01046494

Component

Activity-based travel demand modeling has long focused on individual scheduling decisions. However, household members do not make their activity/travel decisions in isolation from other members of their household. Rather, they interact in many ways; therefore, their activity/travel patterns are inter-dependent. An explicit recognition of joint episodes is crucial to the development of a new generation of activity-based models, whose performance will be improved in capturing or predicting responses to policy changes in land-use and transportation system. This paper develops an integrated spatio-temporal GIS system to support exploration of intra-household interactions. This framework includes two toolkits. One is called “Space-Time Coincidence Analyst”, which helps identify joint activity/travel behavior undertaken by household members. The core of this toolkit is that we develop a set of flexible criteria for classifying joint episodes. The second toolkit is called “Space-Time Path Visualizer”, which not only helps display each individual space-time path for each household member, but also visualizes joint activities undertaken by any two household members. Our system is the first integrated household-based spatio-temporal GIS model, which combines functions of analysis and visualization of intra-household interactions together in a complimentary way. At the same time, these two toolkits can be used individually, which means that the user can choose using either one of them or both at any sequence, depending on their research goals. Furthermore, our framework is not limited to any specific survey data set. In other words, it can be applied to various surveys in different regions.

01042056

07-1597

English

23p

2007

Transportation Research Board 86th Annual Meeting

CD-ROM

Figures (7) ; References; Tables (4)

Activity choices; Geographic information systems; Households; Land use planning; Scheduling; Traffic forecasting; Travel; Travel demand; Travel patterns; Travel surveys

Activity based analysis; Space time fields; Spatiotemporal analysis

Highways; Planning and Forecasting; Public Transportation; Society; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2007 Paper #07-1597

TRIS, TRB

Feb 8 2007 6:15PM