Activity-based approaches are perhaps the most promising alternative to the current travel forecasting methodology. This dissertation first presents a pattern generation model that can serve as a link between activity and trip-based methodologies. The model uses a clustering approach to identify groups of similar activity-travel behavior and relates them to household socioeconomic attributes. Minimally, the pattern generation model is then expanded to serve as the core component of a proposed activity-based microsimulation model that constructs complete origin-destination tables using a wholly activity-based approach. The techniques developed provide due diligence to the complex nature of activity-travel behavior in terms of spatial and temporal constraints, household interactions, and the derived nature of such behavior. A successful application of the expanded model is outlined using data from the 1994 Portland activity-travel survey.

This paper describes the development of SIMAP, an activity-based microsimulation model for travel demand forecasting. The model is part of a larger research effort aimed at the development of innovative transportation planning methodologies that address contemporary legislative and judicial mandates. The model builds upon existing research that demonstrates that travel behavior should be viewed holistically using activity-travel patterns, a time-dependent representation of the activities in which an individual engages. A microsimulation approach integrated with a geographic information system is advanced to synthesize individual 24-hour activity-travel patterns for households that reflect the existing transportation/land use system. By using activity-travel patterns as the basis of the SIMAP, the timing, sequencing and connections between activities are explicitly included in the model. The final product of this research is a prototype modeling system that has the potential to replace some or all aspects of the traditional 'four-step' modeling process.

This paper presents an empirical assessment of the interaction between the land-use transporttion system and travel behavior. A methodology is developed to identify a range of land-use transportation systems using a clustering technique with network and land use inputs. Twenty neighborhoods from Orange County, California, were considered in this process. Three groups, or themes, were found to best represent the neighborhoods in the sample area, one each associated with the conventional defition of neotraditional (TND) and planned unit development (PUD) neighborhoods, and one representing neighborhoods that blend characteristics of TND and PUD. Conventional and more complex measures of individual travel behavior were compared via an analysis of variance between the themes to identify significant differences, controlling for socio-economic differences. Research results included the development of a systematic methodology to identify a more explicit land use and transportation dimension, an estimate of the potential effectiveness of design-oriented solutions to reduce automobile congestion using the developed themes, and a preliminary assessment of the extent to which development themes can be utilized to improve the current modeling framework.

This paper documents the prototype development, application and validation of a pattern synthesis model based on activity-travel pattern classifications. The technique proposed is a microsimulation approach to construct daily activity patterns for individuals established on empirical distributions of representative activity patterns and distributions of additional travel characteristics contained by every pattern. The method clearly recognizes the complex, stochastic nature of activity-travel behavior in terms of activity generation, spatial choice and scheduling components. A successful application of the model is outlined using data from the 1994 Portland Activity Travel Survey.

This paper describes the development of SIMAP, an activity-based microsimulation model for travel demand forecasting, and is part of a larger research effort aimed at the development of innovative transportation planning methodologies designed to address the limitations of current modeling practice in meeting current legislative and judicial mandates. The model builds upon existing research demonstrating that travel behavior should be viewed holistically using activity-travel patterns, a time-dependent representation of the activities and their attributes in which an individual engages. A microsimulation approach integrated with a geographic information system is advanced to synthesize individual, 24-hour activity-travel patterns for households that are reflective of the available transportation and land use system. By using activity-travel patterns as the basis of the SIMAP, the timing, sequencing, and connections between activities are explicitly included in the model where previously they would be disregarded. The final product of this research is  a prototype modeling system that has the potential to replace some or all aspects of the traditional 'four-step' modeling process. 

The next section describes the specifics of SIMAP. Section 3 presents a short discussion of the aggregate activity-travel pattern classification and results. Section 4 summarizes the implementation of the generation model, while Section 5 demonstrates a limited application of SIMAP. Finally, Section 6 concludes this paper by describing how this project's key contribution and suggests some extensions to the work.

Activity-based approaches are perhaps the most promising alternative to the current travel forecasting methodology. This paper presents a pattern generation model that can serve as a link between activity and trip-based methodologies. The model uses a clustering approach to identify groups of similar activity-travel behavior and relates them to household socioeconomic attributes. Minimally, the pattern generation model is offered as a possible replacement to the standard trip generation models. Moreover, it can serve as the core component of a proposed activity-based microsimulation model that constructs complete origin-destination tables using a wholly activity-based approach. The technique proposed clearly recognizes the complex nature of activity-travel behavior in terms of spatial and temporal constraints, household interactions and the derived nature of such behavior. An application of the model is outlined using data from the 1994 Portland activity-travel survey.