Sampling of Alternatives for Route Choice Modeling
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This paper proposes a block logit (BL) model, which is an alternative approach to incorporating covariance between the random utilities of alternatives into a GEV random utility maximization model. The BL is similar to the nested logit (NL), in that it is ...
We present a new method for compressing spatio-temporal audio data for reproduction through Wave Field Synthesis. The data is obtained by sampling the sound field in space at equally-spaced points on a straight line, and transformed into the frequency doma ...
Discrete choice models in general and random utility models in particular may be intractable when the number of alternatives is large. In the transportation context, it typically happens for route choice and destination choice models. In the specific case ...
Discrete choice models are defined conditional to the knowledge of the actual choice set by the analyst. The common practice for is to assume that individual-based choice sets can be deterministically generated based on the choice context and the character ...
This thesis focuses on the route choice behavior of car drivers (uni-modal networks). More precisely, we are interested in identifying which route a given traveler would take to go from one location to another. For the analysis of this problem we use discr ...
In the presence of choice-based sampling strategies for data collection, the property of Multinomial Logit (MNL) models, that consistent estimâtes of all parameters but the constants can be obtained from an Exogenous Sample Maximum Likelihood (ESML) estima ...
When using random utility models for a route choice problem, a critical issue is the significant correlation among alternatives. There are basically two types of models proposed in the literature to address it: (i) a deterministic correction of the path ut ...
Map matching algorithms are the conventional way to generate path observations from GPS data for route choice models. The deterministic matching may introduce extra biases to parameters of route choice models if the matching is wrong. In this paper, a new ...
We consider an estimation procedure for discrete choice models in general and Multivariate Extreme Value (MEV) models in particular. It is based on a pseudo-likelihood function, generalizing the Conditional Maximum Likelihood (CML) estimator by Manski and ...
We consider an estimation procedure for discrete choice models in general and Generalized Extreme Value (GEV) models in particular. It is based on a pseudo-likelihood function, generalizing the Conditional Maximum Likelihood (CML) estimator by Manski and M ...