Transportation planning historically has followed the Rational Planning model of Defining Goals and Objectives, Identifying Problems, Generating Alternatives, Evaluating Alternatives, and Developing the Plan. Other models for planning include Rational actor, Satisficing, Incremental planning, Organizational process, and Political bargaining.
Within the rational planning framework, transportation forecasts have traditionally followed the four step procedure, first implemented on mainframe computers in the 1950s at the Detroit Area Transportation Study and Chicago Area Transportation Study.
The four steps are: ;Trip Generation : How many trips of what purpose are being made, as a function of household demographics and land uses
;Trip Distribution : Matching origins with destinations, often using a gravity model function, equivalent to an entropy maximizing model. Older models include the fratar model.
;Route Assignment : Determining what route trips take. Often Wardrop's principle of user equilibrium is applied (equivalent to a Nash equilibrium), wherein each traveler chooses the shortest (travel time) path, subject to every other driver doing the same. The difficulty is that travel times are a function of demand, while demand is a function of travel time.
The sequential and aggregate nature of transportation forecasting has come under much criticism. While improvements have been made, in particular giving an activity-base to travel demand, much remains to be done. In the 1990s most federal investment in model research went to the Transims project at Los Alamos National Laboratory, giving physicists a crack at the problem (in a scary bit of defense conversion). While the use of supercomputers and the detailed simulations may be an improvement on practice, they have yet to be shown to be better (more accurate) than conventional models. The government sold the rights to redistribute Transims to a national consultancy KPMG rather than make it open source.