A Vision-Based Driver Assistance System using Collaborative Edge Computing

被引：0
|
作者：
Keivani, Arghavan [1 ]
Ghayoor, Farzad [1 ]
Tapamo, Jules-Raymond [1 ]
机构：
[1] Univ KwaZulu Natal, Sch Engn, Durban, South Africa
来源：
2017 GLOBAL WIRELESS SUMMIT (GWS) | 2017年
关键词：
Vision-Based Driver Assistance System; DAS; Edge Computing; 5G; Real-time System; VEHICLE DETECTION; TRACKING; LOOKING;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A conceptual model for a vision-based driver assistance system based on collaborative mobile and edge computing is proposed. Cloudlets are the edges of the 5G cellular network and are capable of providing edge computing solutions to their connected devices. The proposed system monitors the vehicles that are driving in front of an ego car and notifies the driver upon detecting any hazardous condition caused by the other vehicles movements. A smartphone, mounted on the ego car, captures and sends the required information to a cloudlet for further processing. The cloudlet then notifies the smartphone upon detecting any hazardous conditions. This system can be used as a cost-effective driver assistance system and have the potential to reach the mass market and be used in all ranges of vehicles including the lower-end models.
引用
收藏
页码：160 / 164
页数：5
相关论文
共 50 条
  • [1] Embedded vision-based nighttime driver assistance system
    Chen, Yen-Lin
    Chiang, Chuan-Yen
    Liang, Wen-Yew
    Chuang, Cheng-Hung
    [J]. Journal of Convergence Information Technology, 2011, 6 (02) : 283 - 292
  • [2] Vision-based vehicle detection for a driver assistance system
    Kuo, Ying-Che
    Pai, Neng-Sheng
    Li, Yen-Feng
    [J]. COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2011, 61 (08) : 2096 - 2100
  • [3] A Vision-based Safety Driver Assistance System for Motorcycles on a Smartphone
    Fang, Chiung-Yao
    Hsu, Wei-Hong
    Ma, Chung-Wen
    Chen, Sei-Wang
    [J]. 2014 IEEE 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2014, : 328 - 333
  • [4] In and out vision-based driver-interactive assistance system
    H. C. Choi
    S. Y. Kim
    S. Y. Oh
    [J]. International Journal of Automotive Technology, 2010, 11 : 883 - 892
  • [5] CORRIDOR DETECTION AND TRACKING FOR VISION-BASED DRIVER ASSISTANCE SYSTEM
    Jiang, Ruyi
    Klette, Reinhard
    Vaudrey, Tobi
    Wang, Shigang
    [J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2011, 25 (02) : 253 - 272
  • [6] In and out vision-based driver-interactive assistance system
    Choi, H. C.
    Kim, S. Y.
    Oh, S. Y.
    [J]. INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2010, 11 (06) : 883 - 892
  • [7] EMBEDDED SYSTEMS FOR VISION-BASED DRIVER ASSISTANCE
    Staudenmaier, Michael
    Herrmann, Stephan
    [J]. ELECTRONICS WORLD, 2014, 120 (1934): : 18 - 23
  • [8] A Vision-Based Driver Assistance System with Forward Collision and Overtaking Detection†
    Lin, Huei-Yung
    Dai, Jyun-Min
    Wu, Lu-Ting
    Chen, Li-Qi
    [J]. SENSORS, 2020, 20 (18) : 1 - 19
  • [9] On creating vision-based advanced driver assistance systems
    Nieto, Marcos
    Otaegui, Oihana
    Velez, Gorka
    Diego Ortega, Juan
    Cortes, Andoni
    [J]. IET INTELLIGENT TRANSPORT SYSTEMS, 2015, 9 (01) : 59 - 66
  • [10] Employing range imagery for vision-based driver assistance
    Sobottka, K
    Bunke, H
    [J]. ENHANCED AND SYNTHETIC VISION 1998, 1998, 3364 : 177 - 188
12345