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

Author

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  • Stefan Voß

    (Institute of Information Systems, University of Hamburg, 20146 Hamburg, Germany)

Abstract

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.

Suggested Citation

  • Stefan Voß, 2023. "Bus Bunching and Bus Bridging: What Can We Learn from Generative AI Tools like ChatGPT?," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9625-:d:1171940
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    References listed on IDEAS

    as
    1. Liang, Jinpeng & Wu, Jianjun & Qu, Yunchao & Yin, Haodong & Qu, Xiaobo & Gao, Ziyou, 2019. "Robust bus bridging service design under rail transit system disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 132(C), pages 97-116.
    2. Liping Ge & Stefan Voß & Lin Xie, 2022. "Robustness and disturbances in public transport," Public Transport, Springer, vol. 14(1), pages 191-261, March.
    3. Chokri Kooli, 2023. "Chatbots in Education and Research: A Critical Examination of Ethical Implications and Solutions," Sustainability, MDPI, vol. 15(7), pages 1-15, March.
    4. Daganzo, Carlos F., 2009. "A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 913-921, December.
    5. Guilherme Francisco Frederico, 2023. "ChatGPT in Supply Chains: Initial Evidence of Applications and Potential Research Agenda," Logistics, MDPI, vol. 7(2), pages 1-9, April.
    6. Bartholdi, John J. & Eisenstein, Donald D., 2012. "A self-coördinating bus route to resist bus bunching," Transportation Research Part B: Methodological, Elsevier, vol. 46(4), pages 481-491.
    7. Otero, Inmaculada & Salgado, Jesús F. & Moscoso, Silvia, 2022. "Cognitive reflection, cognitive intelligence, and cognitive abilities: A meta-analysis," Intelligence, Elsevier, vol. 90(C).
    8. Zhou, Chang & Tian, Qiong & Wang, David Z.W., 2022. "A novel control strategy in mitigating bus bunching: Utilizing real-time information," Transport Policy, Elsevier, vol. 123(C), pages 1-13.
    9. Zack Aemmer & Andisheh Ranjbari & Don MacKenzie, 2022. "Measurement and classification of transit delays using GTFS-RT data," Public Transport, Springer, vol. 14(2), pages 263-285, June.
    10. Viktoriya Degeler & Léonie Heydenrijk-Ottens & Ding Luo & Niels Oort & Hans Lint, 2021. "Unsupervised approach towards analysing the public transport bunching swings formation phenomenon," Public Transport, Springer, vol. 13(3), pages 533-555, October.
    11. Chen, Yao & An, Kun, 2021. "Integrated optimization of bus bridging routes and timetables for rail disruptions," European Journal of Operational Research, Elsevier, vol. 295(2), pages 484-498.
    12. Yajuan Deng & Xiaolei Ru & Ziqi Dou & Guohua Liang, 2018. "Design of Bus Bridging Routes in Response to Disruption of Urban Rail Transit," Sustainability, MDPI, vol. 10(12), pages 1-17, November.
    13. S. Sajikumar & D. Bijulal, 2022. "Zero bunching solution for a local public transport system with multiple-origins bus operation," Public Transport, Springer, vol. 14(3), pages 655-681, October.
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