Making Household Microsimulation of Travel and Activities Accessible to Planners


Joan L. Walker

Document Type

Journal Article

Publication Date


Subject Area

land use - planning, ridership - elasticity


Trip chaining, Travel time, Travel behavior, Transportation policy, Transportation planning, TransCAD (Computer program), Socioeconomic factors, Socioeconomic aspects, Sensitivity analysis, Nevada, Microsimulation, Mathematical models, Journey time, Households, Errors, Elasticity (Economics), Demographics


There is a large gap between the aggregate, trip-based models used by transportation planning agencies and the activity-based, microsimulation methods espoused by those at the forefront of research. The modeling environment presented here is intended to bridge this gap by providing a palatable way for planning agencies to move toward advanced methods. Three components to bridging the gap are emphasized: an incremental approach, a demonstration of clear gains, and a provision of an environment that eases initial implementation and allows for expansion. The modeling environment (called STEP2) is a household microsimulator, developed in TransCAD, that can be used to implement a four-step model as well as models with longer-term behavior and trip chaining. An implementation for southern Nevada is described, and comparisons are made with the region’s aggregate four-step model. The models perform similarly in numerous ways. A key advantage to the microsimulator is that it provides impacts by socioeconomic group (essential for equity analysis) and individual trip movements (for use in a vehicle microsimulator). A sensitivity analysis indicates that the microsimulation model has less inelastic cross elasticity of transit demand with respect to auto travel times than the aggregate model (aggregation error). The trade-off is that microsimulators have simulation error; results are presented regarding the severity of this error. This work shows that a shift to microsimulation does not necessarily require substantial investment to achieve many of the benefits. One of the greatest advantages is a flexible environment that can expand to include additional sensitivity to demographics and transportation policy variables.