Detailed Information

Cited 0 time in webofscience Cited 3 time in scopus
Metadata Downloads

Local trajectory planning and control for autonomous vehicles using the adaptive potential field

Authors
Kim, DongchanKim, HayoungHuh, Kunsoo
Issue Date
Oct-2017
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
2017 IEEE Conference on Control Technology and Applications (CCTA), v.2017-January, pp.987 - 993
Indexed
SCOPUS
Journal Title
2017 IEEE Conference on Control Technology and Applications (CCTA)
Volume
2017-January
Start Page
987
End Page
993
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/4764
DOI
10.1109/CCTA.2017.8062588
Abstract
In this paper, a new potential field approach is proposed for trajectory planning and control in autonomous vehicles. The potential field of the surrounding environment is generated including vehicles, road boundaries and lane centers. Based on the predicted positions of the vehicles, the location of the ego vehicle and the surrounding potentials are synchronized. In addition, the potential fields of the surrounding vehicles are adaptively modified in shape depending on the relative velocity of the surrounding vehicles. The longitudinal distance required for the lateral avoidance is mathematically calculated and reflected in the potential field. Based on the proposed potential field, the trajectory of the autonomous vehicle is selected as the suboptimal path and the MPC (Model Predictive Control) method is applied for tracking control and the lateral stability of the vehicle. The performance of the proposed algorithm is verified in simulations under various conditions.
Files in This Item
Go to Link
Appears in
Collections
서울 공과대학 > 서울 미래자동차공학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Huh, Kunsoo photo

Huh, Kunsoo
COLLEGE OF ENGINEERING (DEPARTMENT OF AUTOMOTIVE ENGINEERING)
Read more

Altmetrics

Total Views & Downloads

BROWSE