  Analyzing and reconstructing driving scenarios is crucial for testing and
evaluating automated vehicles. This research analyzed left turn /
straight-driving conflicts at unprotected intersections by extracting actual
vehicle motion data from a naturalistic driving database collected by the
University of Michigan. Nearly 7,000 Left turn across path opposite direction
(LTAP/OD) events involving heavy trucks and light vehicles were extracted and
used to build a stochastic model of such LTAP/OD scenarios. Statistical
analysis showed that vehicle type is a significant factor, whereas the change
of season seems to have limited influence on the statistical nature of the
conflict. The results can be used to build HAV testing environments to simulate
the LTAP/OD crash cases in a stochastic manner, which is among the top NHTSA
identified priority light-vehicle pre-crash scenarios.
