A GENERAL FRAMEWORK FOR THE INTEGRATION OF A LAND‐USE MODEL WITH A TRANSPORTATION MODEL COMPONENT

Abstract

SUMMARY Integrated land‐use—transportation models are characterized as models in which the redistributive effects of one subsystem upon the other are explicitly defined and incorporated into the model's structure. At the core of integrated models is a linking procedure whose function is to transform the outputs of one model component into inputs for the other. Despite major efforts made in the past to build operational large scale integrated models, the structural properties of such models remain largely unexplored. This paper describes a general framework for an integrated model consisting of prototype model components. These are an iterative activity allocation model of the Garin‐Lowry type, an equilibrium‐assignment transportation network model, and a linking procedure. Given the level of analysis, this framework is shown useful for exploring the analytics of integrated models and, in particular, their equilibrium properties. By means of many simulation experiments based on an hypothetical numerical example, the operation of the model is demonstrated with an emphasis on the locational interpretation of the integration procedure. On the basis of the empirical results and considering the model's intrinsic assumptions, the following major findings can be cited. First, the effects of nontravel factors (such as basic employment and zonal attractions) upon activity distribution are stronger than effects caused by changes in the transportation system. The latter effects were found to yield nonlinear and, spatially, nonuniform changes in activity location which also tended to be larger in peripheral regions. Second, implicit in the specification of the integration procedure are behavioral assumptions regarding time‐lags in locational adjustments made by activities in reaction to rising cost of travel. The present formulation implies that once located, activities do not revise their locational decisions despite substantial increases in travel costs. At the other extreme, all activities are permitted to readjust their locational preferences after the final interzonal travel costs are derived. The effect upon activity distribution of the latter specification is, of course, larger than that of the former, although less than the effect yielded by changes in nontravel factors. Regarding the equilibrium properties of the integrated system, both the theoretical and empirical analyses show that the entire model will converge into an equilibrium solution and that the corresponding trip patterns are also at equilibrium. These results will hold as long as the operation of the integrated models is completely controlled by the generation functions of the land‐use model and the transportation model component only affects the spatial distribution of activities. Finally, the results from the simulation experiments indicate that the computed mean travel cost parameter tends to stabilize around a certain value as the level of demand for travel, within the system, rises. There is evidence that compensating changes in the location and composition of this demand are the main causes of this phenomenon. In light of these findings, it is possible to point to three key problems whose resolution could largely improve the predictive power of integrated models. First, it would be useful to define activity models in which the generation of activities is, among other things, a function of travel conditions. Second, currently formulated integrated models do not contain trip demand functions and, thus, demand for travel by an activity unit is regarded as completely inelastic. Third, different locating activities respond differently—over time and space—to changíng travel conditions, and models should, therefore, reflect explicitly such differences in activity behavior. A recent paper by Los [14], is an important contribution to the analysis of this issue.

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