4.6 Article

Bus Bunching and Bus Bridging: What Can We Learn from Generative AI Tools like ChatGPT?

Journal

SUSTAINABILITY
Volume 15, Issue 12, Pages -

Publisher

MDPI
DOI: 10.3390/su15129625

Keywords

generative artificial intelligence; ChatGPT; Bing; computational logistics; artificial intelligence; public transport; bus bunching; bus bridging

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This paper explores the application of generative AI tools in sustainable passenger transportation, focusing on issues related to disturbances in public transport, such as bus bunching and bus bridging. Generative AI tools appear to provide meaningful insights and provoke a lot of contemplation, although their academic use is still limited.
Regarding tools and systems from artificial intelligence (AI), chat-based ones from the area of generative AI have become a major focus regarding media coverage. ChatGPT and occasionally other systems (such as those from Microsoft and Google) are discussed with hundreds if not thousands of academic papers as well as newspaper articles. While various areas have considerably gone into this discussion, transportation and logistics has not yet come that far. In this paper, we explore the use of generative AI tools within this domain. More specifically, we focus on a topic related to sustainable passenger transportation, that is, the handling of disturbances in public transport when it comes to bus bunching and bus bridging. The first of these concepts is related to analyzing situations where we observe two or more buses of the same line following close to each other without being planned deliberately and the second is related to the case where buses are used to replace broken connections in other systems, such as subways. Generative AI tools seem to be able to provide meaningful entries and a lot of food for thought while the academic use may still be classified as limited.

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