Intermodal Matching Algorithm Including Public Transportation and Ride-Hailing

  • Conference paper
  • First Online:
Artificial Intelligence Tools and Applications in Embedded and Mobile Systems (ICTA-EMOS 2022)

Part of the book series: Progress in IS ((PROIS))

  • 32 Accesses

Abstract

Mobility in traffic is an often discussed topic in a wide variety of forms. In this chapter, we address the mobility of older people in rural areas by presenting a concept for an algorithm that offers intermodal routes between ride-hailing and public transportation. The algorithm is based on a previously published algorithm for ride-sharing that uses isochrones for detour limitation as a key difference to other solutions and that includes a social metric based on individual preferences as well as filters. We add some improvements, public transportation, and especially the mentioned intermodal option. For simplicity and reasoned for the target group, we limit the number of changes between both ride-hailing and public transportation to one. Regarding the pending implementation, some possibilities to reduce the execution time are discussed. The concept and the planned implementation are done within the REMOBIAS project that addresses mobility in rural areas with the help of an interactive assistant.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Notes

  1. 1.

    https://www.remobias.de

  2. 2.

    https://www.instaride.de

  3. 3.

    https://openrouteservice.org

  4. 4.

    https://nemo-mobilitaet.de

  5. 5.

    https://nemo-mobilitaet.de

  6. 6.

    https://openrouteservice.org

References

  1. Federal Statistical Office: Older people in Germany and the EU, 2016. https://www.bmfsfj.de/resource/blob/113952/83dbe067b083c7e8475309a88da89721/aeltere-menschen-in-deutschland-und-in-der-eu-englisch-data.pdf, Cited 13 Sep 2022.

  2. Küpper, P. (2016). Abgrenzung und Typisierung ländlicher Räume. Johann Heinrich von Thünen-Institut.

    Google Scholar 

  3. Manisalidis, I., Stavropoulou, E., Stavropoulos, A., & Bezirtzoglou, E. (2020). Environmental and health impacts of air pollution: A review. Frontiers in Public Health, 8, 1–2.

    Article  Google Scholar 

  4. Scheelhaase, J., Grimme, W., O’Sullivan, M., Naegler, T., Klötzke, M., Kugler, U., Scheier, B., & Standfuß, T. (2018). Klimaschutz im Verkehrssektor – aktuelle Beispiele aus der Verkehrsforschung. Wirtschaftsdienst, 98(9), 655–663.

    Article  Google Scholar 

  5. Eilers, M., Hempen, S., Frers, S., Stahr, B., Hölscher, N. H., Bürmann, P., Janßen, C., & Marx Gómez, J. (2021). An instant matching algorithm in the context of ride-hailing applications, using isochrones and social scoring. In INFORMATIK 2021. Gesellschaft für Informatik (pp. 103–114). https://doi.org/10.18420/informatik2021-007.

  6. Nils Woitzik. (2007). Das Dial-a-Ride-Problem. https://www.zaik.de/AFS/teachings/ws0708/ORSeminar/aus-arbeitungen/handout_DialARide_NilsWoitzik.pdf. Cited 15 Sep 2022.

  7. Jahns, M., Woisetschläger, D. M., & Seegebarth, B. (2018). Never trust a stranger – Even if (s)he is beautiful? – How attractiveness, gender, and role of associates influence ridesharing intention. In Proceedings of the European Marketing Academy Conference, Glasgow.

    Google Scholar 

  8. Campbell, I., Ali, M. M., & Fienberg, M. L. (2016). Solving the dial-a-ride problem using agent-based simulation. South African Journal of Industrial Engineering, 27, 143–157.

    Article  Google Scholar 

  9. Reise vor9. (2021). LM Group stellt Mobilitätsplattform Qixxit ein. https://www.reisevor9.de/marketing/lm-group-stellt-mobilitaetsplattform-qixxit-ein. Cited 13 Sep 2022.

  10. Nielsen, J. (1994). Usability engineering. Morgan Kaufmann Publishers Inc.

    Google Scholar 

  11. Butenko A., & Marx Gómez, J. (2022). Combined algorithm for Voronoi diagram construction in application to dynamic ride sharing. In MOBILITY 2022: The Twelfth International Conference on Mobile Services, Resources, and Users (pp. 5–8), Porto, Portugal.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sven von Höveling .

Editor information

Editors and Affiliations

Appendix

Appendix

Algorithm 2 Outline of the overall algorithm of the project REMOBIAS

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

von Höveling, S., Theesen, C., Butenko, A., Sasapu, V. (2024). Intermodal Matching Algorithm Including Public Transportation and Ride-Hailing. In: Marx Gómez, J., Elikana Sam, A., Godfrey Nyambo, D. (eds) Artificial Intelligence Tools and Applications in Embedded and Mobile Systems. ICTA-EMOS 2022. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-031-56576-2_22

Download citation

Publish with us

Policies and ethics

Navigation