A path planning algorithm based on fusing lane and obstacle map

Hao Zhu, Mengyin Fu, Yi Yang, Xinyu Wang, Meiling Wang

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

16 Citations (Scopus)

Abstract

This paper proposes a path planning algorithm for autonomous driving in urban environments. The processing of video and Velodyne pointcloud provides information about the positions of lane markers and obstacles in the local map, which are then converted to a lane costmap and obstacle costmap. The referenced GIS follow line is used for generating a series of offset curves, and the best follow line is selected according to a combination of lane, obstacle and background cost. Additional handling of planning path and maximum speed is provided. Our planning algorithm can handle various road types such as U-turn, intersections, and different driving behaviors including passing over or following front vehicles, etc. The proposed navigation framework is implemented on an autonomous vehicle, which exhibits good performance on Future Challenge 2013, Changshu, China.

Original languageEnglish
Title of host publication2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1442-1448
Number of pages7
ISBN (Electronic)9781479960781
DOIs
Publication statusPublished - 14 Nov 2014
Event2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 - Qingdao, China
Duration: 8 Oct 201411 Oct 2014

Publication series

Name2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014

Conference

Conference2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
Country/TerritoryChina
CityQingdao
Period8/10/1411/10/14

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