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This paper provides a review of transport model applications that not only provide a central traffic forecast (or forecasts for a few scenarios), but also quantify the uncertainty in the traffic forecasts in the form of a confidence interval or related measures. Both uncertainty that results from using uncertain inputs (e.g. on income) and uncertainty in the model itself are treated. The paper goes on to describe the methods used and the results obtained for a case study in quantifying uncertainty in traffic forecasts in The Netherlands. Copyright Springer Science+Business Media, LLC 2007
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Stored only when both papers are in the corpus — 123 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.