This paper investigates the effect of headlight type (daytime running lights, high beams, and modulating headlights) and rider color (bright yellow, blue denim, and black clothing and helmet) on the visual conspicuity of a motorcycle to younger (25 to 55 years old) and older drivers (65 and older) of a passenger vehicle in simulated urban and rural environments. Thirty-six participants completed two study drives on the National Advanced Driving Simulator-2. During the drives, participants were presented with six oncoming motorcycles and three leading parked motorcycles, each with a different combination of rider color and headlight type. Participants indicated when each motorcycle was first visible to them by pressing a button on the steering wheel of the driving simulator for different combinations of rider colors and headlight types. Detection distances from the motorcycles to the participant vehicles were recorded and analyzed. Repeated measures of analysis of variance indicated significant main effects of headlight types as well as interaction effects between rider color and headlight type for oncoming motorcycles. Results also revealed significant main effects of driving environments and rider color, and interaction effects among the driving environments, rider color, and age groups of the participants for leading motorcycles. The results revealed the importance of using a modulating headlight and wearing a bright helmet and clothing while riding motorcycles to increase motorcycle conspicuity. These findings can be put into practice in the design of motorcycle conspicuity-related campaigns and interventions, such as encouraging riders to use modulating headlights and to wear appropriate clothing.


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    Title :

    Factors Affecting Drivers' Ability to Detect Motorcycles during Daylight in a Simulated Environment


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2019-04-04




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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