> Handbook of Intelligent Vehicles

Handbook of Intelligent Vehicles


Welcome to the homepage of Handbook of Intelligent Vehicles, a comprehensive reference work from Springer.

The field of intelligent vehicles is growing in automotive industry, intelligent transportation systems (ITS) R&D communities, highway construction and maintenance industry, and military applications. In transportation arena, intelligent vehicles aim to improve driving safety, vehicle handling, comfort, and convenience, while reducing energy usage, environmental impact, and traffic congestion. Intelligent vehicles are also being developed to automate highway maintenance, repair, and construction. In military applications, they provide mobility, reconnaissance, and various applications in hazardous and hostile environment. The Handbook of Intelligent Vehicles is intended to provide a comprehensive coverage of all aspects of this field in surface transportation, covering fundamentals as well as recent technical advances. The goal of this handbook is to serve as the predominant reference in the field of intelligent vehicles for students, researchers, engineers/practitioners, and technical managers.

This handbook is arranged in a user-friendly format in distinct sections, each containing a major area of intelligent vehicles. Within each section are multiple chapters written by internationally renowned authors/experts who are authorities in their fields. A fuller discussion of the handbook's focus and coverage is provided in Aims & Scope.

Azim Eskandarian

(Editor in Chief)

  1. Introduction to Intelligent Vehicles
  2. A Strategic Approach to Intelligent Functions in Vehicles
  3. Sensing and Actuation in Intelligent Vehicles
  4. Situational Awareness in Intelligent Vehicles
  5. Hierarchical, Intelligent and Automatic Controls
  6. Behavioral Adaptation and Acceptance
  7. Simulation Approaches to Intelligent Vehicles
  8. Vehicle Longitudinal Control
  9. Adaptive and Cooperative Cruise Control
  10. Vehicle Lateral and Steering Control
  11. Drive-By-Wire
  12. Energy and Powertrain Systems in Intelligent Automobiles
  13. Global Navigation Satellite Systems: An Enabler for In-Vehicle Navigation
  14. Enhancing Vehicle Positioning Data Through Map-Matching
  15. Situational Awareness and Road Prediction for Trajectory Control Applications
  16. Navigation and Tracking of Road-Bound Vehicles Using Map Support
  17. State-of-the-Art In-Car Navigation: An Overview
  18. Evolution of In-Car Navigation Systems
  19. Fundamentals of Driver Assistance
  20. Driver Behavior Modeling
  21. Using Naturalistic Driving Research to Design, Test and Evaluate Driver Assistance Systems
  22. Intelligent Speed Adaptation (ISA)
  23. Safety and Comfort Systems: Introduction and Overview
  24. Adaptive Cruise Control
  25. Forward Collision Warning and Avoidance
  26. Lane Departure and Lane Keeping
  27. Integral Safety
  28. Lane Change Assistance
  29. Steering and Evasion Assist
  30. Proactive Pedestrian Protection
  31. Parking Assist
  32. Post-crash Support Systems
  33. Map Data for ADAS
  34. Advances in Drowsy Driver Assistance Systems Through Data Fusion
  35. Drowsy Driver Posture, Facial, and Eye Monitoring Methods
  36. Drowsy and Fatigued Driving Problem Significance and Detection Based on Driver Control Functions
  37. Drowsy and Fatigued Driver Warning, Counter Measures, and Assistance
  38. Image Processing for Vehicular Applications
  39. Camera Technologies
  40. Perception Tasks: Lane Detection
  41. Perception Tasks: Obstacle Detection
  42. Perception Tasks: Traffic Sign Recognition
  43. Vision-Based ACC
  44. Vision-Based Blind Spot Monitoring
  45. Vehicular Communications Requirements and Challenges
  46. Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) Communications and Cooperative Driving
  47. Probes and Intelligent Vehicles
  48. Threat Model, Authentication, and Key Management
  49. Security, Privacy, Identifications
  50. Autonomous Driving: Context and State-of-the-Art
  51. Modeling and Learning Behaviors
  52. Vision and IMU Data Fusion: Closed-Form Determination of the Absolute Scale, Speed, and Attitude
  53. Vision-Based Topological Navigation: An Implicit Solution to Loop Closure
  54. Awareness of Road Scene Participants for Autonomous Driving
  55. Iterative Motion Planning and Safety Issue
  56. Risk Based Navigation Decisions
  57. Probabilistic Vehicle Motion Modeling and Risk Estimation
  58. Legal Issues of Driver Assistance Systems and Autonomous Driving
  59. Intelligent Vehicle Potential and Benefits
  60. Applications and Market Outlook