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Full Description
This book reflects the latest research trends, methods and experimental results in the field of Artificial Intelligence and Autonomous Transportation, which covers abundant state-of-the-art research theories and ideas. As a vital research area that is highly relevant to current developments in a number of technological domains, the topics covered include Autonomous Transportation Systems, Autonomous Transportation Management and Control Technology, Autonomous Transportation Equipment Technology, Vehicular Networking and Information Security, Emerging Technologies and Future Mobility, Intelligent water transportation technology, Cross-Domain Transportation Technology, and so on. The goal of the proceedings is to provide a major interdisciplinary forum for researchers, engineers, academics, and industry professionals to present the most innovative research and development in the field of Artificial Intelligence and Autonomous Transportation. Engineers and researchers from academia, industry, and government will also explore an insight view of the solutions that combine ideas from multiple disciplines in this area. The volumes serve as an excellent reference work for researchers and graduate students working in the areas of rail transportation, electrical engineering, and information technology.
Contents
A Framework for Autonomous Transportation Systems: A Case Study on Autonomous Vehicles Following Dynamics Simulation.- Anti-collision strategy of stacker and reclaimer based on GJK algorithm.- Research on the Contact Force Characteristics of a Rigid Suspension Pantograph-catenary Based on the Rigid-flexible Coupling Model.- Background Filtering Algorithm for Road Measured LiDAR Based on Cumulative Quantity Comparison.- Adaptive Artificial Potential Field Ship Motion Planning.- Efficient Trajectory Planning in Polar Ice Regions: Enhancing Ship Maneuverability and Path Optimization.- Ship Collision Avoidance Decision-Making Based on Extencive Game Theory:Analysis of the Death Cross Situation.- An Accelerated Two-Stage Motion Planner for Autonomous Parking Using ADMM.- Research on Hybrid Beamforming Based on Manifold Optimization.
