Intelligent Transport Systems : 8th International Conference, INTSYS 2024, Pisa, Italy, December 5-6, 2024, Revised Selected Papers (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering)

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Intelligent Transport Systems : 8th International Conference, INTSYS 2024, Pisa, Italy, December 5-6, 2024, Revised Selected Papers (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 426 p.
  • 言語 ENG
  • 商品コード 9783031863691
  • DDC分類 388.312

Full Description

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.

Contents

.- 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.

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