A Household Survey via an Internet GIS for Models of Activity Scheduling (2000)	[ back to top ]
Investigator: Ming-Sheng Lee Support: U.S. Department of Transportation and California Department of Transportation via UCTC Summary: This project uses data from a geographic information system (GIS)-based household survey on the Internet to build a production system model of household activity scheduling. The model is a rule-based system that shows how activities are initially scheduled and dynamically changed during execution. Transactional opportunistic problem solving are being used to simulate dynamic scheduling behavior. The model is being verified by comparing model outputs to activity patterns recorded in the existing activity/travel diaries.
Development of an Activity-Based Microsimulation Model for Generating Synthetic Activity-Travel Patterns (1999)	[ back to top ]
Investigator: Anup A. Kulkarni Support: U.S. Department of Transportation and California Department of Transportation via UCTC Summary: The focus of this project is the development of an activity travel pattern generator for travel demand forecasting. The research is a necessary step in the development of novel transportation planning methodologies required to address the limitations of current modeling practice in meeting legislative and judicial mandates. The approach builds upon existing research, conducted over two decades at UCI, 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 activity4ravel patterns for households that are reflective of the available transportation and land use system. By using activity-travel patterns as the basis of the microsimulation, the timing, sequencing, and connections between activities are included in the model where previously they would be lost. The final product of this research will be a prototype modeling system that has the potential to replace some or all aspects of the traditional 'four-step' modeling process.
Modeling the Dynamics of Activity Scheduling (1998)	[ back to top ]
Investigator: Michael G. McNally Support: U.S. Department of Transportation and California Department of Transportation via UCTC Summary: Computational process models (CPM), which have the ability to replicate interdependent choices made by an individual, can improve our understanding of the activity scheduling process. They can also be used with discrete choice models and microsimulation techniques to forecast the consequences of policy measures. This research builds a geographical information system-interfaced CPM which can be used to examine the process of human activity scheduling. Using a GIS land-use and network data base, the model allows location of activities to exact locations on the street network. Data for the model are drawn from 1985 and 1994 travel and activity surveys from Portland, Oregon, and from other sources. The research also devises practical ways of applying the model to advanced traveler information systems (ATIS).
Activity-Based Evaluation of Travel Characteristics in Alternate Land Development and Network Structures (1997)	[ back to top ]
Investigator: Michael G. McNally Support: U.S. Department of Transportation and California Department of Transportation Summary: This research applies an activity-based approach to investigate fundamental characteristics of travel behavior. The approach integrates household activities, land use distributions, regional demographics, and transportation networks in a framework which explicitly recognizes the complexity of travel behavior in terms of spatial and temporal constraints, household interactions and transport accessibility. The research is designed to provide the basic input to more policy-sensitive alternatives to the conventional modeling process. It will incorporate activity-based concepts with fundamental relationships which exist between the activity and transport systems. The research will utilize two extensive and somewhat unique data bases: an Orange County, California, data base comprised of conventional trip diaries and extensive GIS-based land use and transportation data; and the Portland, Oregon, data base comprised of two-day activity diaries and an even more extensive supporting activity data base. These data sets will enable a comparative assessment of the relative contributions of external factors (especially land use and network structure) to travel behavior in each region.
Application of Activity-Based Household Travel Analyses to Study the Impact of Transportation Policies and Neighborhood Characteristics on Accessibility (1997)	[ back to top ]
Investigators: Will Recker and Thomas F. Golob Support: U.S. Department of Transportation and California Department of Transportation Summary: Generic algorithms have been successfully used to solve the household activity pattern problem (HAPP) of analyzing and predicting the optimal path of household members through time and space as they complete a prescribed agenda of activities. This model has been advocated for its ability to remove existing barriers to the operationalization of activity-based approaches in travel behavior analysis. This project will incorporate a behavioral structure in the mathematical procedure that optimizes household activity/travel paths, and will demonstrate its application to policy-sensitive travel demand situations using travel/activity diary information drawn from households in the metropolitan Portland, Oregon, area. The data will provide rich insight into the impacts of transportation policy and neighborhood characteristics on accessibility. It will also provide a comprehensive framework for understanding and predicting such higher-level travel decisions as activity substitution, transfer of accessibility to other members of the household via carpooling, and trip chaining.
