Collision-free and kinematically feasible path planning along a reference path for autonomous vehicle

Mengyin Fu, Kai Zhang, Yi Yang*, Hao Zhu, Meiling Wang

*Corresponding author for this work

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

11 Citations (Scopus)

Abstract

For the local path planning problem of autonomous vehicle in a complicated environment, a method combining cubic hermite spline curves with the kinematic model of autonomous vehicle is developed. And a novel algorithm for obstacle avoidance, called navigation circle, is proposed to take the road structure into account, which is a practical method for real-time path planning. In the new method, one of the trajectory generated by cubic hermite spline curves or navigation circle is optimized through the kinematic model of autonomous vehicle to get the kinematically feasible trajectory. The optimization is actually a numerical forward propagation and is easy to implement. The simulation experiment is conducted on the Robot Operating System (ROS) platform, which is based on replaying the data of the real world obtained from sensors or other modules on autonomous vehicle. Satisfactory simulation results verify the validity and the efficiency of the proposed method as well as the planner's capability to navigate in a realistic scenario.

Original languageEnglish
Title of host publicationIV 2015 - 2015 IEEE Intelligent Vehicles Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages907-912
Number of pages6
ISBN (Electronic)9781467372664
DOIs
Publication statusPublished - 26 Aug 2015
EventIEEE Intelligent Vehicles Symposium, IV 2015 - Seoul, Korea, Republic of
Duration: 28 Jun 20151 Jul 2015

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
Volume2015-August

Conference

ConferenceIEEE Intelligent Vehicles Symposium, IV 2015
Country/TerritoryKorea, Republic of
CitySeoul
Period28/06/151/07/15

Fingerprint

Dive into the research topics of 'Collision-free and kinematically feasible path planning along a reference path for autonomous vehicle'. Together they form a unique fingerprint.

Cite this