On-Road Trajectory Planning for General Autonomous Driving with Enhanced Tunability - Robotics Institute Carnegie Mellon University

On-Road Trajectory Planning for General Autonomous Driving with Enhanced Tunability

Tianyu Gu, John M. Dolan, and Jin-Woo Lee
Conference Paper, Proceedings of 13th International Conference on Intelligent Autonomous Systems (IAS '14), pp. 247 - 261, July, 2014

Abstract

In order to achieve smooth autonomous driving in real-life urban and highway environments, a motion planner must generate trajectories that are locally smooth and responsive (reactive), and at the same time, far-sighted and intelligent (deliberative). Prior approaches achieved both planning qualities for full-speed-range operations at a high computational cost. Moreover, the planning formulations were mostly a trajectory search problem based on a single weighted cost, which became hard to tune and highly scenario-constrained due to overfitting. In this paper, a pipelined (phased) framework with tunable planning modules is proposed for general on-road motion planning to reduce the computational overhead and improve the tunability of the planner.

BibTeX

@conference{Gu-2014-7911,
author = {Tianyu Gu and John M. Dolan and Jin-Woo Lee},
title = {On-Road Trajectory Planning for General Autonomous Driving with Enhanced Tunability},
booktitle = {Proceedings of 13th International Conference on Intelligent Autonomous Systems (IAS '14)},
year = {2014},
month = {July},
editor = {(eds.: E. Menegatti, N. Michael, K. Berns, H. Yamaguchi), Springer Verlag, ISBN 978-3-319-08337-7},
pages = {247 - 261},
keywords = {On-Road Motion planning, Autonomous Passenger Vehicle},
}