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Vehicle Control of Autonomous Vehicles: A Comprehensive Guide to Mastering Autonomous Driving

John Dos Passos

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Published in Vehicle Control Of Autonomous Vehicles: Autonomous Vehicle Control Autonomous Steering Control Control Of Collision Avoidance Autonomous Braking Control (tech Research)

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As the world rapidly embraces the era of autonomous vehicles, mastering vehicle control becomes paramount for engineers, researchers, and industry professionals. This comprehensive guidebook delves into the fascinating realm of vehicle dynamics, actuator control, and advanced algorithms, equipping readers with the knowledge and skills to navigate the future of transportation.

vehicle control of autonomous vehicles: Autonomous Vehicle Control, Autonomous Steering Control, Control of Collision Avoidance, Autonomous Braking Control (tech research)

5 out of 5

Language	:	English
File size	:	10957 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	171 pages
Lending	:	Enabled

Chapter 1: Vehicle Dynamics for Autonomous Vehicles

1.1 Fundamentals of Vehicle Dynamics

Newton's Laws of Motion applied to vehicle systems
Kinematic and dynamic models of vehicle behavior
Understanding tire-road interactions and friction forces

1.2 Modeling and Simulation Techniques

Developing accurate mathematical models for vehicle dynamics
Using simulation tools to analyze vehicle performance
Validating models through experimental testing

Chapter 2: Actuator Control for Autonomous Vehicles

2.1 Types of Actuators in Autonomous Vehicles

Electric motors for propulsion and steering
Hydraulic systems for braking and suspension control
Pneumatic systems for gear shifting and clutch operation

2.2 Control Techniques for Actuators

PID control for basic actuator operation
Model-based control for improved performance
Advanced control algorithms for fault tolerance and optimization

Chapter 3: Advanced Algorithms for Autonomous Vehicle Control

3.1 Path Planning and Trajectory Optimization

Algorithms for generating safe and efficient vehicle trajectories
Optimization techniques to minimize energy consumption and travel time
Integration of environmental information for real-time decision-making

3.2 Model Predictive Control for Autonomous Vehicles

Principles of Model Predictive Control (MPC)
Formulating optimization problems for vehicle control
Implementing MPC algorithms in real-time environments

Chapter 4: Case Studies and Applications

4.1 Autonomous Vehicle Design and Development

Case study on designing and building an autonomous vehicle prototype
Overview of industry best practices and safety standards
Challenges and opportunities in autonomous vehicle development

4.2 Applications in Transportation and Logistics

Autonomous cars for passenger transportation
Autonomous trucks for long-haul freight transport
Autonomous drones for package delivery and aerial surveillance

This comprehensive guidebook provides a solid foundation for understanding the intricate world of vehicle control for autonomous vehicles. By mastering the principles of vehicle dynamics, actuator control, and advanced algorithms outlined in this book, readers will gain the expertise needed to design, develop, and deploy safe and efficient autonomous vehicles. As the industry continues to evolve, this guide will serve as an invaluable resource for engineers, researchers, and visionaries shaping the future of transportation.

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vehicle control of autonomous vehicles: Autonomous Vehicle Control, Autonomous Steering Control, Control of Collision Avoidance, Autonomous Braking Control (tech research)

5 out of 5