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Radar for Fully Autonomous Driving

Radar for Fully Autonomous Driving
Author: Matt Markel
Publisher: Artech House
Total Pages: 360
Release: 2022-04-30
Genre: Technology & Engineering
ISBN: 1630818976

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This is the first book to bring together the increasingly complex radar automotive technologies and tools being explored and utilized in the development of fully autonomous vehicles – technologies and tools now understood to be an essential need for the field to fully mature. The book presents state-of-the-art knowledge as shared by the best and brightest experts working in the automotive radar industry today -- leaders who have “been there and done that.” Each chapter is written as a standalone "master class" with the authors, seeing the topic through their eyes and experiences. Where beneficial, the chapters reference one another but can otherwise be read in any order desired, making the book an excellent go-to reference for a particular topic or review you need to understand. You’ll get a big-picture tour of the key radar needs for fully autonomous vehicles, and how achieving these needs is complicated by the automotive environment’s dense scenes, number of possible targets of interest, and mix of very large and very small returns. You’ll then be shown the challenges from – and mitigations to – radio frequency interference (RFI), an ever-increasing challenge as the number of vehicles with radars – and radars per vehicle grow. The book also dives into the impacts of weather on radar performance, providing you with insights gained from extensive real-world testing. You are then taken through the integration and systems considerations, especially regarding safety, computing needs, and testing. Each of these areas is influenced heavily by the needs of fully autonomous vehicles and are open areas of research and development. With this authoritative volume you will understand: * How to engage with radar designers (from a system integrator / OEM standpoint); * How to structure and set requirements for automotive radars; * How to address system safety needs for radars in fully autonomous vehicles; * How to assess weather impact on the radar and its ability to support autonomy; * How to include weather effects into specifications for radars. This is an essential reference for engineers currently in the autonomous vehicle arena and/or working in automotive radar development, as well as engineers and leaders in adjacent radar fields needing to stay abreast of the rapid developments in this exciting and dynamic field of research and development.


Radar Signal Processing for Autonomous Driving

Radar Signal Processing for Autonomous Driving
Author: Jonah Gamba
Publisher: Springer
Total Pages: 142
Release: 2019-08-02
Genre: Technology & Engineering
ISBN: 9811391939

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The subject of this book is theory, principles and methods used in radar algorithm development with a special focus on automotive radar signal processing. In the automotive industry, autonomous driving is currently a hot topic that leads to numerous applications for both safety and driving comfort. It is estimated that full autonomous driving will be realized in the next twenty to thirty years and one of the enabling technologies is radar sensing. This book presents both detection and tracking topics specifically for automotive radar processing. It provides illustrations, figures and tables for the reader to quickly grasp the concepts and start working on practical solutions. The complete and comprehensive coverage of the topic provides both professionals and newcomers with all the essential methods and tools required to successfully implement and evaluate automotive radar processing algorithms.


Radar Signal Processing for Autonomous Driving

Radar Signal Processing for Autonomous Driving
Author: Jonah Gamba
Publisher:
Total Pages:
Release: 2020
Genre: Automated vehicles
ISBN: 9789811391941

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The subject of this book is theory, principles and methods used in radar algorithm development with a special focus on automotive radar signal processing. In the automotive industry, autonomous driving is currently a hot topic that leads to numerous applications for both safety and driving comfort. It is estimated that full autonomous driving will be realized in the next twenty to thirty years and one of the enabling technologies is radar sensing. This book presents both detection and tracking topics specifically for automotive radar processing. It provides illustrations, figures and tables for the reader to quickly grasp the concepts and start working on practical solutions. The complete and comprehensive coverage of the topic provides both professionals and newcomers with all the essential methods and tools required to successfully implement and evaluate automotive radar processing algorithms.


