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Autonomous Road Vehicle Path Planning and Tracking Control [Kõva köide]

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Autonomous Road Vehicle Path Planning and Tracking ControlSuurem pilt
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Püsilink: https://www.kriso.ee/db/9781119747949.html
Märksõnad:
Comprehensive explorations of vehicle, path, and path tracking models, model-in-the-loop simulation models, and hardware-in-the-loop models. In-depth examinations of collision free path planning and collision avoidance. Perfect for advanced undergraduateand graduate students with an interest in autonomous vehicles, Autonomous Road Vehicle Path Planning and Tracking Control is also an indispensable reference for practicing engineers working in autonomous driving technologies and the mobility groups and sections of automotive OEMs"--

Discover the latest research in path planning and robust path tracking control

In Autonomous Road Vehicle Path Planning and Tracking Control, a team of distinguished researchers delivers a practical and insightful exploration of how to design robust path tracking control. The authors include easy to understand concepts that are immediately applicable to the work of practicing control engineers and graduate students working in autonomous driving applications. Controller parameters are presented graphically, and regions of guaranteed performance are simple to visualize and understand.

The book discusses the limits of performance, as well as hardware-in-the-loop simulation and experimental results that are implementable in real-time. Concepts of collision and avoidance are explained within the same framework and a strong focus on the robustness of the introduced tracking controllers is maintained throughout.

In addition to a continuous treatment of complex planning and control in one relevant application, the Autonomous Road Vehicle Path Planning and Tracking Control includes:

  • A thorough introduction to path planning and robust path tracking control for autonomous road vehicles, as well as a literature review with key papers and recent developments in the area
  • Comprehensive explorations of vehicle, path, and path tracking models, model-in-the-loop simulation models, and hardware-in-the-loop models
  • Practical discussions of path generation and path modeling available in current literature
  • In-depth examinations of collision free path planning and collision avoidance

Perfect for advanced undergraduate and graduate students with an interest in autonomous vehicles, Autonomous Road Vehicle Path Planning and Tracking Control is also an indispensable reference for practicing engineers working in autonomous driving technologies and the mobility groups and sections of automotive OEMs.

