  Rush hour and sustained traffic flows in eight cities are studied using the
IBM Mega Traffic Simulator to understand the importance of road structures and
vehicle acceleration in the prevention of gridlock. Individual cars among the
tens of thousands launched are monitored at every simulation time step using
live streaming data transfer from the simulation software to analysis software
on another computer. A measure of gridlock is the fraction of cars moving at
less than 30% of their local road speed. Plots of this fraction versus the
instantaneous number of cars on the road show hysteresis during rush hour
simulations, indicating that it can take twice as long to unravel clogged roads
as fill them. The area under the hysteresis loop is used as a measure of
gridlock to compare different cities normalized to the same central areas. The
differences between cities, combined with differences between idealized models
using square or triangular road grids, indicate that gridlock tends to occur
most when there are a small number of long roads that channel large fractions
of traffic. These long roads help light traffic flow but they make heavy flows
worse. Increasing the speed on these long roads makes gridlock even worse in
heavy conditions. City throughput rates are also modeled using a smooth ramp up
to a constant vehicle launch rate. Models with increasing acceleration for the
same road speeds show clear improvements in city traffic flow as a result of
faster interactions at intersections and merging points. However, these
improvements are relatively small when the gridlock is caused by long roads
having many cars waiting to exit at the same intersection. In general, gridlock
in our models begins at intersections regardless of the available road space in
the network.
