  We present a model of traffic flow on generic urban road networks based on
cellular automata. We apply this model to an existing road network in the
Australian city of Melbourne, using empirical data as input. For comparison, we
also apply this model to a square-grid network using hypothetical input data.
On both networks we compare the effects of non-adaptive vs adaptive traffic
lights, in which instantaneous traffic state information feeds back into the
traffic signal schedule. We observe that not only do adaptive traffic lights
result in better averages of network observables, they also lead to
significantly smaller fluctuations in these observables. We furthermore compare
two different systems of adaptive traffic signals, one which is informed by the
traffic state on both upstream and downstream links, and one which is informed
by upstream links only. We find that, in general, both the mean and the
fluctuation of the travel time are smallest when using the joint
upstream-downstream control strategy.
