을 수행할 수 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.97-106
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• 2024

The Data Storage System for Automated Driving(DSSAD) is a system that records driving information of Lv.4 or higher autonomous vehicles and is different from EDR that records car information in emergency situations. The study of DSSAD recordings is important for responding to various events that may occur in the future commercialization of Lv.4 autonomous vehicles. Therefore, in this study, we conducted a expressway automated driving demonstration and analyzed the collected data to derive the recording elements of DSSAD. During our two-year demonstration of autonomous driving on expressways, we collected and analyzed instances of disengagement. Our findings indicate that 51.6% of disengagement on expressways occurred during lane changes. From the study, we have identified DSSAD record elements for analyzing disengagement situations. Furthermore, implications of future research direction of disengagement analysis were presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.33-39
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• 2014

Automatic driving needs many functions such as the obstacle recognition, the lane recognition, and the lane change, etc. In this paper, we realized a system which automatically drove the three-kinds of vehicle driving course, to introduce and apply the concept of 'color recognition' that expands the scope of 'lane recognition' for vehicle driving. We made the reduced each course compared with RC(Radio Control) car size, and controlled the steering considering the position and the slope of the detection line and the speed. Because the RC car does not have the brake function, we consider the speed and the position of the detection line to stop the RC car.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.65-70
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• 2022

Lane change in urban environments is a challenge for both human-driving and automated driving due to their complexity and non-linearity. With the recent development of deep-learning, the use of the RNN network, which uses time series data, has become the mainstream in this field. Many researches using RNN show high accuracy in highway environments, but still do not for urban environments where the surrounding situation is complex and rapidly changing. Therefore, this paper proposes a lane change possibility decision network by adopting Attention layer, which is an SOTA in the field of seq2seq. By weighting each time step within a given time horizon, the context of the road situation is more human-like. A total 7D vectors of x, y distances and longitudinal relative speed of side front and rear vehicles, and longitudinal speed of ego vehicle were used as input. A total 5,614 expert data of 4,098 yield cases and 1,516 non-yield cases were used for training, and the performance of this network was tested through 1,817 data. Our network achieves 99.641% of test accuracy, which is about 4% higher than a network using only LSTM in an urban environment. Furthermore, it shows robust behavior to false-positive or true-negative objects.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.5
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• pp.1-8
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• 1997

The purpose of this study is to suggest the methods to model driver input and evaluate the handling performances of a vehicle by dynamic simulation using ADAMS (Automated Dynamic Analysis of Mechanical Systems) software. The driver input was modeled using the PID controller to follow the desired velocities and paths. The gains of the controller were decided by the trial and error methods aided by Ziegler-Nichols rule. It was successful to apply the rule for the vehicle model to follow the desired values of steady state cornering and lane change maneuver. As the results, handling performances of baseline and two variegated vehicles were evaluated. The theoretical provement was performed to explain the differences.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.17-26
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• 2023

This paper presents extended state feedback control based on impulse response for lane change of autonomous driving vehicle. The triple characteristic root of path tracking system and longitudinal velocity determine feedback gains. We suggest a resemblance of impulse response curve of the system and lane change trajectory of the vehicle. The root affects the duration of lane change and lateral acceleration. The effect of limited lateral acceleration and saturation of steering angle will be analyzed and discussed. Finally, simulation results will show the trajectory of lane change based on impulse response under limitation of lateral acceleration.

• 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.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.691-694
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• 2009

전세계적으로 운전자의 주행시 차선변경이나 정지시 돌발적으로 지나가는 옆차선의 차량을 감시함으로서 교통사고발생율을 대폭 감소시킬 수 있기 때문에 많은 시스템들이 개발되고 있다. 그러나 대부분 비젼시스템과 연결되는 고정형 타입으로서 운전자의 시각을 지원해 주는 경우가 많았다. 본 연구에서는 회전형으로 제작되어 사용자가 원하는 대로 감시영역을 축소시키거나 확대시킬 수 있는 방식으로서 사각지대 감지를 위한 서보모터의 회전속도/각도와 초음파센서의 측정거리 및 LED의 ON-OFF 등 각종 파라미터를 조절함으로서 최적의 사양을 선정하였고 시험을 통해 그 타당성을 증명하였다.