August 12, 2003, Chapter 22, Combinatorial Auctions, Peter Crampton, Yoav Shoham and Richard Steinberg (editors), to be published, Review DRAFT NOT for Distribution
Auctions for the Safe, Efficient and Equitable Allocation of Airspace System Resources
Michael Ball
Robert H. Smith School of Business & Institute for Systems Research
University of Maryland
College Park, MD 20742
George L. Donohue and Karla Hoffman
Systems Engineering and Operations Research Department
George Mason University
Fairfax, VA 22030
ABSTRACT:
In this paper, we present evidence of the need for the specification of property rights associated with airport departure and arrival time slots and then provide the rationale and means for using auctions to allocate such property rights. We provide a historical look at slot allocation in the U.S. and the consequences of prior and current practices on both safety and competition. It is shown that the particular characteristics of aviation slot allocation suggest the need for three types of market mechanisms: an auction of long-term leases of arrival and/or departure slots, a market that supports inter-airline exchange of long-term leases and a near-real-time market that allows for the exchange of slots on a particular day of operation. We describe how certain concepts and tools underlying Collaborative Decision Making (CDM) provide a natural basis for developing the near-real-time market and present a broad overview of the special characteristics of aviation slot auctions and appropriate research topics.
11.0 Introduction/Background
Most countries attempt to design their air transportation system so that it is economically viable, safe and efficient. As the system evolves, changes are necessary to assure that these goals continue to be met. Although air transportation in the United States has a comparable safety record to that of automobile travel (on an exposure to risk time basis, (The Royal Society 1992)), the margin of safety is slowly eroding under the demands for more enplanement opportunities. The 1978 deregulation of the US route structure was intended to increase competition within the airline industry and thereby improve efficiency, decrease cost to travelers and expand the overall flying opportunities. This policy initially provided increased enplanement opportunities at reduced prices because there was sufficient capacity in the system to allow such growth. However, the current policies and procedures do not produce a similar effect in a capacitated system. In fact, these policies impede the need to build additional airports and overhaul the technology both within air traffic control and on airplanes. Without such expansion, more system elements are likely to become capacity-limited. In such a system it is essential to use system resources efficiently. We therefore provide suggestions for mechanisms to both expand the capacity and to assure that the current, limited capacity is used both safely and efficiently.
As the U.S. National Air Transportation System (NATS) becomes highly capacity constrained along multiple dimensions, it requires feedback mechanisms that can react along multiple time scales to adjust system behavior (Fan and Odoni 2002). Today, almost a quarter of a century after airline deregulation in 1978, strategic airspace management exercises little or no control over the number of aircraft that are scheduled to land and depart from various airports. It can only react when the system is overloaded. Thus, the U.S. airlines implicitly are responsible for setting constraints on airport operations as part of their scheduling process. The policies of the U.S. Department of Transportation (DoT) and the Federal Aviation Administration (FAA) effectively encourage these airlines to overbook and then cancel or delay flights leaving the system regularly in crisis mode, with re-scheduling the norm rather than the exception. Similarly, regional governments that wish to determine their demographic growth patterns are powerless to shape, or even to suggest, how the airspace in their region is used. The driving forces behind this paper are the questions: what forces led to this situation and what policy changes might be made to improve the U.S. national air transportation system crisis.
We begin by providing a description of the history of the U.S. Aviation System and then proceed, thereafter, to explain how market-clearing mechanisms might be able to rectify many of the shortcomings of the current system (see (Mineta 1997; Commision on the Future of the US Aerospace Industry, 2002) for background.)
.
History of US Aviation:
From 1938 to 1978 the Civil Aviation Board (CAB) managed the nation’s air transportation route (and industry) structure (Gleimer 1996). Many, including most economists, felt this administrative process did an inefficient job of providing transportation services (Rochester 1976; Preston 1987). Figure 1 shows how the growth rate of Revenue Passenger Miles (RPM), normalized by GDP, was stagnating just prior to 1978 (data taken from (DOT/BTS 2001)). Prior to 1978, air travel was relatively expensive and considered by many to be only for the upper echelons of society. Immediately after the deregulation act, prices fell and industry productivity and frequency of service increased dramatically. Fig. 2 illustrates how deregulation in both the U.S. and Europe initially increased airline productivity (Alamdari and Morrel 1997), even though FAA productivity did not change (with the exception of the effect caused by the air traffic controllers strike in 1981). However, after 1990, there was a leveling off of airline productivity (Donohue 2002). The lack of incentives to adopt new technology and the political inability to add new airport infrastructure began to limit growth, thereby creating the inevitable rise in queuing delays as the system approached the maximum demand to capacity ratio (Donohue and Shaver 2000).
Figure 1. US Transportation Growth for Major Modes normalized to 1960 levels and GDP growth. Source US Department of Transportation Statistics.
