Environmental Perception for Automated Vehicles PDF Download

Author: Jae Bum Choi
Publisher:
ISBN: 9783736992665
Category :
Languages : en
Pages : 200

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Book Description

Author: Huihui Pan
Publisher: Springer Nature
ISBN: 9819977908
Category : Technology & Engineering
Languages : en
Pages : 308

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Book Description
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.

Author: Xin Bi
Publisher: Springer Nature
ISBN: 9811580936
Category : Technology & Engineering
Languages : en
Pages : 252

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Book Description
This book focuses on the principles and technology of environmental perception in unmanned systems. With the rapid development of a new generation of information technologies such as automatic control and information perception, a new generation of robots and unmanned systems will also take on new importance. This book first reviews the development of autonomous systems and subsequently introduces readers to the technical characteristics and main technologies of the sensor. Lastly, it addresses aspects including autonomous path planning, intelligent perception and autonomous control technology under uncertain conditions. For the first time, the book systematically introduces the core technology of autonomous system information perception.

Author: Huihui Pan (Of Haerbin gong ye da xue)
Publisher:
ISBN: 9789819977925
Category : Intelligent transportation systems
Languages : en
Pages : 0

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Book Description
"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."--

Author: Muhammad Abdul Haseeb
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
An environment perception system is one of the most critical components of an automated vehicle, which is defined as a vehicle where the driver does not require to monitor the vehicle's behavior and its surroundings during driving. This thesis addresses some of the main challenges in the development of vision-based environment perception methods for automated driving, focusing on railway vehicles. The thesis aims at developing methods for detecting obstacles on the rail tracks in front of a moving train to reduce the number of collisions between trains and various obstacles, thus increasing the safety of rail transport. In the field of autonomous obstacle detection for automated driving, besides recognising the objects on the way, the crucial information for collision avoidance is estimated distances between the vehicle and the recognised objects (e.g. cars, pedestrians, cyclists). With the limited capabilities of current state-of-the-art sensor-based environment perception approaches, it is unrealistic to detect distant objects and estimates the distance to them. Mid-to-long-range obstacle detection system is one of the fundamental requirements for heavy vehicles such as railway vehicles or trucks, due to required long braking distance. However, this problem is unaddressed in the computer vision community. The emphasis of this thesis is on the development of robust and reliable algorithms for real-time vision-based mid-to-long-range obstacle detection. In this thesis, the algorithms for obstacle detection from single cameras were developed and evaluated on images captured from RGB, Thermal and Night-Vision Cameras. The developed algorithms are based on advanced machine/deep learning techniques. The development of machine-learning-based algorithms was supported by a novel mid-to-long-range obstacle detection dataset for railways that is proposed in the thesis, which compiles annotated images with the object class, bounding box, and ground truth distance to the object. The developed novel methods for autonomous long-range obstacle detection, tracking, and distance estimation for railways were evaluated on real-world images, which were recorded in different illumination and weather conditions by the obstacle detection system mounted on a static test-bed set-up on the straight rail track and as well on a moving train. Although the focus is on railways, the developed algorithms are also capable to use for road vehicles, hence evaluated on the images of road-scene captured by a camera mounted on moving cars.

Author: David Fernández-Llorca
Publisher:
ISBN: 9783039434039
Category :
Languages : en
Pages : 752

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Book Description
This book presents the results of the successful Sensors Special Issue on Intelligent Vehicles that received submissions between March 2019 and May 2020. The Guest Editors of this Special Issue are Dr. David Fernández-Llorca, Dr. Ignacio Parra-Alonso, Dr. Iván García-Daza and Dr. Noelia Parra-Alonso, all from the Computer Engineering Department at the University of Alcalá (Madrid, Spain). A total of 32 manuscripts were finally accepted between 2019 and 2020, presented by top researchers from all over the world. The reader will find a well-representative set of current research and developments related to sensors and sensing for intelligent vehicles. The topics of the published manuscripts can be grouped into seven main categories: (1) assistance systems and automatic vehicle operation, (2) vehicle positioning and localization, (3) fault diagnosis and fail-x systems, (4) perception and scene understanding, (5) smart regenerative braking systems for electric vehicles, (6) driver behavior modeling and (7) intelligent sensing. We, the Guest Editors, hope that the readers will find this book to contain interesting papers for their research, papers that they will enjoy reading as much as we have enjoyed organizing this Special Issue.

Author: Markus Maurer
Publisher: Springer
ISBN: 3662488477
Category : Technology & Engineering
Languages : en
Pages : 706

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Book Description
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".

Author: George T. Martin
Publisher: Routledge
ISBN: 1351109936
Category : Business & Economics
Languages : en
Pages : 154

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Book Description
The Autonomous Vehicle (AV) has been strongly heralded as the most exciting innovation in automobility for decades. Autonomous Vehicles are no longer an innovation of the future (seen only in science fiction) but are now being road-tested for use. And yet while the technical and economic success and possibilities of the AV have been widely debated, there has been a notable lack of discussion around the social, behavioural, and environmental implications. This book is the first to address these issues and to deeply consider the environmental and social sustainability outlook for the AV and how it will impact on communities. Environmental and social sustainability are goals unlike those of technical development (a new tool) and economic development (a new investment). The goal of sustainability is development of societies that live well and equitably within their ecological limits. Is it reasonable and desirable that only technical and economic success comprise the swelling AV parade, or should we be looking at the wider impacts on personal well-being, wider society, and the environment? The uptake for AVs looks to be lengthy, disjointed, and episodic, in large measure because it faces a range of known unknown risks. This book assesses the environmental and social sustainability potential for AVs based on their prospective energy use and their impacts on climate change, urban landscapes, public health, mobility inequalities, and individual and social well-being. It examines public attitudes about AV use and its risk of fostering a rebound effect that compromises potential sustainability gains. The book concludes with a discussion of critical issues involved in sustainable AV diffusion.

Author: Daniel Watzenig
Publisher: Springer
ISBN: 3319318950
Category : Technology & Engineering
Languages : en
Pages : 619

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Book Description
The main topics of this book include advanced control, cognitive data processing, high performance computing, functional safety, and comprehensive validation. These topics are seen as technological bricks to drive forward automated driving. The current state of the art of automated vehicle research, development and innovation is given. The book also addresses industry-driven roadmaps for major new technology advances as well as collaborative European initiatives supporting the evolvement of automated driving. Various examples highlight the state of development of automated driving as well as the way forward. The book will be of interest to academics and researchers within engineering, graduate students, automotive engineers at OEMs and suppliers, ICT and software engineers, managers, and other decision-makers.

Author: Tim Fingscheidt
Publisher: Springer Nature
ISBN: 303101233X
Category : Technology & Engineering
Languages : en
Pages : 435

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Book Description
This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence. Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.