128 Pages 6 B/W Illustrations
    by Chapman & Hall

    128 Pages 6 B/W Illustrations
    by Chapman & Hall

    128 Pages 6 B/W Illustrations
    by Chapman & Hall

    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.



    AI for Advanced Driver Assistance Systems  

    Automatic Parking 

    Traffic Sign Recognition 

    Driver Monitoring System    


    AI for Autonomous Driving  



    Motion Control 


    AI for In-Vehicle Infotainment Systems  

    Gesture Control 

    Voice Assistant 

    User Action Prediction  


    AI for Research & Development 

    Automated Rules Generation  

    Virtual Testing Platform    

    Synthetic Scenario Generation  


    AI for Services  

    Predictive Diagnostics  

    Predictive Maintenance  

    Driver Behavior Analysis  


    The Future of AI in Cars 

    A Tale Of Two Paradigms  

    AI & Car Safety  

    AI & Car Security  


    Further Reading 



    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.