• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.91-102
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• 2019

Autonomous vehicles can be exposed to severe danger when failure occurs in any of its components. For this reason many countries are making efforts on the legislative issue how to objectively evaluate failure safety of an autonomous vehicle when such a vehicle is commercially available to a customer in the near future. In level-3 automation, a driver must take over the control of his vehicle when failure occurs, and the driver's controllability must be secured for escape from the imminent danger. In this paper, quantitative methods have been developed for evaluating failure safety of the level-3 autonomous vehicle, and they were validated by simulation. And also, we confirmed that the proposed evaluation method can quantitatively evaluate the failure safety.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.6
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• pp.731-738
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• 2013

This paper describes a fault-tolerant driving control strategy for an independent steer-by-wire system in sixwheel-drive/six-wheel-steering vehicles. An algorithm has been designed to realize vehicle maneuverability that is as close as possible to that of non-faulty vehicles by inducing high slip ratio of the wheel through a faulty steer-by-wire system in order to reduce the lateral tire force, which is resistant to the yaw motion. Considering the transition of the longitudinal tire force of a wheel with a faulty steer-by-wire component, the longitudinal tire forces are optimally distributed to the other wheels. Fault-tolerant driving performance has been investigated via computer simulations. Simulation studies show that the proposed algorithm can significantly improve the maneuverability of a vehicle with a faulty steer-by-wire system as compared to the optimal traction distribution method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.299-312
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• 2021

Autonomous vehicles using V2X can drive safely information on areas outside the sensor coverage of autonomous vehicles conventional autonomous vehicles. As V2X technology has emerged as a key component of autonomous vehicles, research on V2X security is actively underway research on risk analysis due to failure of V2X communication is insufficient. In this paper, the service scenario and function of autonomous driving system V2X were derived by presenting the intersection scenario of the autonomous vehicle, the malfunction was defined by analyzing the hazard of V2X. he ISO26262 Part3 process was used to analyze the risk of malfunction of autonomous vehicle V2X. In addition, a fault injection scenario was presented to verify the fail-safe of the simulation-based intersection scenario.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.10
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• pp.931-940
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• 2017

This paper describes a predictive fault diagnosis algorithm for autonomous vehicles based on a kinematic model that uses a sliding mode observer. To ensure the safety of autonomous vehicles, reliable information about the environment and vehicle dynamic states is required. A predictive algorithm that can interactively diagnose longitudinal environment and vehicle acceleration information is proposed in this paper to evaluate the reliability of sensors. To design the diagnosis algorithm, a longitudinal kinematic model is used based on a sliding mode observer. The reliability of the fault diagnosis algorithm can be ensured because the sliding mode observer utilized can reconstruct the relative acceleration despite faulty signals in the longitudinal environment information. Actual data based performance evaluations are conducted with various fault conditions for a reasonable performance evaluation of the predictive fault diagnosis algorithm presented in this paper. The evaluation results show that the proposed diagnosis algorithm can reasonably diagnose the faults in the longitudinal environment and acceleration information for all fault conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.525-526
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• 2016

전기자동차 (EV)에서 구동용 모터의 토크 제어를 위한 인버터에는 제어 연산 및 고장 진단 기능을 수행하기 위한 MCU가 있으며, MCU는 상위 제어기 차량 제어 유닛 (VCU)에게 현재 모터 및 인버터의 상태를 주기적으로 전달하고, 현재 차량 주행에 적합한 토크 지령을 받아 토크 제어를 수행하게 된다. 이를 위해 MCU는 전류, 전압 및 위치 센서의 값을 읽어 제어를 수행하게 되며, 제어의 결과 값으로 pulse width modulation (PWM)을 생성하여 이를 통해 모터에 전압을 공급하게 된다. 즉 차량의 구동에 있어 PWM 신호는 가장 중요한 부분이다. 하지만 생산 불량 또는 진동에 의한 납땜 불량 또는 MCU 전원 고장 등으로 MCU에 고장이 발생하게 되면 이상 PWM을 생성하게 되고 정상적인 토크 제어가 불가능해진다. 이때 안전하게 EV를 정지 시키는 알고리즘이 필요하게 되며, 이를 수행 할 supervisor control unit (SCU)가 인버터 컨트롤 보드에 추가되어야 한다. 본 논문에서는 고속으로 주행하던 차량에서 메인 MCU가 고장 날 경우에 안전하게 EV를 정차시키는 방법에 대해 다루었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.258-260
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• 2017

Smart mobility is rapidly emerging as a next-generation eco-friendly transportation system, and the market is booming every year. However, due to the characteristics of the devices that use electricity as the power source, the motor and the battery are different from the performance and actual performance indicated by the manufacturer depending on the user's weight and driving environment. Therefore, The frequency of the overload is increased and the failure and damage of the device are increasing. In this paper, we propose an application that provides personalized recommended driving guidance and overloaded driving situation notification at the actual driving separately from the recommended driving provided by the manufacturer after measuring the driving environment of the user, so as to prevent malfunction and damage of the smart mobility device, To ensure safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.129-143
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• 2019

As the importance of autonomous vehicle safety is emphasized, the application of ISO-26262, a development verification guideline for improving safety and reliability, and the safety verification of autonomous vehicles are becoming increasingly important, in particular, SAE standard level 3 or higher level autonomous vehicles detect and decision the surrounding environment instead of the human driver. Therefore, if there is and failure or malfunction in the autonomous driving function, safety may be seriously affected. So autonomous vehicles, it is essential to apply and verity the safety concept against failure and malfunctions. In this study, we study the fault injection scenarios for safety evaluation and verification of autonomous vehicles using ISO-26262 part3 process and STPA were studied and safety measures for safety concept design were studied through simulation bases fault injection test.

• Journal of Auto-vehicle Safety Association
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• v.9 no.4
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• pp.32-37
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• 2017

For automated vehicles, the integrity and fault tolerance of environment perception sensor have been an important issue. This paper presents radar, vision, lidar(laser radar) fusion-based fault detection algorithm for autonomous vehicles. In this paper, characteristics of each sensor are shown. And the error of states of moving targets estimated by each sensor is analyzed to present the method to detect fault of environment sensors by characteristic of this error. Each estimation of moving targets isperformed by EKF/IMM method. To guarantee the reliability of fault detection algorithm of environment sensor, various driving data in several types of road is analyzed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2128-2132
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• 2017

Smart mobility is rapidly emerging as a next-generation eco-friendly transportation system, and the market is booming every year. However, due to the characteristics of the devices that use electricity as the power source, the motor and the battery are different from the performance and actual performance indicated by the manufacturer depending on the user's weight and driving environment. Therefore, The frequency of the overload is increased and the failure and damage of the device are increasing. In this paper, we propose an application that provides personalized recommended driving guidance and overloaded driving situation notification at the actual driving separately from the recommended driving provided by the manufacturer after measuring the driving environment of the user, so as to prevent malfunction and damage of the smart mobility device, To ensure safety.