Large Aperture Array Radar Systems for Automotive Applications

Large Aperture Array Radar Systems for Automotive Applications
Author: Fabian Schwartau
Publisher: Cuvillier Verlag
Total Pages: 144
Release: 2021-10-18
Genre: Technology & Engineering
ISBN: 3736965079

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The radar, besides camera and Lidar systems, is a core sensor to enable autonomous driving. The relatively limited angular resolution is the major drawback of the radar. This thesis shows the development of a conceptual future radar system for automotive applications. The focus is on providing a large antenna aperture to achieve the required high angular resolution. Two genetic algorithms are developed to optimize the antenna array for a good side lobe level while providing high angular resolution. Two demonstrators are built to implement certain aspects of the proposed radar system and prove the general concept viable. The first demonstrator features a large aperture with a limited side lobe level and is using a modular approach. The modules are synchronized with a radio over fiber system. The second demonstrator uses the previously proposed antenna array, which is implemented with a synthetic aperture radar approach. The system’s capabilities in a real scenario are demonstrated, and the reconstruction of a high-resolution three-dimensional image from the captured data is shown. Das Radar stellt, neben Kamera- und Lidar-Systemen, einen zentralen Sensor für das autonome Fahren dar. Dabei ist die relativ geringe Winelauflösung der primäre Nachteil des Radars. Diese Arbeit zeigt die Entwicklung eines konzeptionellen zukünftigen Radarsystems für automobile Anwendungen. Der Schwerpunkt liegt auf der Umsetzung einer großen Antennenapertur, um die erforderliche hohe Winkelauflösung zu erreichen. Zwei evolutionäre Algorithmen werden vorgestellt, um das Antennen-Array auf einen guten Nebenkeulen-Pegel zu optimieren und gleichzeitig eine hohe Winkelauflösung zu erreichen. Zwei Demonstratoren werden gebaut, um bestimmte Aspekte des vorgeschlagenen Radarsystems zu implementieren und die Durchführbarkeit des allgemeinen Konzepts zu zeigen. Der erste Demonstrator weist eine große Apertur mit einem begrenzten Nebenkeulen-Niveau auf und verwendet einen modularen Ansatz. Die Module sind mit einem Radio-over-Fiber-System synchronisiert. Der zweite Demonstrator verwendet die zuvor entworfene Antennenanordnung, die mit einem Radar mit synthetischer Apertur realisiert wird. Die Fähigkeiten des Systems werden in einem realen Szenario demonstriert und die Rekonstruktion eines hochauflösenden dreidimensionalen Bildes aus den erfassten Daten gezeigt.


Millimeter Wave Radar

Millimeter Wave Radar
Author: Stephen L. Johnston
Publisher:
Total Pages: 686
Release: 1980
Genre: Technology & Engineering
ISBN:

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Autonomous Vehicle Technology

Autonomous Vehicle Technology
Author: James M. Anderson
Publisher: Rand Corporation
Total Pages: 215
Release: 2014-01-10
Genre: Transportation
ISBN: 0833084372

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The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.


Deep Learning Methods for Automotive Radar Signal Processing

Deep Learning Methods for Automotive Radar Signal Processing
Author: Rodrigo Pérez González
Publisher: Cuvillier
Total Pages: 136
Release: 2021-06-28
Genre:
ISBN: 9783736974623

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For autonomous driving to become a reality, future sensor systems must be able to not only capture the vehicle's environment, but also to provide semantic information. In this work, deep learning methods, meant to enhance-or even replace-the classical radar signal processing chain, are developed and evaluated in the context of automotive applications. For this purpose, state of the art computer vision approaches are adapted and applied to radar signals in order to detect and classify different road users.


Polarimetric Radar for Automotive Applications

Polarimetric Radar for Automotive Applications
Author: Tristan Visentin
Publisher: Saint Philip Street Press
Total Pages: 0
Release: 2020-10-09
Genre: Computers
ISBN: 9781013283420

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Current automotive radar sensors prove to be a weather robust and low-cost solution, but are suffering from low resolution and are not capable of classifying detected targets. However, for future applications like autonomous driving, such features are becoming ever increasingly important. On the basis of successful state-of-the-art applications, this work presents the first in-depth analysis and ground-breaking, novel results of polarimetric millimeter wave radars for automotive applications. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.


