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Books on the topic 'Autonomous Driving Systems'

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Author: Grafiati
Published: 9 March 2023

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1

Shi, Weisong, and Liangkai Liu. Computing Systems for Autonomous Driving. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81564-6.

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2

Joseph, Lentin, and Amit Kumar Mondal. Autonomous Driving and Advanced Driver-Assistance Systems (ADAS). Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003048381.

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3

Waschl, Harald, Ilya Kolmanovsky, and Frank Willems, eds. Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-91569-2.

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4

Trimble, Tammy E., Stephanie Baker, Jason Wagner, Wendy Wagner, Lisa Loftus-Otway, Brad Mallory, Susanna Gallun, et al. Implications of Connected and Automated Driving Systems, Vol. 4: Autonomous Vehicle Action Plan. Washington, D.C.: Transportation Research Board, 2018. http://dx.doi.org/10.17226/25292.

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5

Zuev, Sergey, Ruslan Maleev, and Aleksandr Chernov. Energy efficiency of electrical equipment systems of autonomous objects. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1740252.

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When considering the main trends in the development of modern autonomous objects (aircraft, combat vehicles, motor vehicles, floating vehicles, agricultural machines, etc.) in recent decades, two key areas can be identified. The first direction is associated with the improvement of traditional designs of autonomous objects (AO) with an internal combustion engine (ICE) or a gas turbine engine (GTD). The second direction is connected with the creation of new types of joint-stock companies, namely electric joint-stock companies( EAO), joint-stock companies with combined power plants (AOKEU). The energy efficiency is largely determined by the power of the generator set and the battery, which is given to the electrical network in various driving modes. Most of the existing methods for calculating power supply systems use the average values of disturbing factors (generator speed, current of electric energy consumers, voltage in the on-board network) when choosing the characteristics of the generator set and the battery. At the same time, it is obvious that when operating a motor vehicle, these parameters change depending on the driving mode. Modern methods of selecting the main parameters and characteristics of the power supply system do not provide for modeling its interaction with the power unit start-up system of a motor vehicle in operation due to the lack of a systematic approach. The choice of a generator set and a battery, as well as the concept of the synthesis of the power supply system is a problem studied in the monograph. For all those interested in electrical engineering and electronics.
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6

Trimble, Tammy E., Stephanie Baker, Jason Wagner, Myra Blanoo, Wendy Wagner, Lisa Loftus-Otway, Brad Mallory, et al. Implications of Connected and Automated Driving Systems, Vol. 5: Developing the Autonomous Vehicle Action Plan. Washington, D.C.: Transportation Research Board, 2018. http://dx.doi.org/10.17226/25291.

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7

Shi, Weisong, and Liangkai Liu. Computing Systems for Autonomous Driving. Springer International Publishing AG, 2022.

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8

Shi, Weisong, and Liangkai Liu. Computing Systems for Autonomous Driving. Springer International Publishing AG, 2021.

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9

Ziefle, Martina, Houbing Song, Guido Dartmann, Anke Schmeink, and Volker Lücken. Smart Transportation: AI Enabled Mobility and Autonomous Driving. Taylor & Francis Group, 2021.

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10

Ziefle, Martina, Houbing Song, Guido Dartmann, Anke Schmeink, and Volker Lücken. Smart Transportation: AI Enabled Mobility and Autonomous Driving. Taylor & Francis Group, 2021.

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11

DARPA Urban Challenge: Autonomous Vehicles in City Traffic. Springer London, Limited, 2009.

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12

Waschl, Harald, Ilya Kolmanovsky, and Frank Willems. Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions: Development, Testing and Verification. Springer, 2019.

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13

Waschl, Harald, Ilya Kolmanovsky, and Frank Willems. Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions: Development, Testing and Verification. Springer, 2018.

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14

Iagnemma, Karl, Martin Buehler, and Sanjiv Singh. The DARPA Urban Challenge: Autonomous Vehicles in City Traffic. Springer, 2012.

