Skip to main content

A Case-Study for a Human-Centered Approach to Traffic Management Systems

  • 719 Accesses

Part of the Communications in Computer and Information Science book series (CCIS,volume 1583)


Autonomous traffic management (ATM) allows autonomous vehicles to cooperate and can thus lead to an increased traffic efficiency, enhanced traffic safety and decreased ecological footprint of traffic. For the adoption of autonomous vehicles (AVs), humans have to accept and trust them, but so far, the research field of ATM has focused mainly on the aspired safety and efficiency gain instead of an increase in trust and user acceptance of the technology. In this paper, we discuss the need for a human-centered approach for ATM.

For demonstration purposes we designed a turning scenario at an urban intersection with just AVs. The traffic scenario was then simulated with the traffic simulation package SUMO. We implemented a simple ATM system that can interact and manage the behavior of the traffic participants. We present the results of the traffic simulation and the proposed ATM and discuss why the human factors perspective should be considered for the design of ATM. We argue how a human-centered ATM could be used to find a good trade-off between safe and efficient traffic and a comfortable and trustworthy user experience.


  • Traffic management systems
  • Autonomous vehicles
  • Human-centered design
  • Traffic simulations

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-031-06394-7_34
  • Chapter length: 8 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
USD   84.99
Price excludes VAT (USA)
  • ISBN: 978-3-031-06394-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   109.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.


  1. Alam, M., Ferreira, J., Fonseca, J.: Intelligent transportation systems. In: Studies in Systems, Decision and Control (2016)

    Google Scholar 

  2. Dimitrakopoulos, G., Demestichas, P.: Intelligent transportation systems. IEEE Veh. Technol. Mag. 5(1), 77–84 (2010)

    CrossRef  Google Scholar 

  3. Wagner, P.: Traffic control and traffic management in a transportation system with autonomous vehicles. In: Maurer, M., Gerdes, J.C., Lenz, B., Winner, H. (eds.) Autonomous Driving, pp. 301–316. Springer, Heidelberg (2016).

    CrossRef  Google Scholar 

  4. El Hamdani, S., Benamar, N.: Autonomous traffic management: open issues and new directions. In: 2018 International Conference on Selected Topics in Mobile and Wireless Networking (MoWNeT), pp. 1–5. IEEE, June 2018

    Google Scholar 

  5. Rida, N., Ouadoud, M., Hasbi, A.: Traffic signal control for a single intersection-based intelligent transportation system. In: Digital Transformation and Innovative Services for Business and Learning, pp. 159–180. IGI Global (2020)

    Google Scholar 

  6. Koopmann, B., Puch, S., Ehmen, G., Fränzle, M.: Cooperative maneuvers of highly automated vehicles at urban intersections: a game-theoretic approach. In: VEHITS, pp. 15–26 (2020)

    Google Scholar 

  7. Lee, J.D., See, K.A.: Trust in automation: designing for appropriate reliance. Hum. Factors 46(1), 50–80 (2004)

    CrossRef  MathSciNet  Google Scholar 

  8. Nastjuk, I., Herrenkind, B., Marrone, M., Brendel, A.B., Kolbe, L.M.: What drives the acceptance of autonomous driving? An investigation of acceptance factors from an end-user’s perspective. Technol. Forecast. Soc. Chang. 161, 120319 (2020)

    CrossRef  Google Scholar 

  9. Scherer, S., Dettmann, A., Hartwich, F., Pech, T., Bullinger, A.C., Wanielik, G.: How the driver wants to be driven-modelling driving styles in highly automated driving. In: 7. Tagung Fahrerassistenzsysteme (2015)

    Google Scholar 

  10. Yusof, N.M., Karjanto, J., Terken, J., Delbressine, F., Hassan, M.Z., Rauterberg, M.: The exploration of autonomous vehicle driving styles: preferred longitudinal, lateral, and vertical accelerations. In: Proceedings of the 8th International Conference On Automotive User Interfaces and Interactive Vehicular Applications, pp. 245–252, October 2016

    Google Scholar 

  11. Hamed, M.M., Easa, S.M., Batayneh, R.R.: Disaggregate gap-acceptance model for unsignalized T-intersections. J. Transp. Eng. 123(1), 36–42 (1997)

    CrossRef  Google Scholar 

  12. Ragland, D.R., Arroyo, S., Shladover, S.E., Misener, J.A., Chan, C.Y.: Gap acceptance for vehicles turning left across on-coming traffic: implications for (2005)

    Google Scholar 

  13. Yan, X., Radwan, E., Guo, D.: Effects of major-road vehicle speed and driver age and gender on left-turn gap acceptance. Accid. Anal. Prev. 39(4), 843–852 (2007)

    CrossRef  Google Scholar 

  14. Radwan, E., Guo, D.: Effects of major-road vehicle speed and driver age and gender on left-turn gap acceptance. Accid. Anal. Prev. 39, 843–52 (2007).

    CrossRef  Google Scholar 

  15. Hartwich, F., Beggiato, M., Krems, J.F.: Driving comfort, enjoyment and acceptance of automated driving-effects of drivers’ age and driving style familiarity. Ergonomics 61(8), 1017–1032 (2018)

    CrossRef  Google Scholar 

  16. Drewitz, U., et al.: Towards user-focused vehicle automation: the architectural approach of the autoakzept project. In: Krömker, H. (ed.) HCII 2020. LNCS, vol. 12212, pp. 15–30. Springer, Cham (2020).

    CrossRef  Google Scholar 

  17. Trende, A., Gräfing, D., Weber, L.: Personalized user profiles for autonomous vehicles. In: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings, pp. 287–291, September 2019

    Google Scholar 

  18. Krajzewicz, D., Hertkorn, G., Rössel, C., Wagner, P.: SUMO (Simulation of Urban MObility)-an open-source traffic simulation. In: Proceedings of the 4th Middle East Symposium on Simulation and Modelling (MESM 2002), pp. 183–187 (2002)

    Google Scholar 

Download references


This work was supported by the DFG-grants RI 1511/3-1 to JWR, LU 1880/3-1 to AT (both “Learning from Humans – Building for Humans”) and FR 2715/4-1 (“Integrated Socio-technical Models for Conflict Resolution and Causal Reasoning”) to MF.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Alexander Trende .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Trende, A., Krefting, I., Unni, A., Rieger, J., Fränzle, M. (2022). A Case-Study for a Human-Centered Approach to Traffic Management Systems. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2022 Posters. HCII 2022. Communications in Computer and Information Science, vol 1583. Springer, Cham.

Download citation

  • DOI:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06393-0

  • Online ISBN: 978-3-031-06394-7

  • eBook Packages: Computer ScienceComputer Science (R0)