Figure 2. A relative comparison of Productivity Trends for the US Air Traffic Control System and both US and European Airlines Post Deregulation (industry data taken from (Alamdari and Morrell 1997)
Even prior to 1978, however, some airports were already congested. Four airports had been arrival slot controlled since 1968 under the High Density Rule (HDR): New York’s Kennedy (JFK) and LaGuardia (LGA), Chicago O’Hare (ORD) and Washington’s (Reagan) National (DCA). Today, the air transportation situation looks very different than it did in 1978. Many U.S. airports are becoming scheduled at levels that exceed the FAA’s estimate of a maximum safe operational rate (DOT Benchmark report 2001) (Haynie 2002). The major domestic U.S. air carriers use the hub-and-spoke system that brings passengers from smaller cities to hubs that will then transport them in an economical way to their final destination. Hub operations tend to concentrate very large numbers of flight arrivals and departures over short time periods. In some cases, airlines maintain near-monopoly control over hub airports so that newer airlines face significant barriers to entry into these airports.
On April 5, 2000, the semi-deregulation of the slot controls went into effect with the enactment of the AIR-21 bill (Federal Register 2000), which among other things, directed the DoT to totally eliminate slot controls at the four US HDR airports by 2007, and to increase immediately the number of slots allocated for regional service at LGA. This act led to the immediate and extreme congestion of air traffic activity at LGA (Fan and Odoni 2002). Strong “network effects” meant that the LGA delays induced additional delays throughout the NATS.
LGA has been arrival slot controlled (approximately 32 arrivals per runway per hour) since 1968, due to concerns about congestion and community noise at that airport. These slot controls were maintained even after the CAB was abolished in 1978. Figure 3 shows the scheduled number of flights at LGA in 2000. The schedule consists of both arrivals and departures in 15-minute intervals from 7 am in the morning to 10 pm at night. LGA has one arrival runway and one orthogonal crossing departure runway. The FAA officially considers the maximum safe level of operations under favorable weather conditions to be 40 arrivals and 40 departures per hour (i.e. 10 arrivals per 15 minute epoch) under visual conditions. Under reduced visual conditions (Instrument Flight Rules or IFR), this airport is supposed to be reduced to 32 arrivals and 32 departures per hour (i.e. 8 arrivals per 15 minute epoch). Figure 4 shows that the actual operational rates under the more restrictive, and slightly more hazardous IFR conditions frequently exceed the (32,32) rate (DOT Benchmark 2001). It will be shown later that this rate was set by Runway Occupancy Time (ROT) considerations and not aircraft wake vortex separation standards, which are more restrictive. The wake vortex problem was unknown in 1968 when most commercial aircraft were of medium size. With the introduction of both wide-body aircraft (heavy) and small regional jets (RJ’s) in a highly dynamic mixture, this safety problem is of growing concern (Haynie, 2002).
Figure 3. LGA Scheduled Number of Arrivals in 15 minute increments compared to the FAA estimate of safe aircraft operational separation of 8 (32 Arrivals / Hr.) under Instrument Meteorological Conditions (IMC) (FAA 2001)
Figure 4. LGA one-hour IMC Arrival-Departure Operation Rates for April and October 2000 (FAA 2001). Notice that Arrivals in excess of 33 Arrivals per Hour imply average aircraft separations of less than 3 n mi or 80 second separation.
The fact that there are two different capacity levels: one for good weather conditions and another for inclement conditions, further complicates the process of scheduling. Also, FAA regulated separation rates change depending upon whether a small aircraft follows a large aircraft (in which case the separation must be larger) due to aircraft wake vortex encounter concerns. These alternative landing and takeoff separation rules are quite complex and not considered in the overall determination of how many flights should be allowed to be scheduled during any given time period.
A question naturally arises: why do the airlines schedule operations that exceed the safe departure/arrival rate that an airport can support, thus generating excessive flight delays, cancellations and loss-of-separation violations? The answer is competition. If airline A acts responsibly and does not increase its schedule at a congested airport, it will have voluntarily provided another airline with the opportunity to schedule more flights at that airport. Conversely, if airline B decides to increase its schedule in an attempt to increase city pair options and flight frequency (but in reality only increasing congestion and delay for all airlines), airline A may lose market share. Under policies currently in effect, if scheduled flights at that airport are, at some time in the future, legislatively or procedurally reduced through re-regulation, then the airline with the greatest scheduled flights is likely to argue and receive more of the available flights. Thus, the risk is not only the reduction of market share currently, but also the risk of a permanent reduction in market share. In addition, at an airport not dominated by a single carrier (e.g. LGA), when an airline adds another flight the delay experienced by that flight may be small relative to the total delay to other flights caused by that additional flight. Thus, only a small portion of the “delay cost” of adding the flight may be internalized by the initiating airline.
LGA may be the extreme case, but many US airports and airlines are experiencing similar situations. Table 1 shows the demand to capacity ratio of 20 major US airports. The Demand/Capacity (D/C) ratio is based upon FAA computed good weather capacity calculations and measured average operational rates. When the D/C ratio approaches one, queuing theory predicts that the delay will grow exponentially.
