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Automatic Steering Methods for Autonomous
Automobile Path Tracking
Jarrod M. Snider
CMU-RI-TR-09-08
February 2009
Robotics Institute
Carnegie Mellon University
Pittsburgh, Pennsylvania
c
Carnegie Mellon University
Abstract
This research derives, implements, tunes and compares selected path tracking methods for controlling a car-like
robot along a predetermined path. The scope includes commonly used methods found in practice as well as some
theoretical methods found in various literature from other areas of research. This work reviews literature and identifies
important path tracking models and control algorithms from the vast background and resources. This paper augments
the literature with a comprehensive collection of important path tracking ideas, a guide to their implementations and,
most importantly, an independent and realistic comparison of the performance of these various approaches. This
document does not catalog all of the work in vehicle modeling and control; only a selection that is perceived to be
important ideas when considering practical system identification, ease of implementation/tuning and computational
efficiency. There are several other methods that meet this criteria, however they are deemed similar to one or more of
the approaches presented and are not included. The performance results, analysis and comparison of tracking methods
ultimately reveal that none of the approaches work well in all applications and that they have some complementary
characteristics. These complementary characteristics lead to an idea that a combination of methods may be useful for
more general applications. Additionally, applications for which the methods in this paper do not provide adequate
solutions are identified.
II
Acknowledgements
This work would not have been possible without the support, motivation and encouragement of Dr. Chris Urmson,
under whose supervision I chose this area of research. I would like to acknowledge the advice and guidance of Dr.
William ”Red” Whittaker, whom never ceases to amaze and inspire me. Special thanks go to Tugrul Galatali, whose
knowledge and assistance was instrumental in the success of this research and paper.
I acknowledge Mechanical Simulation for their generous support and discount of CarSim. Without CarSim, quality
analysis and comparison of tracking methods may not have been possible.
I would also like to thank the members of my family, especially my wife, Amy, and my son Xavier for supporting
and encouraging me in everything I do.
III
Contents
1 Introduction 1
1.1 Experimental Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1.1 Lane Change Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1.2 Figure Eight Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1.3 Road Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Geometric Path Tracking 8
2.1 Geometric Vehicle Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2 Pure Pursuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2.1 Tuning the Pure Pursuit Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 Stanley Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.1 Tuning the Stanley Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3 Path Tracking Using a Kinematic Model 18
3.1 Kinematic Bicycle Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.1.1 Path Coordinates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2 Kinematic Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.2.1 Chained Form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.2.2 Smooth Time-Varying Feedback Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2.3 Input Scaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.2.4 Tuning the Kinematic Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4 Path Tracking Control Using a Dynamic Model 28
4.1 Dynamic Vehicle Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.1.1 Linearized Dynamic Bicycle Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.1.2 Path Coordinates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.1.3 Model Parameter Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.2 Optimal Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
4.2.1 Tuning the Optimal Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.3 Optimal Control with Feed Forward Term . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.3.1 Tuning the Optimal Controller with Feed Forward Term . . . . . . . . . . . . . . . . . . . . 44
IV
4.4 Optimal Preview Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.4.1 Tuning the Optimal Preview Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5 Performance Comparison 61
5.1 Tracking Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
6 Conclusions and Future Work 65
V
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- sooAnderson2021-02-27Automatic Steering Methods for Autonomous Automobile Path Tracking Carnegie Mellon University February 2009
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