**Sub-Problem 3b: Using a
Microscopic
Simulation Model**

While the HCM model
for signalized intersections can be used to evaluate the performance of the
U.S. 95/Styner Avenue-Lauder Avenue as we showed in sub-problem 3a, we
should also consider the use of a microscopic simulation model. Why? The HCM model is only an approximate solution for conditions when demand
exceeds capacity. Since it considers only macroscopic conditions, the HCM cannot provide the same level of accuracy as
can a microscopic simulation
model for high demand periods or when the flows from one intersection
interact with the flows from an adjacent intersection.

There are several microscopic simulation models that can
be used for this problem. The application of microscopic simulation is
covered in Chapter 34 of the HCM 2000. You are encouraged to review
this chapter to learn more about some of the advantages and disadvantages of
using microscopic simulation models. Here, we will use one such model,
the CORSIM model developed by the Federal Highway Administration. It should
be emphasized that the CORSIM model is being used here for illustrative
purposes, and other microscopic simulation models are available that would
work equally well.

Microscopic simulation models consider much more detail
than macroscopic models such as the HCM. Individual vehicle
interactions and the detailed operation of traffic controllers are two of
the more important features of these microscopic models. This more
detailed treatment of traffic flow and controller operations allows the
models to consider more directly the oversaturated conditions that we found
in sub-problem 3a. In addition, we can input the traffic flow data for
all four time periods for this problem at once and not have to run several
analyses as we did in sub-problem 3a. The models are also stochastic in
nature, which means they explicitly account for the probabilistic nature of
traffic flow and driver behavior. But there is a cost for this
additional detail: more input data, more time required to ensure
that the model is calibrated for local conditions, and multiple simulations
in order to assure that statistically valid results are obtained.