• Journal of Auto-vehicle Safety Association
• /
• v.11 no.3
• /
• pp.37-42
• /
• 2019

This paper presents an autonomous acceleration planning algorithm for pedestrian collision avoidance at urban. Various scenarios between pedestrians and a vehicle are designed to maneuver the planning algorithm. To simulate the scenarios, we analyze pedestrian's behavior and identify limitations of fusion sensors, lidar and vision camera. Acceleration is optimally determined by considering TTC (Time To Collision) and pedestrian's intention. Pedestrian's crossing intention is estimated for quick control decision to minimize full-braking situation, based on their velocity and position change. Feasibility of the proposed algorithm is verified by simulations using Carsim and Simulink, and comparisons with actual driving data.

• Journal of the KSME
• /
• v.43 no.8
• /
• pp.57-63
• /
• 2003

2002년 한 해 동안 동역학 및 제어 분야의 연구 동향을 동역학, 진동, 계측, 제어, 기구학, 로봇공학, 차량공학 등으로 나누어 각 분야에 대하여 정리하였다.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.2
• /
• pp.7-13
• /
• 2022

This paper presents a yaw moment control based on estimated mass for manual-shift commercial vehicles. In yaw moment controller, parameter uncertantiy of vehicle mass is important because the desired yaw moment depends on vehicle parameter. However, in the case of commercial vehicle, the weight of the loaded vehicle is more than twice as much as compared to the unloaded vehicle. The proposed algorithm estimates the vehicle mass by using the longitudinal dynamic and gear shifting characteristics. The estimated mass is used to adaptively modify the vehicle parameters. In addition, this paper estimates the chamber pressure of a pneumatic brake and generates the target yaw moment through on/off valve control. MATLAB/Simulink and Trucksim were performed under sine with dwell test. The results demonstrate that the proposed algorithm improves the lateral and rollover stability.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.7 no.9
• /
• pp.212-219
• /
• 1999

This paper describes the NANDO VDC (Vehicle Dynamics Control) system for the vehicle stability enhancement and consists of the control strategies , computer simulation and tests on the various road surface. This VDC system controls the dynamic vehicle motion in the emergency situation such as the final oversteer/understeer andallows the vehicle to follow the course as desired by the driver. The system is based on an active yaw control and its performance verified by the test is shown. Also the comparison between the MANDO VDC System and a competitor is carried out.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.11 no.4
• /
• pp.173-179
• /
• 2003

In this paper, a real-time multibody vehicle dynamics and control model has been developed for a virtual reality intelligent vehicle simulator. The simulator consists of low PCs for a virtual reality visualization system, vehicle dynamics and control analysis system a control loading system, and a network monitoring system. Virtual environment is created by 3D Studio Max graphic tool and OpenGVS real-time rendering library. A real-time vehicle dynamics and control model consists of a control module based on the sliding mode control for adaptive cruise control and a real-time multibody vehicle dynamics module based on the subsystem synthesis method. To verify the real-time capability of the model, cut-in, cut-out simulations have been carried out.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.4
• /
• pp.7-13
• /
• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.3
• /
• pp.205-211
• /
• 2017

To achieve an advanced control of automobiles, it is necessary to acquire the values of the parameters of a vehicle in real time to conduct precise vehicle control practices such as automatic platooning control. Vehicle control is especially required in controlling trucks, as the mass and inertia change widely according to the loading conditions. Thereafter, we propose to estimate the yaw moment of inertia of the truck in real-time during travelling, by applying the dual Kalman filter algorithm, which estimates the state variables and values of the parameters simultaneously in real-time. The simulation results show that the proposed method is effective for the estimation, which uses commercial software for simulating and analyzing the vehicle dynamics.

• Proceedings of the KSME Conference
• /
• 2003.11a
• /
• pp.1714-1717
• /
• 2003

ECCOMAS Thematic Conference Multibody 2003 was held at IST (Instituto Superior Technico), Lisbon, Portugal from July 1 to July 4. 2003. And MBDV(Multibody Dynamics and Vibration) in the 2003 ASME DETC was held at Chicago, U.S.A. from September 2 to September 6. In this paper, the presented papers in these conferences were reviewed and the trends in the multibody dynamics are summarized. The session titles in these conferences include Flexible Multibody Dynamics, Vehicle Dynamics, Contact, Biomechanics, Real-time Challenges, Spatial manipulator and Control, Multidisciplinary Applications, and Advanced Education. The poster session was also organized for more discussions in the Multibody2003 conference.

• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2320-2322
• /
• 2004

전자제어식 미끄럼방지 제동장치 (ABS, Antilock Brake System)는 차량의 급제동시 발생할 수 있는 바퀴의 슬립을 방지하여 차량의 제동거리를 단축시키고 주행 성능을 향상시키는 차량 내 안전장치이다. 지난 몇 년 동안 공압식 제동시스템을 사용하는 대형차량에 적합한 미끄럼방지 제동 제어기를 연구해 왔다. 이 제어기는 바퀴의 슬립율과 그 변화량을 이용한 제어 법칙을 유도하여, 제어 파라미터로 사용하고 있다. 이러한 제어 파라미터의 튜닝에는 맡은 반복적인 실험이 요구된다. 이러한 요구에 부응하기 위하여 차량의 제동을 실시간으로 모사 할 수 있는 HILS (Hardware In-the Loop Simulation) 시스템을 개발, 구축하였다. 개발 HILS는 공압식 브레이크 시스템 및 14 자유도를 가지는 차량 동역학 모델 및 타이어-바퀴 동역학을 소프트웨어 모델로 사용하고, 개발 중인 전자제어식 미끄럼 방지 제동 제어기를 하드웨어로 사용하여, 바퀴속도 센서 신호 모의 장치 및 공압 엑추에이터 모의 신호등의 인터페이스 장치를 사용하여 제동중인 차량의 상태를 실시간으로 시뮬레이션 및 감시할 수 있다. 이 개발 HILS를 이용하여 제동 제어기의 제어 파라미터의 튜닝을 짧은 시간에 성공적으로 끝낼 수 있었을 뿐만 아니라, HILS 실험을 마친 제어기는 미끄럼 방지 제동 시험장에서 실차 주행 시험을 무사히 마침으로써, 개발 기간과 비용을 절감할 수 있는 하드웨어를 이용하는 시뮬레이션의 효용성을 간접적으로 증명하였다.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.10
• /
• pp.967-974
• /
• 2017

In this paper, a differential-braking-based yaw moment control system was developed to guarantee robust performance against road bank angle. A new target yaw rate model was established by combining the signal from a lateral acceleration sensor and 2-DOF single track model. In addition, a disturbance observer was utilized to take into account parameter uncertainties in yaw dynamics and to improve robust performance of the controller. CARSIM, which is a multi-DOF vehicle dynamic simulation tool, was used to verify the performance of the proposed controller in various driving scenarios. The simulation results indicate that the stability of the vehicle was robustly maintained by the controller, which is characterized by the reflection of the signal of a lateral acceleration sensor signal and by the compensation of the errors in the model parameters via the disturbance observer.