http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
김종철(Jong-Chul Kim),고봉철(Bong-Chul Ko),정혁진(Hyok-Jin Chong),임형준(Hyung-Jun Rim) 한국자동차공학회 2010 한국자동차공학회 부문종합 학술대회 Vol.2010 No.5
The paper is development of SRSW(Smart Rear Side Warning) system using 24GHz radar. SRSW system consists of two radar sensors and HMI for driver and ECU. To distinguish closing and falling back vehicle SRSW system use extended kalman filter algorithm. LED and motorized seat belt are used for subject driver to warn the side and rear collision. And hazzard lamp is used for other vehicle driver to warn rear collision. To implemet tracking algorithm and warning algorithm in real time SRSW use ECU. And SRSW systems use TTC warning algorithm for BSD(Blind Spot Detection), LCA(Lane Change Assist) and RPC(Rear Pre Crash). These algorithms are tested and verified on the proving ground and real road.
정용환(Yonghwan Jeong),이경준(Kyoungjun Lee),정혁진(Hyok-Jin Chong),고봉철(Bong-Chul Ko),이경수(Kyongsu Yi) 대한기계학회 2015 대한기계학회 춘추학술대회 Vol.2015 No.11
This paper presents a vehicle sensor fault tolerant algorithm for automated vehicles. The proposed algorithm consists of a fault detection algorithm and virtual sensor. The fault detection algorithm is designed to monitor the health of steering wheel angle, yaw-rate, and wheel speed sensors. Three yaw-rate estimators using different sensor measurements are used to construct a bank of residuals. A fault of vehicle sensor leads to increase the unique subset of residuals and an adaptive threshold is used to identify the increase of residuals. The virtual sensor is composed of steering wheel angle, yaw-rate, and wheel speed estimators which uses measurements from normal operating sensors. After a faulty sensor is identified, measurement from faulty sensor is replaced by measurement from virtual sensor. The fault tolerant performance and reliability of the proposed algorithm have been validated via computer simulation.