Browsing by Subject "vehicle type choice"

Now showing 1 - 4 of 4

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.
A Joint Flexible Econometric Model System of Household Residential Location and Vehicle Fleet Composition/Usage Choices
(Springer, 2010) Eluru, Naveen; Bhat, Chandra R.; Pendyala, Ram M.; Konduri, Karthik C.
Modeling the interaction between the built environment and travel behavior is of much interest totransportation planning professionals due to the desire to curb vehicular travel demand throughmodifications to built environment attributes. However, such models need to take into accountself-selection effects in residential location choice, wherein households choose to reside inneighborhoods and built environments that are conducive to their lifestyle preferences andattitudes. This phenomenon, well-recognized in the literature, calls for the specification andestimation of joint models of multi-dimensional land use and travel choice processes. However,the estimation of such model systems that explicitly account for the presence of unobservedfactors that jointly impact multiple choice dimensions is extremely complex and computationallyintensive. This paper presents a joint GEV-based logit regression model of residential locationchoice, vehicle count by type choice, and vehicle usage (vehicle miles of travel) using a copulabased framework that facilitates the estimation of joint equations systems with error dependencestructures within a simple and flexible closed-form analytic framework. The model system isestimated on a sample derived from the 2000 San Francisco Bay Area Household Travel Survey.Estimation results show that there is significant dependency among the choice dimensions andthat self-selection effects cannot be ignored when modeling land use-travel behavior interactions.
A joint tour-based model of tour complexity, passenger accompaniment, vehicle type choice, and tour length
(2011-08-01) Paleti, Rajesh; Pendyala, Ram M.; Bhat, Chandra R.; Konduri, Karthik C.
Tour-based model systems are increasingly being deployed to microsimulate daily activity-travel patterns of individuals. There are a host of tour attributes of interest that are modeled within these systems. However, a dimension that is often missed is that of vehicle type choice, a variable of considerable importance in the energy consumption and emissions estimation arena. Another issue that arises is that most tour attributes are modeled independently or sequentially with loose coupling across the models, thus ignoring important endogeneity effects that may exist across multiple tour dimensions. This paper considers four key dimensions of tours – tour complexity, passenger accompaniment, vehicle type choice, and tour length – with a view to developing a joint simultaneous equations model system of tour choices while accounting for the presence of correlated unobserved attributes affecting multiple dimensions through appropriate error covariance structures. The paper makes an important methodological contribution by describing and formulating a multi-dimensional joint choice model system capable of accommodating a variety of endogenous variable types (discrete and continuous). The paper makes an important empirical contribution by providing evidence on the nature of the relationships among these tour dimensions of interest within the context of a joint model. The model system is estimated on a sample of tours from the 2009 National Household Travel Survey of the United States. In general, it is found that there is significant evidence of correlated unobserved factors across these tour dimensions and that vehicle type choice affects tour length, a finding that could have important policy implications.
The modeling of household vehicle type choice accommodating spatial dependence effects
(Transportation Research Board of the National Academies, 2013) Paleti, Rajesh; Bhat, Chandra R.; Pendyala, Ram M.; Goulias, Konstadinos G.
Household vehicle ownership and fleet composition are choice dimensions that have important implications for policy making, particularly in the energy and environmental sustainability arena. In the context of household vehicle ownership and type choice, it is conceivable that there are substantial spatial interaction effects due to both observed and unobserved factors. This paper presents a multinomial probit model formulation that incorporates spatial spillover effects arising from both observed and unobserved factors. The model is estimated on the California add-on data set of the 2009 National Household Travel Survey. Model estimation results show that spatial dependency effects are statistically significant. The findings have important implications for model development and application in the policy forecasting arena.