| II. Sensitivity Study MethodThis section describes the sensitivity analysis method used for determining the affect that departure and arrival capacity reduction at one major airport has on the departure and arrival delays at the other 33 major airports in the continental United States.The 34 airports considered in this study are tracked in the Operational Evolution Plan (OEP) of the Federal Aviation Administration (FAA) and are referred to as OEP airports.The sensitivity determination method consists of conducting an ACES simulation with the 34 airport departure and arrival capacities set at their most common settings for establishing the baseline delays.Then, performing a series of ACES runs with airport departure and arrival capacities reduced at each airport one at a time, while maintaining baseline capacity value at the other airports, to determine the change in arrival and departure delays at each of the 34 airports.The Airspace Concept Evaluation System (ACES) was used to do the simulations.ACES is a comprehensive computational model of the national airspace system consisting of air traffic control and traffic flow management models of air route traffic control centers, terminal radar approach controls (TRACON), airports and the air traffic control system command center (ATCSCC). 2It simulates flight trajectories through the enroute-phase of flights, where the enroute-phase for piston-props is 6,000 feet, for turboprops is 8,000 feet and for jet aircraft is 10,000 feet.A queuing model simulates the surface movement and flight through the terminal airspace.Thus, with continuous aircraft dynamics and discrete air traffic control and traffic flow management events, ACES is a hybrid-system.The traffic flow management and air traffic control models in ACES use airport and sector capacity thresholds for delaying flights while they are on the ground and during their enroute phase to ensure that these capacity thresholds are not exceeded.Some of the ACES outputs are arrival and departure counts at airports, traffic counts in sectors and air traffic system performance metrics including arrival, departure, enroute and total delays.Validation studies in Refs. 3 and 4 have shown that ACES generates realistic delays and airport operational metrics similar to those observed in the real-world.Due to these capabilities, ACES was chosen as the system for conducting the airport departure and arrival rate sensitivity study discussed in this paper. | |
| III. Simulation Inputs and OutputsInput for ACES simulations consists of scenario files containing capacity data (airport arrival and departure capacities, and sector capacities), traffic data (scheduled departure times and flight-plans), and adaptation data (sector/center geometric data).These inputs are described below.Delay metrics, the outputs of ACES, are defined in this section. | |
| A. Airport CapacitiesTo determine airport departure and arrival capacities, four-months of data spanning the period from March 1, 2006 through June 30, 2006 reported in the FAA's Aviation System Performance Metrics (ASPM) database were collected.This database can be accessed via the web site: http://www.apo.data.faa.gov/.Airport capacity data for a particular airport can be obtained by selecting the Analysis tab and choosing Airport, Weather and Hourly radio buttons on the graphical user interface.Table 1 shows the airport capacity data for Hartsfield-Jackson Atlanta International airport during each hour of March 17, 2006.The first column shows the local hour and the second column lists the landing and takeoff conditions at that hour.Instrument approach condition is indicated by IA and visual approach condition by VA.The airport departure rate (ADR), which is the number of takeoffs per hour, is tabulated in the third column.The airport arrival rate (AAR), which is the number of landings per hour, is listed in the fourth column of the table.Finally, the total capacity of the airport, which is the sum of the ADR and AAR, is given in the last column of the table.In addition to the items in Table 1, the airport capacity data contain the actual number of arrivals and departures during the hour, cloud-ceiling, visibility, temperature, windspeed, wind-angle and arrival and departure runway configurations. | |
| Baseline CapacitiesThe data of the type listed in Table 1 were analyzed via scripts written in the Matlab language 5 to determine the most frequently used total capacities, along with the associated arrival and departure capacities, for each of the 74 ASPM airports including the 34 OEP airports.Honolulu International airport, which is one of the 35 OEP airports, was excluded from analysis because this study is devoted to airports within the continental United States.After obtaining the most frequently assigned total capacity -mode capacity from the entire dataset, instances with total capacities equal to the selected mode capacity were placed in a subset.Departure and arrival capacities were then selected from this subset based on the minimum of the cost function given in Eq. (1):2 ) ( AAR ADR C C J ! = (1) ADR Cis the airport departure rate and AAR C is the airport arrival rate.Observe that a minimum value of the function is obtained when the ADR is equal to the AAR.Table 2 lists the selected ADR and AAR values corresponding to the mode value of total capacities.The first and the seventh columns list the International Civil Aviation Organization codes for the airports.The second and the eighth columns indicate whether the airport is included in the OEP or not.Mode values of the total capacities are given in columns five and eleven.The frequency of occurrence of the mode value of the total capacity for each of the 74 airports is given as a percentage of the total of 2928 (24 hours !122 days) possible instances in columns six and twelve.The ADR and AAR values listed in this table were used in the ACES simulation for generating the baseline delay values. | |
