01025380

Component

This paper describes a method for efficiently storing, modeling, and processing an individual's travel history collected with a global positioning system (GPS) enabled device. The technique uses a general framework called Hybrid Dynamic Mixed Networks (HDMNs), which are Hybrid Dynamic Bayesian Networks that allow representation of discrete deterministic information in the form of constraints. The paper uses this framework to model a person's travel activity over time and to infer likely destinations and routes given information about the current trip. The paper also presents a preliminary empirical evaluation demonstrating the effectiveness of the modeling framework and algorithms using three variants of the activity model. This research will improve the quality of activity surveys based on electronic data collection methods, as well as improve the usefulness and effectiveness of in-vehicle and hand-held devices for daily activity planning and rescheduling.

01020180

06-0631

English

23p

2006

Transportation Research Board 85th Annual Meeting

CD-ROM

Figures (3) ; References (21) ; Tables (4)

Activity choices; Bayes' theorem; Data collection; Electronics; Global Positioning System; Networks; Routes and routing; Travel patterns; Vehicle electronics

Hybrid choice models

Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2006 Paper #06-0631

TRIS, TRB

Mar 3 2006 10:25AM