Application of Mathematical Methods to Transportation: Modeling and Analysis

Dear Colleagues,

During the last decade, there has been a remarkable surge in the utilization of mathematical methods to tackle multifaceted issues in transportation systems, ranging from traffic congestion to efficient resource allocation. At present, with the advent of big data, smart cities, and an increased focus on sustainability, the need for advanced mathematical models and rigorous analytical techniques in this domain is more pressing than ever.

This Special Issue aims to consolidate and showcase the latest advancements and innovative applications of mathematical methods in transportation modeling and analysis. It seeks to provide a comprehensive view of how these methods are revolutionizing our understanding and management of modern transportation systems.

The topics of interest for publication include, but are not limited to:

1. Development and application of novel mathematical models for traffic flow prediction and control, including those employing machine learning algorithms.
2. Use of optimization techniques for solving complex problems such as vehicle routing, public transportation scheduling, and multimodal transportation system simulation.
3. Stochastic modeling for analyzing uncertainty and risk in transportation systems, including passenger demand fluctuations, travel time variability, and network resilience.
4. Game theoretical frameworks for studying strategic interactions among stakeholders in transportation markets and networks.
5. Network analysis and graph theory applications for understanding and optimizing the structure and dynamics of transportation networks.
6. Data-driven modeling and statistical analyses for extracting valuable insights from large-scale transportation datasets, including traffic flow patterns, user behavior, and environmental impacts.
7. Simulation-based approaches to assess and compare alternative transportation policies, scenarios, or technologies.
8. Integration of mathematical models with decision support systems to enhance transportation planning and policy formulation at local, regional, and national levels.

Prof. Dr. Gang Ren
Dr. Qi Cao
Guest Editors

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• transportation modeling and analysis
• traffic flow prediction and control
• vehicle routing
• public transportation scheduling
• multimodal transportation system simulation
• passenger demand fluctuations
• travel time variability
• network resilience