Artificial Intelligence (AI) is undoubtedly playing an increasingly significant role in automobile technology. In fact, cars inhabit one of just a few domains where you will find many AI innovations packed into a single product.
AI for Cars provides a brief guided tour through many different AI landscapes including robotics, image and speech processing, recommender systems and onto deep learning, all within the automobile world. From pedestrian detection to driver monitoring to recommendation engines, the book discusses the background, research and progress thousands of talented engineers and researchers have achieved thus far, and their plans to deploy this life-saving technology all over the world.
Foreword
Preface
AI for Advanced Driver Assistance Systems
Automatic Parking
Traffic Sign Recognition
Driver Monitoring System
Summary
AI for Autonomous Driving
Perception
Planning
Motion Control
Summary
AI for In-Vehicle Infotainment Systems
Gesture Control
Voice Assistant
User Action Prediction
Summary
AI for Research & Development
Automated Rules Generation
Virtual Testing Platform
Synthetic Scenario Generation
Summary
AI for Services
Predictive Diagnostics
Predictive Maintenance
Driver Behavior Analysis
Summary
The Future of AI in Cars
A Tale Of Two Paradigms
AI & Car Safety
AI & Car Security
Summary
Further Reading
References
Biography
Dr. Josep Aulinas is an Automotive Platform Architect at Nvidia. He specialized in computer vision and robotics and completed his Ph.D. in Simultaneous Localization and Mapping. He joined ADASENS Automotive, where he developed camera-based algorithms as part of Advanced Driver Assistance Systems (ADAS) solutions, such as vehicle recognition and tracking (forward-collision warning, automated emergency braking), lane recognition (lane departure warning, lane keep assist), traffic sign recognition, pedestrian detection (vulnerable road user protection), obstacle recognition with mono and stereo vision, among others. He then led various R+D projects, including lane change assist, camera online calibration, and lens occlusion detection. At Nvidia, he is supporting OEMs define their next-generation architecture, targeting higher levels of ADAS and ultimately Automated Driving (AD).
Hanky Sjafrie is the author of Introduction to Self-Driving Vehicle Technology and an independent consultant specializing in automotive software engineering for Advanced Driver Assistance (ADAS) and Autonomous Driving (AD). Much of his experience was acquired through his deep involvement in these fields while working on various R&D projects for car manufacturers and automotive technology suppliers, ranging from sensor technologies (radars, lidars, ultrasonics, etc.) to automotive cybersecurity. He was actively involved in diverse series development and research projects within the domains of ADAS/AD and infotainment systems at BMW and Audi, as well as at a Silicon Valley-based autonomous driving start-up. Besides working with clients from the automotive industry, he also provides insights into the realm of automotive technology to Siemens, Boston Consulting Group, PricewaterhouseCoopers, and Roland Berger, among others.
