Autonomous Intelligent Vehicles: Theory, Algorithms, and Implementation

This important text/reference presents state-of-the-art research on intelligent vehicles, covering not only topics of object/obstacle detection and recognition, but also aspects of vehicle motion control. With an emphasis on both high-level concepts, and practical detail, the text links theory, algorithms, and issues of hardware and software implementation in intelligent vehicle research. Topics and features: presents a thorough introduction to the development and latest progress in intelligent vehicle research, and proposes a basic framework; provides detection and tracking algorithms for structured and unstructured roads, as well as on-road vehicle detection and tracking algorithms using boosted Gabor features; discusses an approach for multiple sensor-based multiple-object tracking, in addition to an integrated DGPS/IMU positioning approach; examines a vehicle navigation approach using global views; introduces algorithms for lateral and longitudinal vehicle motion control.

Table of Contents

Part I: Autonomous Intelligent Vehicles
Chapter 1: Introduction
Chapter 2: The State-of-the-Art in the USA
Chapter 3: The Framework of Intelligent Vehicles

Part II: Environment Perception and Modeling
Chapter 4: Road Detection and Tracking
Chapter 5: Vehicle Detection and Tracking
Chapter 6: Multiple-Sensor Based Multiple-Object Tracking

Part III: Vehicle Localization and Navigation
Chapter 7: An Integrated DGPS/IMU Positioning Approach
Chapter 8: Vehicle Navigation Using Global Views
Part IV: Advanced Vehicle Motion Control

Chapter 9: The Lateral Motion Control for Intelligent Vehicles
Chapter 10: Longitudinal Motion Control for Intelligent Vehicles