Another way of looking at the congestion issue is to look at a measure of competition at a given airport. The Herfindahl-Hirschman Index (HHI) is a measure of industry competition. According to (Cooper 2000), studies of the hub system within the US have shown that fare revenues are higher on average for trips to and from major hub airports, with a few concentrated hub airports showing significant premiums over a decade; also, the higher premiums are realized by the dominant carrier in that hub, while fares charged by the other carriers in that hub are similar to the fares charged in less concentrated airports. The hub airports that have a dominant carrier typically have a high HHI.
One could argue, on a theoretical basis, that the more competition at an airport, the more tendencies there would be to over-schedule (i.e. monopolists will totally internalize the cost penalty of the delays they cause themselves and therefore not over-schedule). Thus, under current procedures, from the perspective of driving down prices, one would like competition, but from the perspective of keeping congestion at a reasonable level one would like to discourage competition but only if the monopolist would internalize all delay costs and therefore operate at the optimum delay value. Unfortunately, the data in Table 1 does not support this hypothesis.
Table 1. Major Airport Slot Control Status, Maximum Arrival Rate and AircraftSize
Mixture.
Note in Table 1 that non-slot controlled airports like Atlanta Hartsfield (ATL) have both high market concentration (high HHI) and high delay values. Also, even the current slot controlled airports are experiencing high delays because they are operating near the maximum capacity level. If the current slot controls on these high demand airports expire in 2007, they will undoubtedly become even more congested, as seen at LGA in 2001. This argues for the need for slot allocation measures that both encourage competition and avoid congestion.
Perhaps the most important argument for a new slot control system is the effect of operating overscheduled airports at high demand to maximum capacity ratios. The recent data and analysis in (Haynie 2002) indicate that loss of the regulated safe separation distance of aircraft is positively correlated to the aircraft arrival demand to maximum runway capacity ratio (Figure 5). This will be discussed in more detail in the next section.
Figure 5. Number of Near Midair Collisions (NMAC), Runway Incursions (RWY Inc) and Loss of Legal Separation (Legal Sep) Reports filed at 4 airports over the last 13 years correlates with the capacity fraction the airport was operating at the time the incident Occurred (Haynie 2002)
2.0 Current Procedures for Allocating Landing Time Slots
2.1 Technical Procedures
A brief description of how aircraft spacing is determined is in order, as this will become a central issue in any demand regulation scheme. There is a long-standing, internationally recognized, safety principle that two aircraft should never be on an active runway at any one time. Thus aircraft must be separated by a time interval that achieves this fundamental safety objective. The concern is that the leading aircraft may not be able to exit the active runway for a variety of reasons and the following aircraft must not land until the active runway is clear in order to avoid a potential high-speed collision. Aircraft deceleration times vary and Runway Occupancy Time (ROT) can be represented as a Gaussian distribution with a mean of 40 seconds and a standard deviation of 8 seconds. Thus, there is a 99% probability that a preceding aircraft has departed the runway after 64 seconds and a 99.999% probability after 88 seconds. Figure 6 shows the relationship between arrival rates and mean aircraft spacing for a representative range of aircraft landing speeds. In general, larger aircraft approach a runway at a higher speed than do small aircraft because of the extra aerodynamic lift required to keep them aloft. Table 2
shows a representative sample of arrival rates set at a number of major international airports. Note that many are set at a maximum arrival rate of 40 arrivals/rw/hr. As can be seen in figure 6 this represents an AVERAGE aircraft spacing of 3 nautical miles or an AVERAGE time separation of 90 seconds.
Figure 6. Relationship between Aircraft arrival rate and Average Aircraft spacing in distance and time for a representative range of approach speeds.
Table 2. Representative list of major international airports with published maximum runway arrival rates. Note that for this set of major airports the four non-slot controlled airports are all in the US.
With the introduction of the Boeing 747 wide-body aircraft into commercial service in the 1970’s, the aviation community became aware of a new hazard for smaller, lighter-weight aircraft following very heavy aircraft. The lift required to support any aircraft ultimately gets left in it’s wake in the form of both turbulence (a result of drag) and a set of counter-rotating vortex pairs. Aircraft are generally designed to withstand a significant amount of turbulence due to convective weather (i.e. thunder storms) but the coherent induced rolling encounter of a significantly smaller aircraft in the wing-tip vortex of a wide-body heavy aircraft can be fatal. In the 1970’s and 1980’s, conservative safe aircraft separation times were estimated (based upon wake vortex[KH1] knowledge at the time) and established as separation times in excess of ROT during weather conditions that required air traffic control separation responsibility. In clear weather, the aircraft pilot was warned that he/she was following a heavy aircraft and the wake should be avoided (Unfortunately for the pilots, the wake vortex is invisible most of the time.) Table 3 shows aircraft separation time estimates taken from a study on the aircraft mixture and maximum arrival rate at LAX based upon wake vortex separation times (Hansen, 2001). This table illustrates that for many aircraft pair combinations observed at LAX, separation times in excess of 90 seconds should be maintained. This assumes that both the FAA air traffic control function and the pilot in the aircraft can assure planned separation to within accuracy of several seconds. Using today’s technology, this is impossible.