This paper develops a new combined network equilibrium model by using more behaviorally sound mathematical forms to represent the four travel choices（i.e., trip frequency,destination, mode, and route） in a conventio...This paper develops a new combined network equilibrium model by using more behaviorally sound mathematical forms to represent the four travel choices（i.e., trip frequency,destination, mode, and route） in a conventional travel demand forecasting process. Trip frequency choice relates to the traveler decision on “making a trip” or “not making a trip”so it is given by a binary logit model. Destination choice is formulated as a parameterized dogit model of which the captivity parameters（expressed as functions of independent variables） allow individual travelers to be captive to specific destinations. Mode choice is given by a two-level nested logit model to avoid IIA restriction. Trip assignment is based on Wardrop＇s “user-optimized” principle. All model forms describing travel choices are in response to the level of services incurred by the transportation system. Through the introduction of inclusive values, the traveler decisions concerning trip frequency, destination, mode, and route choices are inherently interrelated and jointly determined.To obtain solutions of the new combined model, it was reformulated as an equivalent convex programming problem with linear constraints, a great advantage from the computational aspects. The model was applied empirically to a transportation network in New Jersey. The application results show that the new model is consistently better than the commonly used logit combined model in reproducing the observed trip flows from origin zones, origin to destination（O-D） trip flows, O-D trip flows by mode, and trip flows on the network links.展开更多
A new stop frequency model was developed to predict the daily number of maintenance activity stops made by individual household heads during a typical weekday. This new model was based on the modification of a convent...A new stop frequency model was developed to predict the daily number of maintenance activity stops made by individual household heads during a typical weekday. This new model was based on the modification of a conventional multivariate ordered probit(MOP) model by maintaining the probit assumption for the marginal distributions while introducing nonnormal dependence among the error terms using copula functions. Therefore, the copulabased MOP model would relieve the restriction of imposing joint normality on the error terms in the conventional MOP model. The new MOP model would not only account for the intrahousehold interactions in stop-making decisions, but also allow the best functional form to be determined for representing dependencies among household heads. Using the New York Metropolitan Transportation Council’s 2010/2011 regional household travel survey data, the copula-based MOP model was employed to examine stop-making behavior for individual household heads residing in New York City and its adjacent counties in Mid-Hudson Valley and New Jersey. Empirical results provided useful insights into the observed effects of sociodemographics, land use density, transportation service, and work schedule together with potential unobserved common effects on the inter-relatedness of spousal stop-making decisions at the household level. The results show that the MOP model with a Clayton copula structure provides the best data fits and there is a very strong positive dependence among error terms of stop-making equations. Furthermore, the dependence among the maintenance activity propensities of household heads is asymmetric, with a stronger tendency of household heads to simultaneously have low maintenance activity levels than to simultaneously have high maintenance activity levels.展开更多
文摘This paper develops a new combined network equilibrium model by using more behaviorally sound mathematical forms to represent the four travel choices（i.e., trip frequency,destination, mode, and route） in a conventional travel demand forecasting process. Trip frequency choice relates to the traveler decision on “making a trip” or “not making a trip”so it is given by a binary logit model. Destination choice is formulated as a parameterized dogit model of which the captivity parameters（expressed as functions of independent variables） allow individual travelers to be captive to specific destinations. Mode choice is given by a two-level nested logit model to avoid IIA restriction. Trip assignment is based on Wardrop＇s “user-optimized” principle. All model forms describing travel choices are in response to the level of services incurred by the transportation system. Through the introduction of inclusive values, the traveler decisions concerning trip frequency, destination, mode, and route choices are inherently interrelated and jointly determined.To obtain solutions of the new combined model, it was reformulated as an equivalent convex programming problem with linear constraints, a great advantage from the computational aspects. The model was applied empirically to a transportation network in New Jersey. The application results show that the new model is consistently better than the commonly used logit combined model in reproducing the observed trip flows from origin zones, origin to destination（O-D） trip flows, O-D trip flows by mode, and trip flows on the network links.
文摘A new stop frequency model was developed to predict the daily number of maintenance activity stops made by individual household heads during a typical weekday. This new model was based on the modification of a conventional multivariate ordered probit(MOP) model by maintaining the probit assumption for the marginal distributions while introducing nonnormal dependence among the error terms using copula functions. Therefore, the copulabased MOP model would relieve the restriction of imposing joint normality on the error terms in the conventional MOP model. The new MOP model would not only account for the intrahousehold interactions in stop-making decisions, but also allow the best functional form to be determined for representing dependencies among household heads. Using the New York Metropolitan Transportation Council’s 2010/2011 regional household travel survey data, the copula-based MOP model was employed to examine stop-making behavior for individual household heads residing in New York City and its adjacent counties in Mid-Hudson Valley and New Jersey. Empirical results provided useful insights into the observed effects of sociodemographics, land use density, transportation service, and work schedule together with potential unobserved common effects on the inter-relatedness of spousal stop-making decisions at the household level. The results show that the MOP model with a Clayton copula structure provides the best data fits and there is a very strong positive dependence among error terms of stop-making equations. Furthermore, the dependence among the maintenance activity propensities of household heads is asymmetric, with a stronger tendency of household heads to simultaneously have low maintenance activity levels than to simultaneously have high maintenance activity levels.
