Real-Time lane detection and forward collision warning system based on stereo vision

Wenjie Song, Mengyin Fu, Yi Yang, Meiling Wang, Xinyu Wang, Alain Kornhauser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

This paper presents a real-Time and robust lane detection and forward collision warning technique based on stereo cameras. First, obstacles image is obtained through stereo matching and UV-disparity segmentation algorithm. Then, Inverse Perspective Mapping(IPM) and Sobel filtering are conducted to generate a low-noise top view of the road by fusing the obstacles image and the original image. Next, Hough Transformation for the top view map is completed and the extreme points(poles) are calculated as the detected lanes according to the traffic lanes model. Besides, the host lane is selected or supplemented among all the detected lanes and the nearest obstacle in this host lane is detected for the forward collision warning. Experimental results on the public data set indicate that our method can work effectively and real-Timely in the normal structured environment.

Original languageEnglish (US)
Title of host publicationIV 2017 - 28th IEEE Intelligent Vehicles Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages493-498
Number of pages6
ISBN (Electronic)9781509048045
DOIs
StatePublished - Jul 28 2017
Event28th IEEE Intelligent Vehicles Symposium, IV 2017 - Redondo Beach, United States
Duration: Jun 11 2017Jun 14 2017

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings

Other

Other28th IEEE Intelligent Vehicles Symposium, IV 2017
CountryUnited States
CityRedondo Beach
Period6/11/176/14/17

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Automotive Engineering
  • Modeling and Simulation

Fingerprint Dive into the research topics of 'Real-Time lane detection and forward collision warning system based on stereo vision'. Together they form a unique fingerprint.

Cite this