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International Conference on Human Systems Engineering and Design: Future Trends and Applications

IHSED 2019: Human Systems Engineering and Design II pp 341–346Cite as

Symbolic Similarity of Traffic Signals Based on Human Visual Perception

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1026))

Abstract

Icons with identical features convey to users a semantic structure, but a strong visual grouping hint may hinder users from locating interface items. This study took traffic lights as an example to explore the degree to which similarities within a set of icons influence user decisions. The experiment simulated the situation of traffic lights with four types of symbols. Ten participants were asked to respond correctly to the green signal. The behavioral experiment showed that participants have the lowest reaction time to symbols exclusive elements that have no effect on semantics. The relationship between the reaction time and symbolic similarities of those four types of traffic lights was analyzed by the proposed method of computing item similarity. The results showed similarity values were highly consistent with the reaction time. The implications of the results are applicable to design a set of icons that have less effect on the user’s quick recognition.

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Acknowledgments

This work was supported jointly by National Natural Science Foundation of China (no. 71871056), National Natural Science Foundation of China (no. 71471037), Science and Technology on Avionics Integration Laboratory and Aeronautical Science Fund (No. 20185569008).

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Authors and Affiliations

  1. School of Mechanical Engineering, Southeast University, Nanjing, 211189, China

    Yaping Huang, Haiyan Wang, Chengqi Xue, Xiaozhou Zhou & Yiming Shi

Authors
  1. Yaping Huang
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  2. Haiyan Wang
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  3. Chengqi Xue
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  4. Xiaozhou Zhou
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  5. Yiming Shi
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Corresponding author

Correspondence to Haiyan Wang .

Editor information

Editors and Affiliations

  1. Institute for Advanced Systems Engineering, University of Central Florida, Orlando, FL, USA

    Tareq Ahram

  2. University of Central Florida, Orlando, FL, USA

    Waldemar Karwowski

  3. Department of Computer Science, Universität der Bundeswehr München, Neubiberg, Germany

    Stefan Pickl

  4. Université de Reims Champagne Ardenne, Reims Cedex 2, France

    Redha Taiar

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Huang, Y., Wang, H., Xue, C., Zhou, X., Shi, Y. (2020). Symbolic Similarity of Traffic Signals Based on Human Visual Perception. In: Ahram, T., Karwowski, W., Pickl, S., Taiar, R. (eds) Human Systems Engineering and Design II. IHSED 2019. Advances in Intelligent Systems and Computing, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-27928-8_52

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