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    Autonomous Driving

    Technology, Business, and Regulation

    AvJianxin Zhao,Liang Wang

    Inbunden, Engelska, 2027

    1 468 kr

    Slutsåld

    Beskrivning

    Navigate autonomous vehicle technology, business, and regulatory frameworks together Autonomous driving development demands more than clever algorithms. Autonomous Driving: Technology, Business, and Regulation treats autonomy as a systems problem. It links sensing, algorithms, hardware/software platforms, data, vehicle value chains, market structure, commercialization, batteries, safety standards, and legal frameworks. Written by authors from academia and industry, the book gives readers a holistic view of how autonomous-driving systems are built, deployed, financed, and governed. Coverage spans multiple technical topics in autonomous driving, including: localization, perception, prediction, motion planning, end-to-end learning, V2X communication, automotive operating systems and chips, data management, and cloud-based development workflows, etc. The book also examines regional market models and their legal frameworks, value-chain shifts across suppliers and platforms, business models, deployment verticals, EV batteries, the safety frameworks that shape real-world autonomy. Each topic is treated through the book’s central theme: managing uncertainty across technology, business, and regulation. Readers will also find: Detailed treatment of cooperative autonomous driving algorithms and platforms, and their role in future smart mobility infrastructure and transportation coordinationAnalysis of vehicle hardware and software platforms, including E/E architecture, domain controllers, SoCs, AUTOSAR, QNX, middleware, and vehicle-cloud workflowsExamination of investment strategies, value chain, and competitive dynamics shaping the commercial landscape of the autonomous vehicle industryAnalysis of legal frameworks governing autonomous vehicle and its operation across multiple international jurisdictionsDomain-expert perspectives giving readers a concise practitioner view in the industryIntegration of academic research findings with practical engineering and deployment challenges faced by industry practitionersIndustry professionals, graduate students, researchers, investors, and policymakers seeking a clear map of autonomous driving will find this book connects technical depth with the business and regulatory constraints that shape deployment. It equips readers to understand the field as a working ecosystem, not as a single breakthrough technology.

    Produktinformation

    • Utgivningsdatum:2027-01-25
    • Format:Inbunden
    • Språk:Engelska
    • Upplaga:27001
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394340798

    Utforska kategorier

    • Tillverkningsindustri inom Ekonomi och Ledarskap
    • Motorfordon inom Naturvetenskap och teknik
    • Artificiell intelligens inom Data och IT

    Mer om författaren

    Jianxin Zhao, PhD, is a postdoctoral researcher at the Karlsruhe Institute of Technology (KIT). He completed his PhD at the University of Cambridge under Prof. Jon Crowcroft. He is the author of several technical books. He designs and optimizes Applied AI systems. Liang Wang, PhD, is an adjunct professor at University of Helsinki and Chief AI Architect at Nokia Technologies, where he designs and implements advanced analytics systems. He holds an MBA from Aalto University and a PhD from University of Helsinki. Alexey Vinel, PhD, is a professor at the KIT as head of the Cooperative Autonomous Systems group, and the Halmstad University. He conducts research on vehicular communications, cooperative autonomous driving, and smart mobility. He is an IEEE Senior Member.

    Innehållsförteckning

    • ForewordAcknowledgmentsAcronyms1 Introduction 11.1 What This Book Is and Is Not 31.2 On Autonomy Levels 61.3 Embrace the Uncertainty 71.4 On Electric Vehicles 81.5 Autonomous Driving: A Short History 9I. Technology 122 Algorithms: Part 1 132.1 Localization: Sensors 152.2 Route Planning: Global 202.3 Prediction 212.4 Behavior Planning and Reinforcement Learning 332.5 Trajectory Planning 413 Algorithms: Part 2 493.1 Environment Perception 503.2 "Where am I?" 603.3 Object Tracking 693.4 Route Search 723.5 Prediction 753.6 Motion Planning 773.7 End-to-End Autonomous Driving 804 Hardware Platform 854.1 Brief History of Automotive Chips 864.2 E/E Architecture Evolution 884.3 Computation Hardware 914.4 Hardware for Safety 964.5 Snapdragon Computation Platforms 1004.6 Communication Hardware 1025 Software Platform 1075.1 Software Architecture Overview 1085.2 System Software: Hypervisor 1105.3 System Software: Middleware 1125.4 System Software: OS Core 1175.5 Functional Software 1205.6 Application Software 1225.7 Vehicle-Cloud Synergy 1255.8 Case Study: Evolution of Apollo 1266 Data Management 1316.1 Data Ecosystem 1326.2 Data Architectures 1346.3 Data Governance 1376.4 Data Management 1396.5 Case Study: Cloud-Based Data Management 1507 V2X: Cooperative Driving 1577.1 DSRC and C-V2X 1597.2 Application Scenarios 1607.3 Global Efforts on V2X 1637.4 Collaborative Perception 169II. Business and Regulation 1748 Global Market Dynamics 1758.1 US: Fragmented Leadership 1778.2 China: Policy-Driven Innovation at Scale 1818.3 Europe: Regulation-Driven Advancement 1848.4 Hybrid Models 1879 Value Chain and Ecosystem 1899.1 Vehicle Physical Systems 1909.2 Vehicle Communication Infrastructure 2029.3 Domain Controllers 2069.4 Sensors 2099.5 Cloud Services 2119.6 Changing Landscape 21410 Business Models 21710.1 Platform-Based Model 21810.2 Mobility-as-a-Service Model 22010.3 Fleet Ownership Model 22210.4 Subscription Model 22410.5 Data Monetization Model 22510.6 Preventing Model Degradation 22711 Commercialization Tarpit 22911.1 Funding Mechanisms 23111.2 Commercialization Stages 23311.3 Survivors 23911.4 Commercialization Cycles 24311.5 Commercial Alliance Structures 24512 Industry Verticals 24912.1 Autonomous Freight Trucking 25312.2 Autonomous Shuttles 25712.3 Urban Distribution 26012.4 Special Scenarios 26312.5 Robotaxi 26613 Battery 27313.1 Battery as System 2713.2 Raw Materials 27613.3 Cell Components 28013.4 Manufacturing 28413.5 Cost Reduction 28813.6 Recycling 29013.7 Battery Safety 29513.8 Reflection 29814 Safety Standards and Regulations 30114.1 Functional Safety 30314.2 Safety of the Intended Functionality 31614.3 Cybersecurity 319A Autonomous Driving Legal Frameworks of the EU and China: A Comparative Study 323A.1 Legislative Progress Overview 323A.2 Product Approval and Road Operation 327A.3 Liability Attribution 330A.4 Data Governance 336Index 341