Full paper |
Simulation Models of Traffic FlowJohn Taplin
|
This paper reviews the range of traffic models, with particular attention
to microsimulation. Although there are major types, there are so many hybrids that it is
difficult to classify them all. The standard way of assigning traffic to a network is to
find a static equilibrium from which no driver would be able to find a quicker route. This
gives fairly good predictions of the link flows resulting from driver choices. Traffic is
loaded on to shortest routes, times are modified by a speed-flow function, leading to
reassignment to more routes, and the solution is iterated until all used routes between
each origin-destination pair take equal time.
An alternative is stochastic user equilibrium, taking explicit account of the variability
of choice. Each route between an O-D pair that does not backtrack is given an initial
share by logit distribution. Again, travel times are modified to take account of
congestion, and there is a somewhat messy iterative process to reach equilibrium.
Curiously, stochastic user equilibrium is as deterministic as 'deterministic user
equilibrium'. A criticism of equilibrium models is that the process of adjustment after a
change to the network may be of more interest than the apparently stable outcome.
Microsimulation has been used for small components of the network but recent models at the
single vehicle level can simulate whole urban networks, using a great deal of computer
power. One uses cellular automata, such that each cell in a spatial lattice is updated
according to its own state and the states of its nearby neighbours at the previous time
step. More conventional microsimulations use simple rule based behaviour. Simulations are
designed not only to show the emergent order but also the impact of incidents which
generate spreading instabilities. Microsimulation is also used to capture the expected
effects of route information, as well as indicating control and routing strategies.