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Development of a legibility model and PC software to predict the legibility of text on traffic signs for high luminance and constrast conditions

Vatan, Sahika

Abstract Details

2003, Master of Science (MS), Ohio University, Industrial and Manufacturing Systems Engineering (Engineering).
In recent times there has been an introduction of new and more retroreflective sheeting materials for traffic sign legends and backgrounds. It has been suspected that higher brightness may actually have a detrimental effect on legibility performance when reading traffic signs under automobile headlight illumination at night. The objective of this study is to develop a legibility model and modify a PC software to predict the legibility of text on traffic signs for high luminance and contrast conditions for near minimum size threshold conditions. The legibility model is based on experimental results from a previous study conducted at the ORITE Human Factors and Ergonomics Laboratory at Ohio University, which investigated the nighttime legibility of traffic signs as a function of legend and background luminance. Two functions were derived which when applied to the legend luminance for positive contrast or the background luminance for negative contrast enables us to predict fairly accurately the probability of correct identification for Landolt rings presented in the dark near threshold (visual angle)conditions.
Helmut Zwahlen (Advisor)
167 p.

Recommended Citations

Citations

  • Vatan, S. (2003). Development of a legibility model and PC software to predict the legibility of text on traffic signs for high luminance and constrast conditions [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1175712386

    APA Style (7th edition)

  • Vatan, Sahika. Development of a legibility model and PC software to predict the legibility of text on traffic signs for high luminance and constrast conditions. 2003. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1175712386.

    MLA Style (8th edition)

  • Vatan, Sahika. "Development of a legibility model and PC software to predict the legibility of text on traffic signs for high luminance and constrast conditions." Master's thesis, Ohio University, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1175712386

    Chicago Manual of Style (17th edition)