Smart Urban Mobility: When Mobility Systems Meet Smart Data
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Abstract (arXiv)
Cities around the world are expanding dramatically, with urban population growth reaching nearly 2.5 billion people in urban areas and road traffic growth exceeding 1.2 billion cars by 2050. The economic contribution of the transport sector represents 5% of the GDP in Europe and costs an average of US 482.05 billion in the United States. These figures indicate the rapid rise of industrial cities and the urgent need to move from traditional cities to smart cities. This article provides a survey of different approaches and technologies such as intelligent transportation systems (ITS) that leverage communication technologies to help maintain road users safe while driving, as well as support autonomous mobility through the optimization of control systems. The role of ITS is strengthened when combined with accurate artificial intelligence models that are built to optimize urban planning, analyze crowd behavior and predict traffic conditions. AI-driven ITS is becoming possible thanks to the existence of a large volume of mobility data generated by billions of users through their use of new technologies and online social media. The optimization of urban planning enhances vehicle routing capabilities and solves traffic congestion problems, as discussed in this paper. From an ecological perspective, we discuss the measures and incentives provided to foster the use of mobility systems. We also underline the role of the political will in promoting open data in the transport sector, considered as an essential ingredient for developing technological solutions necessary for cities to become healthier and more sustainable.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 May 2020.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2025Privacy-Preserving Federated Learning for Fair and Efficient Urban Traffic Optimizationcited by 0
- 2026diffGHOST: Diffusion based Generative Hedged Oblivious Synthetic Trajectoriescited by 0
- 2026From Mobile Data to Business Insights: An End-to-End Analytics Framework for Large-Scale Urban Mobility Analysis and Decision Supportcited by 0
- 2026From Mobile Data to Business Insights: An End-to-End Analytics Framework for Large-Scale Urban Mobility Analysis and Decision Support3 Jul 2026
- 2026diffGHOST: Diffusion based Generative Hedged Oblivious Synthetic Trajectories11 May 2026
- 2025Privacy-Preserving Federated Learning for Fair and Efficient Urban Traffic Optimization9 Nov 2025