Autonomous Driving Perception

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Autonomous Driving Perception

Author : Rui Fan
Publisher : Springer Nature
ISBN 13 : 981994287X
Total Pages : 391 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Autonomous Driving Perception by : Rui Fan

Download or read book Autonomous Driving Perception written by Rui Fan and published by Springer Nature. This book was released on 2023-10-06 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the captivating world of computer vision and deep learning for autonomous driving with our comprehensive and in-depth guide. Immerse yourself in an in-depth exploration of cutting-edge topics, carefully crafted to engage tertiary students and ignite the curiosity of researchers and professionals in the field. From fundamental principles to practical applications, this comprehensive guide offers a gentle introduction, expert evaluations of state-of-the-art methods, and inspiring research directions. With a broad range of topics covered, it is also an invaluable resource for university programs offering computer vision and deep learning courses. This book provides clear and simplified algorithm descriptions, making it easy for beginners to understand the complex concepts. We also include carefully selected problems and examples to help reinforce your learning. Don't miss out on this essential guide to computer vision and deep learning for autonomous driving.

Learning to Drive

Author : David Michael Stavens
Publisher : Stanford University
ISBN 13 :
Total Pages : 104 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Learning to Drive by : David Michael Stavens

Download or read book Learning to Drive written by David Michael Stavens and published by Stanford University. This book was released on 2011 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every year, 1.2 million people die in automobile accidents and up to 50 million are injured. Many of these deaths are due to driver error and other preventable causes. Autonomous or highly aware cars have the potential to positively impact tens of millions of people. Building an autonomous car is not easy. Although the absolute number of traffic fatalities is tragically large, the failure rate of human driving is actually very small. A human driver makes a fatal mistake once in about 88 million miles. As a co-founding member of the Stanford Racing Team, we have built several relevant prototypes of autonomous cars. These include Stanley, the winner of the 2005 DARPA Grand Challenge and Junior, the car that took second place in the 2007 Urban Challenge. These prototypes demonstrate that autonomous vehicles can be successful in challenging environments. Nevertheless, reliable, cost-effective perception under uncertainty is a major challenge to the deployment of robotic cars in practice. This dissertation presents selected perception technologies for autonomous driving in the context of Stanford's autonomous cars. We consider speed selection in response to terrain conditions, smooth road finding, improved visual feature optimization, and cost effective car detection. Our work does not rely on manual engineering or even supervised machine learning. Rather, the car learns on its own, training itself without human teaching or labeling. We show this "self-supervised" learning often meets or exceeds traditional methods. Furthermore, we feel self-supervised learning is the only approach with the potential to provide the very low failure rates necessary to improve on human driving performance.

Learning to Drive

Author : David Michael Stavens
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (745 download)

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Book Synopsis Learning to Drive by : David Michael Stavens

Download or read book Learning to Drive written by David Michael Stavens and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Every year, 1.2 million people die in automobile accidents and up to 50 million are injured. Many of these deaths are due to driver error and other preventable causes. Autonomous or highly aware cars have the potential to positively impact tens of millions of people. Building an autonomous car is not easy. Although the absolute number of traffic fatalities is tragically large, the failure rate of human driving is actually very small. A human driver makes a fatal mistake once in about 88 million miles. As a co-founding member of the Stanford Racing Team, we have built several relevant prototypes of autonomous cars. These include Stanley, the winner of the 2005 DARPA Grand Challenge and Junior, the car that took second place in the 2007 Urban Challenge. These prototypes demonstrate that autonomous vehicles can be successful in challenging environments. Nevertheless, reliable, cost-effective perception under uncertainty is a major challenge to the deployment of robotic cars in practice. This dissertation presents selected perception technologies for autonomous driving in the context of Stanford's autonomous cars. We consider speed selection in response to terrain conditions, smooth road finding, improved visual feature optimization, and cost effective car detection. Our work does not rely on manual engineering or even supervised machine learning. Rather, the car learns on its own, training itself without human teaching or labeling. We show this "self-supervised" learning often meets or exceeds traditional methods. Furthermore, we feel self-supervised learning is the only approach with the potential to provide the very low failure rates necessary to improve on human driving performance.

