Advancements and Innovations in Smart Transportation
Description
This book is a collection of original peer-reviewed papers presented at the 2025 3rd International Conference on SmartRail, Traffic and Transportation Engineering, which is organized by Fujian University of Technology and Beijing Jiaotong University, and held on October 31-November 2, 2025, in Pingtan Island, China. It delves into key areas of transportation engineering, including Intelligent Transportation, Cooperative Control, Intelligent Rail Transit, Transportation Organization, Advanced Rail Vehicle-Track-Bridge Systems, AI and Big Data Applications in Transportation, Optimization and Control in Intelligent Networks as well as Green and Sustainable Transportation Systems. The book provides valuable insights into the latest advancements and trends in transportation engineering and technology, with a particular emphasis on smart and sustainable transportation. As a comprehensive resource, it serves as an essential reference for professionals, researchers, and students working in the field of transportation engineering and related disciplines.
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Persons
Yanhui Wang received the Ph.D. degree in mining engineering from the University of Science and Technology Beijing (USTB), Beijing, China, in 2003. He is currently working as a Professor with the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing. His research interests include ground-penetrating radar, machine learning, safety science, and real-world applications.
Jia Liming is a professor at Beijing Jiaotong University, a member of the National Carbon Neutrality Technology Expert Committee, a vice president of the China Electrotechnical Society, and a supervisor of the China Intelligent Transportation Association. He was awarded the Special Allowance of the State Council of China, the "Millions of Talent Projects" National candidates, the National Outstanding Scientific and Technical Workers.
Content
A Network-Based SI Model for Event Impact Propagation in Expressway Systems: The Greater Bay Area Case.- Information Provision for Alleviating Traffic Congestion: A Bi-level Approach.- Development of a MATSim-Based Simulation Platform for Shared Autonomous Vehicles (SAV) and Its Application in Supply-Demand Analysis.- Research on Driving Behavior and Directional Sign Settings in Expressway Exit Sections.- WMA-BiGRU-Pixel Attention: A Framework for High-Precision Traffic Flow Prediction.- A Scheme for Mitigating Holiday Congestion on Ramps of Interchange Overpasses.- Rule-Based Multi-Vehicle Lane-Changing Scenario Detection and Parameter Analysis in NDS Data.- Intelligent Traffic Signal Control Using Deep Learning.- Modeling Traffic Dynamics of Bidirectional Bicycle Flow.- Quantifying the Potential Modal Substitution of Ride-Hailing for Public Transit: A Utility-Based Approach in Shenzhen.- A Comprehensive Review of Demand Responsive Transit Research and Practice (2020-2025): Technological Approaches, Model Optimization, and Application.- Road Traffic Congestion Mitigation and Resilience Enhancement.- Asymmetric Congestion Management and Route Optimization at Toll Stations.- Long-Term Expressway Traffic Flow Prediction Model Based on Long Short-Term Memory Neural Network.- An Intelligent Bus Intersection Speed Guidance Model Based on Multi-objective Collaborative Optimization.- Research on the Speed Guidance Effect and Usage Intention of Connected Vehicles at Intersections Under Sparse Traffic Flow--Take Yili Modern Smart Health.- Research on Traffic Volume Prediction Based on the Improved GM (1,1)-LSTM Hybrid Model.- A Hybrid Suburban Railway Passenger Flow Prediction Model: Multi-Scale Causal Dilated Convolution with Spatio-Temporal Attention Network.- Research on Characteristics of Integrated Urban-Rural Passenger Transport Network Considering Travel Impedance.- Research on the Nonlinear Impact of Built Environment on Taxi Origin-destination Ridership.- A Hybrid Approach to Ride-Hailing Demand Prediction Using Temporal Correlation and Attention Mechanisms.- Applications of Large Language Models in Traffic Flow Prediction.