Towards the design of vision-based intelligent vehicle system: methodologies and challenges

被引:14
|
作者
Dewangan, Deepak Kumar [1 ]
Sahu, Satya Prakash [2 ]
机构
[1] Siksha O Anusandhan Deemed Univ, Dept Comp Sci & Engn, Bhubaneswar, Odisha, India
[2] Natl Inst Technol, Dept Informat Technol, Raipur, CG, India
关键词
Artificial intelligence; Autonomous driving; Computer vision; Driver assistance systems; Intelligent vehicle system; Road safety; CONVOLUTIONAL NEURAL-NETWORK; TRAFFIC LIGHT RECOGNITION; ROBUST LANE DETECTION; FASTER R-CNN; PEDESTRIAN DETECTION; DETECTION ALGORITHM; SIGN DETECTION; ROAD; SEGMENTATION; VIDEO;
D O I
10.1007/s12065-022-00713-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Rapid growth in technology has changed the way humans live. Ongoing development in the automobile industry is creating intelligent vehicles and this mode of transportation will assist human society. The need for this survey arises to identify the scope of an intelligent vehicle through a computer vision approach equipped with recent technological trends. In this article, the major technological phases of intelligent vehicles are analyzed and discussed. The operational mechanism in these phases is mostly based on vision sensors that facilitate these vehicles to perceive the heterogeneous and dynamic environments and help them to make appropriate decisions. This study identifies various state-of-art techniques and phase-wise datasets used in the literature. It highlights the advancement in different phases, challenges, and scopes for the design and development of intelligent vehicles system.
引用
收藏
页码:759 / 800
页数:42
相关论文
共 50 条
  • [21] Vision-based intelligent robots
    Nguyen, MC
    INPUT/OUTPUT AND IMAGING TECHNOLOGIES II, 2000, 4080 : 41 - 47
  • [22] A vision-based system for autonomous underwater vehicle navigation
    Foresti, GL
    Gentili, S
    Zampato, M
    OCEANS'98 - CONFERENCE PROCEEDINGS, VOLS 1-3, 1998, : 195 - 199
  • [23] A Vision-Based Nighttime Surrounding Vehicle Detection System
    Chen, Xiu-Zhi
    Liao, Kuan-Kai
    Chen, Yen-Lin
    Yu, Chao-Wei
    Wang, Che
    2018 7TH IEEE INTERNATIONAL SYMPOSIUM ON NEXT-GENERATION ELECTRONICS (ISNE), 2018, : 195 - 197
  • [24] A vision-based vehicle behavior monitoring and warning system
    Chang, TH
    Lin, CH
    Hsu, CS
    Wu, YJ
    2003 IEEE INTELLIGENT TRANSPORTATION SYSTEMS PROCEEDINGS, VOLS. 1 & 2, 2003, : 448 - 453
  • [25] Vision-based vehicle detection for a driver assistance system
    Kuo, Ying-Che
    Pai, Neng-Sheng
    Li, Yen-Feng
    COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2011, 61 (08) : 2096 - 2100
  • [26] Vision-based navigation system for autonomous transportation vehicle
    Morimoto E.
    Suguri M.
    Umeda M.
    Precision Agriculture, 2005, 6 (3) : 239 - 254
  • [27] Vision-based vehicle classification
    Gupte, S
    Masoud, O
    Papanikolopoulos, NP
    2000 IEEE INTELLIGENT TRANSPORTATION SYSTEMS PROCEEDINGS, 2000, : 46 - 51
  • [28] Vision-based vehicle guidance
    Bertozzi, M
    Broggi, A
    COMPUTER, 1997, 30 (07) : 49 - &
  • [29] Function-based design process for an intelligent ground vehicle vision system
    Nagel, Robert L.
    Perry, Kenneth L.
    Stone, Robert B.
    McAdams, Daniel A.
    JOURNAL OF ELECTRONIC IMAGING, 2010, 19 (04)
  • [30] Vision-based system design - sensor selection
    Behman, Aaron
    Taylor, Adam
    ELECTRONICS WORLD, 2017, 123 (1969): : 18 - 19