| Reduced CapacitiesMatlab scripts were also used to identify instances where total capacities, Total C , were close to 50% of the baseline capacities, Mode C , listed in Table 2.The desire was to identify instances in real data when ADR and AAR were severely reduced.The ADR and AAR values corresponding to 50% capacities were obtained based on the minimum of Eq. (2):2 2 ) 5 . 0 ( ) ( Total Mode AAR ADR C C C C J ! + ! = (2)These ADR and AAR values for the 34 OEP airports are listed in Table 3.This second set consists of the reduced airport departure and arrival capacities that were used in ACES simulations for comparisons against the baseline capacities listed in Table 2.Note that the reduced total capacities are not exactly 50% of the mode capacity; they are as close to 50% as possible based on the actual four-months of airport capacity data that were analyzed.For example, the reduced total capacity of Cincinnati/Northern Kentucky International Airport (KCVG) in Table 3 is 69% of the baseline total capacity of 156 aircraft/hour in Table 2. | |
| B. Flight-Plans and Adaptation DataFlight-plans for the simulations were derived from the Aircraft Situation Display to Industry (ASDI) data, which is provided via the FAA's Enhanced Traffic Management System (ETMS) 6 , spanning the period from zero Coordinated Universal Time (UTC) on 17 March 2006 to zero UTC on 19 March 2006.These days were selected because 1) they were within the March 1, 2006 to June 30, 2006 time period and 2) they had experienced high traffic-volume, low weather impact and low delays.There were 48,258 departures on the 17 th (a Friday) and 35,394 departures on the 18 th (a Saturday) according to the Centers: Summary of Domestic Operations Report in the FAA's Air Traffic Operations Network (OPSNET) database. 7Delay data obtained from the OPSNET database for these days are provided in Table 4.The second row of the table lists the total number of aircraft delayed by fifteenminutes or more.The third and the fourth rows show the number of aircraft delayed due to weather and due to traffic-volume.Total delay is given in the fifth row.Average delay given in the sixth row is obtained as the ratio of the total delay to the total number of aircraft delayed by fifteen-minutes or more.It can be verified that these two days are low delay days by comparing the total time delay values in Table 4 with those in | |
| C. Flight Schedule and ConnectivityThe flight connectivity data, data conditioning steps and delay metrics are described in this section. | |
| Flight Connectivity DataFlight connectivity data relating the same physical aircraft to two or more flights segments were obtained from the Bureau of Transportation Statistics (BTS) for the two days.Airline flightnumbers were used as tail-numbers for flights not found in the BTS data.The airline flight-numbers, aircraft tailnumbers and the associated flight-plans for all the flights were then included in the Flight Data Set (FDS) file.The subsequent step consists of assigning a departure time to the flights in the FDS file.Scheduled departure times derived from the BTS data are assigned to the flights in the FDS file found in the BTS data.For flights that are not in the BTS data, proposed departure times from flight-plan messages in the ASDI data are assigned as scheduled departure times.In instances when the route of flight is available but the departure time is not, average taxi times reported in the FAA's Aviation System Performance Metrics (ASPM) database are subtracted from the departure message times reported in the ASDI data to estimate the gate departure times.Scheduled departure times are then set to these gate departure times.After assigning a scheduled departure time for every flight, an ACES simulation is run without airport and sector capacity constraints to compute the unconstrained arrival time of each flight at its destination airport.These computed arrival times are then used as scheduled arrival times at the destination airports of the flights. | |
| Data ConditioningData conditioning steps are needed to compensate for missing and incomplete data.Although the data conditioning steps taken introduce some errors in the simulation, they help keep most flights in the simulation.Errors are due to discrepancies between the airline flight schedule and the simulated flight schedule Although departure schedules are provided as ACES input, arrival schedules for the flights are created during the configuration step of ACES.These computed arrival times need to be earlier than the scheduled departure times of the next segment of the flights.Data in the initial FDS file are therefore processed further to ensure that flight connectivity is preserved and that the arrival and departure schedules linked to the same physical aircraft account for the turn-around-time.Turn-around-time is defined as the time required for unloading the aircraft after arrival at the gate and preparing it for departure.Turn-around-time was assumed to be 40minutes irrespective of the size of the aircraft.The procedure for checking flight connectivity and turnaround-times is summarized in Fig. 1.The process is begun by running an ACES simulation with the initial FDS file and storing the results in the output database.The output database is examined to retrieve flights with a common tail-number.These flights are sorted in time and then a check is performed to determine if the destination airport of the previous flight segment is the same as the origin of the next segment.If the check fails, a new tailnumber is assigned to the subsequent flight segments.For example, consider the four flight segments in Table 5.Since the first segment of the flight ends at Los Angles International (KLAX) and the next segment begins at KLAX, these two segments are proper.The third segment starts at Chicago O'Hare International (KORD) which indicates that the flight connectivity between the second and the third leg is broken.A new tail-number, N12345-1, is assigned in the FDS file to associate this flight with a different aircraft.Tail-numbers of the subsequent segments are also altered.This means that the tail-number of the fourth segment in Table 5 is also altered to N12345-1 because it shares its airport of origin with the airport of destination of segment three.Next, the scheduled arrival and departure times of the