| Summary: | Indiana University-Purdue University Indianapolis (IUPUI) === Pedestrian Automatic Emergency Braking (PAEB) system for avoiding/mitigating
pedestrian crashes have been equipped on some passenger vehicles. At present,
there are many e orts for the development of common standard for the performance
evaluation of PAEB. The Transportation Active Safety Institute (TASI) at Indiana
University-Purdue University-Indianapolis has been studying the problems and ad-
dressing the concerns related to the establishment of such a standard with support
from Toyota Collaborative Safety Research Center (CSRC). One of the important
components in the PAEB evaluation is the development of standard testing facili-
ties at night, in which 70% pedestrian crash social costs occurs [1]. The test facility
should include representative low-illuminance environment to enable the examination
of sensing and control functions of di erent PAEB systems. This thesis work focuses
on modeling low-illuminance driving environment and describes an approach to recon-
struct the lighting conditions. The goal of this research is to characterize and model
light sources at a potential collision case at low-illuminance environment and deter-
mine possible recreation of such environment for PAEB evaluation. This research is
conducted in ve steps. The rst step is to identify lighting components that ap-
pear frequently on a low-illuminance environment that a ect the performance of the
PAEB. The identi ed lighting components include ambient light, same side/opposite
side light poles, opposite side car headlight. Next step is to collect all potential pedes-
trian collision cases at night with GPS coordinate information from TASI 110 CAR
naturalistic driving study video database. Thirdly, since ambient lighting is relatively random and lack of a certain pattern, ambient light intensity for each potential col-
lision case is de ned and processed as the average value of a region of interest on all
video frames in this case. Fourth step is to classify interested light sources from the
selected videos. The temporal pro le method, which compressing region of interest
in video data (x,y,t) to image data (x,y), is introduced to scan certain prede ned
region on the video. Due to the fact that light sources (except ambient light) impose
distinct light patterns on the road, image patterns corresponding to speci c light
sources can be recognized and classi ed. All light sources obtained are stamped with
GPS coordinates and time information which are provided in corresponding data les
along with the video. Lastly, by grouping all light source information of each repre-
sentative street category, representative light description of each street category can
be generated. Such light description can be used for lighting construction of PAEB
test facility.
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