Multi-objective optimisation of safety related systems: An application to Short Term Conflict Alert.

Abstract

Copyright © 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Notes: In this paper multi-objective optimisation is used for the first time to adjust the 1500 parameters of Short-Term Conflict Alert systems to optimise the Receiver Operating Characteristic (ROC) by simultaneously reducing the false positive rate and increasing the true positive alert rate, something that previous work by other researchers had not succeeded in doing. Importantly for such safety-critical systems, the method also yields an assessment of the confidence that may be placed in the optimised ROC curves. The paper results from a collaboration with NATS and a current KTP project, also with NATS, is deploying the methods in air-traffic control centres nationwide.Many safety related and critical systems warn of potentially dangerous events; for example, the short term conflict alert (STCA) system warns of airspace infractions between aircraft. Although installed with current technology, such critical systems may become out of date due to changes in the circumstances in which they function, operational procedures, and the regulatory environment. Current practice is to "tune," by hand, the many parameters governing the system in order to optimize the operating point in terms of the true positive and false positive rates, which are frequently associated with highly imbalanced costs. We cast the tuning of critical systems as a multiobjective optimization problem. We show how a region of the optimal receiver operating characteristic (ROC) curve may be obtained, permitting the system operators to select the operating point. We apply this methodology to the STCA system, using a multiobjective (1+1) evolution strategy, showing that we can improve upon the current hand-tuned operating point, as well as providing the salient ROC curve describing the true positive versus false positive tradeoff. We also provide results for three-objective optimization of the alert response time in addition to the true and false positive rates. Additionally, we illustrate the use of bootstrapping for representing evaluation uncertainty on estimated Pareto fronts, where the evaluation of a system is based upon a finite set of representative data