High Precision Distance Measurement Based on Monocular Vision for Intelligent Traffic

被引：0

作者：

Zou B. ^{[1
,2
]}

Yuan Y.-X. ^{[1
,2
]}

机构：

[1] Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan

[2] Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan

来源：

Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2018年 / 18卷 / 04期

关键词：

ADAS; Distance measurement; Integrated transportation; Lane identifying; Monocular vision;

D O I：

10.16097/j.cnki.1009-6744.2018.04.008

中图分类号：

学科分类号：

摘要：

The preceding vehicle distance is a significant factor, affecting driving safety. A preceding vehicle distance measurement based on monocular vision for future intelligent traffic system is proposed. First, the model of internet of vehicles is proposed with the fusion of internet of things, intelligent recognition, and cloud computing technology. The vehicle can send back the location information and the preceding vehicle image to the internet of vehicles in real time, and request the nearby traffic signs and the geometry of the preceding vehicle. Then, establish a mathematical model of the monocular camera, and introduce a distance measurement based on monocular vision with a cooperation sign of traffic signs and lane lines. Finally, a preceding vehicle adaptive vision distance measurement is designed by comprehensive application of the distance measurement based on monocular vision. The simulation demonstrates that the distance measurement based on monocular vision is valid and effective, enriching driving assistance system. Copyright © 2018 by Science Press.

引用

页码：46 / 53and60

页数：5314

共 8 条

[1] Li Y.C., Hu Z.Z., Hu Y.Z., Et al., Accurate localization based on GPS and image fusion for intelligent vehicles, Journal of Transportation Systems Engineering and Information Technology, 17, 3, pp. 112-119, (2017)
[2] Qin H., The analysis and design method of big data-driven vehicular network cyber-physical system, (2016)
[3] Zhong X.M., Yu G.Z., Ma Y.L., Et al., Traffic sign recognition based on fast regionbased convolutional neural networks, 2016 CG-IVT, (2016)
[4] Cao S.Y., Liu Y.H., Li X.Z., Vehicle detection method based on fast R-CNN, Journal of Image and Graphics, 22, 5, pp. 671-677, (2017)
[5] Wang L.F., Study on preceding vehicles detection with multifeatures and distance measurement based on monocular vision, (2016)
[6] Tong Z.Y., The design of preceding vehicles detection and distance measurement system based on machine vision, (2015)
[7] Xu D., Tan M., Li Y., Visual Measurement and Control for Robot(2nd Edition), (2011)
[8] Xu L., Cao Z., Liu X., A monocular vision system for pose measurement in indoor environment, IEEE International Conference on Robotics and Biomimetics, pp. 1977-1982, (2017)

← 1 →