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채흥석(Heongseok Chae),정용환(Yonghwan Jeong),이명수(Myungsu Lee),민경찬(Kyongchan Min),이경수(Kyongsu Yi) 대한기계학회 2015 대한기계학회 춘추학술대회 Vol.2015 No.11
Regulation for the testing and operation of automated vehicles on public roadways has been recently developed all over the world. For example, the licensing standards for autonomous vehicles have been proposed in California and Nevada. However, safety performance evaluation scenarios for automated vehicles have not been proposed yet. It is important to comprehensively evaluate the safety performance of automated vehicles before they are produced and deployed. This paper presents lane change evaluation scenario of automated vehicles. Because lane change is frequently happened in driving situation, lane change evaluation is crucial. The scenario evaluates safety of automated vehicles changing lane, utilizing target vehicle placed on rear-side (next lane) of automated vehicles. The target vehicle is equipped with adaptive cruise control and auto emergency braking based on human driver data. Safety evaluation factors in lane change situation are also developed. This scenario is investigated via computer simulation.
고속도로 합류점 주행을 위한 강건 모델 예측 기법 기반 자율주행 차선 변경 알고리즘 개발
채흥석(Heongseok Chae),정용환(Yonghwan Jeong),민경찬(Kyongchan Min),이명수(Myungsu Lee),이경수(Kyongsu Yi) 대한기계학회 2017 大韓機械學會論文集A Vol.41 No.7
본 논문에서는 고속도로의 합류지점 상황에서 자율주행을 위한 운전 모드 결정 알고리즘의 개발 및 평가를 진행하였다. 합류 상황을 위한 자율주행 알고리즘 개발에 있어 적절하게 합류를 결정하는 운전 모드 결정이 필수적이다. 운전자 모드는 총 2가지로 차선 유지, 차선 변경(합류)이다. 합류 모드 결정은 주변 차량의 정보 및 합류 차선에 남은 거리를 기반으로 결정된다. 합류 모드 결정 알고리즘에서는 합류 가능 여부를 판단하고 합류가 가능할 때, 안전하고 빠르게 합류하기 위한 최적의 위치를 찾는다. 안전 주행 영역은 주변 차량의 정보 및 주행 모드를 기반으로 정의된다. 안전 주행 영역으로 자율주행차량을 유지하기 위한 조향각과 종방향 가속도를 얻기 위해 여러 제한 조건이 더해진 강건 모델 예측기법이 사용되었다. 본 논문에서 제안된 알고리즘은 컴퓨터 시뮬레이션을 이용해 검증되었다. 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.
High-level Urban Automated Driving with Sensor Fusion based Integrated Environment Representation
Beomjun Kim(김범준),Yonghwan Jeong(정용환),Heongseok Chae(채흥석),Kyongchan Min(민경찬),Kyongsu Yi(이경수) 대한기계학회 2016 대한기계학회 춘추학술대회 Vol.2016 No.12
This paper describes a fully automated driving algorithm on complex urban roads with LiDAR, vision, and GPS/map based environment representation with guaranteed safety. The proposed algorithm consists of the following three steps: an environment representation, a safety driving envelope decision, and a motion optimization. An environment representation system consists of three main modules: object classification, vehicle/non-vehicle tracking and map/lane based localization. A motion planning modules derives an optimal motion as a function of time, from the environment representation results. A safety envelope decision module determines the complete driving corridor that leads to the destination while assigning all objects to either the left or right corridor bound. In the case of moving objects such as other traffic participants, their behaviors are anticipated in the near future. A motion optimization module uses the safety envelop as a constraint and computes a trajectory that the vehicle stays in its bounds. The vehicle control module feeds back the pose estimate of the localization module to guide the vehicle along the planned trajectory. The effectiveness of the proposed automated driving algorithm is evaluated via vehicle tests. Test results show the robust performance on an inner-city street scenario.
자율주행 버스를 위한 모델 독립식 종 방향 가속도 제어기의 동특성 연구
조아라(Ara Jo),임형호(Hyungho Lim),정용환(Yonghwan Jeong),채흥석(Heongseok Chae),이경수(Kyongsu Yi) 대한기계학회 2018 대한기계학회 춘추학술대회 Vol.2018 No.12
This paper presents a longitudinal acceleration controller using a model-free control scheme, so-called model-free cruise controller(MFCC), for the automated bus. The MFCC could control throttle and brake without vehicle information by estimating the vehicle parameters using an adaptation algorithm. The adaptation algorithm of the vehicle parameters was modified to consider the driving condition and dynamic characteristics. Adaptation gain for the algorithm was adjusted in order to improve the acceleration tracking performance. Dynamic analysis model of the bus was developed using Carsim, and then the proposed algorithm was evaluated using Carsim and MATLAB/Simulink. The performance of the MFCC controller and the dynamic characteristics of the bus model were investigated. The results will be utilized to complement the adaptation algorithm and the switching algorithm of the controller.