Hands-On Vision and Behavior for Self-Driving Cars

Author : Luca Venturi
Publisher : Packt Publishing Ltd
ISBN 13 : 1800201931
Total Pages : 374 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis Hands-On Vision and Behavior for Self-Driving Cars by : Luca Venturi

Download or read book Hands-On Vision and Behavior for Self-Driving Cars written by Luca Venturi and published by Packt Publishing Ltd. This book was released on 2020-10-23 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to learning visual perception for self-driving cars for computer vision and autonomous system engineers Key FeaturesExplore the building blocks of the visual perception system in self-driving carsIdentify objects and lanes to define the boundary of driving surfaces using open-source tools like OpenCV and PythonImprove the object detection and classification capabilities of systems with the help of neural networksBook Description The visual perception capabilities of a self-driving car are powered by computer vision. The work relating to self-driving cars can be broadly classified into three components - robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field. You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real self-driving car is a huge cross-functional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You’ll even be able to tackle core challenges in self-driving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller. By the end of this book, you’ll be equipped with the skills you need to write code for a self-driving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers. What you will learnUnderstand how to perform camera calibrationBecome well-versed with how lane detection works in self-driving cars using OpenCVExplore behavioral cloning by self-driving in a video-game simulatorGet to grips with using lidarsDiscover how to configure the controls for autonomous vehiclesUse object detection and semantic segmentation to locate lanes, cars, and pedestriansWrite a PID controller to control a self-driving car running in a simulatorWho this book is for This book is for software engineers who are interested in learning about technologies that drive the autonomous car revolution. Although basic knowledge of computer vision and Python programming is required, prior knowledge of advanced deep learning and how to use sensors (lidar) is not needed.

Belief State Planning for Autonomous Driving: Planning with Interaction, Uncertain Prediction and Uncertain Perception

Author : Hubmann, Constantin
Publisher : KIT Scientific Publishing
ISBN 13 : 3731510391
Total Pages : 178 pages
Book Rating : 4.7/5 (315 download)

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Book Synopsis Belief State Planning for Autonomous Driving: Planning with Interaction, Uncertain Prediction and Uncertain Perception by : Hubmann, Constantin

Download or read book Belief State Planning for Autonomous Driving: Planning with Interaction, Uncertain Prediction and Uncertain Perception written by Hubmann, Constantin and published by KIT Scientific Publishing. This book was released on 2021-09-13 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents a behavior planning algorithm for automated driving in urban environments with an uncertain and dynamic nature. The algorithm allows to consider the prediction uncertainty (e.g. different intentions), perception uncertainty (e.g. occlusions) as well as the uncertain interactive behavior of the other agents explicitly. Simulating the most likely future scenarios allows to find an optimal policy online that enables non-conservative planning under uncertainty.

Autonomous Driving

Author : Markus Maurer
Publisher : Springer
ISBN 13 : 3662488477
Total Pages : 706 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Autonomous Driving by : Markus Maurer

Download or read book Autonomous Driving written by Markus Maurer and published by Springer. This book was released on 2016-05-21 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies? Experts from Germany and the United States define key societal, engineering, and mobility issues related to the automation of vehicles. They discuss the decisions programmers of automated vehicles must make to enable vehicles to perceive their environment, interact with other road users, and choose actions that may have ethical consequences. The authors further identify expectations and concerns that will form the basis for individual and societal acceptance of autonomous driving. While the safety benefits of such vehicles are tremendous, the authors demonstrate that these benefits will only be achieved if vehicles have an appropriate safety concept at the heart of their design. Realizing the potential of automated vehicles to reorganize traffic and transform mobility of people and goods requires similar care in the design of vehicles and networks. By covering all of these topics, the book aims to provide a current, comprehensive, and scientifically sound treatment of the emerging field of “autonomous driving".

Introduction to Self-Driving Vehicle Technology

Author : Hanky Sjafrie
Publisher : CRC Press
ISBN 13 : 1000712079
Total Pages : 182 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Introduction to Self-Driving Vehicle Technology by : Hanky Sjafrie

Download or read book Introduction to Self-Driving Vehicle Technology written by Hanky Sjafrie and published by CRC Press. This book was released on 2019-11-21 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible. It is aimed at people who want to get their teeth into self-driving vehicle technology, by providing genuine technical insights where other books just skim the surface. The book tackles everything from sensors and perception to functional safety and cybersecurity. It also passes on some practical know-how and discusses concrete SDV applications, along with a discussion of where this technology is heading. It will serve as a good starting point for software developers or professional engineers who are eager to pursue a career in this exciting field and want to learn more about the basics of SDV algorithms. Likewise, academic researchers, technology enthusiasts, and journalists will also find the book useful. Key Features: Offers a comprehensive technological walk-through of what really matters in SDV development: from hardware, software, to functional safety and cybersecurity Written by an active practitioner with extensive experience in series development and research in the fields of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Covers theoretical fundamentals of state-of-the-art SLAM, multi-sensor data fusion, and other SDV algorithms. Includes practical information and hands-on material with Robot Operating System (ROS) and Open Source Car Control (OSCC). Provides an overview of the strategies, trends, and applications which companies are pursuing in this field at present as well as other technical insights from the industry.

