Calibration of trip distribution by generalised linear models
Generalised linear models (GLMs) provide a flexible and sound basis for calibrating gravity models for trip distribution, for a wide range of deterrence functions (from steps to splines), with K factors and geographic segmentation. The Tanner function fitted Wellington Transport Strategy Model data...
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University of Canterbury. Department of Civil and Natuaral Resources Engineering
2013
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ndltd-canterbury.ac.nz-oai-ir.canterbury.ac.nz-10092-76852015-03-30T15:29:34ZCalibration of trip distribution by generalised linear modelsShrewsbury, John StephenCalibrationdeterrence functiondeviancegeospatialgravityhierarchical generalised linear modelmatrix estimationmixed logitMVESTMregressionsparsitytransport modeltrip distributionGeneralised linear models (GLMs) provide a flexible and sound basis for calibrating gravity models for trip distribution, for a wide range of deterrence functions (from steps to splines), with K factors and geographic segmentation. The Tanner function fitted Wellington Transport Strategy Model data as well as more complex functions and was insensitive to the formulation of intrazonal and external costs. Weighting from variable expansion factors and interpretation of the deviance under sparsity are addressed. An observed trip matrix is disaggregated and fitted at the household, person and trip levels with consistent results. Hierarchical GLMs (HGLMs) are formulated to fit mixed logit models, but were unable to reproduce the coefficients of simple nested logit models. Geospatial analysis by HGLM showed no evidence of spatial error patterns, either as random K factors or as correlations between them. Equivalence with hierarchical mode choice, duality with trip distribution, regularisation, lorelograms, and the modifiable areal unit problem are considered. Trip distribution is calibrated from aggregate data by the MVESTM matrix estimation package, incorporating period and direction factors in the intercepts. Counts across four screenlines showed a significance similar to a thousand-household travel survey. Calibration was possible only in conjuction with trip end data. Criteria for validation against screenline counts were met, but only if allowance was made for error in the trip end data.University of Canterbury. Department of Civil and Natuaral Resources Engineering2013-05-09T03:18:57Z2013-05-09T03:18:57Z2012Electronic thesis or dissertationTexthttp://hdl.handle.net/10092/7685enNZCUCopyright John Stephen Shrewsburyhttp://library.canterbury.ac.nz/thesis/etheses_copyright.shtml |
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NDLTD |
language |
en |
sources |
NDLTD |
topic |
Calibration deterrence function deviance geospatial gravity hierarchical generalised linear model matrix estimation mixed logit MVESTM regression sparsity transport model trip distribution |
spellingShingle |
Calibration deterrence function deviance geospatial gravity hierarchical generalised linear model matrix estimation mixed logit MVESTM regression sparsity transport model trip distribution Shrewsbury, John Stephen Calibration of trip distribution by generalised linear models |
description |
Generalised linear models (GLMs) provide a flexible and sound basis for calibrating gravity models for trip distribution, for a wide range of deterrence functions (from steps to splines), with K factors and geographic segmentation. The Tanner function fitted Wellington Transport Strategy Model data as well as more complex functions and was insensitive to the formulation of intrazonal and external costs. Weighting from variable expansion factors and interpretation of the deviance under sparsity are addressed.
An observed trip matrix is disaggregated and fitted at the household, person and trip levels with consistent results. Hierarchical GLMs (HGLMs) are formulated to fit mixed logit models, but were unable to reproduce the coefficients of simple nested logit models.
Geospatial analysis by HGLM showed no evidence of spatial error patterns, either as random K factors or as correlations between them. Equivalence with hierarchical mode choice, duality with trip distribution, regularisation, lorelograms, and the modifiable areal unit problem are considered.
Trip distribution is calibrated from aggregate data by the MVESTM matrix estimation package, incorporating period and direction factors in the intercepts. Counts across four screenlines showed a significance similar to a thousand-household travel survey. Calibration was possible only in conjuction with trip end data. Criteria for validation against screenline counts were met, but only if allowance was made for error in the trip end data. |
author |
Shrewsbury, John Stephen |
author_facet |
Shrewsbury, John Stephen |
author_sort |
Shrewsbury, John Stephen |
title |
Calibration of trip distribution by generalised linear models |
title_short |
Calibration of trip distribution by generalised linear models |
title_full |
Calibration of trip distribution by generalised linear models |
title_fullStr |
Calibration of trip distribution by generalised linear models |
title_full_unstemmed |
Calibration of trip distribution by generalised linear models |
title_sort |
calibration of trip distribution by generalised linear models |
publisher |
University of Canterbury. Department of Civil and Natuaral Resources Engineering |
publishDate |
2013 |
url |
http://hdl.handle.net/10092/7685 |
work_keys_str_mv |
AT shrewsburyjohnstephen calibrationoftripdistributionbygeneralisedlinearmodels |
_version_ |
1716798951992066048 |