Literature survey for autonomous vehicles: sensor fusion, computer vision, system identification and fault tolerance

被引:27
作者
Mohamed, Amr [1 ]
Ren, Jing [1 ]
El-Gindy, Moustafa [1 ]
Lang, Haoxiang [1 ]
Ouda, A. N. [1 ]
机构
[1] UOIT, Fac Engn & Appl Sci, 2000 Simcoe St N, Oshawa, ON L1H 7K4, Canada
关键词
autonomous vehicles; sensor fusion; computer vision; system identification; fault tolerance;
D O I
10.1504/IJAAC.2018.095104
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Autonomous vehicle technologies are receiving great attention with increasing demands for autonomy for both civilian and military purposes. In previous work (Mohamed et al., 2016), the recent developments in autonomous vehicles in the fields of advanced control, perception and motion planning techniques is surveyed. In this paper, the state of research w.r.t. autonomous vehicles from different perspectives will be described. The capability to integrate data and knowledge from different sensors are essential. In addition, advanced perception techniques and the capability to locate obstacles and targets are necessary to properly operate autonomous systems. Moreover, achieve reliable levels of performance by determining the faults and enabling the system to operate with these faults in mind. Fault tolerance is required to analysing the measured input/output signals of the system. This paper will briefly survey the recent developments in the field of autonomous vehicles from the perspectives of sensor fusion, computer vision, system identification and fault tolerance.
引用
收藏
页码:555 / 581
页数:27
相关论文
共 53 条
[1]   Sensor location with respect to fault tolerance properties [J].
Aitouche, Abdelouahab ;
Ould-Bouamama, Belkacem .
INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL, 2010, 4 (03) :298-316
[2]  
[Anonymous], 2006, ADAPTIVE APPROXIMATI
[3]  
Aras M. S. M., 2013, Journal of Theoretical and Applied Information Technology, V56, P136
[4]  
Axenie Cristian, 2010, WSEAS Transactions on Systems and Control, V5, P205
[5]  
Azmi MWN, 2017, PROCEEDINGS OF MECHANICAL ENGINEERING RESEARCH DAY 2017 (MERD), P57
[6]   A fault tolerant architecture for data fusion: A real application of Kalman filters for mobile robot localization [J].
Bader, Kaci ;
Lussier, Benjamin ;
Schon, Walter .
ROBOTICS AND AUTONOMOUS SYSTEMS, 2017, 88 :11-23
[7]  
Benosman M, 2009, MATH PROBL ENG, V2010, P1
[8]  
Bhat A, 2017, IEEE REAL TIME, P87, DOI 10.1109/RTAS.2017.33
[9]  
Brown C., 1992, DATA FUSION ROBOTICS, P267
[10]  
Burschka D, 2016, IEEE T INTELL TRANSP, V18, P2137