The Personal Travel Assistant (PTA): Measuring the dynamics of human travel behavior
AbstractThe fundamental research question that was addressed with the project is whether a simple, continuously collected GPS sequence can be used to accurately measure human behavior. We applied Hybrid Dynamic Mixed Network (HDMN) modeling techniques to learn behaviors given an extended GPS data stream. This research project was designed to be an important component of a much larger effort. Unfortunately, the promised funding from a commercial sponsor for the larger project did not materialize, and so we did not have the resources to deploy a prototype personal travel assistant system. Work focused on developing the HDMN model. The learning and inference steps using the HDMN model were much slower than would be acceptable in an operational Personal Travel Assistant (PTA) system. We conducted research into alternate formulations that would improve convergence, handle noisy data more robustly and reduce the need for human intervention. This report describes how this projectâ€™s results fit into the larger research context, details the work done for this UCTC grant, and outlines future directions of research based on the findings of this project.
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Bibliographic InfoPaper provided by University of California Transportation Center in its series University of California Transportation Center, Working Papers with number qt94s473v6.
Date of creation: 01 Aug 2010
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- McNally, Michael G. & Lee, Ming S., 2002. "Putting Behavior in Household Travel Behavior Data: An Interactive GIS-Based Survey via the Internet," University of California Transportation Center, Working Papers qt2zt2733n, University of California Transportation Center.
- Recker, W. W., 1995. "The household activity pattern problem: General formulation and solution," Transportation Research Part B: Methodological, Elsevier, vol. 29(1), pages 61-77, February.
- Sherali, Hanif D. & Narayanan, Arvind & Sivanandan, R., 2003. "Estimation of origin-destination trip-tables based on a partial set of traffic link volumes," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 815-836, November.
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