Creating Autonomous Vehicle Systems

Author : Shaoshan Liu
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1681730081
Total Pages : 198 pages
Book Rating : 4.6/5 (817 download)

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Book Synopsis Creating Autonomous Vehicle Systems by : Shaoshan Liu

Download or read book Creating Autonomous Vehicle Systems written by Shaoshan Liu and published by Morgan & Claypool Publishers. This book was released on 2017-10-25 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.

Engineering Autonomous Vehicles and Robots

Author : Shaoshan Liu
Publisher : John Wiley & Sons
ISBN 13 : 1119570565
Total Pages : 214 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Engineering Autonomous Vehicles and Robots by : Shaoshan Liu

Download or read book Engineering Autonomous Vehicles and Robots written by Shaoshan Liu and published by John Wiley & Sons. This book was released on 2020-05-11 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a step-by-step guide to building autonomous vehicles and robots, with source code and accompanying videos The first book of its kind on the detailed steps for creating an autonomous vehicle or robot, this book provides an overview of the technology and introduction of the key elements involved in developing autonomous vehicles, and offers an excellent introduction to the basics for someone new to the topic of autonomous vehicles and the innovative, modular-based engineering approach called DragonFly. Engineering Autonomous Vehicles and Robots: The DragonFly Modular-based Approach covers everything that technical professionals need to know about: CAN bus, chassis, sonars, radars, GNSS, computer vision, localization, perception, motion planning, and more. Particularly, it covers Computer Vision for active perception and localization, as well as mapping and motion planning. The book offers several case studies on the building of an autonomous passenger pod, bus, and vending robot. It features a large amount of supplementary material, including the standard protocol and sample codes for chassis, sonar, and radar. GPSD protocol/NMEA protocol and GPS deployment methods are also provided. Most importantly, readers will learn the philosophy behind the DragonFly modular-based design approach, which empowers readers to design and build their own autonomous vehicles and robots with flexibility and affordability. Offers progressive guidance on building autonomous vehicles and robots Provides detailed steps and codes to create an autonomous machine, at affordable cost, and with a modular approach Written by one of the pioneers in the field building autonomous vehicles Includes case studies, source code, and state-of-the art research results Accompanied by a website with supplementary material, including sample code for chassis/sonar/radar; GPS deployment methods; Vision Calibration methods Engineering Autonomous Vehicles and Robots is an excellent book for students, researchers, and practitioners in the field of autonomous vehicles and robots.

Autonomous Vehicle Technology

Author : James M. Anderson
Publisher : Rand Corporation
ISBN 13 : 0833084372
Total Pages : 214 pages
Book Rating : 4.8/5 (33 download)

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Book Synopsis Autonomous Vehicle Technology by : James M. Anderson

Download or read book Autonomous Vehicle Technology written by James M. Anderson and published by Rand Corporation. This book was released on 2014-01-10 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The DARPA Urban Challenge

Author : Martin Buehler
Publisher : Springer
ISBN 13 : 364203991X
Total Pages : 628 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis The DARPA Urban Challenge by : Martin Buehler

Download or read book The DARPA Urban Challenge written by Martin Buehler and published by Springer. This book was released on 2009-11-26 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: By the dawn of the new millennium, robotics has undergone a major transformation in scope and dimensions. This expansion has been brought about by the maturity of the field and the advances in its related technologies. From a largely dominant industrial focus, robotics has been rapidly expanding into the challenges of the human world. The new generation of robots is expected to safely and dependably co-habitat with humans in homes, workplaces, and communities, providing support in services, entertainment, education, healthcare, manufacturing, and assistance. Beyond its impact on physical robots, the body of knowledge robotics has produced is revealing a much wider range of applications reaching across diverse research areas and scientific disciplines, such as: biomechanics, haptics, neurosciences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are proving an abundant source of stimulation and insights for the field of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. The goal of the series of Springer Tracts in Advanced Robotics (STAR) is to bring, in a timely fashion, the latest advances and developments in robotics on the basis of their significance and quality. It is our hope that the wider dissemination of research developments will stimulate more exchanges and collaborations among the research community and contribute to further advancement of this rapidly growing field.

