Speed Bump Recognition for Autonomous Vehicles Based on Semantic Segmentation

Jingyi Xu, Li Gao, Yanan Zhao, Xin Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

In this paper, we combine 3Dmax and PreScan to make data sets and use the recognition algorithm to get the region of interest (ROI) of the speed bumps area. Then, we realize the speed bump recognition for autonomous vehicles. Besides, we do the post-processing operations on the area corresponding to the disparity map. Finally, we provide an innovative method to improve the accuracy of the distance measurement of the speed bumps. The results show that the method in this paper can accurately recognize the speed bumps and measure the distance under the requirements of the automotive embedded system.

Original languageEnglish
Title of host publication2021 IEEE 3rd International Conference on Communications, Information System and Computer Engineering, CISCE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages387-393
Number of pages7
ISBN (Electronic)9780738112152
DOIs
Publication statusPublished - 14 May 2021
Event3rd IEEE International Conference on Communications, Information System and Computer Engineering, CISCE 2021 - Beijing, China
Duration: 14 May 202116 May 2021

Publication series

Name2021 IEEE 3rd International Conference on Communications, Information System and Computer Engineering, CISCE 2021

Conference

Conference3rd IEEE International Conference on Communications, Information System and Computer Engineering, CISCE 2021
Country/TerritoryChina
CityBeijing
Period14/05/2116/05/21

Keywords

  • autonomous vehicles
  • semantic segmentation
  • software joint simulation
  • speed bump recognition

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