Meta-analysis of choice set generation effects on route choice model estimates and predictions

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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Meta-analysis of choice set generation effects on route choice model estimates and predictions. / Prato, Carlo Giacomo.

In: Transport, Vol. 27, No. 3, 2012, p. 286-298.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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Prato, Carlo Giacomo / Meta-analysis of choice set generation effects on route choice model estimates and predictions.

In: Transport, Vol. 27, No. 3, 2012, p. 286-298.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

Bibtex

@article{1692bd6451404b9f8f596c1ac8159dd2,
title = "Meta-analysis of choice set generation effects on route choice model estimates and predictions",
abstract = "Large scale applications of behaviorally realistic transport models pose several challenges to transportmodelers on both the demand and the supply sides. On the supply side, path-based solutions to the user assignmentequilibrium problem help modelers in enhancing the route choice behavior modeling, but require them to generatechoice sets by selecting a path generation technique and its parameters according to personal judgments. This paperproposes a methodology and an experimental setting to provide general indications about objective judgments foran effective route choice set generation. Initially, path generation techniques are implemented within a synthetic networkto generate possible subjective choice sets considered by travelers. Next, ‘true model estimates’ and ‘postulatedpredicted routes’ are assumed from the simulation of a route choice model. Then, objective choice sets are applied formodel estimation and results are compared to the ‘true model estimates’. Last, predictions from the simulation of modelsestimated with objective choice sets are compared to the ‘postulated predicted routes’. A meta-analytical approachallows synthesizing the effect of judgments for the implementation of path generation techniques, since a large numberof models generate a large amount of results that are otherwise difficult to summarize and to process. Meta-analysisestimates suggest that transport modelers should implement stochastic path generation techniques with average varianceof its distribution parameters and correction for unequal sampling probabilities of the alternative routes in orderto obtain satisfactory results in terms of coverage of ‘postulated chosen routes’, reproduction of ‘true model estimates’and prediction of ‘postulated predicted routes’.",
keywords = "path-based route choice modeling, meta-analysis, path generation, model estimation, model prediction, large scale model applications, path size correction, logit structure",
author = "Prato, {Carlo Giacomo}",
year = "2012",
volume = "27",
pages = "286--298",
journal = "Transport",
issn = "1648-4142",
publisher = "Vilniaus Gedimino Technikos Universitetas * Leidykla Technika",
number = "3",

}

RIS

TY - JOUR

T1 - Meta-analysis of choice set generation effects on route choice model estimates and predictions

AU - Prato,Carlo Giacomo

PY - 2012

Y1 - 2012

N2 - Large scale applications of behaviorally realistic transport models pose several challenges to transportmodelers on both the demand and the supply sides. On the supply side, path-based solutions to the user assignmentequilibrium problem help modelers in enhancing the route choice behavior modeling, but require them to generatechoice sets by selecting a path generation technique and its parameters according to personal judgments. This paperproposes a methodology and an experimental setting to provide general indications about objective judgments foran effective route choice set generation. Initially, path generation techniques are implemented within a synthetic networkto generate possible subjective choice sets considered by travelers. Next, ‘true model estimates’ and ‘postulatedpredicted routes’ are assumed from the simulation of a route choice model. Then, objective choice sets are applied formodel estimation and results are compared to the ‘true model estimates’. Last, predictions from the simulation of modelsestimated with objective choice sets are compared to the ‘postulated predicted routes’. A meta-analytical approachallows synthesizing the effect of judgments for the implementation of path generation techniques, since a large numberof models generate a large amount of results that are otherwise difficult to summarize and to process. Meta-analysisestimates suggest that transport modelers should implement stochastic path generation techniques with average varianceof its distribution parameters and correction for unequal sampling probabilities of the alternative routes in orderto obtain satisfactory results in terms of coverage of ‘postulated chosen routes’, reproduction of ‘true model estimates’and prediction of ‘postulated predicted routes’.

AB - Large scale applications of behaviorally realistic transport models pose several challenges to transportmodelers on both the demand and the supply sides. On the supply side, path-based solutions to the user assignmentequilibrium problem help modelers in enhancing the route choice behavior modeling, but require them to generatechoice sets by selecting a path generation technique and its parameters according to personal judgments. This paperproposes a methodology and an experimental setting to provide general indications about objective judgments foran effective route choice set generation. Initially, path generation techniques are implemented within a synthetic networkto generate possible subjective choice sets considered by travelers. Next, ‘true model estimates’ and ‘postulatedpredicted routes’ are assumed from the simulation of a route choice model. Then, objective choice sets are applied formodel estimation and results are compared to the ‘true model estimates’. Last, predictions from the simulation of modelsestimated with objective choice sets are compared to the ‘postulated predicted routes’. A meta-analytical approachallows synthesizing the effect of judgments for the implementation of path generation techniques, since a large numberof models generate a large amount of results that are otherwise difficult to summarize and to process. Meta-analysisestimates suggest that transport modelers should implement stochastic path generation techniques with average varianceof its distribution parameters and correction for unequal sampling probabilities of the alternative routes in orderto obtain satisfactory results in terms of coverage of ‘postulated chosen routes’, reproduction of ‘true model estimates’and prediction of ‘postulated predicted routes’.

KW - path-based route choice modeling

KW - meta-analysis

KW - path generation

KW - model estimation

KW - model prediction

KW - large scale model applications

KW - path size correction

KW - logit structure

M3 - Journal article

VL - 27

SP - 286

EP - 298

JO - Transport

T2 - Transport

JF - Transport

SN - 1648-4142

IS - 3

ER -