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Achievements and future priorities of artificial intelligence in transport systems
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2196-5544; 2196-5552
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Ciaran MCNALLY, Páraic CARROLL, Beatriz MARTINEZ-PASTOR, Bidisha GHOSH, Marina EFTHYMIOU and Nikolaos VALANTASIS-KANELLOS (eds), Transport transitions : advancing sustainable and inclusive mobility : Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland - Volume 6: Connected Mobility Ecosystems, Cham : Springer, 2025, Lecture notes in mobility, pp. 41-46, OnlineFirst
[Florence School of Regulation]; [Transport]
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PETROZZIELLO, Elodie, MAROTTA, Alessandro, STĘPNIAK, Marcin, CHEIMARIOTIS, Ilias, LODI, Chiara, Achievements and future priorities of artificial intelligence in transport systems, in Ciaran MCNALLY, Páraic CARROLL, Beatriz MARTINEZ-PASTOR, Bidisha GHOSH, Marina EFTHYMIOU and Nikolaos VALANTASIS-KANELLOS (eds), Transport transitions : advancing sustainable and inclusive mobility : Proceedings of the 10th TRA Conference, 2024, Dublin, Ireland - Volume 6: Connected Mobility Ecosystems, Cham : Springer, 2025, Lecture notes in mobility, pp. 41-46, OnlineFirst, [Florence School of Regulation], [Transport] - https://hdl.handle.net/1814/93801
Abstract
This paper aims at defining future research priorities for artificial intelligence (AI) in transport systems. The point of the departure is the state of the art regarding the application of AI in transport combined with the EU policy needs and the assessment of the recent European projects. The paper presents an overview of the potential benefits that the deployment of AI has for transport. Special focus is put on results of European projects funded within Horizon 2020 Framework Programme. The main achievements of the research have shown that AI can help in the optimisation of applications within the transport means. It can also aid public authorities in improving the overall infrastructure thanks to data gathering and first screening. Further, the deployment of AI is a source of profitable opportunities for various sectors like automotive, software, waterborne, aviation, passenger and freight transport. The final aim of these projects is to boost efficiency, sustainability, and safety by having a human centric AI, aware of every situation it is facing and able of taking prompt decisions. The paper concludes by discussing selected cross-cutting concerns regarding the application of AI in the transport sector. They include definition of software updates for autonomous vehicles’ algorithms, the need for liability regimes and the issue of data scarcity.
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Published online: 11 October 2025
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(c) 2026