An Activity-Based Spatio-Temporal Measure of Accessibility for Transit and Automobile Modes (1997)	[ back to top ]
Investigator: Will Recker Support: U.S. Department of Transportation and California Department of Transportation Summary: A previous project, "Application of Activity-Based Household Travel Analyses to Study the Impact of Transportation Policies and Neighborhood Characteristics on Accessibility," incorporated a behavioral structure in a mathematical procedure that optimizes household/travel activity paths, and demonstrated its application to policy-sensitive travel demand situations among households in Portland, Oregon. This led to the specification of a spatio-temporal measure of accessibility and quantified a potential improvement in this measure for personal auto travel. The current project will extend the modeling system, and its application to Portland, to include public transit modes. This will help identify the potential of public transit to provide accessibility for those activities which Portland residents actually perform. Tests will be conducted to assess the effectiveness of a variety of transit options for this population group. Another portion of the research will refine and complete the incorporation of revealed behavioral relationships in the modeling system.
An Activity-Based Assessment of Trip Generation and the Temporal Stability of Travel Patterns (1996)	[ back to top ]
Investigator: Michael G. McNally Support: U.S. Department of Transportation and California Department of Transportation Summary: Activity-based analysis is a promising, more policy-sensitive, alternative to conventional transportation modeling. This project will develop and refine an activity-based approach to trip generation modeling which integrates household activities, land-use distributions, regional demographics and transportation networks in a framework which explicitly recognizes the complexity of travel behavior. An activity-based approach will be used to develop new models and to assess the temporal stability of individual and household activity patterns. The research will use two extensive data bases: an Orange County, California, data base composed of conventional trip diaries and GIS-based land use and transportation data (1976 and 1991); and the Portland, Oregon, data base composed of 2-day activity diaries and extensive GIS-based supporting data (1985 and 1994). This information will be used to generate and classify daily activity patterns for each data set, and to develop and evaluate an activity-based trip generation model which reflects the influence of accessibility and maintains spatial and temporal linkages in travel behavior.
Generation of Dynamic Trip Tables via An Activity-Based Microsimulation Model (1996)	[ back to top ]
Investigator: Ruey-Min Wang and Michael G. McNally Support: U.S. Department of Transportation and California Department of Transportation Summary: This research represents a first step in the development of a microsimulation model for disaggregate activity-based travel demand forecasting. It integrates household activities, land use distributions, and regional demographics in an explicitly time-dependent fashion. The research is intended to fulfill the modeling requirements of the 1990 Clean Air Act Amendments (CAAA) and the Intermodal Surface Transportation Efficiency Act (ISTEA) in forming one of the basic elements of an alternative to the conventional four-step transportation planning process. This research integrates an existing activity-based travel behavior model into a microsimulation approach. It uses a geographical information system (GIS) platform to manipulate fully specified complex daily travel-activity patterns. The model resulting from this research will allow the impacts of, and the responses to, air quality, network mobility, and land use policies to be dynamically simulated at the household level. This is an approach which addresses some of the limitations in flexibility, sensitivity, and transferability of conventional planning models. The short-run contribution of this research is the development of a methodology for forecasting dynamic, linked-trip, origin-destination demand matrices. Its long-run contribution is potential improvement in the development of alternative transportation planning methods.
Assessing Transit and Pedestrian Roles in Accessibility Using a New Travel Demand Model System with Simultaneous Prediction of Activity Participation, Travel Generation, and Car Ownership	[ back to top ]
Investigator: Thomas F. Golob Summary: Metropolitan planning organizations have expressed considerable interest in activity-based travel forecasting. Several regions have already conducted extensive activity diary surveys. This project will extend a model system previously developed by the investigator and his colleagues for regional planning applications. In this system, travel times by mode are explained in terms of activity durations, there are explicit trade-offs between in-home and out-of-home activities, interactions between household members are captured in terms of activity participation and travel, mobility choices help explain car ownership decisions, and neighborhood and network-based accessibility indices are used to explain activity participation and travel generation. The goal of the research is to determine how activity participation and mobility choices are related to accessibility measures, particularly those related to pedestrian and transit modes.

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