The low luminance and the monotony of highway tunnels are likely to cause drivers to experience a visual illusion while driving. Drivers tend to underestimate their speed and thus are exposed to a higher risk of relatively severe traffic accidents. Finding a low-cost way to reduce this visual illusion and to improve traffic safety is a challenge for current highway tunnel operations. High-frequency visual information can make a driver overestimate speed; low-frequency visual information may induce a driver to underestimate speed. However, quantitative investigations of the influence of visual information of various frequencies and luminance levels on drivers' speed perception are lacking. This paper describes a driving simulation model created with Autodesk's 3ds Max modeling software and tests carried out with simulators and E-Prime research software. The mechanisms of speed perception and reaction time were studied to consider the effect of visual information with high frequencies and with combined high and low frequencies under different luminance levels (100%, 50%, and 25% of standard luminance). The test results revealed that speed overestimation was caused mainly by high-frequency visual information. This overestimation could be reduced by combining high-frequency visual information with low-frequency visual information. With higher luminance, speed overestimation was lessened and drivers' reaction time was shorter. It is suggested that visual information with combined frequencies be employed to control drivers' illusions of speed and to enhance traffic safety.


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    Title :

    Speed Control Method for Highway Tunnel Safety Based on Visual Illusion


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Wan, Hongliang (author) / Du, Zhigang (author) / Ran, Bin (author) / Wang, Mingnian (author)


    Publication date :

    2015-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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