Advances and Applications in SmartRail, Traffic, and Transportation Engineering
Description
This book is a collection of the original peer-reviewed conference papers presented at the 2024 2nd International Conference on SmartRail, Traffic, and Transportation Engineering, organized by Chongqing Jiaotong University and Southwest Jiaotong University. The conference will be held on 25-27 October 2024 in Chongqing, China. It covers topics including SmartRail systems, autonomous vehicles, energy efficiency, sustainable transportation, big data in transportation, and machine learning. Speakers discussed innovative technologies and strategies to improve the efficiency, reliability, and safety of rail networks while exploring the opportunities and challenges of integrating autonomous vehicles into existing transportation networks. It provides valuable insights into the latest developments and trends in transportation engineering and technology, with a focus on electrification and sustainable transportation. It serves as a valuable resource for professionals, researchers, and students working in the field.
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An Improved YOLOv9-Based Algorithm for Monitoring Individuals Climbing on Trains at Railway Intermediary Stations.- A YOLOv5-Based Approach for Detecting Train Occupancy Disruption and Pedestrian Intrusion on Railway Tracks.- Mixed Traffic Flow Detection Algorithm Based on Improved YOLOv5.- The Impact of Contraflow Left-turn Lane Design on Arterial Signal Coordination.- Applicability Analysis and Application Research of Variable Speed Limit Strategy on Highways.- Automated Rutting Measurement System Based on Low-Cost RGB-D Sensor for Asphalt Pavement.- A UAV-based Method for Joint Calibration of Roadside Cameras and Millimeter-wave Radar.- Bridging Heterogeneous Gap: A POI Correlation Learning Graph Convolution Network for Traffic Forecasting.- A straight cruising control strategy for intelligent networked vehicles based on signalized intersection guidance partitioning.- RCTracker: An Efficient Roadside Cooperative Tracker for Real-world Smart Transportation.