This book provides an overview of constructing advanced Autonomous Driving Maps. It includes coverage of such methods as: fusion target perception (based on vehicle vision and millimeter wave radar), cross-field of view object perception, vehicle motion recognition (based on vehicle road fusion information), vehicle trajectory prediction (based on improved hybrid neural network) and the driving map construction method driven by road perception fusion. An Autonomous Driving Map is used for optimization of not only for a single vehicle, but also for the entire traffic system.

Discover the latest research in path planning and robust path tracking control In Autonomous Road Vehicle Path Planning and Tracking Control, a team of distinguished researchers delivers a practical and insightful exploration of how to design robust path tracking control. The authors include easy to understand concepts that are immediately applicable to the work of practicing control engineers and graduate students working in autonomous driving applications. Controller parameters are presented graphically, and regions of guaranteed performance are simple to visualize and understand. The book discusses the limits of performance, as well as hardware-in-the-loop simulation and experimental results that are implementable in real-time. Concepts of collision and avoidance are explained within the same framework and a strong focus on the robustness of the introduced tracking controllers is maintained throughout. In addition to a continuous treatment of complex planning and control in one relevant application, the Autonomous Road Vehicle Path Planning and Tracking Control includes: A thorough introduction to path planning and robust path tracking control for autonomous road vehicles, as well as a literature review with key papers and recent developments in the area Comprehensive explorations of vehicle, path, and path tracking models, model-in-the-loop simulation models, and hardware-in-the-loop models Practical discussions of path generation and path modeling available in current literature In-depth examinations of collision free path planning and collision avoidance Perfect for advanced undergraduate and graduate students with an interest in autonomous vehicles, Autonomous Road Vehicle Path Planning and Tracking Control is also an indispensable reference for practicing engineers working in autonomous driving technologies and the mobility groups and sections of automotive OEMs.

This two-volume set, LNAI 11012 and 11013, constitutes the thoroughly refereed proceedings of the 15th Pacific Rim Conference on Artificial Intelligence, PRICAI 2018, held in Nanjing, China, in August 2018. The 82 full papers and 58 short papers presented in these volumes were carefully reviewed and selected from 382 submissions. PRICAI covers a wide range of topics such as AI theories, technologies and their applications in the areas of social and economic importance for countries in the Pacific Rim.

This two-volume set of CCIS 391 and CCIS 392 constitutes the refereed proceedings of the Fourth International Conference on Information Computing and Applications, ICICA 2013, held in Singapore, in August 2013. The 126 revised full papers presented in both volumes were carefully reviewed and selected from 665 submissions. The papers are organized in topical sections on Internet computing and applications; engineering management and applications; intelligent computing and applications; control engineering and applications; cloud and evolutionary computing; knowledge management and applications; computational statistics and applications.

This book constitutes the proceedings of the 5th International Conference on the Internet of Vehicles, IOV 2018, which took place in Paris, France, in November 2018. This year’s theme was “Technologies and Services Towards Smart City”. The 21 papers presented in this volume were carefully reviewed and selected from 41 submissions. The papers are organized in topical sections named: IoV communications and networking; IoV clouds and services; vehicular modeling and simulation; and vehicular security and privacy.

The healthcare industry is starting to adopt digital twins to improve personalized medicine, healthcare organization performance, and new medicine and devices. These digital twins can create useful models based on information from wearable devices, omics, and patient records to connect the dots across processes that span patients, doctors, and healthcare organizations as well as drug and device manufacturers. Digital twins are digital representations of human physiology built on computer models. The use of digital twins in healthcare is revolutionizing clinical processes and hospital management by enhancing medical care with digital tracking and advancing modelling of the human body. These tools are of great help to researchers in studying diseases, new drugs, and medical devices. Digital Twins and Healthcare: Trends, Techniques, and Challenges facilitates the advancement and knowledge dissemination in methodologies and applications of digital twins in the healthcare and medicine fields. This book raises interest and awareness of the uses of digital twins in healthcare in the research community. Covering topics such as deep neural network, edge computing, and transfer learning method, this premier reference source is an essential resource for hospital administrators, pharmacists, medical professionals, IT consultants, students and educators of higher education, librarians, and researchers.

This book presents a variety of perspectives on vision-based applications. These contributions are focused on optoelectronic sensors, 3D & 2D machine vision technologies, robot navigation, control schemes, motion controllers, intelligent algorithms and vision systems. The authors focus on applications of unmanned aerial vehicles, autonomous and mobile robots, industrial inspection applications and structural health monitoring. Recent advanced research in measurement and others areas where 3D & 2D machine vision and machine control play an important role, as well as surveys and reviews about vision-based applications. These topics are of interest to readers from diverse areas, including electrical, electronics and computer engineering, technologists, students and non-specialist readers. • Presents current research in image and signal sensors, methods, and 3D & 2D technologies in vision-based theories and applications; • Discusses applications such as daily use devices including robotics, detection, tracking and stereoscopic vision systems, pose estimation, avoidance of objects, control and data exchange for navigation, and aerial imagery processing; • Includes research contributions in scientific, industrial, and civil applications.

This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), which is the integration of geospatial studies and AI machine (deep) learning and knowledge graph technologies. It explains key fundamental concepts, methods, models, and technologies of GeoAI, and discusses the recent advances, research tools, and applications that range from environmental observation and social sensing to natural disaster responses. As the first single volume on this fast-emerging domain, Handbook of Geospatial Artificial Intelligence is an excellent resource for educators, students, researchers, and practitioners utilizing GeoAI in fields such as information science, environment and natural resources, geosciences, and geography. Features Provides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectives Covers a wide range of GeoAI applications and case studies in practice Offers supplementary materials such as data, programming code, tools, and case studies Discusses the recent developments of GeoAI methods and tools Includes contributions written by top experts in cutting-edge GeoAI topics This book is intended for upper-level undergraduate and graduate students from different disciplines and those taking GIS courses in geography or computer sciences as well as software engineers, geospatial industry engineers, GIS professionals in non-governmental organizations, and federal/state agencies who use GIS and want to learn more about GeoAI advances and applications.

This book provides a detailed insight into Robotic Process Automation (RPA) technologies linked with AI that will help organizations implement Industry 4.0 procedures. RPA tools enhance their functionality by incorporating AI objectives, such as use of artificial neural network algorithms, text mining techniques, and natural language processing techniques for information extraction and the subsequent process of optimization and forecasting scenarios for the purpose of improving an organization's operational and business processes. The target readers of this book are researchers, professors, graduate students, scientists, policymakers, professionals, and developers working in the IT and ITeS sectors, i.e. people who are working on emerging technologies. This book also provides insights and decision support tools necessary for executives concerned with different industrial and organizational automation-centric jobs, knowledge dissemination, information, and policy development for automation in different educational, government, and non-government organizations. This book is of special interest to college and university educators who teach AI, machine learning, blockchain, business intelligence, cognitive intelligence, and brain intelligence courses in different capacities.

This book systematically discusses the development of autonomous driving, describing the related history, technological advances, infrastructure, social impacts, international competition, China’s opportunities and challenges, and possible future scenarios. This popular science book uses straightforward language and includes quotes from ancient Chinese poems to enhance the reading experience. The discussions are supplemented by theoretical elaborations, presented in tables and figures. The book is intended for auto fans, upper undergraduate and graduate students in the field of automotive engineering.