  We propose that dangerously driven vehicles take a higher priority in
multiple access for vehicle-to-everything communications (V2X). As more
vehicles communicate, it is one's easy anticipation that the air interface will
be crowded and thus a high magnitude of interference occurs. In response to
this issue, we propose to prioritize the multiple access according to the
driver's risky behavior while driving. Specifically, we build a driving
simulator that aims at capturing the driver's distraction. The level of
distraction will be measured in terms of (i) eye movement and (ii) motion. We
build a number of different traffic scenarios including suburban highway, urban
junction, etc. This research features an open source-based, thus low-cost,
implementation of the driving simulator. Then, we apply the quantified driver's
distraction level to the optimization of V2X multiple access.