flight segments are examined to determine if there is adequate turn-around-time between the segments.If it is determined that the condition described by Eq. ( 3) is not met, the scheduled departure time is altered to meet the condition.The amount of change in the departure time also appears in the scheduled time of arrival of this flight segment at the next airport.Since the unimpeded flight time between a pair of origin-destination airports is a constant, a change in departure schedule alters the arrival schedule by the same amount.Once the schedule of a flight segment is altered, schedules of subsequent flight segments are also altered to ensure that the turn-around-time requirement is met.The process summarized in Fig. 1 was applied to the initial FDS file that contained data for 98,674 flights operating out of 2,669 U. S. and foreign airports that were operated during the 48-hour period from March 17 th to the 18 th .Flight schedules and tail-numbers were altered for 37,638 flights to create the modified FDS file. | |
| D. Selection of Time Periods for Capacity ReductionSince the system-wide impact is a function of the time of day when ADR or AAR is reduced, peak-demand times were identified for each airport.A three-hour period around the peak demand time was identified as the time for ADR and AAR reduction at each airport.These times are provided in Table 6.The second and seventh columns list the two dates -3/17/2006 and 3/18/2006 associated with start-times and end-times for reduction of the ADR and AAR values. | |
| E. Delay MetricsThe delay metrics described below are ACES outputs that have been used for the study described in this paper.Scheduled times are employed in the simulation to provide the datum for computation of delays.Delays associated with the departure and arrival, which are defined below, are computed as those in Ref. 3. Scheduled takeoff time, stt t , is defined as:utot sgdt stt t t t + = ,(4)The gate arrival delay, gad t , is obtained as:sgat agat gad t t t ! = . (9)Substituting Eqs. ( 7) and ( 8) in Eq. ( 9) and using the definition in Eq. ( 6), it is seen that) ( ) ( utit atit uft aft dd gad t t t t t t ! + ! + = . (10)Equation (10) shows that the departure delay is accounted as part of the arrival delay.Arrival delay can be reduced by absorbing a part of the departure delay in flight.These metrics were computed with the baseline and reduced airport capacities to study the system-wide impact of capacity reduction at the 34 OEP airports.Results of this study are discussed in the next section. | |
| IV. ResultsResults obtained via ACES simulations with baseline capacities are described in Subsection A and those obtained using reduced capacities are discussed in Subsection B. | |
| A. Baseline Capacity ResultsA simulation was conducted with the conditioned FDS file, baseline sector capacities and baseline airport departure and arrival capacities listed in Table 2.Aircraft-counts in each sector resulting from the baseline ACES simulation were retrieved from the output database and added together to compute the total number of aircraft in the continental United States above 10,000 feet altitude at one-minute intervals.This time history of aircraft count was then compared with the time history of the actual number of flights, above 10,000 feet altitude.Actual flights for those days, recorded in the ASDI data, were processed using NASA's Future ATM Concepts Evaluation Tool (FACET). 9The two time histories are shown in Fig. 2. Observe that the ACES simulation starts with all aircraft on the ground, whereas in the actual air traffic system there are always flights that are airborne.Figure 2 shows that the simulated traffic catches up with the actual traffic around four UTC.The general trend of the simulated traffic is similar to the actual traffic for the twenty-four hours between eight UTC on 17 March 2006 and eight UTC on 18 March 2006 (location marked 32 UTC in Fig. 2).Differences between the time histories are both due to issues with the actual flight data and with the simulation.Several issues related to the quality of ASDI data are described in Ref. 10.These issues make it difficult to exactly determine how many flights are in the airspace at a given instant of time.Flight-plan amendments, cancellations and pop-up flights are not included in the simulation.Flights with track information but missing flight-plans in ASDI data are not included in the simulation.Additionally, the trajectory flown by the real aircraft can be different than the one synthesized in the simulation.During the simulation, aircraft were delayed on the ground and in the air to ensure that the airport and sector capacities were not exceeded.Figure 3 shows the baseline ADR value of 96, scheduled takeoff demand and the achieved takeoff rate at the Hartsfield-Jackson Atlanta airport as a function of time.The time along the abscissa is with respect to 17 March 2006, 0:00 UTC.The dashed line shows the baseline ADR value.The scheduled demand is shown with a solid-line marked with crosses (x) and the achieved departure rate, measured as the number of aircraft that departed in one-hour time period, is shown with another solid-line marked with circles (o).Observe that the scheduled demand was greater than the ADR value, whereas the achieved ('actual') departure rate is close to the ADR value.Comparing the scheduled demand and the achieved rate graphs in Fig. 3 between the locations marked as 28 UTC and 32 UTC, it is seen that the excess demand is modulated by shifting the flights to later times.Actual departure rates beyond 44:00 UTC should be ignored because departed flights that did not reach their destination airports prior to termination of the simulation were not counted.The arrival rate was also controlled in ACES to guarantee that the baseline AAR capacities are not exceeded.Figure 4 shows the baseline AAR value of 96, scheduled arrival demand and the achieved arrival rate at the Hartsfield-Jackson Atlanta airport.Observe that the arrival rate constraint was also met by delaying flights, which is reflected in the duration of the achieved arrival rate being close to the AAR value.It should