'
ISO 26262와 ISO/PAS 21448의 프로세스 통합모델 구축 및 시뮬레이션을 통한 효용성 검증' 의 주제별 논문영향력
논문영향력 요약
주제
AUTOMOTIVE
ISO/PAS 21448
Process
SIMULATION
iso 26262
동일주제 총논문수
논문피인용 총횟수
주제별 논문영향력의 평균
162
0
0.0%
주제별 논문영향력
논문영향력
주제
주제별 논문수
주제별 피인용횟수
주제별 논문영향력
주제어
AUTOMOTIVE
1
0
0.0%
ISO/PAS 21448
3
0
0.0%
Process
117
0
0.0%
SIMULATION
1
0
0.0%
iso 26262
40
0
0.0%
계
162
0
0.0%
* 다른 주제어 보유 논문에서 피인용된 횟수
0
'
ISO 26262와 ISO/PAS 21448의 프로세스 통합모델 구축 및 시뮬레이션을 통한 효용성 검증' 의 참고문헌
미 NHTSA(National Highway Traffic Safety Administration)
Toyota Annual Report
도요타 쇼크의 원인과 전망
한국자동차산업연구소[2009]
“VDA(Verband Der Automobilindustrie)
독일 자동차 산업협회 standard[2004]
[9] “J-NCAP,” www.nasva.go.jp
[8] “LATIN-NCAP,” www.latinncap.com
[7] “A-NCAP,” www.ancap.au
[6] “C-NCAP,” www.c-ncap.org
[63] Ian, Goodfellow, et al. "Generative adversarial nets.Advances in neural information processing systems vol. 3, 2014.
vol . 3[2014]
[62] Functional safety of electrical/electronic/programmable electronic safety related systems-Part1 : General requirements.
[60]C. Neurohr, B. Kramer, M. Buker, E. Bode, M. Franzle, and W. Damm, "Identification Quantification of Hazardous Scenarios for Highly Automated Driving,Researchgate.net, 2020.
[2020]
[5] “Euro NCAP 2025 Roadmap in Pursuit of Vision Zero,” Euro NCAP, 2017.
[56] J. E. Stellet, T. Brade, A. Poddey, S. Jesenski and W. Branz, "Formalisation and algorithmic approach to the automated driving validation problem," 2019 IEEE Intelligent Vehicles Symposium, pp. 45-51, 2019.
[55] O. M. Kirovskii and V. A. Gorelov, "Driver Assistance Systems: Analysis, Tests and the Safety Case. ISO 26262 and ISO PAS 21448," Institute of Physics conference, 2019.
[54] A. Schnellbach and G. Griessnig, "Development of the ISO/PAS 21448," European Conference on Software Process Improvement, pp585-593, 2019.
[51] International Organization for Standardization. ISO/PAS 21448 - Road Vehicles - Safety of the intended functionality, ISO(2019).
[4] “Request for Comments Rear Visibility NCAP,” National Highway Traffic Safety Administration (NHTSA), Department of Transportation (DOT), USA, 2013.
[37] M. Haloi and D. B. Jayagopi, “Robust Lane Detection and Departure Warning System,” IEEE Intelligent Vehicles Symposium, pp.126-131, 2015.
[21] Automated Functional Safety Analysis of Automated Driving Systems: 23rd International Conference, FMICS 2018, Maynooth, Ireland, September 3-4, 2018, Proceedings.
[17] Automated Functional Safety Analysis of Automated Driving Systems.
[15] Functional Safety with ISO 26262-Principles and Practice (webinar) by Vector
[13] SAE_J3016_201806_ADlevel.
[12] Johnston and Walker 2017; Keeney 2017; Kok, et al. 2017.
[11] “ASEAN-NCAP,” www.aseancap.org
[10] “K-NCAP,” www.kncap.org
Toward multimodal image-to-image translation
[2017]
Test Method and Risk Factor Definition of Forward Collision Warning System .
