It is clear as technology and humanity continues to advance, the role
of traffic also grows. As such, we continue to push our understanding of traffic.
We derived an algorithm to predict an individual’s most likely path of travel
from point A to point B by solving a system of differential equations. Data were
collected randomly on a local neighborhood of UNG’s Gainesville Campus about
the different attributes of paths in contrast to the varying driving conditions.
Finally we tested and compared the analytic model with a proposed ideal abstract
graph theoretic model.