Graduation Year

2004

Document Type

Thesis

Degree

M.S.C.E.

Degree Granting Department

Civil Engineering

Major Professor

Ram M. Pendyala, Ph.D.

Committee Member

Steven E. Polzin, Ph.D., P.E.

Committee Member

Jian J. Lu, Ph.D., P.E.

Keywords

Commuter behavior, socio-demographic characteristics, job access, residence and workplace location, transportation equity, social isolation

Abstract

An in-depth-analysis was carried out on short, medium and long commuters using the National Household Travel Survey (NHTS) of 2001 and American Community Survey (ACS) of 2000 to determine the role of individual,household, trip and area related characteristics on commute length. The individuals with commute time less than or equal to 15 min were considered as short commuters and individuals with commute time greater than 15 min but less than 60 min were considered as medium commuters and the individuals with commute time 60 min or more were considered as long commuters. The commute time is considered as a link joining the residence and workplace locations. The availability of the desired mode used is considered as flexibility in moving the location of these points in the area. As the jobs get dispersed the lower income people face more and more transportation problems in linking the residence and workplace. There is a potential threat in their social, physical and economic isolation in the society. The individual, household, and area related characteristics are assumed to influence both the commute time and location of these points. The descriptive analysis using NHTS 2001 and ACS 2000 revealed that the characteristics of short and long commuters are different in nature. A commuter type choice model and commute length measurement models were used to estimate the influence of socio-demographic characteristics on the residential and workplace separation. Multinomial Logit Model (MNL) methodology was adopted to develop the commuter type choice model and Structural Equations Model methodology (SEM) was adopted with commute time and commute distance as endogenous variables to estimate the commute length on a continuous scale. The models confirmed the importance of demographic variables in explaining commuter length.

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