8 ([2020]
Standardized evaluation of camera-based driver state monitoring systems
716-732 .[2019]
SOTIF the Human Factor , EuropeanConference on Software Process Improvement
pp575-584[2019]
S. A radar-based blind spot detection and warning system for driver assistance In Proceedings of the 2017 IEEE Second Advanced Information Technology , Electronic and AutomationControlConference ( IAEAC )
25 ? 26pp . 2204 ? 2208
RoadView : A traffic scene simulator for autonomous vehicle simulation testing
Qingdao , pp . 1160-1165[2014]
Real-time approaching vehicle detection in blind spot area In Proceedings of the 2009
pp . 1 ? 6 .
Real-time Illumination Invariant Lane Detection for Lane Departure Warning System ,
no . 4 , pp . 1816-1824[2015]
Pedestrian Collision Avoidance System for Scenarios with Occlusions
On the validation of complex systems operating in open contexts
[2019]
Multi-aspect Safety Engineering for Highly Automated Driving
vol 11093[2018]
Lane Detection and Tracking Problems in Lane Departure Warning Systems
pp 432[2017]
Lane Detection System with Around View Monitoring for Intelligent vehicle
[2013]
Lane Detection Method Based on Improved RANSAC Algorithm
K. Robust vehicle detection and tracking method for blind spot detection system by using vision sensors
Image-to-image translation with conditional adversarial networks
[2017]
Image style transfer using convolutional neural networks
[2016]
Hybrid Detection for Vehicle Blind Spot using Fisheye Camera : A Framework
[2019]
High-resolution image synthesis and semantic manipulation with conditional gans
[2018]
High Accuracy Driver Identification and Status Monitoring System Research
Vol . 1486[2020]
HIS Color Model Based Lane-Marking Detection
[2006]
Global status report on the road safety
[2013]
Global status report on the road safety
[2015]
Global status report on the road safety
[2018]
Efficient Lane Detection Based on Spatiotemporal Images
vol . 17 , no . 1 , pp . 289-295[2016]
Efficient Lane Detection Algorithm Using Different Filtering Techniques
vol . 88 , no . 3 , pp . 6-11[2014]
D. Mono-camera based side vehicle detection for blind spot detection systems
pp . 147 ? 149 .
Cg2real : Improving the realism of computer generated images using a large collection of photographs
[2010]
C. A real-time vision system for nighttime vehicle detection and traffic surveillance
58 , 2030 ? 2044[2011]
An Adaptive Method for Lane Marking Detection Based on HSI Color Model
vol . 93 , pp.304-311[2010]
APPROACH FOR DERIVING SCENARIOS FOR SAFETY OF THE INTENDED FUNCTIONALITY
A radar-based door open warning technology for vehicle active safety . 2016 International Conference on Information System and Artificial Intelligence ( ISAI )
[2016]
A blind spot detection warning system based on Gabor filtering and optical flow for E-mirror applications
pp . 1 ? 5
A Study on Development of the Camera-Based Blind Spot Detection System Using the Deep Learning Methodology
2941 .[2019]
A Safety Standard Approach for Fully Autonomous Vehicles
[2019]
A Robust Method for Lane Detection under Adverse Weather and Illumination Conditions Using Convolutional Neural Network
[2020]
A Robust Lane Detection Method Based on Vanishing Point Estimation Using the Relevance of Line Segments
vol . 18 , no . 12 , pp . 3254-3266[2017]
A Real-Time Lane Detection Algorithm Based on Intelligent CCD Parameters Regulation
vol . 2012 , pp . 1-16[2012]
A Learning Approach Towards Detection and Tracking of Lane Markings
vol . 13 , no . 3[2012]
A Forward Collision Warning System Using Driving Intention Recognition of the Front Vehicle and V2V Communication
8 ([2020]
'
ISO 26262와 ISO/PAS 21448의 프로세스 통합모델 구축 및 시뮬레이션을 통한 효용성 검증'
의 유사주제(
) 논문