Capturing Customer Profile Enables in-Vehicle User Identification: Design for Data-Based User Behavior Evaluation

  • Julia OrlovskaEmail author
  • Casper Wickman
  • Rikard Söderberg
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 135)


The majority of user-related studies have been focused on finding similarities and discrepancies in different user behavior patterns. User identification therefore plays a critical role for user-related studies. However, the concept of shared vehicles, where various users have different behavioral patterns that can be joined and mixed under the same vehicle ID, brings greater complexity to the process of user differentiation. In order to be able to separate users’ data in shared vehicles, a method for customer profile capturing is proposed. The method design is based on comparisons of every drive cycle to the previously saved data. As a result, this allows with a certain level of likelihood identification of users for every drive cycle. This method design enables the possibility of big data use in more advanced user-related studies.


User identification Customer profile Driver profile User identification data Sensors data Big data User behavior evaluation 


  1. 1.
    Orlovska, J., Wickman, C., Söderberg R.: Big data usage can be a solution for user behavior evaluation: an automotive industry example. In: Procedia CIRP 2018 51st CIRP Conference on Manufacturing Systems (2018)CrossRefGoogle Scholar
  2. 2.
    Orlovska, J., Wickman, C., Söderberg R.: Big data analysis as a new approach for usability attributes evaluation of user interfaces: an automotive industry context. In: Proceedings of the DESIGN 2018 15th International Design Conference (2018)Google Scholar
  3. 3.
    Orr, R.J., Abowd, G.D.: The smart floor: a mechanism for natural user identification and tracking. In: CHI’00 extended abstracts on Human factors in computing systems ACM, pp. 275–276 (2000)Google Scholar
  4. 4.
    Zafarani, R., Tang, L., Liu, H.: User identification across social media. ACM Trans. Knowl. Disc. Data (TKDD) 10(2), 16 (2015)Google Scholar
  5. 5.
    Liu, J., Zhang, F., Song, X., Song, Y.I., Lin, C.Y., Hon, H.W.: What’s in a name?: an unsupervised approach to link users across communities. In: Proceedings of the sixth ACM international conference on Web search and data mining. ACM, pp. 495–504 (2013)Google Scholar
  6. 6.
    Erzin, E., Yemez, Y., Tekalp, A.M., Ercil, A., Erdogan, H., Abut, H.: Multimodal person recognition for human-vehicle interaction. IEEE Multimedia 13(2), 18–31 (2006)CrossRefGoogle Scholar
  7. 7.
    Erdogan, H., Ereil, A., Abut, H.: Experiments on decision fusion for driver recognition. In: Advances for In-Vehicle and Mobile Systems, pp. 1–9. Springer, Boston, MA (2007)Google Scholar
  8. 8.
    Xu, H., Tan, Z.H., Dalsgaard, P., Mattethat, R., Lindberg, B.: A configurable distributed speech recognition system. In: Advances for In-Vehicle and Mobile Systems, pp. 59–70. Springer, Boston, MA (2007)CrossRefGoogle Scholar
  9. 9.
    Lortz, V.B., Kveton, B., Kesavan, V.S., Rathi, S., Rangarajan, A.P.: Intel Corp. User identification and personalized vehicle settings management system. U.S. Patent 9,862,352 (2018)Google Scholar
  10. 10.
    Lee, M., Kwak, H.W., Jang, Y.M., Hwang, B., Lee, S.: Kwungpook National University Industry-Academic Cooperation Foundation. Apparatus and method for enhancing user recognition. U.S. Patent 9,489,574 (2016)Google Scholar
  11. 11.
    Holz, C., Buthpitiya, S., Knaust, M.: Bodyprint: biometric user identification on mobile devices using the capacitive touchscreen to scan body parts. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems. ACM, pp. 3011–3014 (2015)Google Scholar
  12. 12.
    Varaiya, P.: Smart cars on smart roads: problems of control. IEEE Trans. Autom. Control 38(2), 195–207 (1993)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Julia Orlovska
    • 1
    Email author
  • Casper Wickman
    • 2
  • Rikard Söderberg
    • 1
  1. 1.Chalmers University of TechnologyGothenburgSweden
  2. 2.Volvo Car Corporation, Customer Experience CenterGothenburgSweden

Personalised recommendations