Speed Control for Airborne Separation Assistance in Continuous Descent Arrivals

Abstract

Airborne Separation Assistance System (ASAS) is seen as a promising option for the future ATM concept to increase capacity and flight efficiency while maintaining flight safety. One idea of recent interest in ASAS applications is Airborne SPacing Application using enhanced Sequencing and Merging (ASPA-S&M). The S&M is expected to support energy saving arrivals, commonly referred to as Continuous Descent Arrivals (CDA). The motivation for our study is the need to clarify how safety and capacity depend on the setting of spacing criteria and in combination with specific S&M design aspects, and to identify any potential emergent behavior that should be taken into account in the operation design. For this purpose, a preceding study has designed initial mathematical models of the ASAS application for two aircraft trailing. This research develops the models to multiple aircraft trailing under stochastic wind conditions. In this paper, ASAS core components and their interactions are captured to build an integrated model using a Stochastically and Dynamically Colored Petri Net (SDCPN). Through Monte Carlo simulation based on the SDCPN model, we evaluate the performance of ASAS speed control for CDA operation considering the wind effect and multiple trailing aircraft.

Effects of surveillance failure on airborne-based continuous descent approach

“…9, for all initial deviations, the probability of collision risk is smaller than the order of 10 À11 ,which satisfies ICAO's TLS (5:0 Â 10 À9 ). These show that the designed ASAS speed controller in references [6,7] and emergency action work well. Although probabilities of the collision risk in the all cases keep the same order of magnitude, the smaller initial deviation Cases 1 and 2 have far less Minimum Separation Infringement (MSI) events than Case 3 has.…”

“…The other parameters in equations (1) to (3) are given in Table 3. Parameters in ADS-B transmitter/receiver and Delay ASAS/Aircraft Guidance Behaviour (AGB) models in equations (6) to (10) are in Table 4. The given action delay 6.5 s is obtained from reference [16], which is assumed to be the delay of flight crew's action after detecting traffic alert and collision avoidance system alert.…”

“…In an earlier study, an initial mathematical model of time spacing using ASAS speed control [6] was developed, which evaluated the safety of a novel ASAS speed controller for time spacing [7]. This novel controller was shown to behave in a robust way to random errors in the aircraft's initial values, e.g.…”

Comparison of aircraft models and integration schemes for interval management in the tracon

“…In this paper, we examine the IM concept applied to the terminal area, more specifically, in the context of the optimal profile descent (OPD) maneuver [5]. An optimal profile descent acts to minimize the fuel consumption of the aircraft during the descent phase of flight, in the terminal area.…”

Comparing Interval Management Control Laws for Steady-State Errors and String Stability

“…4 A number of speed control algorithms have been developed and tested to support various aspects of the research, including performance analyses using fast-time simulation, human-in-the-loop experiments, and flight tests. [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] The Federal Aviation Administration (FAA) is leading the development of avionics standards and the requisite ATC automation systems to enable IM operations in the U.S. National Airspace System. As a part of the avionics standards effort, a sample IM algorithm has been developed and tested and is described in the recentlypublished Flight-deck Interval Management (FIM) Minimum Operational Performance Standards (MOPS), DO-361.…”