AI-Based Transportation Planning and Operation, Volume II

Dear Colleagues,

With drastic urbanization, cities around the world are facing transportation-induced problems such as congestion, accidents, and air pollution. Transportation planning and operation provides opportunities to satisfy the demand for the movement of people and goods in a safe, economical, convenient, and sustainable manner. Previous studies of transportation planning and operation have depended upon econometrics- or engineering-based modeling, which cannot fully incorporate the power of data-driven or AI-based approaches. Recently, artificial intelligence (AI) technologies, such as deep learning, reinforcement learning, and Bayesian modeling, have provided powerful tools to deal with the complexity and high nonlinearity in the problems of transportation planning and operations. More specifically, AI-based technologies in decision-making, planning, modeling, estimation, and control have facilitated the process of transportation planning and operations. The purpose of this Special Issue is to provide an academic platform to publish high-quality research papers on the applications of innovative AI algorithms to transportation planning and operation. Prospective authors are invited to submit original research and review articles related to the applications of AI or machine learning techniques to transportation planning and operation. The potential topics of interest include but are not limited to the following:

• Big data analytics in transportation
• Data-driven transportation modeling and simulation
• AI-based traffic surveillance
• Traffic operations and management
• Road safety enhancement
• AI-based transportation network design
• Decision-making on transportation issues
• Car sharing technologies
• Pedestrian movement analysis
• Vehicle emission management
• Mobility data analysis for evacuation

Prof. Dr. Keemin Sohn
Guest Editor

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