Artikel
Considerations about the quality assessment of travel time and travel distance distributions in transport modelling: a proposal for a standardized methodology
In travel demand modelling, trip distance distributions or trip time distributions are used to evaluate how well a model fits with observed sample data. Therefore, the comparison of distributions is an essential part in the model validation process. Despite its importance, the common modelling guidelines from the UK, the USA or Austria provide little information about the correct structure and handling of such distributions. Likewise, common statistical methods are not practicable for the validation of transport models. This lack of rules leads to individual solutions, which complicate a model validation and the comparison of models. For example, when comparing two distributions the quality indicator strongly depends on the number of classes. Therefore, guidelines for model validation need to suggest an appropriate way to determine the number of classes. The paper suggests a method for evaluating trip distance distributions and trip time distributions within the model validation process of a travel demand model. It proposes (a) indicators for a classification which consider mode-specific trip distances and trip times (b) a generic classification method based on an equiquantile class width, quality indicators for comparing two distributions and (c) to use relative frequencies instead of absolute frequencies for the calculation of the quality indicators.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Transportation ; ISSN: 1572-9435 ; Volume: 48 ; Year: 2020 ; Issue: 3 ; Pages: 1285-1309 ; New York, NY: Springer US
- Klassifikation
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Handel, Kommunikation, Verkehr
- Thema
-
Quality assessment
Travel demand modelling
Trip distance distributions
Trip time distributions
Frequency distributions
Key performance indicators
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Pestel, Eric
- Ereignis
-
Veröffentlichung
- (wer)
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Springer US
- (wo)
-
New York, NY
- (wann)
-
2020
- DOI
-
doi:10.1007/s11116-020-10095-y
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Pestel, Eric
- Springer US
Entstanden
- 2020
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