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A Knowledge-Based AI Framework for Mobility as a Service

Author

Listed:
  • Enayat Rajabi

    (Center for Applied Intelligent Systems Research, Halmstad University, 301 18 Halmstad, Sweden
    Shannon School of Business, Cape Breton University, Sydney, NS B1P 6L2, Canada)

  • Sławomir Nowaczyk

    (Center for Applied Intelligent Systems Research, Halmstad University, 301 18 Halmstad, Sweden)

  • Sepideh Pashami

    (Center for Applied Intelligent Systems Research, Halmstad University, 301 18 Halmstad, Sweden)

  • Magnus Bergquist

    (Center for Applied Intelligent Systems Research, Halmstad University, 301 18 Halmstad, Sweden)

  • Geethu Susan Ebby

    (Shannon School of Business, Cape Breton University, Sydney, NS B1P 6L2, Canada)

  • Summrina Wajid

    (Center for Applied Intelligent Systems Research, Halmstad University, 301 18 Halmstad, Sweden)

Abstract

Mobility as a Service (MaaS) combines various modes of transportation to present mobility services to travellers based on their transport needs. This paper proposes a knowledge-based framework based on Artificial Intelligence (AI) to integrate various mobility data types and provide travellers with customized services. The proposed framework includes a knowledge acquisition process to extract and structure data from multiple sources of information (such as mobility experts and weather data). It also adds new information to a knowledge base and improves the quality of previously acquired knowledge. We discuss how AI can help discover knowledge from various data sources and recommend sustainable and personalized mobility services with explanations. The proposed knowledge-based AI framework is implemented using a synthetic dataset as a proof of concept. Combining different information sources to generate valuable knowledge is identified as one of the challenges in this study. Finally, explanations of the proposed decisions provide a criterion for evaluating and understanding the proposed knowledge-based AI framework.

Suggested Citation

  • Enayat Rajabi & Sławomir Nowaczyk & Sepideh Pashami & Magnus Bergquist & Geethu Susan Ebby & Summrina Wajid, 2023. "A Knowledge-Based AI Framework for Mobility as a Service," Sustainability, MDPI, vol. 15(3), pages 1-15, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2717-:d:1055836
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    References listed on IDEAS

    as
    1. Konstantina Arnaoutaki & Efthimios Bothos & Babis Magoutas & Attila Aba & Domokos Esztergár-Kiss & Gregoris Mentzas, 2021. "A Recommender System for Mobility-as-a-Service Plans Selection," Sustainability, MDPI, vol. 13(15), pages 1-27, July.
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    Cited by:

    1. Malene Freudendal-Pedersen & Malene Rudolf Lindberg & Katrine Hartmann-Petersen & Toke Haunstrup Christensen, 2023. "Outgrowing the Private Car—Learnings from a Mobility-as-a-Service Intervention in Greater Copenhagen," Sustainability, MDPI, vol. 15(17), pages 1-19, September.

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