• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.14-25
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• 2021

This paper presents a RLS based adaptive sliding mode observer (A-SMO) for unknown fault reconstruction in longitudinal autonomous driving. Securing the functional safety of autonomous vehicles from unexpected faults of sensors is essential for avoidance of fatal accidents. Because the magnitude and type of the faults cannot be known exactly, the RLS based A-SMO for unknown acceleration fault reconstruction has been designed with relationship function in this study. It is assumed that longitudinal acceleration of preceding vehicle can be obtained by using the V2V (Vehicle to Vehicle) communication. The kinematic model that represents relative relation between subject and preceding vehicles has been used for fault reconstruction. In order to reconstruct fault signal in acceleration, the magnitude of the injection term has been adjusted by adaptation rule designed based on MIT rule. The proposed A-SMO in this study was developed in Matlab/Simulink environment. Performance evaluation has been conducted using the commercial software (CarMaker) with car-following scenario and evaluation results show that maximum reconstruction error ratios exist within range of ±10%.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.26-38
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• 2022

This paper proposes multiple RLS and actuator performance index-based adaptive actuator fault-tolerant control and detection algorithms for longitudinal autonomous driving. The proposed algorithm computes the desired acceleration using feedback law for longitudinal autonomous driving. When actuator fault or performance degradation exists, it is designed that the desired acceleration is adjusted with the calculated feedback gains based on multiple RLS and gradient descent method for fault-tolerant control. In order to define the performance index, the error between the desired and actual accelerations is used. The window-based weighted error standard deviation is computed with the design parameters. Fault level decision algorithm that can represent three fault levels such as normal, warning, emergency levels is proposed in this study. Performance evaluation under various driving scenarios with actuator fault was conducted based on co-simulation of Matlab/Simulink and commercial software (CarMaker).

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.35-42
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• 2022

This paper presents a stochastic model predictive control (SMPC) for stop maneuver of autonomous vehicles considering perception uncertainty of stopped vehicle. The vehicle longitudinal motion should achieve both driving comfortability and safety. The comfortable stop maneuver can be performed by mimicking acceleration profile of human driving pattern. In order to implement human-like stop motion, we propose a reference safe inter-distance and velocity model for the longitudinal control system. The SMPC is used to track the reference model which contains the position uncertainty of preceding vehicle as a chance constraint. We conduct simulation studies of deceleration scenarios against stopped vehicle in urban environment. The test results show that proposed SMPC can execute comfortable stop maneuver and guarantee safety simultaneously.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.47-55
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• 2024

The paper presents a docking-type automatic landing system that works in tandem with Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs). The system utilizes a pyramid-shaped landing gear and pad for effective landing. In marine environments, a docking device guides the drone to land securely. To test the system, a ship's behavior was simulated using a 3-DoF motion platform, and the successful operation and utility of the docking-type automatic landing system were demonstrated.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.3
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• pp.199-212
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• 2014

This paper describes an autonomous air combat guidance law using a Virtual Pursuit Point (VPP) in one-on-one close engagement for Unmanned Combat Aerial Vehicle (UCAV). The VPPs that consist of virtual lag and lead points are introduced to carry out tactical combat maneuvers. The VPPs are generated based on fighter's aerodynamic performance and Basic Fighter Maneuver (BFM)'s turn circle, total energy and weapon characteristics. The UCAV determines a single VPP and executes pursuit maneuvers based on a smoothing function which evaluates probabilities of the pursuit types for switching maneuvers with given combat states. The proposed law is demonstrated by high-fidelity real-time combat simulation using commercial fighter model and X-Plane simulator.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.491-499
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• 2020

There are policies that foster the drone industry, which either put a legal precedent on drones through the "Drone Act" or grant a delay or exemption in applying the safety measures of "the Aviation Safety Act". Yet, the definition of a drone is unclear, requiring further discussion on commercial usage. Therefore, we have studied cases domestically and abroad, and also analyzed issues with the current aviation legislation. It was found that a drone is defined as "an unmanned aircraft where a pilot is not on board, and its net weight is 150 kg or less". However, there are several issues, such as that a drone taxi requires a pilot on board, and its weight is 150 kg or more. Thus, we propose to define a drone as "an unmanned aerial vehicle (provided, that its own net weight should be 300 kg or under, or not be limited to weight) under Article 2 (3) of the "Aviation Security Act" as prescribed by Ordinance of the Ministry of Land, Infrastructure, and Transport, which operates either by remote, automatically, or autonomously; or an unmanned aircraft under Article 2 (6) of the "Aviation Security Act".

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.14-19
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• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.1021-1031
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• 2020

With the advent of industry 4.0 technologies like the artificial intelligence and the autonomous flight, 'Urban Air Mobility (UAM)' is being considered as an effective alternative to resolve the ground urban traffic congestion. Accordingly, many companies in the world including Korea are investigating on the development of UAM vehicles and operation systems. In this study, after identifying and classifying the essential elements of the UAM operation, the UAM system operational concept has been derived, then detailed analyses for each element has been performed. Based on the conceptual analysis of the UAM operation system, UAM flight routes in Seoul and Gyeong-In area have been established and confirmed to be operable through the performance analysis of UAM vehicles. The flight route analysis in this study is expected to be applied to UAM flight routes establishment in various cities in the future.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.8
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• pp.577-584
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• 2016

UAV(Unmaned Aerial Vehicle), which is autonomous flight without pilots. Recently, UAV is being applied to various fields such as video recording, aerial photogrammetry. In particular, UAV is getting a lot of attention in the field of space-related information because of it's data acquisition speed and economic feasibility. But analytical study of an unmanned air-side technologies are lacking. In this study, the research of equipment for the unmanned aerial surveys and UAV technologies and trend analysis for generation of terrain model and ortho image effectively were performed. As a result, the ways to improve the utilization field of unmanned aerial surveying and processing of fixed-wing and rotary-wing unmanned aircraft. were suggested. If analytical research on generation of terrain models and ortho image will be performed, production efficiency of the geospatial information industry is expected to be significantly increased.