摘要：Evaluation of the conspicuity of
roadway environments for their environmental impact on driving performance is
vital for roadway safety. Existing meters and tools for roadway measurements
cannot record light and geometry data simultaneously in a high resolution. This
study introduced a new method that adopted recently developed high dynamic
range (HDR) photogrammetry to measure the luminance and XYZ coordinates of
millions of points across a road scene with
the same device—a camera, and a MatLab code for data treatment and
visualization. To validate this method, the roadway environments of a straight
and flat section of Jayhawk Boulevard (482.8 m long) at Lawrence, KS and a
roundabout (15.3 m in diameter) at its end were measured under clear and cloudy
sky in the daytime and at nighttime with dry and wet pavements. Eight HDR
images of the roadway environments under different viewing conditions were
generated using the HDR photogrammetric techniques and calibrated. From each
HDR image, synchronous light and geometry data were extracted in Radiance and
further analyzed to identify potential roadway environmental hazards using the
MatLab code (http://people.ku.edu/~h717c996/research.html). The HDR photogrammetric
measurement with current equipment had a margin of errors for geometry
measurement that varied with the measuring distance, averagely 23.1% - 27.5%
for the Jayhawk Boulevard and 9.3% - 16.2% for the roundabout. The accuracy of
luminance measurement was proven in the literature as averagely 1.5% - 10.1%.
The camera-aided measurement is fast, non-contact, non-destructive, and off the
road, thus, it is deemed more efficient and safer than conventional ways using
meters and tools. The HDR photogrammetric techniques with current equipment
still need improvements on accuracy and speed of the data treatment.
关键词：Measurement; Geometry; Light; Roadway Environment; High Dynamic Range Photogrammetry