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15

Niles, John, and Bern Grush. End of Driving: Transportation Systems and Public Policy Planning for Autonomous Vehicles. Elsevier, 2018.

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16

End of Driving: Transportation Systems and Public Policy Planning for Autonomous Vehicles. Elsevier, 2018.

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17

Joseph, Lentin, and Amit Kumar Mondal. Autonomous Driving and Advanced Driver-Assistance Systems: Applications, Development, Legal Issues, and Testing. CRC Press LLC, 2021.

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18

Joseph, Lentin, and Amit Kumar Mondal. Autonomous Driving and Advanced Driver-Assistance Systems: Applications, Development, Legal Issues, and Testing. Taylor & Francis Group, 2021.

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19

Joseph, Lentin, and Amit Kumar Mondal. Autonomous Driving and Advanced Driver-Assistance Systems: Applications, Development, Legal Issues, and Testing. Taylor & Francis Group, 2021.

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20

Joseph, Lentin, and Amit Kumar Mondal. Autonomous Driving and Advanced Driver-Assistance Systems: Applications, Development, Legal Issues, and Testing. CRC Press, 2021.

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21

Joseph, Lentin, and Amit Kumar Mondal. Autonomous Driving and Advanced Driver-Assistance Systems: Applications, Development, Legal Issues, and Testing. Taylor & Francis Group, 2021.

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22

Loh, Wulf, and Janina Loh. Autonomy and Responsibility in Hybrid Systems. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190652951.003.0003.

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In this chapter, we give a brief overview of the traditional notion of responsibility and introduce a concept of distributed responsibility within a responsibility network of engineers, driver, and autonomous driving system. In order to evaluate this concept, we explore the notion of man–machine hybrid systems with regard to self-driving cars and conclude that the unit comprising the car and the operator/driver consists of such a hybrid system that can assume a shared responsibility different from the responsibility of other actors in the responsibility network. Discussing certain moral dilemma situations that are structured much like trolley cases, we deduce that as long as there is something like a driver in autonomous cars as part of the hybrid system, she will have to bear the responsibility for making the morally relevant decisions that are not covered by traffic rules.
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23

The Darpa Urban Challenge Autonomous Vehicles In City Traffic. Springer, 2009.

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24

Young, Richard. Critical Analysis of Prototype Autonomous Vehicle Crash Rates: Six Scientific Studies from 2015–2018. SAE International, 2021. http://dx.doi.org/10.4271/9781468603422.

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Will Automated Vehicles be Safer than Conventional Vehicles? One of the critically important questions that has emerged about advanced technologies in transportation is how to test the actual effects of these advanced systems on safety, particularly how to evaluate the safety of highly automated driving systems. Richard Young's Critical Analysis of Prototype Autonomous Vehicle Crash Rates does a deep dive into these questions by reviewing and then critically analyzing the first six scientific studies of AV crash rates.
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25

Pathrose, Plato. ADAS and Automated Driving: A Practical Approach to Verification and Validation. SAE International, 2022. http://dx.doi.org/10.4271/9781468604146.

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The day will soon come when you will be able to verbally communicate with a vehicle and instruct it to drive to a location. The car will navigate through street traffic and take you to your destination without additional instruction or effort on your part. Today, this scenario is still in the future, but the automotive industry is racing to toward the finish line to have automated driving vehicles deployed on our roads. ADAS and Automated Driving: A Practical Approach to Verification and Validation focuses on how automated driving systems (ADS) can be developed from concept to a product on the market for widescale public use. It covers practically viable approaches, methods, and techniques with examples from multiple production programs across different organizations. The author provides an overview of the various Advanced Driver Assistance Systems (ADAS) and ADS currently being developed and installed in vehicles. The technology needed for large-scale production and public use of fully autonomous vehicles is still under development, and the creation of such technology is a highly innovative area of the automotive industry. This text is a comprehensive reference for anyone interested in a career focused on the verification and validation of ADAS and ADS. The examples included in the volume provide the reader foundational knowledge and follow best and proven practices from the industry. Using the information in ADAS and Automated Driving, you can kick start your career in the field of ADAS and ADS.
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26

ELIV 2019. VDI Verlag, 2019. http://dx.doi.org/10.51202/9783181023570.

