Preliminary Concepts and Application Areas
1.4 Modeling Transportation Systems
socioeconomic characteristics are referred to asmarket segments. In a study of dif- ferent pricing policies, for example, market segments might be defined according to personal or household income. In the case of goods movements, the user charac- teristics of interest typically relate to attributes of the shipping firm, such as sector of economic activity, firm size, type of plant, production cycle, and so on. In the following chapters, market segments are indicated byi.
Characteristics of individual trips are also of interest. Person trips are often de- scribed in terms of the general activities carried out at the origin and destination ends. The pair of activities defines thetrip purpose: home-based work trips, work- based shopping trips, and so on. A whole sequence of purposes (activities) can be associated with a trip chain. The trip purpose is indicated bys.
Other trip characteristics of interest in a particular analysis may include desired arrival or departure times, and mode, among others, for person trips; and consign- ment size, type of goods (time sensitivity, value, etc.) and mode for freight trips.
18 1 Modeling Transportation Systems: Preliminary Concepts and Application Areas
Fig. 1.8 Structure of transportation system models
characteristics typically predicted include the number of trips in the reference period (demand level) and their distribution between different time intervals within the ref- erence period, among different points, different transportation modes, and possible paths. Demand models, described in Chap. 4, can be applied to passenger as well as to freight demand. Travel demand models are usually derived from random utility theory, described in Chap. 3.
Analysis and design of transportation systems require the estimation of present demand and the forecasting of future demand. These estimates and forecasts can be obtained using different sources of information and statistical procedures. To esti- mate present demand, surveys can be conducted, typically by interviewing a sample of users. From such surveys,direct estimatesof the demand can be derived using results from sampling theory. Alternatively, the demand (present or future) can be estimated using models similar to those that are described in Chap. 4.Model-based estimatesrequire that models be specified (i.e., the functional form and the variables are defined), calibrated (i.e., the unknown model coefficients are determined), and validated (i.e., the ability to reproduce available data is verified). Model estimation procedures are presented in Chap. 8.
Assignment models(or network demand–supply interaction models), studied in Chaps. 5 and 6, predict how O-D demand and path flows will use the various ele- ments of the supply system. Assignment models allow the calculation of link flows, that is, the number of users using each link of the network that represents trans- portation supply in the reference period. Furthermore, link flows may affect the performance of particular transportation facilities through congestion, and therefore may affect the input to demand models. The mutual interdependencies of demand, flows, and costs are captured by assignment models and are addressed in Chaps. 5, 6 and 7. The models described in this book are based on general assumptions already introduced in the previous sections of this chapter. They are summarized below.
• Physical and functional delineation of the system. The transportation system is contained within a defined region (study area) and the external area is considered only through its relationships with the analysis system. These relationships are related to both demand (exchange and crossing trips) and supply (transportation infrastructure and services connecting the external area with the analysis system).
• Spatial discretization (zoning).The geographic area is subdivided into discrete subareas (traffic analysis zones) to which the socioeconomic variables are related.
Departure and arrival points of all the trips traveling to or from a zone are assumed to originate from or go to an arbitrary location in the zone known as thezone centroid.
• Identification of relevant transportation services.Only those facilities and/or ser- vices that connect study area traffic zones together, or that connect them with external traffic zones, are explicitly represented and modeled.
Further assumptions about the representation of time include the following.
• Identification of relevant model periods.This refers to the definition of the length of the analysis period, selection of the significant cyclic variations to be modeled, and identification of the corresponding reference or model periods.
• Assumptions about within-period variability. The within-period stationary ap- proach, adopted in Chaps. 2, 4, 5, and 6, assumes that travel demand and sup- ply have constant average characteristics over a period of time long enough to allow stationary conditions to be reached. Under this assumption, the significant variables assume values that are independent of the reference time. Alternatively, within-period dynamic models explicitly represent the variation of supply and some demand dimensions within each reference period. Within-period dynamic models are still at a relatively early stage of development and are discussed in Chap. 7.
• Type of demand–supply interaction.In the equilibrium approach, it is assumed that the system is in anequilibrium configurationin which demand, flows, and costs are mutually consistent. Equilibrium assignment models have been exten- sively studied and are described in Chaps. 6 and 7. Alternatively, it is possible to adopt abetween-period dynamicapproach to modeling demand–supply interac- tion by explicitly representing system evolution over different reference periods.
Models of this type are considered in Chap. 6.
Finally, traditional transportation models are sometimes integrated with models that predictactivity locationandproduction levels. These models differ according to the size of the study area (urban, regional, and national) and the type of activi- ties that are considered as endogenous. For example, they may relate to household location in an urban area or to production levels in different sectors of the economy at a multiregional level. Models that jointly analyze the transportation and activity systems are referred to as land use–transportation interaction models. This class of model is less widely used than transportation system models, and their systematic analysis goes beyond the scope of this book. An example of a model that analyzes various interactions among production levels, economic activity location, and trans- portation is described in Chap. 4, in the context of freight demand models.
20 1 Modeling Transportation Systems: Preliminary Concepts and Application Areas