The simple, time-dependent probability model known as a finite markov chain is described and used to analyzed origin and destination data. Such models have considerable potential for adding meaningful insights into travel behavior on multipurpose trips. These models also generate valuable information for use in the analysis of non- residential trip generation. Linkage parameters can be used to explain spatial variation in the trip attraction of a given nonresidential land use. The markov models add a new dimension to the analysis of household travel behavior. Given sets of socioeconomically homogeneous households, trip length /measured in number of stops/, linkages, and purpose distribution information may be added to the current body of knowledge associated with household travel behavior. There is a spatial connotation that probabilistic models can be given. By using areal units, such as census tracts or traffic analysis zones, in addition to land use or trip purpose to define a given state of the markov process, information as to the spatial distribution of trip ends may be derived.
Abstract