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Smart city article details

Title Artificial Intelligence-Based Decision Support System For Sustainable Urban Mobility
ID_Doc 10555
Authors Shulajkovska M.; Smerkol M.; Noveski G.; Bohanec M.; Gams M.
Year 2024
Published Electronics (Switzerland), 13, 18
DOI http://dx.doi.org/10.3390/electronics13183655
Abstract As urban populations rise globally, cities face increasing challenges in managing urban mobility. This paper addresses the question of identifying which modifications to introduce regarding city mobility by evaluating potential solutions using city-specific, subjective multi-objective criteria. The innovative AI-based recommendation engine assists city planners and policymakers in prioritizing key urban mobility aspects for effective policy proposals. By leveraging multi-criteria decision analysis (MCDA) and ±1/2 analysis, this engine provides a structured approach to systematically and simultaneously navigate the complexities of urban mobility planning. The proposed approach aims to provide an open-source interoperable prototype for all smart cities to utilize such recommendation systems routinely, fostering efficient, sustainable, and forward-thinking urban mobility strategies. Case studies from four European cities—Helsinki (tunnel traffic), Amsterdam (bicycle traffic for a new city quarter), Messina (adding another bus line), and Bilbao (optimal timing for closing the city center)—highlight the engine’s transformative potential in shaping urban mobility policies. Ultimately, this contributes to more livable and resilient urban environments, based on advanced urban mobility management. © 2024 by the authors.
Author Keywords artificial intelligence; decision support; recommendation systems; smart city


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