RNAV Benefit Analysis Pre and Post Implementation

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Presentation transcript:

RNAV Benefit Analysis Pre and Post Implementation ATO-P Operations Research and William J Hughes Technical Center October 2006

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.

DFW 365 Days Moving Averages Average taxi-out times Delays, percent and minutes

DFW 365 Days Moving Averages Average taxi-out times Delays, percent and minutes

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.

DFW 365 Days Moving Average 60 Miles Out Duration

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.

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 .

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.

Arrival Rates Runway 8R 2015 Scenario

Arrival Rates, Runway 8L 2015 Scenario

Arrival Rates Runway 26L 2015 Scenario

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.