ADS-B based Trajectory Prediction and Conflict Detection for Air Traffic Management

Abstract

The Automatic Dependent Surveillance Broadcast (ADS-B) system is a key component of CNS/ATM recommended by the International Civil Aviation Organization (ICAO) as the next generation air traffic control system. ADS-B broadcasts identification, positional data, and operation information of an aircraft to other aircraft, ground vehicles and ground stations in the nearby region. This paper explores the ADS-B based trajectory prediction and the conflict detection algorithm. The multiple-model based trajectory prediction algorithm leads accurate predicted conflict probability at a future forecast time. We propose an efficient and accurate algorithm to calculate conflict probability based on approximation of the conflict zone by a set of blocks. The performance of proposed algorithms is demonstrated by a numerical simulation of two aircraft encounter scenarios.

Probability estimation in aircraft conflict detection: a simple and computationally effective method with accuracy certificates

“…In this section, we compare the proposed approach with the geometric approaches in [4], [5], and [6] through two numerical examples. Results are reported in Sections V-A and V-B.…”

“…However, if it can be reduced to computing integrals of 1D Gaussian densities, then, a high quality approximation of each single 1D integral can be obtained so that the resulting method is classified as analytical (see Section II). This is the idea exploited in the geometric methods in [4]- [6] and also in the one proposed here, which is a simple extension of the method proposed in [6]. Despite its simplicity, this extension has the twofold positive effect of improving the quality of the estimate of the conflict probability and also providing a deterministic bound on its accuracy.…”

“…Several probabilistic CD methods have been proposed in the literature using analytical [4]- [6], numerical [2], [7]- [10], and sample-based [11], [12] approaches.…”

“…Note that the obtained estimate is an upper bound on the instantaneous probability of conflict, given that an over-approximation of the conflict zone is adopted. The method proposed in [5] for overestimating the instantaneous conflict probability is further improved in [6] by covering the elliptical conflict zone with a finite number of rectangular sets. The estimation error of the geometric method is thus reduced.…”

“…We shall next explain in some detail how we compute p UB c and p LB c . