Advertisement

Understanding the Usefulness and Acceptance of Adaptivity in Smart Public Transport

  • Christine KellerEmail author
  • Susann Struwe
  • Waldemar Titov
  • Thomas Schlegel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11596)

Abstract

Adaptive passenger information for enhanced mobility experience may be the next step towards a smart public transport. In our research project, we explored adaptive passenger information and investigated options to increase the intelligibility of adaptive features. We set up an online questionnaire to study the acceptance of adaptivity in public transport information systems. In this paper, we describe our approach to adaptivity in public transport, the design of the questionnaire and we discuss results of our study.

Keywords

Smart public transport Passenger information Adaptive systems 

Notes

Acknowledgements

This work was conducted within the scope of the research project “SmartMMI - model- and context-based mobility information on smart public displays and mobile devices in public transport” and was funded by the German Federal Ministry of Transport and Digital Infrastructure as part of the mFund initiative (Funding ID: 19F2042A). We would like to thank Nadine Vollers for her excellent contribution to the project.

References

  1. 1.
    Abu-Issa, A., et al.: A smart city mobile application for multitype, proactive, and context-aware recommender system. In: 2017 International Conference on Engineering and Technology (ICET), p. 1–5, August 2017.  https://doi.org/10.1109/ICEngTechnol.2017.8308181
  2. 2.
    Alegre, U., Augusto, J.C., Clark, T.: Engineering context-aware systems and applications: a survey. J. Syst. Softw. 117, 55–83 (2016).  https://doi.org/10.1016/j.jss.2016.02.010. http://www.sciencedirect.com/science/article/pii/S0164121216000467CrossRefGoogle Scholar
  3. 3.
    Alt, F., et al.: Designing shared public display networks – implications from today’s paper-based notice areas. In: Lyons, K., Hightower, J., Huang, E.M. (eds.) Pervasive 2011. LNCS, vol. 6696, pp. 258–275. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-21726-5_17CrossRefGoogle Scholar
  4. 4.
    Camacho, T.D., Foth, M., Rakotonirainy, A.: Pervasive technology and public transport: opportunities beyond telematics. IEEE Pervasive Comput. 12(1), 18–25 (2013).  https://doi.org/10.1109/MPRV.2012.61CrossRefGoogle Scholar
  5. 5.
    Camacho, T., Foth, M., Rakotonirainy, A., Rittenbruch, M., Bunker, J.: The role of passenger-centric innovation in the future of public transport. Public Transp. 8(3), 453–475 (2016).  https://doi.org/10.1007/s12469-016-0148-5CrossRefGoogle Scholar
  6. 6.
    Cheverst, K., Davies, N., Mitchell, K., Friday, A.: Experiences of developing and deploying a context-aware tourist guide: the guide project. In: Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, MobiCom 2000, pp. 20–31. ACM, New York (2000).  https://doi.org/10.1145/345910.345916
  7. 7.
    Cheverst, K., Davies, N., Mitchell, K., Friday, A., Efstratiou, C.: Developing a context-aware electronic tourist guide: some issues and experiences. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2000, pp. 17–24. ACM, New York (2000).  https://doi.org/10.1145/332040.332047
  8. 8.
    Chow, V.T.F., et al.: Utilizing real-time travel information, mobile applications and wearable devices for smart public transportation. In: 2016 7th International Conference on Cloud Computing and Big Data (CCBD), pp. 138–144, November 2016.  https://doi.org/10.1109/CCBD.2016.036
  9. 9.
    Davidsson, P., Hajinasab, B., Holmgren, J., Jevinger, Å., Persson, J.A.: The fourth wave of digitalization and public transport: opportunities and challenges. Sustainability 8(12), 1248 (2016).  https://doi.org/10.3390/su8121248CrossRefGoogle Scholar
  10. 10.
