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

Prato, Carlo Giacomo (2012) Meta-analysis of choice set generation effects on route choice model estimates and predictions. Transport, 27 3: 286-298. doi:10.3846/16484142.2012.719840

Author Prato, Carlo Giacomo
Title Meta-analysis of choice set generation effects on route choice model estimates and predictions
Journal name Transport   Check publisher's open access policy
ISSN 1648-4142
Publication date 2012-09-01
Year available 2012
Sub-type Article (original research)
DOI 10.3846/16484142.2012.719840
Open Access Status Not Open Access
Volume 27
Issue 3
Start page 286
End page 298
Total pages 13
Place of publication Vilnius, Lithuania
Publisher Vilniaus Gedimino Technikos Universitetas * Leidykla Technika
Language eng
Abstract Large scale applications of behaviorally realistic transport models pose several challenges to transport modelers on both the demand and the supply sides. On the supply side, path-based solutions to the user assignment equilibrium problem help modelers in enhancing the route choice behavior modeling, but require them to generate choice sets by selecting a path generation technique and its parameters according to personal judgments. This paper proposes a methodology and an experimental setting to provide general indications about objective judgments for an effective route choice set generation. Initially, path generation techniques are implemented within a synthetic network to generate possible subjective choice sets considered by travelers. Next, true model estimates and postulated predicted routes are assumed from the simulation of a route choice model. Then, objective choice sets are applied for model estimation and results are compared to the true model estimates. Last, predictions from the simulation of models estimated with objective choice sets are compared to the postulated predicted routes. A meta-analytical approach allows synthesizing the effect of judgments for the implementation of path generation techniques, since a large number of models generate a large amount of results that are otherwise difficult to summarize and to process. Meta-analysis estimates suggest that transport modelers should implement stochastic path generation techniques with average variance of its distribution parameters and correction for unequal sampling probabilities of the alternative routes in order to obtain satisfactory results in terms of coverage of postulated chosen routes, reproduction of true model estimates and prediction of postulated predicted routes.
Keyword Large scale model applications
Logit structure
Model estimation
Model prediction
Path generation
Path size correction
Path-based route choice modeling
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Social Science Publications
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Citation counts: TR Web of Science Citation Count  Cited 4 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 4 times in Scopus Article | Citations
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