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| Titolo: |
Intelligent Transport Systems : 8th International Conference, INTSYS 2024, Pisa, Italy, December 5–6, 2024, Revised Selected Papers / / edited by Alexander Kocian, Paolo Milazzo, Ana Lúcia Henriques Martins, Mirco Nanni, Luca Pappalardo
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| Pubblicazione: | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Edizione: | 1st ed. 2025. |
| Descrizione fisica: | 1 online resource (XIV, 426 p. 134 illus., 121 illus. in color.) |
| Disciplina: | 005.3 |
| Soggetto topico: | Information technology - Management |
| Computer Application in Administrative Data Processing | |
| Persona (resp. second.): | KocianAlexander |
| MilazzoPaolo | |
| Henriques MartinsAna Lúcia | |
| NanniMirco | |
| PappalardoLuca | |
| Nota di contenuto: | -- Smart technologies. -- Beat trustfully: The correlation between heart rate and a multi-dimensional trust questionnaire. -- Detecting and Locating Stress in Urban Settings with ChillIn. -- Traceability. -- Interoperable Traceability in Supply Chains: A Use Case in Agritech. -- Treemob: Expressive Mobility Data Representation through Tree-based Structures. -- From GPS Traces to Individual Emission Exposure: a Data-Driven Four-Step Process. -- Capacity Vehicle Routing Problem with Time Windows: Simulation tool for Footprint Network Design. -- Chain of Portable Health Folders: A Systematic Literature Review. -- Integrating Metro Infrastructure in Circular Food Supply Chains: A Model for decentralized Quito’s Food Bank Network Redesign. -- Traffic forecasting and control. -- An AutoML Approach for Bike Demand Forecasting and Redistribution. -- Adaptive Stop-Skipping Scheduling Approach Using Reinforcement Learning. -- Machine Learning Approach for Labeling Undetected Planned Trips in Public Transport Operators. -- Reinforcement Learning Algorithms with Graph Convolution Networks for Traffic Signal Control. -- Optimizing Intelligent Transportation Systems with Multi-Agent Reinforcement Learning: A Socio-Economic Impact Assessment. -- Road safety. -- A Mobile Application to secure pedestrians interacting with automated vehicles. -- A Simulation-based Security Benchmarking Approach for Assessing Cooperative Driving Automation (CDA) Applications. -- Regulations and policies. -- Wireless Interference and Regulatory Frameworks for Frequency Allocation in V2X Communication Systems. -- Runtime norms regulation framework for drones’ smart cities applications. -- Autonomous vehicles. -- A Data-Driven Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Traffic Scenarios. -- Federated Learning for Lane-Change Prediction. -- Evaluating Traffic Control Strategies for Autonomous Shuttle In Different AV penetration, Using SUMO Traffic Simulation. -- Adaptive Video Bitrate Allocation for Remotely Operated Vehicles (ROV). -- Model-based analysis for cooperative transportation under uncertainty and threats. -- Experimental Evaluation of Road-Crossing Decisions by Autonomous Wheelchairs against Environmental Factors. -- Impact of Network Delays on Edge-Assisted Platooning Systems in 5G Networks: Addressing Latency Challenges. -- A model-based approach for analysis of data-alteration attacks in co-operative vehicles. -- A Preliminary Approach To Verify Platoon Behaviour Using Execution Traces and Model Checking. |
| Sommario/riassunto: | This book constitutes the proceedings of the 8th International Conference on Intelligent Transport Systems, INTSYS 2024, held in Pisa, Italy, duirng December 5-6, 2024. The 25 full papers presented in this book were carefully reviewed and selected from 60 submissions. The papers are organized in the following topical sections: smart technologies; traceability; traffic forecasting and control; road safety; regulations and policies; autonomous vehicles; model-based analysis for cooperative transportation under uncertainty and threats. |
| Titolo autorizzato: | Intelligent Transport Systems ![]() |
| ISBN: | 3-031-86370-4 |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910993928703321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |