Subasish Das – författare
2 686 kr
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1 970 kr
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As transportation networks evolve in scale, complexity, and interdependence, artificial intelligence (AI) has emerged as a core enabler of engineering innovation. Artificial Intelligence in Highway Engineering: Optimizing Infrastructure and Mobility responds to this shift with a focused and technically rigorous investigation of AI-driven methods that are fundamentally redefining the design, operation, and strategic management of highway systems.The volume embraces a truly integrative perspective at the nexus of computational modeling, infrastructure analytics, and transportation engineering to tackle multifaceted, domain-specific challenges. Moving beyond theoretical discourse, it delivers a rich analysis grounded in modern-day practice of how algorithmic models interface with physical assets, the dynamic behaviors of urban environments, and real-world system-level constraints. These insights reveal AI’s capacity to inform long-term infrastructure planning, enable adaptive functionalities, and guide high-stakes decisions in unpredictable operational contexts.Emphasizing practical implementation and scalability, this valuable reference resource equips academic and industry readers alike with actionable knowledge on seamlessly embedding contemporary AI architectures to boost transportation networks’ performance and strengthen their reliability as well as advance smart mobility solutions.
Captures both the physical (infrastructure) and dynamic (mobility) elements of modern highway engineering to enhance environmental sustainability, resilience, and operational efficiencyExplores foundational and next-generation AI models-including Kolmogorov-Arnold Networks (KAN), Mamba, deep learning, and graph neural networks-for predictive analytics and intelligent mobility solutionsDemonstrates applied uses of AI in traffic management, crash risk assessment, connected and automated vehicle technologies, and infrastructure lifecycle optimization through practical, hands-on case studiesIntroduces cutting-edge approaches such as AI-enabled digital twins, explainable AI for transparent decision-making, and agent-based simulations for long-term transportation planningProvides fully open-source datasets and code via a GitHub repository, supporting replicability, clarity, and real-world implementation
1 274 kr
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Artificial Intelligence in Highway Safety provides cutting-edge advances in highway safety using AI. The author is a highway safety expert. He pursues highway safety within its contexts, while drawing attention to the predictive powers of AI techniques in solving complex problems for safety improvement. This book provides both theoretical and practical aspects of highway safety. Each chapter contains theory and its contexts in plain language with several real-life examples. It is suitable for anyone interested in highway safety and AI and it provides an illuminating and accessible introduction to this fast-growing research trend.
Material supplementing the book can be found at https://github.com/subasish/AI_in_HighwaySafety. It offers a variety of supplemental materials, including data sets and R codes.
1 274 kr
Läs direkt efter köp
Artificial Intelligence in Highway Safety provides cutting-edge advances in highway safety using AI. The author is a highway safety expert. He pursues highway safety within its contexts, while drawing attention to the predictive powers of AI techniques in solving complex problems for safety improvement. This book provides both theoretical and practical aspects of highway safety. Each chapter contains theory and its contexts in plain language with several real-life examples. It is suitable for anyone interested in highway safety and AI and it provides an illuminating and accessible introduction to this fast-growing research trend.
Material supplementing the book can be found at https://github.com/subasish/AI_in_HighwaySafety. It offers a variety of supplemental materials, including data sets and R codes.
1 059 kr
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2 387 kr
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2 800 kr
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This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners.
Features
Provides a multidisciplinary and holistic understanding of urban mobility with systematic introductions and discussions of theory, methods, technologies, tools, and applications. Covers a wide range of real-world case studies of urban mobility in practice globally that include data, programming code, and tools. Discusses cutting-edge technologies involved in mobility data analytics. Addresses practical challenges in data collection and the ethical implications of mobility research, which are crucial for professionals in the field. Offers future directions of human mobility research under the big data and artificial intelligence (AI) revolution.Urban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences.
2 807 kr
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This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners.
Features
Provides a multidisciplinary and holistic understanding of urban mobility with systematic introductions and discussions of theory, methods, technologies, tools, and applications. Covers a wide range of real-world case studies of urban mobility in practice globally that include data, programming code, and tools. Discusses cutting-edge technologies involved in mobility data analytics. Addresses practical challenges in data collection and the ethical implications of mobility research, which are crucial for professionals in the field. Offers future directions of human mobility research under the big data and artificial intelligence (AI) revolution.Urban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences.