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Symbolic Similarity of Traffic Signals Based on Human Visual Perception

  • Yaping Huang
  • Haiyan WangEmail author
  • Chengqi Xue
  • Xiaozhou Zhou
  • Yiming Shi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (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.

Keywords

Icon similarity Decision-making Traffic signals Visual perception 

Notes

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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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yaping Huang
    • 1
  • Haiyan Wang
    • 1
    Email author
  • Chengqi Xue
    • 1
  • Xiaozhou Zhou
    • 1
  • Yiming Shi
    • 1
  1. 1.School of Mechanical EngineeringSoutheast UniversityNanjingChina

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