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Der Bericht ist ausschließlich als PDF-Dokument erschienen! Content Foreword 1 ADAS Seeing With Sound – Next-level 3D ultrasonic sensors based on echolocation 5 N. Knappstein, Toposens, Munich Ensuring the reliability, availability and safety of fully automated and autonomous transport systems through modern system architectures 11 J. Heinrich, A. Braasch, Institut für Qualitäts- und Zuverlässigkeitsmanagement GmbH, Wuppertal; F. Plinke, Institut für Qualitäts- und Zuverlässigkeitsmanagement GmbH, Hamburg ADAS/AD Systems: Efficient Testing & Validation – From data acquisition to data analytics 21 M. Kremer, M. Kreutz, M. Luxen, S. Christiaens, FEV Europe GmbH, Aachen Problems and solution spaces for driver-initiated handover from automatic to manual driving mode 31 J. Klesing, Nexteer Automotive, Auburn Hills, USA; S. Safour, Nexteer Automotive, Paris, France UX User-centred development of a display concept for fully automated driving – A methodical approach 45 L. Gaue...
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27

Brachman, Ronald J., and Hector J. Levesque. Machines like Us. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14299.001.0001.

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How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. It's sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what's happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today's AI systems. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.
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28

Denton, Tom. Automated Driving and Driver Assistance Systems. CRC Press LLC, 2019.

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29

Automated Driving and Driver Assistance Systems. Taylor & Francis Group, 2019.

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30

Denton, Tom. Automated Driving and Driver Assistance Systems. CRC Press LLC, 2019.

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31

Denton, Tom. Automated Driving and Driver Assistance Systems. CRC Press LLC, 2019.

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32

Fahrzeugsicherheit. VDI Verlag, 2019. http://dx.doi.org/10.51202/9783181023648.

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Dieser VDI-Bericht ist ausschließlich als PDF-Dokument erschienen! Inhalt Vorwort 1 R. Schöneburg, Mercedes-Benz AG S. Müller, Technische Universität Berlin Auswirkung automatisierten Fahrens auf die Fahrzeugsicherheit Sicherheit zukünftiger hochautomatischer Fahrzeuge im Mischverkehr – Anforderungen, Lösungskonzepte und Potenzialabschätzungen 3 H. Freienstein, J. Kolatschek, G. A. D‘Addetta, Bosch Research, Vehicle Safety and Automated Driving, Robert Bosch GmbH Erkennung der kognitiven Belastung eines Fahrers anhand von Vitalparametern aus realen Fahrzeugsensoren 21 F. Ripper, K. Mahdi, Joyson Safety Systems Aschaffenburg GmbH, Berlin Injury Risk on Rearward Facing Seats in Frontal Impact – Sled Tests and Simulation in a Generic Test Environment 41 H. Zellmer, A. Soni, S. Schilling, B. Eickhoff, Autoliv B.V. & Co. KG, Elmshorn The individual safety of a car seat as a central element of autonomous driving – A comprehensive study of ATDs and human body models based...
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33

Chan, Chen-Jung, Jörg Ennuschat, Chien-Liang Lee, Yuh-May Lin, and Stefan Storr, eds. Künstliche Intelligenz und Öffentliches Wirtschaftsrecht. Nomos Verlagsgesellschaft mbH & Co. KG, 2022. http://dx.doi.org/10.5771/9783748934950.