be noted that most of the arrival delays are realized prior to departure at the departure airport and minimally in the airborne phase.In this sense, delays are mostly realized (imposed) at airports of origin both for ADR constraints at airports of origin and AAR constraints at the airports of destination.This is also the way most of the delays occur in the real air traffic system.For example, controlled departure times are issued at airports of origin during a Ground Delay Program at a destination airport.The values of dd t and gad t for each of the 34 OEP airports were obtained from the ACES baseline simulation.Table 7 lists these values along with the number of aircraft that departed from and arrived at each airport and the number of aircraft that landed at each airport during the twenty-four hour period spanning from eight UTC on 17 March 2006 to eight UTC on 18 March 2006 (location marked as 32 UTC in Fig. 2).Columns one and six list the airports.Departure-counts are listed in columns two and seven, and the total departure delays in minutes obtained by summing the departure delays of aircraft delayed by 15-minutes or more are given in columns three and eight.This 15minutes delay metric is commonly used by the FAA for assessing the performance of the air traffic system.Arrival-counts are provided in columns four and nine, and the total arrival delays in minutes obtained as the sum of arrival delays of aircraft delayed by 15-minutes or more are listed in columns five and ten.It should be noted that the delays in Table 7 cannot be compared with the OPSNET delays given in Table 4 because of their definitions.Delays in ACES are compared against schedule, whereas delays in OPSNET are compared with respect to the time when pilot requests permission to depart.In ACES, once a flight incurs departure delay, it can continue to incur departure delays as it arrives and departs from other airports.In the real system, it is possible that departure delay is only accounted once.Delays would not accrue in subsequent flight segments, if the air traffic controller permits the flight to depart soon after departure request is made by the pilot.Departure delay per flight is obtained as the ratio of the total departure delays to the departure-counts and the arrival delay per flight is obtained as the ratio of the total arrival delays to the arrival-counts.These ratios, obtained using the data in Table 7, are shown in Fig. 5.This figure shows that Hartsfield-Jackson Atlanta International (KATL) flights experience the most departure and arrival delays.One of the reasons is apparent from Fig. 3, which shows that the ratio of peak departure demand to departure capacity is 1.7.For comparison, Chicago O'Hare (KORD), which has similar ADR and AAR values as Atlanta, has a peak departure demand to capacity ratio of 1.1.Flights departing from George Bush Intercontinental/Houston Airport (KIAH) and flights arriving at Fort Lauderdale/Hollywood International (KFLL) also experience significant delays.The large difference between 2). | |
| B. Reduced Capacity ResultsOne-hundred-and-two ACES simulations were conducted with reduced ADR and AAR capacities listed in Table 3 for the time-durations given in Table 6.The baseline ADR and AAR values for the non-OEP airports listed in Table 2 were kept for all the simulations, only the values for OEP airports were altered for the sensitivity study.The first set of 34 ACES simulations were conducted by changing the ADR value for each OEP airport one at a time, while keeping the baseline ADR values for the other airports.The baseline AAR values for all OEP airports were kept for this set of simulations.Figure 6 shows an example of the achieved departure rate in response to ADR reduction at the Hartsfield-Jackson Atlanta airport from the baseline rate of 96 aircraft per hour to 48 aircraft per hour during 13:00 UTC through 16:00 UTC.The dashed-line in the graph shows the ADR value and the solid-line marked with circles shows the achieved rate.The scheduled departure demand is shown by the solid-line marked with crosses.The impact of the ADR reduction at Atlanta airport on the departure and arrival delays at the other airports is shown in Fig. 7.This figure shows the percentage increase or decrease in the delay values compared to the baseline delay values at those airports, which are given in columns three, five, eight and ten of Table 7.A key observation is that as departure delays at Atlanta increase, arrival delays at the other airports also increase.This is an expected result based on Eq. ( 10); it is interesting that the departure delays at some of the airports increase.This effect is explained by the fact that departures from these airports are connected to arrivals from Atlanta.The same physical aircraft arriving from Atlanta is flown out of these airports to other out-bound destinations.An arrival delay associated with these flights shows up as departure delay for the connected out-bound flights.Finally, one observes that the arrival delays also increase at Atlanta although the AAR values were not changed.This again is due to delayed departures from airports that depart aircraft for Atlanta.The impact of ADR reduction at each of the 34 OEP airports on the departure delays at other OEP airports is summarized in Table 8.The first column of this table lists the airport whose ADR was reduced and the header row indicates the impacted airport.A value of 89 in the first element of the first row states that total departure delay of flights delayed by 15-minutes or more at Atlanta increased by 89% compared to the baseline departure delay value of 151,897 minutes (see Table 7) due to reduced ADR at Atlanta.Similarly, the second element of the second row shows that the departure delay increased by 57% at Boston Logan airport due to reduced ADR at the Boston Logan airport.Note that the percentage values in the table have been rounded.Viewing Table 8 as a matrix, it is seen that the diagonal elements have a higher value compared to the off-diagonal terms.This is an expected result because ADR reduction at the airport directly affects departures from that airport.Closer examination