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Automatic Optimization of Wayfinding Design.

Haikun Huang, Ni-Ching Lin, Lorenzo Barrett

    IEEE Transactions on Visualization and Computer Graphics
    |October 14, 2017
    PubMed
    Summary
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    This study introduces Way to Go!, an automated approach for generating optimized wayfinding sign designs. It significantly reduces design time for virtual and real-world navigation by considering human factors.

    Area of Science:

    • Computer Science
    • Human-Computer Interaction
    • Urban Planning

    Background:

    • Wayfinding signage is crucial for navigation in both virtual and real-world environments.
    • Manual design of wayfinding systems is complex, time-consuming, and challenging due to numerous navigation scenarios and human behavior.
    • Current methods for creating wayfinding designs can take years for typical layouts.

    Purpose of the Study:

    • To introduce an automated approach, Way to Go!, for generating optimized wayfinding designs.
    • To address the inefficiencies and complexities associated with manual wayfinding design.
    • To provide designers with a tool that considers human navigation factors and optimizes sign placement.

    Main Methods:

    • The Way to Go! approach automatically generates wayfinding designs based on specified navigation scenarios.

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  • It optimizes sign placement by considering human agents' visibility and potential for navigational errors.
  • The system was demonstrated and evaluated on diverse layouts including a train station, downtown area, and canyon.

    • Main Results:

    • The automated approach effectively generates optimized wayfinding designs for various complex layouts.
    • Evaluations show that the generated designs guide pedestrians more effectively and efficiently than conventional methods.
    • The system aids in visualizing destination accessibility and identifying/correcting navigation "blind zones".

    Conclusions:

    • The Way to Go! approach offers a significant improvement over manual wayfinding design processes.
    • Automated generation leads to more effective and efficient pedestrian navigation in diverse environments.
    • This method enhances the usability of architectural spaces and virtual environments by optimizing signage.