Tunable and stable real-time trajectory planning for urban autonomous driving
Tianyu Gu, Jason Atwood, Chiyu Dong, John M Dolan, Jin-Woo Lee
Abstract
This paper investigates real-time on-road motion planning algorithms for autonomous passenger vehicles (APV) in urban environments, and propose a computationally efficient planning formulation. Two key properties, tunability and stability, are emphasized when designing the proposed planner. The main contributions of this paper are: • A computationally efficient decoupled space-time trajectory planning structure. • The formulation of optimization-free elastic-band-based path planning and speed-constraint-based temporal planning routines with pre-determined runtime. • Identification of continuity problems with previous cost-based planners that cause tunability and stability issues.
BibTeX
@inproceedings{iros2015_tunableandstable,
title = {Tunable and stable real-time trajectory planning for urban autonomous driving},
author = {Tianyu Gu and Jason Atwood and Chiyu Dong and John M Dolan and Jin-Woo Lee},
booktitle = {IROS 2015},
year = {2015}
}