Year: 2019 Language: english Author: Huafeng Yu Genre: Handbook Publisher: Springer Format: PDF Quality: eBook Pages count: 215 Description: An autonomous and intelligent system generally refers to a system that can automatically sense and adapt to dynamically varying environment. The term broadly covers numerous emerging and critical applications including self-driving vehicles, unmanned aircraft systems, and autonomous ships. A broad application of modern artificial intelligence and machine learning technologies is featured in these systems. The design, modeling, verification, and validation of today’s autonomous and intelligent systems have become increasingly challenging with growing functional complexity in scale and features, the integration of new artificial intelligence and machine learning technologies, the adoption of more distributed and networked architectural platforms, and stringent demands on various design constraints imposed by performance, fault tolerance, reliability, extensibility, and security. The aforementioned trend on growing complexity presents tremendous design and validation challenges to safety assurance and certification and calls for an immediate attention to this emerging area for developing radically new methodologies and practices to address the grand challenges, as well as enormous opportunities that have been rarely explored in the past. Over the past several years, a large number of academic articles, technical reports, and industrial whitepapers have been published in this area. However, due to the highly interdisciplinary nature of the area, they are often independently reported across diverse technical communities like verification and validation, artificial intelligence, signal processing, system control, computer vision, and circuit design. Recent research and development in these areas has advanced to the point where an organized, integrated account seamlessly integrating the state of the art is immediately needed. This will help in comparing a large body of techniques in the literature and clarifying their trade-offs in terms of performance, cost, utility, etc. For this reason, there is increasing demand to report the state-of-the-art advances recently made by both academic and industrial researchers closely collaborating together in this area.
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Safe, Autonomous and Intelligent Vehicles
Language: english
Author: Huafeng Yu
Genre: Handbook
Publisher: Springer
Format: PDF
Quality: eBook
Pages count: 215
Description: An autonomous and intelligent system generally refers to a system that can
automatically sense and adapt to dynamically varying environment. The term
broadly covers numerous emerging and critical applications including self-driving
vehicles, unmanned aircraft systems, and autonomous ships. A broad application of
modern artificial intelligence and machine learning technologies is featured in these
systems.
The design, modeling, verification, and validation of today’s autonomous and
intelligent systems have become increasingly challenging with growing functional
complexity in scale and features, the integration of new artificial intelligence
and machine learning technologies, the adoption of more distributed and networked
architectural platforms, and stringent demands on various design constraints
imposed by performance, fault tolerance, reliability, extensibility, and security.
The aforementioned trend on growing complexity presents tremendous design and
validation challenges to safety assurance and certification and calls for an immediate
attention to this emerging area for developing radically new methodologies and
practices to address the grand challenges, as well as enormous opportunities that
have been rarely explored in the past.
Over the past several years, a large number of academic articles, technical
reports, and industrial whitepapers have been published in this area. However, due
to the highly interdisciplinary nature of the area, they are often independently
reported across diverse technical communities like verification and validation,
artificial intelligence, signal processing, system control, computer vision, and circuit
design. Recent research and development in these areas has advanced to the point
where an organized, integrated account seamlessly integrating the state of the art is
immediately needed. This will help in comparing a large body of techniques in the
literature and clarifying their trade-offs in terms of performance, cost, utility, etc.
For this reason, there is increasing demand to report the state-of-the-art advances
recently made by both academic and industrial researchers closely collaborating
together in this area.
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