Validation of Runway Capacity Models

• Author(s) / Creator(s)

  • Kim, A.
  • Hansen, M.

• There are many runway capacity estimation models currently available today, and developers usually claim that their models have been validated. However, information about the validation process is often limited, and different models are validated at different levels of complexity. As a result, this paper proposes two validation methodologies that can be used to test model predictions against reality. We demonstrate the methods on two models--the Airfield Capacity Model (ACM) and Runway Simulator (rS)--and two airports—SFO and LAX. The results indicate that both models tend to over-predict capacities under good visibility conditions, and predict wider ranges of capacities than are seen empirically. Overall, capacity estimates from rS are typically more accurate than those from ACM.

• Date created

  2019-11-18

• Subjects / Keywords

  • Validation
  • Acm
  • Runway Capacity
  • Censored Regression
  • Empirical Estimation
  • Capacity Models
  • Rs

• Type of Item

  Conference/Workshop Presentation

• DOI

  https://doi.org/10.7939/r3-v350-h105

• License

  Attribution-NonCommercial 4.0 International