About the Authors xi
Preface xv
List of Abbreviations
xvii
1 Introduction
1(18)
1.1 Motivation and Introduction
1(2)
1.2 History of Automated Driving
3(8)
1.3 ADAS to Autonomous Driving
11(2)
1.4 Autonomous Driving Architectures
13(1)
1.5 Cybersecurity Considerations
13(1)
1.6 Organization and Scope of the Book
14(1)
1.7
Chapter Summary and Concluding Remarks
14(5)
References
15(4)
2 Vehicle, Path, and Path Tracking Models
19(38)
2.1 Tire Force Model
19(14)
2.1.1 Introduction
19(1)
2.1.2 Tire Forces/Moments and Slip
20(3)
2.1.3 Longitudinal Tire Force Modeling
23(1)
2.1.4 Lateral Tire Force Modeling
24(4)
2.1.5 Self-aligning Moment Model
28(1)
2.1.6 Coupling of Tire Forces
29(4)
2.2 Vehicle Longitudinal Dynamics Model
33(3)
2.3 Vehicle Lateral Dynamics Model
36(9)
2.3.1 Geometry of Cornering
36(2)
2.3.2 Single-Track Lateral Vehicle Model
38(4)
2.3.3 Augmented Single-Track Lateral Vehicle Model
42(1)
2.3.4 Linearized Single Track Lateral Vehicle Model
42(3)
2.4 Path Model
45(6)
2.5 Pure Pursuit: Geometry-Based Low-Speed Path Tracking
51(1)
2.6 Stanley Method for Path Tracking
52(2)
2.7 Path Tracking in Reverse Driving and Parking
54(2)
2.8
Chapter Summary and Concluding Remarks
56(1)
References
56(1)
3 Simulation, Experimentation, and Estimation Overview
57(34)
3.1 Introduction to the Simulation-Based Development and Evaluation Process
57(3)
3.2 Model-in-the-Loop Simulation
60(2)
3.2.1 Linear and Nonlinear Vehicle Simulation Models
60(1)
3.2.2 Higher Fidelity Vehicle Simulation Models
61(1)
3.3 Virtual Environments Used in Simulation
62(10)
3.3.1 Road Network Creation
63(2)
3.3.2 Driving Environment Construction
65(3)
3.3.3 Capabilities
68(4)
3.4 Hardware-in-the-Loop Simulation
72(2)
3.5 Experimental Vehicle Testbeds
74(4)
3.5.1 Unified Approach
75(1)
3.5.2 Unified AV Functions and Sensors Library
76(2)
3.6 Estimation
78(9)
3.6.1 Estimation of the Effective Tire Radius
78(1)
3.6.2 Slip Slope Method for Road Friction Coefficient Estimation
79(3)
3.6.3 Results and Discussion
82(5)
3.7
Chapter Summary and Concluding Remarks
87(4)
References
87(4)
4 Path Description and Generation
91(16)
4.1 Introduction
91(1)
4.2 Discrete Waypoint Representation
91(3)
4.3 Parametric Path Description
94(9)
4.3.1 Clothoids
95(2)
4.3.2 Bezier Curves
97(2)
4.3.3 Polynomial Spline Description
99(4)
4.4 Tracking Error Calculation
103(1)
4.4.1 Tracking Error Computation for a Discrete Waypoint Path Representation
103(1)
4.4.2 Tracking Error Computation for a Spline Path Representation
104(1)
4.5
Chapter Summary and Concluding Remarks
104(3)
References
105(2)
5 Collision Free Path Planning
107(52)
5.1 Introduction
107(4)
5.2 Elastic Band Method
111(12)
5.2.1 Path Structure
111(1)
5.2.2 Calculation of Forces
111(3)
5.2.3 Reaching Equilibrium Point
114(1)
5.2.4 Selected Scenarios
115(1)
5.2.5 Results
116(7)
5.3 Path Planning with Minimum Curvature Variation
123(11)
5.3.1 Optimization Based on G2-Quintic Splines Path Description
123(2)
5.3.2 Reduction of Computation Cost Using Lookup Tables
125(3)
5.3.3 Geometry-Based Collision-Free Target Points Generation
128(4)
5.3.4 Simulation Results
132(2)
5.4 Model-Based Trajectory Planning
134(20)
5.4.1 Problem Formulation
134(2)
5.4.2 Parameterized Vehicle Control
136(1)
5.4.3 Constrained Optimization on Curvature Control
137(4)
5.4.4 Sampling of the Longitudinal Movements
141(2)
5.4.5 Trajectory Evaluation and Selection
143(2)
5.4.6 Integration of Road Friction Coefficient Estimation for Safety Enhancement
145(3)
5.4.7 Simulation Results in Complex Scenarios
148(6)
5.5
Chapter Summary and Concluding Remarks
154(5)
References
154(5)
6 Path-Tracking Model Regulation
159(18)
6.1 Introduction
159(1)
6.2 DOB Design and Frequency Response Analysis
160(11)
6.2.1 DOB Derivation and Loop Structure
160(2)
6.2.2 Application Examples
162(9)
6.2.3 Disturbance Rejection Comparison
171(1)
6.3 Q Filter Design
171(1)
6.4 Time Delay Performance
172(3)
6.5
Chapter Summary and Concluding Remarks
175(2)
References
175(2)
7 Robust Path Tracking Control
177(44)
7.1 Introduction
177(1)
7.2 Model Predictive Control for Path Following
178(7)
7.2.1 Formulation of Linear Adaptive MPC Problem
178(2)
7.2.2 Estimation of Lateral Velocity
180(2)
7.2.3 Experimental Results
182(3)
7.3 Design Methodology for Robust Gain-Scheduling Law
185(8)
7.3.1 Problem Formulation
185(1)
7.3.2 Design via Optimization in Linear Matrix Inequalities Form
186(2)
7.3.3 Parameter-Space Gain-Scheduling Methodology
188(5)
7.4 Robust Gain-Scheduling Application to Path-Tracking Control
193(13)
7.4.1 Car Steering Model and Parameter Uncertainty
193(2)
7.4.2 Controller Structure and Design Parameters
195(2)
7.4.3 Application of Parameter-Space Gain-Scheduling
197(3)
7.4.4 Comparative Study of LMI Design
200(2)
7.4.5 Experimental Results and Discussions
202(4)
7.5 Add-on Vehicle Stability Control for Autonomous Driving
206(10)
7.5.1 Direct Yaw Moment Control Strategies
207(4)
7.5.2 Direct Yaw Moment Distribution via Differential Braking
211(2)
7.5.3 Simulation Results and Discussion
213(3)
7.6
Chapter Summary and Concluding Remarks
216(5)
References
216(5)
8 Summary and Conclusions
221(4)
8.1 Summary
221(2)
8.2 Conclusions
223(2)
Index 225
Levent Güvenç, PhD, is Professor in the Department of Mechanical and Aerospace Engineering and the Department of Electrical and Computer Engineering at Ohio State University, USA.

Bilin Aksun-Güvenç, PhD, is Professor in the Department of Mechanical and Aerospace Engineering at Ohio State University, USA.

Sheng Zhu is a Software Engineer on planning and control at DeepRoute.ai with a PhD from the Department of Mechanical and Aerospace Engineering at Ohio State University, USA.

ükrü Yaren Gelbal is Graduate Research Associate in the Department of Electrical and Computer Engineering at Ohio State University, USA.