2021 International Conference on Forensics, Analytics, Big Data, Security (FABS)

Author : IEEE Staff
Publisher :
ISBN 13 : 9781665420068
Total Pages : pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis 2021 International Conference on Forensics, Analytics, Big Data, Security (FABS) by : IEEE Staff

Download or read book 2021 International Conference on Forensics, Analytics, Big Data, Security (FABS) written by IEEE Staff and published by . This book was released on 2021-12-21 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 2021 International Conference on Forensics, Analytics, Big Data, Security (FABS 2021) aims to bring together leading academic scientists, Industry Experts, Researchers and research scholars to exchange and share their experiences and research in open research forum to discuss the latest trends in next generation Digital forensics, Analytics, Big Data and Security techniques The thematic areas are thrust areas of Forensics science and Big Data analytics as per FORBES and Mckinsey report 2020 The conference includes eminent researchers as plenary speakers, session chairs and key note speakers Original contributions involving authentic research work, literature reviews are invited

Multi-sensor Fusion for Autonomous Driving

Author : Xinyu Zhang
Publisher : Springer Nature
ISBN 13 : 9819932807
Total Pages : 237 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Multi-sensor Fusion for Autonomous Driving by : Xinyu Zhang

Download or read book Multi-sensor Fusion for Autonomous Driving written by Xinyu Zhang and published by Springer Nature. This book was released on with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Dynamic Vision for Perception and Control of Motion

Author : Ernst Dieter Dickmanns
Publisher : Springer Science & Business Media
ISBN 13 : 1846286387
Total Pages : 490 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Dynamic Vision for Perception and Control of Motion by : Ernst Dieter Dickmanns

Download or read book Dynamic Vision for Perception and Control of Motion written by Ernst Dieter Dickmanns and published by Springer Science & Business Media. This book was released on 2007-06-02 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on autonomous road-following vehicles brings together twenty years of innovation in the field. The book uniquely details an approach to real-time machine vision for the understanding of dynamic scenes, viewed from a moving platform that begins with spatio-temporal representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation techniques.

Robust Environmental Perception and Reliability Control for Intelligent Vehicles

Author : Huihui Pan
Publisher : Springer Nature
ISBN 13 : 9819977908
Total Pages : 308 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Robust Environmental Perception and Reliability Control for Intelligent Vehicles by : Huihui Pan

Download or read book Robust Environmental Perception and Reliability Control for Intelligent Vehicles written by Huihui Pan and published by Springer Nature. This book was released on 2023-11-25 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes. Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy. Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods. Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers. Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account. Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios. Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.

Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles

Author : Alexander Schaub
Publisher : Springer
ISBN 13 : 3658190876
Total Pages : 267 pages
Book Rating : 4.6/5 (581 download)

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Book Synopsis Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles by : Alexander Schaub

Download or read book Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles written by Alexander Schaub and published by Springer. This book was released on 2017-07-18 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Alexander Schaub examines how a reactive instinctive behavior, similar to instinctive reactions as incorporated by living beings, can be achieved for intelligent mobile robots to extend the classic reasoning approaches. He identifies possible applications for reactive approaches, as they enable a fast response time, increase robustness and have a high abstraction ability, even though reactive methods are not universally applicable. The chosen applications are obstacle avoidance and relative positioning – which can also be utilized for navigation – and a combination of both. The implementation of reactive instinctive behaviors for the identified tasks is then validated in simulation together with real world experiments.

Self-Driving Vehicles and Enabling Technologies

Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1838810676
Total Pages : 198 pages
Book Rating : 4.8/5 (388 download)

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Book Synopsis Self-Driving Vehicles and Enabling Technologies by :

Download or read book Self-Driving Vehicles and Enabling Technologies written by and published by BoD – Books on Demand. This book was released on 2021-09-22 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the development and technical progress of self-driving vehicles in the context of the Vision Zero project from the European Union, which aims to eliminate highway system fatalities and serious accidents by 2050. It presents the concept of Autonomous Driving (AD) and discusses its applications in transportation, logistics, space, agriculture, and industrial and home automation.