RT Journal Article
T1 Bayesian approach to model choice analysis in freight transport models (Case study: Central Bioceanic Railway Corridor)
A1 Gregorio Vicente, Óscar De
A1 González Pérez, Beatriz
A1 Gómez Villegas, Miguel Ángel
AB Transport planning requires tool to model the current and future situation of an infrastructures network. In this way, different scenarios of passenger flows, vehicles or freight can be predicted and serve as information for decision making. One of these tools are the so called "Demand models", among which the four steps models (Generation/attraction, Distribution, Modal choice, Network assignment) is a remarkable example for its widespread use. This paper presents a novel Bayesian approach to the third step of a demand transport model. Traditional discrete choice models are the ones most commonly used at this purpose, although other methods such as neural networks have been used by some authors. A Bayesian network is proposed as tool for estimating the decisions made by users when they face the need to choose which transport alternatives to use for sending cargo in a case study corresponding to the Central Bioceanic Corridor in South America. The results from fitting a logit model and a Bayesian network are compared and show the Bayesian network to be a promising tool to be applied in this kind of applications.
PB Asociación Nacional de Ingenieros Industriales de España
SN 0012-7361
YR 2017
FD 2017
LK https://hdl.handle.net/20.500.14352/18189
UL https://hdl.handle.net/20.500.14352/18189
LA eng
NO Gregorio Vicente, Ó., González Pérez, B. & Gómez Villegas, M. Á.  «APROXIMACIÓN BAYESIANA APLICADA AL REPARTO MODAL EN MODELOS DE TRANSPORTE DE MERCANCIAS. CASO PRÁCTICO: CORREDOR FERROVIARIO BIOCEÁNICO CENTRAL)». DYNA INGENIERIA E INDUSTRIA, vol. 92, n.o 1, 2017, pp. 580-86. DOI.org (Crossref), https://doi.org/10.6036/8126.
NO Ministerio de Economía, Comercio y Empresa (España)
NO Universidad Complutense de Madrid/Banco de Santander
DS Docta Complutense
RD 6 abr 2025