One of the main barriers to a better understanding of activities and travel patterns is the difficulty in collecting long-duration data. Previous studies have examined computer-aided interview techniques. Others have researched the potential for global positioning system (GPS) antennas to collect more accurate travel data. This dissertation combines these two techniques by adding the use of wireless communications technology to integrate streaming, real-time GPS data with a dynamically generated, web-based activity survey. In addition, three separate analysis techniques are examined using the results of an informal pilot test. The purpose of these analysis techniques is to weave together the large set of GPS data that can be collected with the much smaller set of activity responses that can be expected. The net result represents both an advance in data collection techniques, as well as a new, peer-to-peer approach to gathering and sharing experiential transportation information, an approach that should be incorporated into future Intelligent Transportation Systems designs.

Long records of activities and travel for individuals, essential for understanding the dynamic changes in traveler behavior, do not exist due to the difficulty of collecting such data. To address this need, an on-line activity survey was designed that is tightly intertwined with real-time position data streaming over wireless data links from in-vehicle GPS data collection devices. While the technology to construct such a survey has existed for some time, the author has been unable to find other published examples of such as survey system. Some preliminary observations of the system based on a small, informal pilot survey are reported.

Recent trends toward operationalization of activity-based microsimulation models are producing new research questions related to the development of comprehensive models of human behavior. This paper provides a view of what will be necessary for the development of a dynamic, longitudinal, agent-based microsimulation model of human activity in urban settings. The discussion outlines a conceptual model of an environmentally situated human agent that must adapt to its environment in order to meet its goals. The agent's ability to perceive, interpret and decide upon how to interact with its environment is viewed as a series of sub-models that are themselves the target of a set of learning procedures.

This paper examines the problem of describing an activity in a concise, usable way. An activity is defined by a vector of observed attributes. Including more observed attributes improves the explanatory power and theoretical completeness of any model of activities, but simultaneously leads to a combinatorial explosion when considering questions about choosing between activities or sequences of activities -- questions that arise in simulation applications. This paper first builds a description of individual activities using a vector of observed attributes. Then, latent variable analysis is used to reduce this vector to just two latent variables, which together explain most of the variation in the original variables.

GPS recording devices offer a painless way to collect travel data, but are not directly useful to a standard activity survey. This paper documents one method for linking activities with location data. Based on a small but extended pilot survey, a technique has been developed to estimate the most likely activity at a destination, based on the respondents' past responses. If destinations and activities were randomly paired, this information would be irrelevant. But the pilot survey also demonstrated that activities are tightly clustered in space.

The Tracer system consists of any number of mobile extensible data collection units (EDCU) communicating wirelessly in real time with a base station server. The mobile EDCUs store speed, longitude, latitide and timestamp readings from a global positioning system (GPS) antenna. They also transmit these readings wirelessly, in real time, over a cellular digital packet data (CDPD) modem. A small pilot study with four vehicles was conducted to test the system. Three vehicles have collected over 100 days worth of data, and the other vehicle has collected over 70 days worth of data. The operational experience gained from this wireless data collection implementation is documented here. The results demonstrate that long-term wireless data collection is feasible, but that the CDPD's link instability can add errors to the data stream.

This paper describes the development and implementation of an agent-based activity microsimulation kernel based upon the concept that human activity is the negotiated interaction of socially and physically situated individuals and organizations. The kernel uses a modification of the contract-net protocol from the distributed artificial intelligence literature to represent the "physics" of interaction in human activity settings. The details of the kernel design and implementation are discussed.