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Effect of vehicle swiveling headlamps and highway geometric design on nighttime sight distance

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  • De Santos-Berbel, César
  • Castro, Maria

Abstract

Sight distance is a fundamental factor in the design of highways as it determines their operational and safety performance, particularly in nighttime. Vehicles are increasingly being equipped with driving assistance systems such as adaptive frontlighting systems, from which potential safety benefits can be derived. One of the main capabilities of adaptive headlights is controlling headlamp swiveling when driving on horizontal curves to light up a greater section of the roadway ahead. In this study, the vehicle headlight beam was recreated to simulate swiveling systems that adapt the headlight beam to the highway geometry. Diverse horizontal spread angle values were assumed for the headlight lighting pattern. Based on horizontal curvature, a total of 24,663 mathematical functions that control the headlight swiveling angle were simulated. Next, headlight sight distance (HSD) was estimated on a 3D virtual model of an in-service highway, under assumptions of fixed and swiveling headlamps. Two types of algorithms were proposed for the swiveling headlights, one based on the trajectory curvature and another one predictive. The sets of HSD results were then analyzed and compared, the effects of the swiveling headlights on HSD being quantified along the highway section studied. In addition, the performance of diverse swiveling headlights was analyzed under different 3D highway alignment combinations. Finally, the robustness of the proposed procedure was validated.

Suggested Citation

  • De Santos-Berbel, César & Castro, Maria, 2020. "Effect of vehicle swiveling headlamps and highway geometric design on nighttime sight distance," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 170(C), pages 32-50.
    • Handle: RePEc:eee:matcom:v:170:y:2020:i:c:p:32-50
    DOI: 10.1016/j.matcom.2019.08.012
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    References listed on IDEAS

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    1. Bagdasar, Ovidiu & Berry, Stuart & O’Neill, Sam & Popovici, Nicolae & Raja, Ramachandran, 2019. "Traffic assignment: Methods and simulations for an alternative formulation of the fixed demand problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 360-373.
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