G. J. Bakker

CONTRASTING SAFETY ASSESSMENTS OF A RUNWAY INCURSION SCENARIO: EVENT SEQUENCE ANALYSIS VERSUS MULTI-AGENT DYNAMIC RISK MODELLING

In the safety literature it has been argued, that in a complex socio-technical system safety cannot be well analysed by event sequence based approaches, but requires to capture the complex interactions and performance variability of the socio-technical system. In order to evaluate the quantitative and practical consequences of these arguments, this study compares two approaches to assess accident risk of an example safety critical sociotechnical system. It contrasts an event sequence based assessment with a multi-agent dynamic risk model (MA-DRM) based assessment, both of which are performed for a particular runway incursion scenario. The event sequence analysis uses the well-known event tree modelling formalism and the MA-DRM based approach combines agent based modelling, hybrid Petri nets and rare event Monte Carlo simulation. The comparison addresses qualitative and quantitative differences in the methods, attained risk levels, and in the prime factors influencing the safety of the operation. The assessments show considerable differences in the accident risk implications of the performance of human operators and technical systems in the runway incursion scenario. In contrast with the event sequence based results, the MA-DRM based results show that the accident risk is not manifest from the performance of and relations between individual human operators and technical systems. Instead, the safety risk emerges from the totality of the performance and interactions in the agent based model of the safety critical operation considered, which coincides very well with the argumentation in the safety literature.

A Particle System for Safety Verification of Free Flight in Air Traffic

Under free flight, an aircrew has both the freedom to select their trajectory and the responsibility of resolving conflicts with other aircraft. The general belief is that free flight can be made safe under low traffic conditions. Increasing traffic, however, raises safety verification issues. This problem is formulated as one of estimating for a large scale stochastic hybrid system the probability of reaching a small collision set. The huge state space prohibits the use of existing numerical approaches to solve this safety verification problem. As an alternative we study randomization methods, the simplest of which would be to run many Monte Carlo simulations with a stochastic model of free flight operations, and count the number of runs during which a collision between two or more aircraft occurs. The huge state space prohibits such a straightforward MC simulation approach. By exploiting recent particle system theory by Del Moral and co-workers, this paper develops a sequential Monte Carlo simulation approach for the estimation of collision risk in a future air traffic scenario. The working of the resulting particle system is demonstrated for an eight aircraft scenario under free flight air traffic conditions

Air traffic complexity and the interacting particle system method: An integrated approach for collision risk estimation

In this paper, we explore the possibility of using air traffic complexity metrics to accelerate the Interacting Particle System (IPS) method for collision risk estimation. Collision risk estimation is an essential task to assess the performance and impact of, e.g., possible modifications of the current air traffic management system or new operational concepts. The standard Monte Carlo approach to probability estimation requires a number of simulations that scales as the inverse of the probability to be estimated. This makes it impracticable for estimating the probability of a rare event such as a collision, and calls for ad-hoc solutions. In the IPS method, the collision risk is estimated as the product of the conditional probabilities of an increasing sequence of conditionally not-so-rare events, where aircraft get at progressively smaller distances one from the other. Additional computational saving can be obtained by adopting importance sampling techniques where initial aircraft configurations that are more prone to lead to a collision are favored. The idea that we pursue in this paper is to select those configurations by using some complexity metric. In particular, we propose to combine IPS with a probabilistic complexity metric that explicitly accounts for the uncertainty affecting the aircraft motion. Preliminary results obtained by applying this integrated approach to a free flight scenario are presented in the paper.

Effects of surveillance failure on airborne-based continuous descent approach

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.

Safety assessment of a future taxi into position and hold operation by agent-based dynamic risk modelling

Agent-based dynamic risk modelling supports the design of future air traffic operations by risk analysis methods that account for the performance variability of the interacting operators and systems, and the resulting emergence of safety occurrences. The paper shows the application of this modelling approach in a risk assessment cycle of a future A-SMGCS level 3 supported taxiing into position and hold operation. Accident risk results have been obtained by Monte Carlo simulations of a multi-agent dynamic risk model. The uncertainty in the risk has been evaluated using sensitivity analysis and feedback of operational experts.

Strengthening air traffic safety management by moving from outcome-based towards risk-based evaluation of runway incursions

Current safety management of aerodrome operations uses judgements of severity categories to evaluate runway incursions. Incident data show a small minority of severe incursions and a large majority of less severe incursions. We show that these severity judgements are mainly based upon the outcomes of runway incursions, in particular on the closest distances attained. As such, the severity-based evaluation leads to coincidental safety management feedback, wherein causes and risk implications of runway incursions are not well considered. In this paper we present a new framework for the evaluation of runway incursions, which effectively uses all runway incursions, which judges same types of causes similarly, and which structures causes and risk implications. The framework is based on risks of scenarios associated with the initiation of runway incursions. As a basis an inventory of scenarios is provided, which can represent almost all runway incursions involving a conflict with an aircraft. A main step in the framework is the assessment of the conditional probability of a collision given a runway incursion scenario. This can be effectively achieved for large sets of scenarios by agent-based dynamic risk modelling. The results provide detailed feedback on risks of runway incursion scenarios, thus enabling effective safety management.

Interacting Particle System-based Estimation of Reach Probability for a Generalized Stochastic Hybrid System

Abstract This paper studies estimation of reach probability for a generalized stochastic hybrid system (GSHS). For diffusion processes a well-developed approach in reach probability estimation is to introduce a suitable factorization of the reach probability and then to estimate these factors through simulation of an Interacting Particle System (IPS). The theory of this IPS approach has been extended to arbitrary strong Markov processes, which includes GSHS executions. Because Monte Carlo simulation of GSHS particles involves sampling of Brownian motion as well as sampling of random discontinuities, the practical elaboration of the IPS approach for GSHS is not straightforward. The aim of this paper is to elaborate the IPS approach for GSHS by using complementary Monte Carlo sampling techniques. For a simple GSHS example, it is shown that and why the specific technique selected for sampling discontinuities can have a major influence on the effectiveness of IPS in reach probability estimation.