Autonomous Vehicles

Autonomous Vehicles
Author: Fouad Sabry
Publisher: One Billion Knowledgeable
Total Pages: 106
Release: 2021-02-03
Genre: Computers
ISBN: 046358838X

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Elon Musk thought that his company Tesla will have fully autonomous cars ready by the end of 2020. "There are no fundamental challenges left," he said recently. "There are a number of minor issues. And then there's a struggle to solve all these little problems and bring the whole thing together." Although the technology to allow a car to complete a journey without human interference (what the industry calls "level 5 autonomy") can move quickly, the development of a vehicle that can do so safely and legally is another matter. The novelty of autonomous technology is intended to turn our legal and social ties into daily transport. Importantly, without a driver behind the wheel, autonomous vehicles raise concerns about the liability and responsibility for the conduct of the lane. Therefore, this book is structured to answer many questions about autonomous vehicles and make you not only understand all the aspects of this emerging technology, but master the discussions and debates about the following topics: Chapter One: The rise of autonomous vehicles Autonomous vehicles become reality History of Autonomous vehicles Road Items Weights Society of Automotive Engineers (SAE International) Chapter Two: Tesla Autopilot AutoPilot AI Advanced Sensor Coverage Wide, Main and Narrow Forward Cameras Wide Main Narrow Forward Looking Side Cameras Rearward Looking Side Cameras Rear View Camera Radar Ultrasonic Sensors Processing Power Increased 40x Tesla Vision Autopilot Navigate on Autopilot Autosteer+ Smart Summon Full Self-Driving Capability From Home To your Destination Chapter Three: A level-by-level explainer of autonomous vehicles Classification System For The Development Of Innovations The J3016 Guidelines Six SAE level Criticism of SAE classification Level 0: No automation Level 1: Driver assistance Level 2: Partial automation Level 3: Conditional automation Level 4: High automation Level 5: Full automation Chapter Four: Main Connectivity Specifications Of Autonomous Vehicles Vehicle-To-Everything Architectures must be both redundant and real-time. The demand for high-speed data would increase only Security and other applications Include external connectivity Autonomous driving efficiency and reliability are non-negotiable More and more electrified cars would need a new approach to safety Next generation Car Design Would Need Miniaturized Solutions Co-creation of the future of mobility Chapter Five: Building Passenger Trust Is Key Technology for self-driving cars is accelerating fast, but our driverless future isn't going anywhere if people don't trust it. rules of the road implicit laws are more challenging The math-based AV safety model What is Sensitive Protection Responsibility? RSS is compatible with other AV systems How are AVs safely sharing the road with human drivers? 01 Safe distance: Don't hit the car in front of you 02 Cutting in: Don't cut it in recklessly 03 Right of Way: Right of way is given, not taken 04 Limited Visibility: Be cautious in areas with limited visibility 05 Avoid Crashes: If you can avoid a crash without causing another one, you must Moving past the miles-driven Improving road safety with RSS today RSS to gain support Baidu Valeo China ITS Alliance RAND Corp. The Arizona Institute for Automated Mobility Joint Research Institutes Chapter Six: The reasons Autonomous vehicles still aren’t on our roads The Gap Between the Invention and The Application Sensors Machine Learning The Open Road Regulations Social Acceptability Chapter Seven: Legal frameworks and other national initiatives The United States European Union Membership United Arab Emirates Japan Australia Chapter Eight: Liability, ethics and human rights implications The novelty of autonomous vehicles The critical debate Autonomy Threats Chapter Nine: Leading opinions on an ethical rollout for autonomous vehicles The Three Laws of Robotics The Ethical Dilemmas of Autonomy The Worst-Case Scenario The Trolley Issue Chapter Ten: Social and economic implications Roads Safety Vehicles Ownership and Vehicles Insurance Jobs Chapter Eleven: Ongoing research and impediments to autonomous vehicle development Research and Development The Social Acceptance of Autonomous Vehicles Chapter Twelve: The Sensor Types Drive Autonomous Vehicles Multiple Redundant Sensor Systems Overview of the study SAE Levels Short DESCRIPTIONS No car manufacturer has reached level 3 or higher Which sensors are needed? Camera and LIDAR Systems Cameras Back and 360° cameras Front-Facing Camera Systems RADAR Sensor LiDAR Summary and insight