reveals that for some of the airports, departure delays do not increase significantly with reduced ADR values.It was determined that for these airports, the departure demand is either lower or only slightly greater than the reduced ADR values.The only two airports -KMEM and KPHX for which the reduced ADR values were found to be same as the baseline values in the four months of operational data (see Tables 2 and3), additional departure delays were not expected.The effect of ADR reduction on the arrival delays is shown in Table 9. Viewing the data in Table 9 as a matrix, it is seen that the values of diagonal elements are low, which indicates that reduced ADR at an airport does not significantly increase arrival delays at that airport.Some airports -Atlanta (KATL), Houston (KIAH), John F. Kennedy (KJFK), San Francisco (KSFO) and Salt Lake City (KSLC) did not follow this trend.Reduced ADR at these airports had the effect of increasing arrival delays at these airports.Examining the rows of Table 9, it is seen that the off-diagonal terms are large for some airports.For example, the value of 41 in the first row under the KDFW heading means that total delays of flights arriving at Dallas/Fort Worth (KDFW) that were delayed by fifteenminutes or more increased by 41% compared to the baseline value in Table 7 due to reduced ADR at Atlanta.Increase in arrival delay should be expected because the delay caused by ADR reduction at the airports of origin can be expected to be propagated to the airports of destination.The significance of increase in delay should be judged by comparing the baseline delay value for the airport against the baseline delay values of other airports, which are given in Table 7.For example, an increase of 50% in delays at Atlanta is considerably more significant compared to the same increase at Salt Lake City.The next set of 34 ACES simulations were conducted with reduced AAR values at each of the 34 OEP airports.Baseline ADR values were kept for all the airports.Figure 8 shows the impact of AAR reduction at Atlanta on the other OEP airports.The bar-graphs show that the total arrival delay due to flights arriving late by fifteen-minutes or more increases by more than 90% compared to the baseline arrival delay in Table 7.The figure shows that departure delays at several airports increase due to reduced AAR at Atlanta.This is to be expected because the arrival constraint at Atlanta is met by delaying the out-bound flights to Atlanta at their airports of origin.Arrival delay at Atlanta also contributes to departure delay at Atlanta due to in-bound out-bound flight connectivity.This departure delay then propagates as arrival delay at other airports.In some instances, the departure and arrival delays are reduced slightly at other airports.This is essentially due to shifting of the departure and arrival times of the affected flights to times of lower demand at these airports.The results shown in both Figs.7 and 8 demonstrate that the impact of capacity reduction at one airport on the delays at another airport is complicated because of network (flight-connectivity) effects.Mathematical modeling of these effects is difficult, and therefore, a simulation capability like ACES is required for such an analysis.The impact of reduction of AAR at each airport on the departure delays at 34 OEP airports is summarized in Table 10.Data trends in this table are similar to those seen in Fig. 8.It should be noted that departure delays at La Guardia (KLGA), Minneapolis-Saint Paul (KMSP), Chicago O'Hare (KORD), San Francisco (KSFO) and Salt Lake City (KSLC) increase significantly due to their own reduced AAR rates.The sensitivity of arrival delays at the 34 OEP airports to reduced AAR at other airports is summarized in Table 11.This table shows that the reducing AAR at the airports, increases arrival delays significantly.Delays increase by more than 100% at Cleveland-Hopkins (KCLE), Charlotte/Douglas (KCLT), Newark Liberty (KEWR), Washington Dulles (KIAD), John F Kennedy (KJFK), La Guardia (KLGA), Minneapolis-Saint Paul (KMSP), Chicago O'Hare (KORD), Philadelphia (KPHL), Phoenix Sky Harbor (KPHX) and Salt Lake City (KSLC).The off-diagonal terms show that arrival delays also increase considerably at some airports due to AAR reduction at other airports.Instances are also seen where arrival delays decrease by a small amount.0 0 0 2 1 KPDX 0 0 0 -1 -1 0 1 -1 -2 2 1 -2 0 1 -3 4 KPHL 0 0 1 1 0 0 0 0 0 0 0 3 0 0 0 1 KPHX 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KPIT 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KSAN 0 0 -1 -2 1 2 0 -1 1 1 0 -1 -1 0 1 2 -1 KSEA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KSFO 0 0 0 0 0 -1 0 6 2 -1 0 0 0 0 8 11 KSLC 0 0 -2 -2 -1 -1 0 4 2 1 0 -3 -1 0 1 3 0 KSTL 0 -1 -1 0 0 -1 0 0 0 0 0 -1 0 0 0 0 KTPA 0 0 1 0 0 0 0 -10 KDEN 3 -1 1 -1 0 0 1 5 -2 -1 2 4 4 -3 1 3 KDFW 0 0 0 0 0 0 0 1 0 0 0 1 1 1 0 0 KDTW 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 KEWR 0 1 0 0 1 1 1 0 0 0 0 0 -1 0 0 0 KFLL -1 1 0 0 0 0 0 0 -1 0 0 0 0 0 0 1 KIAD 0 0 0 0 0 0 0 -3 0 0 0 0 -2 1 0 -1 KIAH 0 0 2 0 1 2 0 -1 0 1 2 2 -2 3 2 3 KJFK 0 1 0 0 0 1 0 -3 2 0 0 0 -1 -1 0 1 KLAS 0 0 1 0 0 0 0 2 0 1 0 15 1 4 1 0 KLAX 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KLGA 95 2 1 0 2 2 -1 -2 2 0 3 0 -1 1 0 4 KMCO 0 2 -2 0 0 1 0 -410 0 -1 0 1 0 -1 1 0 0 0 0 0 0 -1 0 KCLE 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 KCLT 0 0 1 1 2 1 1 1 1 1 1 0 0 0 1 1 KCVG 0 0 1 1 0 1 1 0 1 1 1 0 0 0 0 1 KDCA 0 0 0 0 0 0 0 0 0 1 0 0 0 0 -1 0 KDEN 0 0 -1 -1 2 1 5 4 2 2 2 -1 1 1 2 3 KDFW 0 1 0 2 0 0 0 3 1 1 1 0 0 0 0 2 KDTW 0 0 0 1 0 1 1 1 0 0 0 0 0 0 1 1 KEWR 0 2 2 3 5 2 3 0 2 4 3 2 2 2 1 2 KFLL 0 0 0 0 1 0 0 1 0 2 1 1 0 3 -2 1 KIAD 0 0 -1 2 1 0 0 0 0 1 0 0 0 1 0 2 KIAH 0 1 280 KSAN 0 0 0 2 2 0 -2 1 -1 1 -1 -1 1 1 2 1 KSEA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 KSFO 0 1 1 1 0 3 0 9 2 1 0 0 1 5 8 10 KSLC 0 0 0 4 0 1 -1 4 -1 0 0 -2 1 2 4 2 KSTL 0 0 0 0 0 0 -1 1 0 1 1 -1 0 0 1 0 KTPA 0 0 2 0 1 0 1 1 0 1 1 1 0 1 00 0 0 -1 0 0 1 0 0 0 0 0 0 0 1 KCLE 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 KCLT 1 1 0 1 0 2 1 1 1 0 3 0 0 0 2 1 KCVG 