In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems

Mauro Vallati, Lukáš Chrpa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In recent years, Artificial Intelligence (AI) has been increasingly used in traffic management and control, particularly in the smart city context. However, the vast majority of recent AI-based approaches rely on data-driven black-box models that hinder the ability to understand the behaviour and dynamics that lead to a given output. On the contrary, Good Old-Fashioned Artificial Intelligence approaches that are based on symbolic models, such as automated planning, can provide the transparency and explainability needed in real world applications. This paper focuses on the benefits of using automated planning techniques in Intelligent Transportation Systems (ITS), with a focus on explainability. A case study is presented to demonstrate how the components of an automated planning system can support explainability, the types of explanations that can be obtained, and the way in which such explanations can be generated.
Original languageEnglish
Title of host publicationProceedings of the 26th IEEE International Conference on Intelligent Transportation Systems
Subtitle of host publicationITSC 2023
Publication statusAccepted/In press - 13 Jul 2023
Event26th IEEE International Conference on Intelligent Transportation Systems - Bilbao, Spain
Duration: 24 Sep 202328 Sep 2023
Conference number: 26


Conference26th IEEE International Conference on Intelligent Transportation Systems
Abbreviated titleITSC 2023
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