• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.2
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• pp.81-86
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• 2013

This paper presents the lane change system for collision avoidance. The proposed algorithm for the collision avoidance consists of path generation and path following. Using a calculated TTC (Time to Collision), partial braking is operated and collision avoidance path is generated considering relative distance, velocity and acceleration. Based on the collision avoidance path, desired yaw angle and yaw rate are calculated for the automated path following. The lateral controller is designed by a Lyapunov function approach using 3 D.O.F vehicle model and vehicle parameters. The required steering angle is determined from wheel velocity, longitudinal and lateral velocity in order to follow the desired yaw angle and yaw rate. This system is developed MATLAB/Simulink and its performance is evaluated using the commercial software CarSim.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.1-8
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• 2023

In this paper, we developed a mid-range automotive radar systems based on the performance requirements and test procedures of the intelligent transport systems, that is lane change decision aid systems (LCDAS). The mid-range automotive radar has the maximum detection range up to 80m and an update time within 50ms. The computational loads of a signal processing were reduced by using ROI preprocessing technique. Considering actual driving environments, radar performance evaluations were conducted in two driving scenarios at an automotive proving ground.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.639-645
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• 2018

This paper is intended to develop a decision model that can be applied to autonomous vehicles and autonomous mobile vehicles. The developed module has an independent configuration for application in various driving environments and is based on a platform for organically operating them. Each module is studied for decision making on lane changes and for securing safety through reinforcement learning using a deep learning technique. The autonomous mobile moving body operating to change the driving state has a characteristic where the next operation of the mobile body can be determined only if the definition of the speed determination model (according to its functions) and the lane change decision are correctly preceded. Also, if all the moving bodies traveling on a general road are equipped with an autonomous driving function, it is difficult to consider the factors that may occur between each mobile unit from unexpected environmental changes. Considering these factors, we applied the decision model to the platform and studied the lane change decision system for implementation of the platform. We studied the decision model using a modular learning method to reduce system complexity, to reduce the learning time, and to consider model replacement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.87-92
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• 2013

This study is to analyze the impacts of different High-Pass lane speed limits. Paramics, microscopic simulation software, was used to perform microscopic simulations. For the simulations, Incheon toll gate traffic count data was used. The Paramics simulation results show that higher High-Pass speed limit (70Km/h) produced better traffic flow condition and less air pollution cost compared to existing High-Pass speed limit (30Km/h).

• 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.

• 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.

• 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 KIPS Transactions:PartB
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• v.15B no.6
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• pp.543-552
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• 2008

ATIS(Advanced Traveler Information System) is the system to offer a real-time traffic information or traffic situation for the benefit of the client. One of traffic information collection methods for ATIS research is the method of image analysis. The method is divided into two : one is the method to set two loop detectors at the area and the other is the method detecting the vehicle through an image analysis. In this paper, we propose a real-time traffic information collection system to mix two methods. The system installs multiple virtual detection lines and traces the location of the vehicle. Use of multiple virtual detection lines supplements the defect of the method of loop detectors. And we drew a representative pixels in the detecting area and used it for image analysis. This is to solve the problem of time delay which increases as the image size increases. We gathered traffic images and experimented using the system and got 92.32% of detection accuracy.

• 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.