  In this paper, we extended road-based topological analysis to both nationwide
and urban road networks, and concentrated on a sensitivity study with respect
to the formation of self-organized natural roads based on the Gestalt principle
of good continuity. Both Annual Average Daily Traffic (AADT) and Global
Positioning System (GPS) data were used to correlate with a series of ranking
metrics including five centrality-based metrics and two PageRank metrics. It
was found that there exists a tipping point from segment-based to road-based
network topology in terms of correlation between ranking metrics and their
traffic. To our big surprise, (1) this correlation is significantly improved if
a selfish rather than utopian strategy is adopted in forming the self-organized
natural roads, and (2) point-based metrics assigned by summation into
individual roads tend to have a much better correlation with traffic flow than
line-based metrics. These counter-intuitive surprising findings constitute
emergent properties of self-organized natural roads, which are intelligent
enough for predicting traffic flow, thus shedding substantial insights into the
understanding of road networks and their traffic from the perspective of
complex networks.
  Keywords: topological analysis, traffic flow, phase transition, small world,
scale free, tipping point

Data Analysis, Statistics and Probability;Physics and Society