    Dey, A.K., Abowd, G.D.: Towards a better understanding of context and context-awareness. In: Computer Human Interaction 2000 Workshop on the What, Who, Where, When, Why and How of Context-Awareness (2000)Google Scholar
  11. 11.
    Paymans, T.F., Lindenberg, J., Neerincx, M.: Usability trade-offs for adaptive user interfaces: ease of use and learnability, pp. 301–303, January 2004.  https://doi.org/10.1145/964442.964512
  12. 12.
    Foth, M., Schroeter, R.: Enhancing the experience of public transport users with urban screens and mobile applications. In: Proceedings of the 14th International Academic MindTrek Conference: Envisioning Future Media Environments, MindTrek 2010, pp. 33–40. ACM, New York (2010).  https://doi.org/10.1145/1930488.1930496
  13. 13.
    Handte, M., Foell, S., Wagner, S., Kortuem, G., Marrón, P.J.: An internet-of-things enabled connected navigation system for urban bus riders. IEEE Internet Things J. 3(5), 735–744 (2016).  https://doi.org/10.1109/JIOT.2016.2554146CrossRefGoogle Scholar
  14. 14.
    Hörold, S., Kühn, R., Mayas, C., Schlegel, T.: Interaktionspräferenzen für personas im öffentlichen personenverkehr. In: Eibl, M. (ed.) Mensch & Computer 2011: überMEDIEN|üBERmorgen, pp. 367–370. Oldenbourg-Verlag, Chemnitz (2011)CrossRefGoogle Scholar
  15. 15.
    Keller, C., Brunk, S., Schlegel, T.: Introducing the public transport domain to the web of data. In: Benatallah, B., Bestavros, A., Manolopoulos, Y., Vakali, A., Zhang, Y. (eds.) WISE 2014. LNCS, vol. 8787, pp. 521–530. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-11746-1_38CrossRefGoogle Scholar
  16. 16.
    Lim, B.Y., Dey, A.K., Avrahami, D.: Why and why not explanations improve the intelligibility of context-aware intelligent systems. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2009, pp. 2119–2128. ACM, New York (2009).  https://doi.org/10.1145/1518701.1519023
  17. 17.
    Oliveira, L., Bradley, C., Birrell, S., Davies, A., Tinworth, N., Cain, R.: Understanding passengers’ experiences of train journeys to inform the design of technological innovations. In: Re: Research - the 2017 International Association of Societies of Design Research (IASDR) Conference, Cincinnati, Ohio, USA, pp. 838–853 (2017)Google Scholar
  18. 18.
    Oliveira, L., Bradley, C., Birrell, S., Tinworth, N., Davies, A., Cain, R.: Using passenger personas to design technological innovation for the rail industry. In: Kováčiková, T., Buzna, Ľ., Pourhashem, G., Lugano, G., Cornet, Y., Lugano, N. (eds.) INTSYS 2017. LNICST, vol. 222, pp. 67–75. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-93710-6_8CrossRefGoogle Scholar
  19. 19.
    Sahibzada, H., Hornecker, E., Echtler, F., Fischer, P.T.: Designing interactive advertisements for public displays. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI 2017, pp. 1518–1529. ACM, New York (2017).  https://doi.org/10.1145/3025453.3025531
  20. 20.
    Schlegel, T., Keller, C.: Model-based ubiquitous interaction concepts and contexts in public systems. In: Jacko, J.A. (ed.) HCI 2011. LNCS, vol. 6761, pp. 288–298. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-21602-2_32CrossRefGoogle Scholar
  21. 21.
    Schneider-Hufschmidt, M., Malinowski, U., Kuhme, T. (eds.): Adaptive User Interfaces: Principles and Practice. Elsevier Science Inc., New York (1993)Google Scholar
  22. 22.
    Tumas, G., Ricci, F.: Personalized mobile city transport advisory system. In: Höpken, W., Gretzel, U., Law, R. (eds.) Information and Communication Technologies in Tourism 2009, pp. 173–183. Springer, Vienna (2009).  https://doi.org/10.1007/978-3-211-93971-0_15CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Christine Keller
    • 1
    Email author
  • Susann Struwe
    • 2
  • Waldemar Titov
    • 1
  • Thomas Schlegel
    • 1
  1. 1.Institute of Ubiquitous Mobility SystemsKarlsruhe University of Applied SciencesKarlsruheGermany
  2. 2.TTI GmbH - IBIZKarlsruheGermany

Personalised recommendations