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The increasing use of artificial intelligence (AI for short) is bringing about revolutionary changes - including in public commercial law. In this conference volume, many possible applications of artificial intelligence and the associated legal issues are addressed from Taiwanese, Austrian and German perspectives. The reference areas cover diverse topics: the responsibility for AI use in public administration, real laboratories, autonomous driving, the use of AI in agriculture, remote biometric identification systems, social scoring, anti-money laundering, AI use in online gambling, and the EU Commission's draft European Law on Artificial Intelligence. With contributions by Prof. Dr. Chen-Jung Chan, Prof. Dr. Jörg Ennuschat, Jessica Heuser, Johannes Fritsch, Prof. Dr. Chien-Liang Lee, Prof. Dr. Yuh-May Lin, Felix Reimann, Prof. Dr. Stefan Storr and Dr. Matthias Zußner.
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34

Liao, S. Matthew, ed. Ethics of Artificial Intelligence. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190905033.001.0001.

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Featuring seventeen original essays on the ethics of artificial intelligence (AI) by today’s most prominent AI scientists and academic philosophers, this volume represents state-of-the-art thinking in this fast-growing field. It highlights central themes in AI and morality such as how to build ethics into AI, how to address mass unemployment caused by automation, how to avoid designing AI systems that perpetuate existing biases, and how to determine whether an AI is conscious. As AI technologies progress, questions about the ethics of AI, in both the near future and the long term, become more pressing than ever. Should a self-driving car prioritize the lives of the passengers over those of pedestrians? Should we as a society develop autonomous weapon systems capable of identifying and attacking a target without human intervention? What happens when AIs become smarter and more capable than us? Could they have greater than human-level moral status? Can we prevent superintelligent AIs from harming us or causing our extinction? At a critical time in this fast-moving debate, thirty leading academics and researchers at the forefront of AI technology development have come together to explore these existential questions.
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35

Stanton, Neville, Patrick Langdon, and Kirsten M. A. Revell. Designing Interaction and Interfaces for Automated Vehicles: User-Centred Ecological Design and Testing. Taylor & Francis Group, 2021.

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36

Stanton, Neville A., Patrick Langdon, and Kirsten M. A. Revell. Designing Interaction and Interfaces for Automated Vehicles. Taylor & Francis Group, 2021.

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37

Stanton, Neville, Patrick Langdon, and Kirsten M. A. Revell. Designing Interaction and Interfaces for Automated Vehicles: User-Centred Ecological Design and Testing. Taylor & Francis Group, 2021.

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38

Stanton, Neville, Patrick Langdon, and Kirsten M. A. Revell. Designing Interaction and Interfaces for Automated Vehicles: User-Centred Ecological Design and Testing. Taylor & Francis Group, 2021.

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39

Gautney, Heather. The New Power Elite. Oxford University PressNew York, 2022. http://dx.doi.org/10.1093/oso/9780190637446.001.0001.

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Abstract A “remake” of C. Wright Mills’ The Power Elite, this book charts patterns of elite domination amid paradigmatic changes in the structuring of U.S. social institutions and political life since the postwar period that lay bare the essentially corrupt and authoritarian nature of neoliberal capitalism and the power elites behind it. Driven by an inexhaustible pursuit of profits and wealth accumulation, power elites of the last half century conceived of and imposed a new form of global capitalism that has positioned the “free market” as an ultimate political and cultural authority. In the process, they have suppressed policies and rules, social movements, and political organizations that might impede profitability and exacted an unspeakable toll on human and planetary life. Similar to Mills, The New Power Elite elucidates the means through which today’s elites accumulate wealth and power, including the subordination of military and governmental systems, media and culture, and labor, finance, and production to “market imperatives.” It departs from Mills, however, in accounting for major transformations in the political geography of corporations and labor, the rise of finance capital, and role of U.S. imperialism in the structuring of global capitalism. And, unlike Mills, the book argues that while the American State, mass media, and cultural institutions can still operate as a sites of contestation, political, military, and cultural institutions today should not be considered as autonomous from market forces, as their principal function is to serve the interests of capital and operate on its behalf.
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