Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
development, neo- traditional neighborhood develop- ment, and new transit, bicycle, and pedestrian facilities and services; and ⢠Alternative work and school arrangements such as satellite or home- based telecommuting, flexible work hours, and distance- learning classes. Travel demand models should be able to provide quantifiable impact measures, by market segment, that address issues such as market equity, social exclusion, environmental justice, quality of life, and environmental (emissions) impacts of policy measures. Some of the policies identified here can be reflected by adjusting a modal level- of- service variable associated with one or more facilities. For example, a new toll on a bridge can be reflected by imposing a cost on the specific highway links that represent the bridge. Other policies may be subtler and may not be as easy to capture or in a model. For example, how does one represent a flexible work hour policy to reflect its impacts on travel behav- ior? Potentially, activity- based travel demand models that include consideration of work constraints, flexibil- ity and rigidity of different activities, and activity inter- dependencies would be able to accommodate the effects of a flex work hour policy. Consideration of New Technologies Technology is playing an increasingly bigger role in shap- ing human activity patterns, residential and work loca- tion choices, travel behavior, use of time, and freight logistics. The interactions between technology and travel behavior are closely intertwined with peopleâs use of time. On the one hand, technology may substitute for travel while, on the other hand, technology may comple- ment or lead to more (spontaneous) travel. Similarly, there are new transportation technologies including trav- eler information and guidance and navigation systems, intelligent transportation systems, and alternative fuel vehicle technologies that impact travel behavior. Travel demand models used for forecasting should reflect the telecommunicationsâtravel behavior interaction. Changes to Spatial and Temporal Resolution Many implementations of tour- based model systems are based on the traditional zone- based spatial representa- tion of a region and discrete time- of- day periods. Until models move toward a truly continuous representation of the spaceâtime domain (which is happening at a rapid pace in R&D), the rather discrete representation of space and time is likely to continue. In such case, it would be desirable to have a model system that is reasonably robust to changes in spatial and temporal resolution. It is possible that zone systems will be altered, zones will be split, and zones will be added. In general, a travel demand model should be aspatial and thus unaffected by the definition of the zonal system. If additional time- of day periods are desired, it should be easy to re- estimate and recalibrate the components of the model system affected by the re- definition of time periods. Accommodation of Emerging Behavioral Paradigms and Concepts There is literature documenting behavioral phenomena inadequately captured by traditional travel demand modeling paradigms. Despite concern about the lack of a sound behavioral theory driving or underlying innova- tive model development, there is a growing body of work that is helping to identify behavioral paradigms and con- cepts that ought to be incorporated into models of activ- ity and travel demand. While one may debate the need to accommodate these concepts, the profession must move toward recognizing established behavioral relationships, if only to make the models more defensible and explica- ble. Some concepts include the following: ⢠Interdependencies and interactions: There are interdependencies and interactions that are key to activ- ityâtravel demand modeling. These include modal, tem- poral, and spatial (location) interdependencies among trips in a chain and among chains in a daily activ- ityâtravel pattern, interdependencies in activity engage- ment across days and weeks, interactions among household members, and residenceâworkâschool loca- tion interdependency. ⢠Constraints and flexibility: There is much to be learned about constraints and flexibility associated with various activities and their attributes; much has been dis- covered as well. There are many constraints that play a key role in shaping activityâtravel patterns, including modal, situational, institutional, household (obligatory), and personal constraints. ⢠Positive utility of travel: There is some evidence that suggests that travel is not purely a disutility that is minimized by individuals. A model system that could accommodate alternative utilitarian paradigms might be able to capture the situations in which travel, by itself, offers a positive utility. ⢠Time use and activity patterns: Travel demand is inextricably tied to the demand for pursuing activities that are distributed in time and space and the time avail- able to pursue them. Thus, time use and activity analysis play an important role in modeling travel demand. His- 159VALIDATION AND ASSESSMENT OF ACTIVITY- BASED SYSTEMS