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Abstract

For higher density operation in terminal manoeuvring area, Airborne Surveillance Application System (ASAS) is seen as a promising option in the future air traffic management (ATM). One idea of recent interest in ASAS application is Interval Management (IM), which is expected to support energy-saving arrivals, commonly referred as Continuous Descent Approach (CDA). The questions are how the IM application achieves safety and capacity in the CDA environment, and how to identify any potential emergent behaviour that should be taken into account in the operation design. The motivation for this study is the need to properly understand the nominal and non-nominal behaviour of many aircraft when the ASAS application is applied to the CDA environment.

For this purpose, this study has conducted a preliminary safety assessment of the ASAS speed control for multiple trailing aircraft in CDA operation. This article focuses on ASAS surveillance failure as one of the critical events during flight. Using Stochastically and Dynamically Coloured Petri Net (SDCPN), ASAS core components and their interactions are modelled. Through Monte Carlo simulation via the SDCPN models, the impact of the ASAS surveillance failure on the airborne-based CDA operation is assessed.

Keywords

air traffic management continuous descent airborne spacing Petri net complex system modelling sequential Monte Carlo simulation

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References

RTCA. Safety, performance and interoperability requirements document for airborne spacing – enhanced interval management (ASPA-IM), RTCA, (Washington, DC). 26 February 2011.

Package I Requirements Focus Group (RFG). Application definition sub-group: Package I: Enhanced sequencing and merging operations (ASPA-S&M), Application Definition 2.3.0 ed., ASPA, 20 January 2009.

Shah, A. P., Pritchett, A. R., Feigh, K. M., Kalarev, S. A., Jadhav, A., Corker, K. M., Holl, D. M., and Bea, R. C. Analyzing air traffic management systems using agent based modeling and simulation. In Proceedings of the 6th USA/Europe ATM R&D Seminar, Baltimore, Maryland, 14 July 2005.

Everdij

M. H. C.

Blom

H. A. P.

Bakker

G. J.

Modeling lateral spacing and separation for airborne separation assurance using Petri nets. J. Simul.: Trans. Soc. Model. Simul. Int., 2007, 83, 401–414.

Blom

H. A. P.

Klein Obbink

Bakker

G. J.

Simulated safety risk of an uncoordinated airborne self separation concept of operation. ATC-Q., 2009, 17, 63–93.

Itoh, E., Everdij, M. H. C., Bakker (Bert), G. J., and Blom, H. A. P. Speed control for airborne separation assistance in continuous descent arrivals. In Proceedings of the 9th AIAA Aviation Technology, Integration, and Operations, Hilton Head, South Carolina, 21–23 September 2009, AIAA paper no. 2009-6909 (American Institute of Aeronautics and Astronautics, Reston, Virginia).

Itoh, E., Van der Geest, P. J., and Blom, H. A. P. Improved airborne spacing control for trailing aircraft. In Proceedings of the 2009 Asia-Pacific International Symposium on Aerospace technology, Gufu, Japan, 4–6 November 2009.

Everdij

M. H. C.

Klompstra

M. B.

Blom

H. A. P.

Klein Obbink

Compositional specification of a multi-agent system by stochastically and dynamically coloured Petri nets. In: Blom

H. A. P.

Lygeros

(eds). Stochastic hybrid systems: Theory and safety critical applications, 2006, (Springer, New York), 325–350.

Everdij

M. H. C.

Blom

H. A. P.

Hybrid Petri nets with diffusion that have into-mappings with generalized stochastic hybrid processes. In: Blom

H. A. P.

Lygeros

(eds). Stochastic hybrid systems: theory and safety critical applications, 2006, (Springer, New York), 31–63.

10.

Everdij, M. H. C. Compositional modelling using Petri nets with the analysis power of stochastic hybrid processes. PhD Thesis, Department of Applied Mathematics, The University of Twente, 2010.

11.

Blom

H. A. P.

Krystul

Bakker

G. J.

Klompstra

M. B.

Klein Obbink

Free flight collision risk estimation by sequential Monte Carlo simulation. In: Cassandras

C. G.

Lygeros

(eds). Stochastic hybrid systems; recent developments and research trends, 2007, ch. 10, pp. 249–281 (Taylor & Francis/CRC Press, New York).

12.

Blom

H. A. P.

Bakker

G. J.

Krystul

Rare event estimation for a large-scale stochastic hybrid system with air traffic application. In: Rubino

Tuffin

(eds). Rare event simulation using Monte Carlo methods, 2009, (John Wiley & Sons Ltd, New York), 193–214.

13.

Itoh, E., Bakker (Bert), G. J., and Blom, H. A. P. Comparison of two algorithms for speeding up Monte Carlo simulation in rare event estimation for stochastic hybrid systems. In Proceedings of the 2011 Winter Simulation Conference (under review), Phoenix, Arizona, 11–14 December 2011.

14.

Eurocontrol. CoSpace – Towards the use of spacing instructions, 2006, available from http://www.eurocontrol.int/eec/public/standard_page/SSP_cospace_home.html (access date 19 April 2006).

15.

Van der Geest

P. J.

The AMAAI modeling toolset forthe analysis of in-trail following dynamics. Deliverable D2: description and user guide, NLR-CR-2002-112, 2002, (Amsterdam, The Netherlands, National Aerospace Laboratory.

16.

RTCA. Minimum operational performance standards for traffic alert and collision avoidance system II (TCAS II) airborne equipment, DO-185A, RTCA, 1997, (Washington, DC.

Effects of surveillance failure on airborne-based continuous descent approach

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