Undoubtedly, the detection of peripheral objects and pedestrians while driving is an important visual task. However, there are few data that describe the impact of parameters such as headlamp illumination, peripheral angle and target reflectance upon the speed and accuracy with which one can detect peripheral targets. The present paper outlines a framework for the development of a model that predicts reaction times and detection percentages to small targets of varying reflectance, and located at various positions in the field of view. The preliminary model closely matches data from independently-performed field studies using halogen and high intensity discharge headlamp sets having illumination characteristics that conform to North American and European requirements for headlamp beam patterns. The modeling approach discussed in the paper allows characteristics such as the effective field of view to be described. Further, the approach could be extended to incorporate driver age, target size, visual clutter, spectral power distribution, glare and ambient roadway illumination into the model predictions. Such a model could serve as a useful complement to existing models of on-axis (foveal) visual performance in driving context
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