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Read MoreA driver’s response in daytime and nighttime conditions can be evaluated through detailed and scientific approaches that determine the view available to a driver, operator, pedestrian, or other viewer, and analyze the decisions a driver or operator made based on that information. Our expertise in nighttime and daytime visibility establishes the tools and techniques for accurate representation of a driver’s view, and scientific peer reviewed processes for displaying the results to others. These methods and processes are detailed in the following scientific publications, which demonstrate our expertise in daytime and nighttime visibility and driver response.
The potential effect of moonlight is sometimes investigated when the visibility of an object or person in the roadway from a driver’s perspective is an issue. In this paper, methods typically used to quantify visibility were performed during conditions with no moon and with a full moon. The authors reveal the results of this testing about the quantifiable change in visibility distance attributable to added moonlight.
Collision statistics show that more than half of all pedestrian fatalities caused by vehicles occur at night. The recognition of objects at night is a crucial component in driver responses, and in preventing nighttime pedestrian accidents. The authors of this paper build on previous findings and incorporate the responses of drivers to objects in the road at night found in the SHRP-2 naturalistic database.
Driver visibility from commercial vehicles is often an issue in post-accident litigation. It is imperative for an engineer to accurately document the areas of visibility for the driver. This paper outlines procedures for calculating and modeling the driver visibility from commercial vehicles. The authors discuss several techniques which have been used successfully to convey visibility information to adjusters and juries.
Nighttime driving environments contain complex lighting conditions such as forward and signal lighting systems of vehicles, street lighting, and retro reflective markers and signage. This paper discusses processes for creating simulated driving environments by utilizing the realistic manner in which cameras capture complex lighting environments, and combining this imagery with projection mapping techniques that result in a photorealistic environment where variables for different driving scenarios can be changed to create a number of driving environments for testing, evaluating, and visual representation.
Computer simulation of nighttime lighting in urban environments can be complex due to the myriad of light sources present, including vehicle headlamps. Within a lighting simulation, photometric files are often used to simulate light sources such as street lamps and exterior building lights in nighttime environments. This paper examines the validity of using these same photometric file types for the simulation of vehicle headlamps by comparing the light distribution from actual vehicle headlamps to photometric files of these same headlamps.
Nighttime crashes often involve complex lighting conditions. The visibility of an object at night is largely due to the luminance contrast between the object and its background. This difference depends on many factors, one of which is the amount of illumination produced by a vehicle’s headlamps. This paper focuses on a method for digitally modeling a vehicle headlamp, such that the illumination produced by the headlamps can be evaluated.
This paper presents a methodology for generating video realistic computer simulated rain, and the effect rain has on driver visibility. The techniques and methodologies presented in this publication rely on techniques of video tracking and projection mapping that have been previously published. The paper demonstrates that through these methodologies, video realistic simulated rain can be created that accurately represent the driver’s visibility in adverse weather conditions.
Attempting to generate calibrated photographs and video during twilight conditions can be difficult, since the time available to capture the light changes rapidly over time. In contrast, during nighttime conditions, when the sun is no longer contributing light directly or indirectly through the sky dome, matching a specific time of night is not as relevant. This paper presents a methodology for accurately representing dawn and dusk lighting conditions (twilight) through photographs and video recordings.
The fundamental differences between the conventional forms of visualizations, like computer animations and graphics, and Virtual Reality (VR) are subtle. A VR environment can be understood as a series of two-dimensional images, stitched together to be a seamless single 360-degree image. The research presented in this paper compares the conventional methods of representing driver and pedestrian views through animations and visualization with a VR environment of the same content.
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