Browsing by Subject "travel behavior"
Now showing 1 - 6 of 6
- Results Per Page
- Sort Options
Item An Analysis of the Factors Influencing Differences in Survey-Reported and GPS-Recorded Trips(Elsevier, 2012) Bricka, Stacey G.; Sen, Sudeshna; Paleti, Rajesh; Bhat, Chandra R.Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional surveyreported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPSrecorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-hour period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.Item A Copula-Based Joint Multinomial Discrete-Continuous Model of Vehicle Type Choice and Miles of Travel(Springer, 2009) Spissu, Erika; Pinjari, Abdul R.; Pendyala, Ram M.; Bhat, Chandra R.In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete-continuous model system formulated in this study explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e., self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components. The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation approaches for joint discrete-continuous model systems. The model system, when applied to simulate the impacts of a doubling in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.Item Econometric Calibration of the Joint Time Assignment - Mode Choice Model(Informs, 2008) Munizaga, Marcela; Jara-Diaz, Sergio; Greeven, Paulina; Bhat, Chandra R.This paper describes the derivation and the econometric calibration of a joint time assignment - mode choice model with a microeconomic foundation, to be applied to the TASTI (Time ASsignment Travel and Income) database. The econometric procedure is a full information maximum likelihood with three nonlinear continuous equations and one discrete choice. We use Lee's transformation to include correlations between the continuous and discrete equations. This allows us to estimate (a) the value of time as a resource or value of assigning time to a pleasurable activity, (b) the value of assigning time to work, and (c) the value of assigning time to travel. We apply the method and obtain reasonable results. Finally, we identify some econometric challenges for further research.Item A Joint Count-Continuous Model of Travel Behavior with Selection Based on a Multinomial Probit Residential Density Choice Model(2013-07) Bhat, Chandra R.; Astroza, Sebastian; Sidharthan, Raghuprasad; Jobair Bin Alam, Mohammad; Khushefati, Waleed H.This paper formulates a multidimensional choice model system that is capable of handling multiple nominal variables, multiple count dependent variables, and multiple continuous dependent variables. The system takes the form of a treatment-outcome selection system with multiple treatments and multiple outcome variables. The Maximum Approximate Composite Marginal Likelihood (MACML) approach is proposed in estimation, and a simulation experiment is undertaken to evaluate the ability of the MACML method to recover the model parameters in such integrated systems. These experiments show that our estimation approach recovers the underlying parameters very well and is efficient from an econometric perspective. The parametric model system proposed in the paper is applied to an analysis of household-level decisions on residential location, motorized vehicle ownership, the number of daily motorized tours, the number of daily non-motorized tours, and the average distance for the motorized tours. The empirical analysis uses the NHTS 2009 data from the San Francisco Bay area. Model estimation results show that the choice dimensions considered in this paper are inter-related, both through direct observed structural relationships and through correlations across unobserved factors (error terms) affecting multiple choice dimensions. The significant presence of self-selection effects (endogeneity) suggests that modeling the various choice processes in an independent sequence of models is not reflective of the true relationships that exist across these choice dimensions, as also reinforced through the computation of treatment effects in the paper.Item Modeling Residential Sorting Effects to Understand the Impact of the Built Environment on Commute Mode Choice(Springer, 2007) Pinjari, Abdul R.; Pendyala, Ram M.; Bhat, Chandra R.; Waddell, PaulThis paper presents an examination of the significance of residential sorting or self selection effects in understanding the impacts of the built environment on travel choices. Land use and transportation system attributes are often treated as exogenous variables in models of travel behavior. Such models ignore the potential self selection processes that may be at play wherein households and individuals choose to locate in areas or built environments that are consistent with their lifestyle and transportation preferences, attitudes, and values. In this paper, a simultaneous model of residential location choice and commute mode choice that accounts for both observed and unobserved taste variations that may contribute to residential self selection is estimated on a survey sample extracted from the 2000 San Francisco Bay Area household travel survey. Model results show that both observed and unobserved residential self selection effects do exist; however, even after accounting for these effects, it is found that built environment attributes can indeed significantly impact commute mode choice behavior. The paper concludes with a discussion of the implications of the model findings for policy planning.Item Parental Attitudes Towards Children Walking and Bicycling to School(Transportation Research Board of the National Academies, 2012) Seraj, Saamiya; Sidharthan, Raghuprasad; Bhat, Chandra R.; Pendyala, Ram M.; Goulias, Konstadinos G.Recent research suggests that, besides traditional socio-demographic and built environment attributes, the attitudes and perceptions of parents towards walking and bicycling play a crucial role in deciding their children’s mode choice to school. However, very little is known about the factors that shape these parental attitudes towards their children actively commuting to school. The current study aims to investigate this unexplored avenue of research and identify the influences on parental attitudes towards their children walking and bicycling to school, as part of a larger nationwide effort to make children more physically active and combat rising trends of childhood obesity in the US. Through the use of a multivariate ordered response model (a model structure that allows different attitudes to be correlated), the current study analyses five different parental attitudes towards their children walking and bicycling to school, based on data drawn from the California add-on sample of the 2009 National Household Travel Survey. In particular, the subsample from the Los Angeles – Riverside – Orange County area is used in this study to take advantage of a rich set of micro-accessibility measures that are available for this region. It is found that school accessibility, work patterns, current mode use in the household, and sociodemographic characteristics shape parental attitudes towards children walking and bicycling to school. The study findings provide insights on policies, strategies, and campaigns that may help shift parental attitudes to be more favourable towards their children walking and bicycling to school.