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RNAV Benefit Analysis Pre and Post Implementation at ATO-P Operations Research

This study conducted at the William J. Hughes Technical Center in October 2006 assesses the impact of RNAV procedures on air traffic operations at DFW and IAH airports. Using data from 2003-2006, the analysis includes pre- and post-departure routes at DFW and future scenarios for RNAV approaches at IAH. Key findings reveal reductions in taxi-out times, flight delays, and improved efficiency in flight durations post-RNAV implementation. Additionally, future scenario simulations demonstrate enhanced runway utilization and reduced distances and times for flights. This study aims to provide insights into the benefits of RNAV procedures for air traffic management.

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RNAV Benefit Analysis Pre and Post Implementation at ATO-P Operations Research

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  1. RNAV Benefit AnalysisPre and Post Implementation ATO-P Operations Research and William J Hughes Technical Center October 2006

  2. Highlights • DFW: Pre-, post-departure routes • Used ASPM circle data, 2003-2006, for first 60 miles of flight (40 miles radius). • Taxi-out time trend lines. • IAH: Pre-, post-arrival routes • Ran future scenario simulations using pre-, post-RNAV approaches. • Used collected sample days before, after RNAV implementation as seeds to build future scenarios.

  3. DFW 365 Days Moving AveragesAverage taxi-out timesDelays, percent and minutes

  4. DFW 365 Days Moving AveragesAverage taxi-out timesDelays, percent and minutes

  5. DFW: Taxi-Out Time • Average taxi-out time slightly lower than peak value in 2004. • 2.08% or 22 seconds • Percent of flights delayed 20-60 minutes has been reduced up to 20%. • Percent of flights delayed greater than 60 minutes remains unchanged. • Demand in 2006 has gone down by 13% compared to 2004.

  6. DFW 365 Days Moving Average60 Miles Out Duration

  7. DFW Departure Routes • Significant reduction in both average time, standard deviation. • Average cross time, i.e., 40 miles radius, decreased by 3 minutes or 25%. • Standard deviation has fallen by 1.8 minutes or 50%. • All due to RNAV procedures? • Downward trends started before RNAV implementation.

  8. IAH Future Scenario • Simulated RNAV, baseline scenarios for 2015. • Used 5/18/2005, 11/17/2005 as pre-, post-RNAV sample days. • Added future demand using TAF and Fratar Method. • Gathered for all runways • Flight times • Distances from corner posts to runways • Interarrival times, distances • 11/17/2005 had 6% more flights. • Carried over to future scenarios. • Runway utilization, configuration varied for pre-, post- days .

  9. Future Scenario Simulation Results • RNAV scenario compared to baseline scenario • Data normalized for runway configuration • Average of 3.3 miles distance reduction • 69 seconds time reduction • Standard deviations reduced by • 1 mile • 27 seconds • Average interarrival time standard deviation unchanged. • Standard deviation of interarrival time falls but not statistically significant.

  10. Arrival Rates Runway 8R2015 Scenario

  11. Arrival Rates, Runway 8L2015 Scenario

  12. Arrival Rates Runway 26L2015 Scenario

  13. Future Work • Use 12 days of pre-, post RNAV data to build future scenarios for IAH. • Compare RNAV, baseline scenarios results. • Look at DCA pre-, post-RNAV implementation. • Evaluate NGATs benefit claims resulting from implementing RNAV and RNP.

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