Editing Mode choice (section)

==Disaggregate travel demand models==
Travel demand theory was introduced in the appendix on traffic generation.  The core of the field is the set of models developed following work by [[Stan Warner]] in 1962 (Strategic Choice of Mode in Urban Travel:  A Study of Binary Choice).  Using data from the CATS, Warner investigated classification techniques using models from biology and psychology.   Building from Warner and other early investigators, disaggregate demand models emerged.  Analysis is disaggregate in that individuals are the basic units of observation, yet aggregate because models yield a single set of parameters describing the choice behavior of the population.  Behavior enters because the theory made use of consumer behavior concepts from economics and parts of choice behavior concepts from psychology.  Researchers at the [[University of California, Berkeley]] (especially [[Daniel McFadden]], who won a [[Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel|Nobel Prize in Economics]] for his efforts) and the [[Massachusetts Institute of Technology]] ([[Moshe Ben-Akiva]]) (and in MIT associated consulting firms, especially [[Cambridge Systematics]]) developed what has become known as choice models, direct demand models (DDM), Random Utility Models (RUM) or, in its most used form, the multinomial logit model (MNL).

Choice models have attracted a lot of attention and work;  the Proceedings of the [[International Association for Travel Behavior Research]] chronicles the evolution of the models.  The models are treated in modern transportation planning and transportation engineering textbooks.

One reason for rapid model development was a felt need.  Systems were being proposed (especially transit systems) where no empirical experience of the type used in diversion curves was available. Choice models permit comparison of more than two alternatives and the importance of attributes of alternatives.  There was the general desire for an analysis technique that depended less on aggregate analysis and with a greater behavioral content. And there was attraction, too, because choice models have logical and behavioral roots extended back to the 1920s as well as roots in [[Kelvin Lancaster]]’s [[consumer behavior theory]], in [[utility theory]], and in modern [[statistics|statistical]] methods.