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 KDCA 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 KDEN 5 -1 1 0 -1 2 3 0 0 1 1 3 4 3 1 -1 KDFW 0 0 1 1 0 1 2 1 1 1 1 3 2 2 0 0 KDTW 0 0 2 1 0 2 0 0 0 0 1 1 0 -1 0 0 KEWR 0 3 3 3 2 2 3 4 0 1 4 1 0 1 4 1 KFLL 0 1 1 1 0 0 1 0 0 0 2 1 0 1 1 2 KIAD 0 0 0 0 0 4 4 4 2 0 1 3 -1 0 1 0 KIAH 1 0 1 7 1 4 4 -1 2 2 4 5 -1 4 3 2 KJFK 0 3 0 1 2 3 2 4 0 1 1 4 1 2 4 4 KLAS 0 0 5 3 0 8 2 5 1 7 0 21 2 8 4 1 KLAX 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KLGA 2 2 4 2 4 3 7 1 3 0 8 1 -1 1 -1 3 5 KMCO 0 0 1 1 0 1 1 0 1 0 0 0 0 0 -1 -1 KMDW 0 0 2 0 0 3 0 3 0 0 0 0 0 0 2 0 KMEM 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KMIA 0 0 0 1 0 1 0 0 1 0 1 0 0 0 0 2 KMSP 1 140 0 0 KSAN 1 -1 -2 0 0 0 0 1 1 2 0 4 0 2 1 -1 KSEA 0 0 0 1 0 1 0 3 0 0 0 0 0 1 0 0 KSFO 0 0 0 0 0 2 3 4 1 3 0 8 17 11 1 0 KSLC 0 -1 1 -3 0 1 -1 5 -1 4 0 7 5 77 2 -1 KSTL -1 -1 0 0 -1 0 2 0 1 0 2 0 0 1 0 -1 KTPA 1 0 3 1 0 0 0 2 0 0 1 1 0 1 1 2The final set of 34 ACES simulations were conducted with both ADR and AAR reduced together at each airport, one at a time, while keeping baseline ADR and AAR values at the other airports to complete the sensitivity study.Tables 12 and13 summarize these results.Table 12 presents the impact on departure delays at the 34 OEP airports and Table 13 shows the impact on arrival delays.Both these tables show that the departure and arrival delays increase substantially at the airports were capacity is reduced.Other observations made in the previous tables remain the same for these tables too.The data presented in Tables 12 and13 show that the percentage change in departure and arrival delays at the affected airports due to both reduced ADR and AAR capacities is close to the maximum of delay change due to reduced ADR capacities or AAR capacities given in Tables 8 through 11.For example, departure delay increase of 93% at Dallas Fort Worth (KDFW) due to both ADR and AAR reduction at Hartsfield-Jackson Atlanta (KATL) (see Table 12) is closer to 85% increase in departure delays due AAR reduction at KATL (see Table 10) compared to 39% increase in departure delays due ADR reduction at KATL (see Table 8).These initial results show that it might not be possible to simply add the impact due to ADR capacity reduction to that due to AAR reduction to derive the combined impact of both ADR and AAR capacity reduction.The utility of the sensitivity data in Tables 8 through 13 for developing delay forecasting models remains to be seen.The results also provide insight into flight demand between pairs of airports.For example, the impact of capacity reduction at Atlanta on delays at Dallas Fort Worth (KDFW) is much more compared to those at San Francisco International (KSFO).This insight can also be gained by analyzing origin-destination pairs in the ACES FDS file.System-wide impact due to each airport is easily determined by first using the percent change in delays given in the rows of Tables 8 through 13 with the baseline delay values reported in Table 7 for determination of delay increase or decrease at each affected airport, and then adding these delay values.Figure 9 shows the increase in system-wide departure delays due to ADR and AAR reduction, obtained using the values in Table 12. Figure 10 depicts the impact on system-wide arrival delays obtained using values in Table 13.Both Figs. 9 and 10, show that capacity constraints at Atlanta, compared to constraints at other airports, have a significantly higher impact on the total system departure and arrival delays.One of the reasons is that there are significantly more flights with connected segments out of Atlanta compared to any other airport.Atlanta had 1,347 connected flights compared to 1,017 at Chicago, the airport with the next higher number of connected flights.In the real system the delays at Atlanta might be considerably less because of the following reasons.Fifty-percent capacity for three hours with a peak demand capacity ratio of 3.3 (see Fig. 6), which means three times the demand, is extreme.When delays are this severe, flights are cancelled in the real system.Flights were not cancelled during the ACES simulations.0 3 -2 0 2 0 0 1 0 0 0 KBWI 0 1 0 -2 1 -1 0 1 -2 2 1 -2 -2 0 -1 0 KCLE 0 1 1 29 1 2 1 -1 1 2 1 0 2 0 -1 0 KCLT 0 0 -1 -1 28 2 -1 -2 4 2 1 -1 -1 0 0 1 KCVG 0 0 0 0 0 6 0 0 0 1 0 0 0 0 -1 0 KDCA 0 1 -1 1 0 0 6 0 1 1 0 0 0 0 -1 0 KDEN 0 0 1 0 -1 1 2 20 -2 0 1 1 2 0 1 4 KDFW 0 0 0 1 0 0 1 3 38 0 0 0 0 0 0 0 KDTW 0 0 0 1 0 2 1 -1 -1 10 0 -1 1 0 0 0 KEWR 0 11 4 4 7 4 1 -2 0 19 14 1 8 0 0 -1 KFLL 0 -1 -2 -2 2 -1 0 -1 3 3 1 20 -1 0 -1 2 KIAD 0 1 -2 4 2 3 0 0 3 3 6 0 14 0 0 1 KIAH 0 0 -1 1 1 1 3 -2 6 2 -1 -1 1 0 0 1 KJFK 0 12 -180 0 -1 -1 -1 0 0 0 0 0 0 0 0 0 0 KSAN 0 0 1 0 -1 -1 0 -2 0 0 0 0 2 0 2 1 KSEA 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 KSFO 0 0 -1 -1 -1 -1 -1 6 -2 -1 0 0 -2 0 -2 31 KSLC 0 -1 -2 0 -1 -3 1 11 5 -1 1 0 -1 0 0 7 KSTL 0 -1 -2 -2 0 -2 2 2 -2 1 0 -2 1 0 -2 -4 KTPA 0 0 -2 -1 2 0 -20 -4 0 -1 0 0 -1 1 1 KMDW 0 0 1 3 0 0 0 1 -1 -1 0 0 0 0 1 0 KMEM 1 0 2 -2 3 -1 1 0 0 -2 0 0 0 -3 3 0 KMIA 0 -1 1 0 0 -1 0 0 -1 0 0 -1 0 0 -1 0 KMSP 0 -1 0 1 0 0 -1 5 -2 6 0 0 0 1 0 1 KORD 0 0 2 1 -1 2 0 -1 2 9 -1 -1 0 -1 -4 -2 KPDX 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KPHL 0 1 -1 0 1 -1 0 0 -3 0 1 0 0 1 -2 0 KPHX -1 -2 5 5 0 -2 -1 14 0 0 2 0 -1 -2 -3 13 4 KPIT 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 -1 0 KSAN 0 0 0 0 1 0 0 -1 0 0 0 0 0 0 0 2 KSEA 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 1 KSFO -1 0 2 -1 0 1 -3 2 1 -2 -3 -1 -1 0 4 17 KSLC 0 0 3 6 -1 0 1 -1 1 -3 -3 -2 -1 -1 -1 2 2 KSTL 0 -1 0 2 0 2 -3 -1 -6 1 -2 -2 0 0 -2 0 KTPA 0 -1 1 -1 -1 1 -2 2 -1 1 0 0 -1 0 0 -10 0 -1 0 -1 0 1 0 4 0 -1 0 -2 -1 0 KBWI 0 -1 -1 -6 -1 -1 0 0 -1 0 0 0 -1 1 1 0 -1 KCLE 0 0 1 0 0 1 -1 0 0 1 -1 -1 -1 0 1 0 0 KCLT -1 -1 0 2 -1 1 -1 0 1 0 9 1 0 0 -2 0 KCVG 0 0 0 0 0 0 0 0 0 0 0 1 0 0 -1 0 KDCA 0 0 0 0 0 0 -1 2 0 0 0 1 -1 0 -1 -1 -1 KDEN 4 -1 -1 4 0 0 2 2 2 0 5 3 -1 3 1 -1 KDFW 0 0 0 0 0 2 0 -2 0 0 0 1 -1 1 0 0 KDTW 0 0 0 -6 -1 1 1 1 -1 0 1 1 -1 -1 1 -1 KEWR 0 -1 0 -1 -1 -1 2 -1 0 0 1 3 -1 -2 1 1 0 KFLL 2 2 0 0 -1 1 -1 -1 2 0 5 1 0 1 1 1 KIAD 0 -1 0 1 1 -1 0 1 -1 0 3 3 -2 2 0 