- Bilevel Traffic Flow Control Model for Highway Network Based on Deep Reinforcement Learning Under Emergency Events.- Real-time Traffic Guidance for Congested Highway Network based on Macroscopic Fundamental Diagram.- INSGA-II for Multi-objective Intelligent Traffic Control: Fujian-Taiwan HSR Case Study.- Dedicated CAV Lanes on Expressway with On-Ramps: A Simulation-Based Evaluation.- Evaluation of Cross-Modal Data Fusion's Present Situation in Intelligent Transportation Applications.- Space-GAIN: A Framework for Deflection Data Restoration Based on Generative Adversarial Imputation Networks.- Experiments on Multi-UAV Path Planning Using DRL Based on Graph Neural Networks.- Deep Learning Prediction and the MassMotion Platform for Data-Driven Emergency Evacuation Simulation and Bottleneck Identification in Rail Transit Stations.- Development of Highway Interchange Throughput Model by Combination of UAV Data and Microscopic Traffic Simulation.- Odd-Even Grouping Strategy Based Adaptive Fuzzy System and Application of Trafficflow Prediction.- Forecasting Short-Term Passenger Flow in Urban Rail Transit: A Long Short-Term Memory Neural Network with Pearson-Based Feature Selection.- A Game-Theoretic Approach to Cooperative Lane Changing in Mobile Bottleneck Zones.- Research on Ubiquitous Perception Systems for Smart Highways in Complex Traffic Scenarios.- Predictive Imitation Learning Control for Autonomous Vehicles via Deep Neural Networks.- Adaptive Model for Short-term Passenger Flow Prediction in Urban Rail Transit Networks Based on Multi-modal Data Fusion.- Agent-Based MLLM for Intelligent Buoy Analysis on Edge Devices.- Research on Multi-source Data Fusion and Intelligent Identification Mechanism of Abnormal Operating Conditions in Rail Transit Systems.- Analysis of Pedestrian Crossing Patterns in Unsignalized Zebra Crossing Sections.- Detection of Road Debris on Highways Based on Improved YOLOv8-STAM-MFE and ByteTrack.- The Impact of Driver Behavior and Environmental Determinants on Fatal Traffic Accidents at Rural Intersections.- CISRA Dataset: Subjective Risk Assessment for Human-Driven and Automated Vehicles in Cut-In Scenarios.- Time Headway Prediction in Highway Merging Zones Based on Bi-LSTM-Attention.- Fatigue Monitoring for Metro Drivers via Multimodal Deep Learning.- Analysis of the Behavioral Factors of Two-wheeled Electric Vehicles Running Red Lights Based on Multivariate Logit Regression Analysis.- ForkSafeNet: A Real-Time Lightweight Object Detection Method for Forklift Driving Safety.- A Classification Framework for Road Traffic Risk in Icy and Snowy Environments.- Video-Based Machine Learning Approaches for Quantifying Pedestrian Safety in Traffic Intersections.- Safety Evaluation of Quasi-unattended Tunnel Management Systems Using Hierarchical Fuzzy Theory.- FDI Attack Detection of Unmanned Aerial Vehicles in Traffic Scenarios Integrating Kronecker Product.- Study on the Coupling Effect of Different Crowd Interaction Behaviors on Evacuation Efficiency in Subway Stations.- Identifying Driving Risk Considering Multiple Types of Risky Driving Behaviours Based on TKAN Model.- Bayesian Deep Reinforcement Learning for Autonomous Driving with Uncertain Pedestrian Intent.- Numerical Analysis and Composition Ratios Influence Crowds During Emergency Evacuations.- A Study on Differences in Driver Behavior and Risk Perception Under the Influence of Autonomous Vehicles Based on the Random Forest Algorithm.- Driver Keypoint Detection in Traffic Scenarios Based on Human Pose Estimation.- Research on Safe Decision-Making for Highway Scenario Autonomous Driving Based on Deep Reinforcement Learning.- Modeling Crash Risk at Freeway Interchanges Considering Dynamic Traffic Flow Characteristics.- Research on Prediction and Discrimination of Driving Risk Level Based on Extreme Value Theory.- Study on the Impact Characteristics of Slope Photovoltaic Facilities on Drivers' Visual Behavior Under Different Lighting Conditions.- Liability in Autonomous Vehicle Accidents: Decoding the Obligations of the Owner, Manufacturer, and Insurer Comparatively.- Data-driven Cause Analysis of Water Traffic Accidents.