The built environment, activity space, and time allocation: An activity-based framework for modeling the land use and travel connection

Cities and metropolitan regions face several challenges including rising urban populations, sprawled land use patterns, and related auto dependence, energy consumption, greenhouse emissions, and human health effects. An important aspect of addressing these challenges involves understanding the connection between urban environments and spatial and temporal characteristics of individual activity-travel behavior. Advances in the research arena can inform the development of land use and transportation policies that facilitate access to local opportunities, reduce auto dependence, promote healthy travel behavior such as walking and bicycling, and generate travel time savings. Further, research efforts on this subject can help to measure the successes of existing transportation and land use planning tools in terms of their "secondary" effects on individuals' spatial accessibility, time allocation, and quality of life.; This dissertation uses secondary travel data from the 2006 Greater Triangle Travel Study (N=5,107 households) in central North Carolina. It systematically tests the connection between land use and activity-travel behavior by presenting three perspectives: one that focuses on the census block group level; another that focuses on the individual level; and one that focuses on the trip level. The analysis at the census block group level, termed as the census block group level activity pattern analysis in this research, examines how the built environment of a census block-group is associated with the aggregated distribution of activities and trips occurring within the census block-group. The individual-level analysis, termed as the individual activity space and time allocation analysis, links individuals' spatial and temporal footprints to the built environment at the home location, traffic conditions at the home location, weather conditions, and individual/household characteristics. The trip-level analysis, termed as the trip distance and duration analysis, demonstrates how environmental factors at the trip origin and destination and activity/trip characteristics are associated with the distance and duration of each trip.; This research takes an activity-based and time use approach to study the land use-travel connection, which fills the gap between activity modeling and land use-travel modeling in the existing literature. Evidence found in this research supports the notion that transportation problems can be ameliorated through the use of land use strategies. The research also points out that the strength of the land use-travel connection is conditional on other environmental factors such as traffic and weather conditions, as well as activity context such as activity type and time of day. Given the single study location, the transferability of findings for the Triangle area in North Carolina to other urban regions is somewhat limited.; More specifically, the census block group level activity pattern analysis indicates that dense developments are not necessarily positively associated with diversity in activity categories or demographic diversity of the individuals who were involved with activities in the area. Greater land use diversity is associated with higher activity density and greater activity diversity but lower alternative mode share. Grid street patterns and the presence of sidewalks are both associated with higher activity density and more alternative mode share.; The individual activity space and time allocation analysis shows that small activity area size---less spatially dispersed daily activity locations---are related to dense developments, more retail stores, the presence of sidewalks, and the presence of heavy traffic in the residential neighborhood and are related to cold weather and precipitation. Most of the built environment factors show no association with time allocations to out-of-home activities or leisure activities, while they do show various associations with travel time allocations depending on...