Graduation Year
2010
Document Type
Thesis
Degree
M.S.C.E.
Degree Granting Department
Civil and Environmental Engineering
Major Professor
Abdul R. Pinjari, Ph.D.
Committee Member
Xuehao Chu, Ph.D.
Committee Member
Steven E. Polzin, Ph.D.
Keywords
mobility, NHTS, socio-demographics, multinomial logit model, mixed-multinomial logit model
Abstract
The number of elderly is increasing; to meet their transportation needs, it is important to clearly understand their travel patterns and preferences. Since travel patterns and preferences depend on socio-demographic and other factors, it is essential to identify these factors first to understand the travel behavior of the elderly. The main purpose of this thesis is to analyze the travel patterns and preferences of the elderly age 65 and above using 2009 National Household Travel Survey (NHTS) data. This thesis presents a detailed descriptive analysis of 2009 NHTS data to understand the travel patterns of the elderly. Along with a descriptive analysis, a multinomial logit model and a mixed- multinomial logit model are estimated to explore the factors associated with the overall travel preferences of the elderly and to identify individuals among the elderly who are the least mobile and at risk for social isolation.
The analysis results indicate the differences in the trip characteristics between the elderly and non-elderly. Variation is found even among the different groups of the elderly. The model estimation results show the presence of different travel preferences among the elderly and identify those individuals among the elderly who are immobile for longer periods (e.g., a week) and at risk for social isolation. Elderly individuals with different travel preferences should be considered separately in research to determine the appropriate outcomes that can help transportation planners and policy makers improve planning and policy related to elderly individuals.
Scholar Commons Citation
Sikder, Sujan, "An Analysis of the Travel Patterns and Preferences of the Elderly" (2010). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/3469