2 KIAH 1 -1 -2 -2 -1 2 -1 -1 -1 1 1 0 -3 2 -1 -2 KJFK -1 0 -1 0 -2 -2 1 -2 -1 1 -2 0 0 0 -2 1 KLAS 0 1 2 -2 1 0 0 1 1 1 3 10 -2 6 0 3 KLAX 0 0 0 0 0 0 0 0 0 1 0 2 0 1 0 0 KLGA 153 -2 9 1 -2 -2 5 -2 0 3 5 2 -2 1 0 0 KMCO 0 1 -1 1 0 0 -2 0 1 0 3 1 0 0 1 0 KMDW 0 1 48 0 0 0 0 2 0 0 -1 1 0 0 1 0 KMEM 2 -2 -1 65 0 -4 1 -1 0 2 4 2 -3 1 0 2 KMIA 0 -1 2 -1 16 0 0 0 1 0 0 1 -1 0 -1 1 KMSP 0 0 4 0 0 405 -2 1 0 0 4 1 -1 -1 -3 3 -1 KORD 0 -1 -1 2 -1 5 275 -2 0 0 3 12 -1 -1 -2 2 -1 KPDX 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KPHL 0 1 3 -72 KMCO 0 1 0 -1 -1 1 -1 1 -1 1 0 1 -1 0 0 2 KMDW 0 0 1 3 0 0 0 1 0 5 0 0 0 0 0 0 KMEM 0 0 1 2 0 2 1 -1 6 4 -2 0 2 0 -1 2 KMIA 0 -1 -1 0 0 -1 -1 -1 0 0 -1 -2 -1 0 0 -1 KMSP 0 1 0 5 0100 0 -1 -1 -1 0 0 0 0 0 0 0 0 0 0 KSAN 0 0 -1 -2 2 2 1 -3 1 1 0 0 -1 0 0 -2 KSEA 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 KSFO 0 -1 -2 -3 -1 0 -1 13 0 -1 0 -1 -2 0 6 34 KSLC -1 -1 -3 -1 -4 -1 0 10 7 0 -1 -1 -2 0 -1 8 KSTL 0 -1 -3 -3 -1 -2 1 2 -2 1 0 -2 -1 0 -2 -2 KTPA 0 1 -1 -12 0 -1 0 -1 1 0 KBWI 1 -2 1 -2 -1 3 -1 2 -2 0 1 -1 2 -1 1 5 KCLE 1 0 6 0 0 0 0 1 -1 0 2 0 0 -1 0 -1 KCLT 2 0 2 0 4 6 5 -1 1 0 2 1 0 -2 -3 2 1 KCVG 0 1 1 0 0 0 1 -3 0 0 0 1 0 0 1 0 KDCA 1 1 0 0 -1 1 2 -3 1 0 1 -1 0 -1 1 3 KDEN 2 -1 1 0 0 3 5 2 -1 3 -5 17 -3 1 1 4 KDFW 0 0 0 1 0 0 4 -4 0 0 1 1 -1 0 -1 3 0 KDTW 1 -1 1 -3 -1 2 1 0 -1 0 1 2 1 -2 1 -1 KEWR 2 4 1 1 5 4 17 -5 1 0 23 -1 0 -3 0 3 KFLL 0 5 2 -1 -3 1 -1 -2 1 0 -1 1 2 -1 -1 1 15 KIAD 3 0 1 2 -2 0 1 0 0 0 5 0 0 0 13 4 KIAH 2 -2 4 2 -1 7 0 -1 -1 1 -2 3 -4 2 6 3 KJFK 2 2 -2 -1 1 4 2 -3 1 -1 9 -1Figure 2 .2Figure 2. ACES simulated aircraft counts and actual aircraft counts comparison. | |
| Figure 3 .3Figure 3. Departure rate achieved at Hartsfield-Jackson Atlanta airport with baseline airport and sector capacities. | |
| Figure 4 .4Figure 4. Arrival rate achieved at Hartsfield-Jackson Atlanta airport with baseline airport and sector capacities. | |
| Figure 5 .5Figure 5. Baseline departure and arrival delays at the 34 OEP airports. | |
| Figure 6 .6Figure 6.Departure rate achieved at Hartsfield-Jackson Atlanta airport with reduced ADR. | |
| Figure 9 .9Figure 9. System-wide impact of ADR and AAR reduction on departure delays. | |
| Table | |
| Table 2 .2Baseline capacities for the 74 ASPM airports.. Hartsfield-Jackson Atlanta International airportcapacity on March 17, 2006.Local Hour Weather ADR AAR Total0IA96961IA96962IA96963IA96964IA96965IA96966IA96787IA96828VA96949VA969410VA969411VA969412VA969413VA969414VA969415VA969416VA969417VA969418VA969419VA969420VA969421VA969422VA969423VA9694 | |
| Table 8 of8Ref. 8. Along with the flight-plan data, adaptation data and capacity data are required for ACES simulation.Sector and center geometry definitions in the January 1, 2005 adaptation data obtained from ETMS have been used to generate the results in this paper.Baseline sector capacity values are also derived from January 1, 2005 ETMS data tables. | |
| Table 4 .4OPSNET delay data.Date3/17/2006 3/18/2006 3/19/2006# Aircraft Delayed7831441Weather1661199Volume396129Total Delay (min.)22,05414,21070,119Average Delay (min.)28.1729.8548.66 | |
| Table 3 .3Reduced capacities for the 34 OEP airports.Airport ADR AAR Total Airport ADR AAR TotalKATL484896 KLGA2550KBOS262652 KMCO3672KBWI282856 KMDW2448KCLE282856 KMEM56116KCLT303060 KMIA3262KCVG5157108 KMSP2652KDCA262652 KORD50100KDEN6262124 KPDX3264KDFW5659115 KPHL2654KDTW6048108 KPHX48108KEWR303060 KPIT4080KFLL181836 KSAN2856KIAD303262 KSEA2856KIAH484896 KSFO2752KJFK202040 KSLC4080KLAS303464 KSTL3264KLAX5357110 KTPA1939 | |
| Table 5 .5Flight segments operated by the same physical aircraft.Segment Tail-Origin Destinationnumber1N12345 KSFO KLAX2N12345 KLAX KDEN3N12345 KORD KIAD4N12345 KIADKORD | |
| Table 6 .6Time periods for reduced ADR and AAR values at the 34 OEP airports.Airport Start-Start-End-End-Airport Start-Start-End-End-datetimedatetimedatetimedatetime(UTC)(UTC)(UTC)(UTC)KATL3/1713:00 03/17 16:00 KLGA03/17 19:00 03/1722:00KBOS3/1723:00 03/182:00 KMCO 03/17 20:00 03/1723:00KBWI3/1720:00 03/17 23:00 KMDW 03/17 23:00 03/182:00KCLE3/1723:00 03/182:00 KMEM 03/17 13:00 03/1716:00KCLT3/1723:00 03/182:00 KMIA03/17 23:00 03/182:00KCVG 3/1723:00 03/182:00 KMSP03/17 23:00 03/182:00KDCA 3/1723:00 03/182:00 KORD03/180:00 03/183:00KDEN 3/1716:00 03/17 19:00 KPDX03/17 14:00 03/1717:00KDFW 3/1723:00 03/182:00 KPHL03/17 23:00 03/182:00KDTW 3/1722:00 03/181:00 KPHX03/17 16:00 03/1719:00KEWR 3/1723:00 03/182:00 KPIT03/17 19:00 03/1722:00KFLL3/1721:00 03/180:00 KSAN03/17 15:00 03/1718:00KIAD3/1720:00 03/17 23:00 KSEA03/181:00 03/184:00KIAH3/1718:00 03/17 21:00 KSFO03/17 18:00 03/1721:00KJFK3/1721:00 03/180:00 KSLC03/17 16:00 03/1719:00KLAS3/1723:00 03/182:00 KSTL03/17 18:00 03/1721:00KLAX 3/183:00 03/186:00 KTPA03/17 21:00 03/180:00where sgdttatt=tagdt+tatot,(5)where agdttdd=tatt!tstt.(6)Scheduled gate arrival time, sgat t , is defined as:tsgat=tstt+tuft+tutit,(7)where stt t is the scheduled takeoff time (wheels-off time), uft t is the unimpeded flight time and utit t is the unimpededtaxi-in time. Actual gate arrival time, agat t , is similarly defined is terms of the actual takeoff time, att t , actual flighttime, aft t , and the actual taxi-in time, atit t , as:tagat=tatt+taft+tatit.t is the scheduled gate departure time and utot t is the unimpeded (assuming it is the only aircraft) taxi-out time.Recollect that the scheduled gate departure time is available in the FDS file and that the unimpeded taxi times for the airports are obtained from the ASPM database.The actual takeoff time, att t , is similarly defined as: t is the actual gate departure time and atot t is the actual taxi-out time.Actual times are not real ones but simulated times.Departure delay is then obtained as: | |
