  With the advent of connected and automated vehicle (CAV) technology, there is
an increasing need to evaluate driver behavior while using such technology. In
this first of a kind study, a pedestrian collision warning (PCW) system using
CAV technology, was introduced in a driving simulator environment, to evaluate
driver braking behavior, in the presence of a jaywalking pedestrian. A total of
93 participants from diverse socio-economic backgrounds were recruited for this
study, for which a virtual network of downtown Baltimore was created. An eye
tracking device was also used to observe distractions and head movements. A Log
logistic accelerated failure time (AFT) distribution model was used for this
analysis, to calculate speed reduction times; time from the moment the
pedestrian becomes visible, to the point where a minimum speed was reached, to
allow the pedestrian to pass. The presence of the PCW system significantly
impacted the speed reduction time and deceleration rate, as it increased the
former and reduced the latter, which proves the effectiveness of this system in
providing an effective driving maneuver, by drastically reducing speed. A jerk
analysis is conducted to analyze the suddenness of braking and acceleration.
Gaze analysis showed that the system was able to attract the attention of the
drivers, as the majority of the drivers noticed the displayed warning. The
familiarity of the driver with the route and connected vehicles reduces the
speed reduction time; gender also can have a significant impact as males tend
to have longer speed reduction time, i.e. more time to comfortably brake and
allow the pedestrian to pass.
