  A better understanding of interactive pedestrian behavior in critical traffic
situations is essential for the development of enhanced pedestrian safety
systems. Real-world traffic observations play a decisive role in this, since
they represent behavior in an unbiased way. In this work, we present an
approach of how a subset of very considerable pedestrian-vehicle interactions
can be derived from a camera-based observation system. For this purpose, we
have examined road user trajectories automatically for establishing temporal
and spatial relationships, using 110h hours of video recordings. In order to
identify critical interactions, our approach combines the metric
post-encroachment time with a newly introduced motion adaption metric. From
more than 11,000 reconstructed pedestrian trajectories, 259 potential scenarios
remained, using a post-encroachment time threshold of 2s. However, in 95% of
cases, no adaptation of the pedestrian behavior was observed due to avoiding
criticality. Applying the proposed motion adaption metric, only 21 critical
scenarios remained. Manual investigations revealed that critical pedestrian
vehicle interactions were present in 7 of those. They were further analyzed and
made publicly available for developing pedestrian behavior models3. The results
indicate that critical interactions in which the pedestrian perceives and
reacts to the vehicle at a relatively late stage can be extracted using the
proposed method.
