NESTED LOGIT TRAVEL DEMAND MODELS FOR MORE THAN TWO ALTERNATIVES IN URBAN CORRIDORS
The nested logit model (nl) is a generalisation of the simple or multinomial logit (mnl) model that copes with the "independence from irrelevants alternatives" problem of the latter. Being a generalisation, however, means that it is more difficult and expensive to calibrate and use. This paper uses data for the Garforth-Leeds corridor in west Yorkshire (1975 based) and for the Las Condes-CBD corridor in Santiago, Chile (1981 based) to calibrate mnl and nested logit models for these two different environments, in order to analyse and evaluate the justification of the use of more general specifications as the nl. The problem of structural specification of nl models in practice is also addressed. For the British case a comparison is also made of aggregate and disaggregate n. specifications. (Author/TRRL)
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/0860501132
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Supplemental Notes:
- Transportation Analysis and Models. Proceedings of Seminar Q held at the PTRC 10th Summer Annual Meeting, University of Warwick, England.
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Corporate Authors:
PTRC Education and Research Services Limited
110 Strand
London WC2, England -
Authors:
- DE DIOS ORTUZAR, J
- Fernandez, J E
- Conference:
- Publication Date: 1982
Media Info
- Features: Figures; References; Tables;
- Pagination: p. 353-366
Subject/Index Terms
- TRT Terms: Accuracy; Decision making; Logits; Modal split; Probability; Transportation planning
- ITRD Terms: 6171: Calibration; 8022: Chile; 8525: Conference; 285: Demand (econ); 698: Journey; 6473: Mathematical model; 675: Modal split; 1155: Transport; 8119: United Kingdom
- Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 00381645
- Record Type: Publication
- Source Agency: Transport Research Laboratory
- ISBN: 0-86050-113-2
- Report/Paper Numbers: REPORT
- Files: ITRD, TRIS
- Created Date: May 30 1984 12:00AM