Advertisement

Impact of Speedometer Forms on Integration Task Performance for Train Driving

Conference paper
  • 879 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1212)

Abstract

Accurate speed control can effectively improve the efficiency of train operation. The advantages and disadvantages of the speed display form directly impact the interaction efficiency and the driver’s correct situational awareness of the train running state. Three kinds of train speedometer forms were designed, and the existing interface was compared with the three types. 28 subjects were selected to carry out four speed control experiments. The results showed that, the response time and accuracy performance were the highest in the case of color highlighting; the response time performance was higher but the accuracy performance was the lowest in the case of graph without numbers; the accuracy was higher but the response time was the lowest in the case of scale sparsity. This study shows that the speed display design should be give priority to color highlighting, while weighting the influences of number highlighting and scale sparsity.

Keywords

Train driving Speedometer form Integration task Eye movement 

References

  1. 1.
    Vuchic, V.R.: Maintaining Performance with Full Automation, vol. 3, pp. 36–39 (2014)Google Scholar
  2. 2.
    Boles, D.B., Wickens, C.D.: Display formatting in information integration and nonintegration tasks. J. Hum. Factors Ergon. Soc. 29(4), 395–406 (1987)CrossRefGoogle Scholar
  3. 3.
    Payne, D.G., Lang, V.A., Blackwell, J.M.: Mixed versus pure display format in integration and nonintegration visual display monitoring tasks. J. Hum. Factors Ergon. Soc. 37(3), 507–527 (1995)CrossRefGoogle Scholar
  4. 4.
    Juanfang, Xu: Car dashboard interface design based on SEEV attention model. J. Mach. Design 12, 119–122 (2016)Google Scholar
  5. 5.
    Xu, J.: Analysis and Research on Cognitive Errors of Digital Interface Information by Eye Tracking. School of Mechanical Engineering Southeast University (2015)Google Scholar
  6. 6.
    Macwhinney, B., James, J.S.S., Schunn, C., et al.: TEP–a system for teaching experimental psychology using E-Prime. J. Behav. Res. Methods, Instrum. Comput. J. Psychon. Soc., Inc. 33(2), 287–296 (2001)Google Scholar
  7. 7.
    Card, S.K., Moran, T.P., Newell, A. (eds.) The Psychology of Human-Computer Interaction. CRC Press, Boca Raton (1983)Google Scholar
  8. 8.
    Wu, X., Xue, C., Zhou, F.: An experimental study on visual search factors of information features in a task monitor-ing interface. In: 17th International Conference on Human- Computer Interaction, pp. 525–536. Springer Press, Los Angeles (2005)Google Scholar
  9. 9.
    Kruger, J.L., Hefer, E., Matthew, G.: Measuring the impact of subtitles on cognitive load: eye tracking and dynamic audio visual texts. In: Conference on Eye Tracking South Africa. ACM, pp. 67–71. ACM Press, South Africa (2013)Google Scholar
  10. 10.
    Goldberg, J.H., Kotval, X.P.: Computer interface evaluation using eye movements: methods and constructs. Int. J. Ind. Ergon. 24(6), 631–645 (1999)CrossRefGoogle Scholar
  11. 11.
    Mayr, U., Kuhns, D., Rieter, M.: Eye movements reveal dynamics of task control. J. Exp. Psychol. Genera. 142(2), 489–509 (2013)CrossRefGoogle Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.State Key Laboratory of Rail Traffic Control and SafetyBeijing Jiaotong UniversityBeijingChina
  2. 2.School of Locomotive and Rolling StockZhengzhou Railway Vocational & Technical CollegeZhengzhouChina

Personalised recommendations