| Table 7 .7Baseline delay results for 34 OEP airports.Airport Dep.Dep. DelayArr.Arr. DelayAirport Dep.Dep. DelayArr.Arr. Delaycount! 15 min.count! 15 min.count! 15 min.count! 15min.KATL1,761151,897 1,787166,517 KLGA64714,71718,934KBOS63312,13956813,336 KMCO56017,17820,659KBWI41812,5584269,586 KMDW4544,1945,509KCLE4184,1704083,707 KMEM6137,9963,278KCLT73510,1047356,940 KMIA5897,13011,928KCVG7216,6536063,368 KMSP7493,9425,657KDCA42810,8764336,157 KORD1,55811,015 1,55215,074KDEN8753,1748775,233 KPDX3721,6192,506KDFW1,0354,508 1,0016,009 KPHL80221,18210,715KDTW7514,8607275,714 KPHX95328,81217,893KEWR76021,31671314,047 KPIT3573,5613,524KFLL44811,49948720,481 KSAN3372,4743,617KIAD5968,0256107,532 KSEA4992,1963,184KIAH93045,94284312,642 KSFO5928,74619,072KJFK57412,6205087,847 KSLC6992,9343,610KLAS93517,49682616,825 KSTL4202,7984,258KLAX1,0136,1768607,700 KTPA4065,7346,431departure arrival | |
| Table 8 .8Impact of ADR reduction at one airport on departure delays at other OEP airports.100.0090.0080.00Change in delay (%)30.00 40.00 50.00 60.00 70.0020.0010.000.00KATLKBOSKBWIKCLEKCLTKCVGKDCAKDENKDFWKDTWKEWRKFLLKIADKIAHKJFKKLASKLAXKLGAKMCOKMDWKMEMKMIAKMSPKORDKPDXKPHLKPHXKPITKSANKSEAKSFOKSLCKSTLKTPAAirportdeparture arrival Figure 7. Impact of ADR reduction at Hartsfield-Jackson Atlanta airport on delays at other OEP airports. | |
| Table 9 .9Impact of ADR reduction at one airport on arrival delays at other OEP airports.AirportKATLKBOSKBWIKCLEKCLTKCVGKDCAKDENKDFWKDTWKEWRKFLLKIADKIAHKJFKKLASKLAXKATL37101734263536274127106135514KBOS02311060022106-11KBWI | |
| Table 10 .10Impact of AAR reduction at one airport on departure delays at other OEP airports.100.0090.0080.0070.00Change in Delay (%)20.00 30.00 40.00 50.00 60.0010.000.00-10.00-20.00KATLKBOSKBWIKCLEKCLTKCVGKDCAKDENKDFWKDTWKEWRKFLLKIADKIAHKJFKKLASKLAXKLGAKMCOKMDWKMEMKMIAKMSPKORDKPDXKPHLKPHXKPITKSANKSEAKSFOKSLCKSTLKTPAAirportdeparture arrival Figure 8. Impact of AAR reduction at Hartsfield-Jackson Atlanta airport on delays at other OEP airports. | |
| Table 11 .11Impact of AAR reduction at one airport on arrival delays at other OEP airports.AirportKATLKBOSKBWIKCLEKCLTKCVGKDCAKDENKDFWKDTWKEWRKFLLKIADKIAHKJFKKLASKLAXKATL96-701238528-114277-122-65KBOS0471-1000200-1-103-10KBWI016220-10-310-20-1-10KCLE0011020200-110-10111KCLT001517701-1010-1-1-111KCVG00000530-1-20000010KDCA01000-1480-20-1-1000-1KDEN00121235811-100-1-24KDFW010000-118001000-10KDTW001-1000-1-2510-100-11KEWR022700-10-26115-102-12KFLL0-1103-330-1004310-22KIAD00142220030-10213KIAH0002-1-230-21-1-153020KJFK05183920-3-10-2012411KLAS001300-1-3100000985KLAX00000000000000028KLGA015-21112-334-1030-40-1-242KMCO0011100 | |
| Table 12 .12Impact of ADR and AAR reduction at one airport on departure delays at other OEP airports.AirportKATLKBOSKBWIKCLEKCLTKCVGKDCAKDENKDFWKDTWKEWRKFLLKIADKIAHKJFKKLASKLAXKATL1009155617413527938792432513012KBOS05820104-302011010KBWI01111-100-211-2-1000KCLE011341210120020-11KCLT00006121-2421-1-1001KCVG000002800010010-10KDCA01-1100110110000-10KDEN001-1-13187112000-14KDFW0001001411100000-10KDTW0001021-1-1360-11000KEWR01264652-20195628000KFLL0-1-1-12-100330330001KIAD02-2534003460540-10KIAH01060323114-10130-11KJFK01418271105-121010002KLAS0000001244100007727KLAX00000003000000112KLGA023-11896295846-35601 | |
| Table 13 .13Impact of ADR and AAR reduction at one airport on arrival delays at other OEP airports.2-2-17 | |
| Airport Increase in total system delay (minutes) arrival delay 256,989 minutesFigure 10.System-wide impact of ADR and AAR reduction on arrival delays.800006000040000200000KATLKORDKLGAKPHLKMSPKEWRKLASKJFKKIAHKPHXKSFOKBOSKSLCKIADKCLTKDFWKDENKFLLKTPAKMDWKMIAKMEMKCLEKPDXKCVGKSEAKDCAKDTWKLAXKMCOKSANKPITKBWIKSTL800006000040000200000KATLKORDKLGAKMSPKPHXKLASKPHLKEWRKSFOKJFKKIAHKCLTKFLLKSLCKIADKBOSKDFWKTPAKDENKCLEKSEAKMEMKMDWKDCAKCVGKLAXKDTWKMIAKMCOKPDXKSANKBWIKSTLKPIT | |
| Airport Increase in total system delay (minutes) departure delay 215,807 minutes | |
| AcknowledgmentsThe authors wish to thank Dr. Robert Windhorst of NASA Ames Research Center for his support of this study.We also thank the Raytheon Team for enhancing the flight-connectivity functionality in the Airspace Concept Evaluation System (ACES), without which this study would not have been possible.Finally, we thank Tom Romer of NASA Ames Research Center for suggesting additional ways of examining the data and critiquing our results.His comments have helped improve the paper. | |
| The results presented in this paper were generated with a single day of air traffic data.The trends seen in the results are expected to hold for days with similar characteristics as those of the day used for computing the results.If the demand patterns change, numerical values will change but the method described in the paper can be used to generate the new sensitivity matrices.The impact of capacity reduction was studied by altering capacities one airport at a time.On the typical day multiple airports are impacted.The impact of combinations of ADR and AAR capacity reductions at multiple airports has not been studied. | |
| V. SummaryThis paper described a method for sensitivity study in which the airport departure rate (ADR) and airport arrival rate (AAR) were reduced at each of the 34 major airports in the United States, one at a time, and the impact on the departure and arrival delays at these airports was assessed.To compute these delay values, the Airspace Concept Evaluation System (ACES) was used.One-hundred-and-three ACES simulations were conducted to complete the study.In the first set of 34 runs, only the ADR values were altered.The AAR values were kept at their baseline level.In the second set of 34 runs, the AAR values were changed.The ADR values were kept at their baseline level.Both the ADR and AAR values were reduced for the final set of 34 simulations.The results obtained show that ADR reduction at an airport directly increases the departure delay at that airport.This departure delay then appears as arrival delay at the other airports.It was observed that the departure delays at other airports increase indirectly due to flight-connectivity effects.Reduction of AAR was seen to increase the arrival delay at the affected airport.Passing back of this arrival delay causes the departure delay to increase at the airports sending flights to this affected airport.Flight-connectivity was responsible for causing departure delays at the affected airport.Data tables in the paper provide numerical values that quantify the degree of impact of capacity reduction at one major airport on another. | |
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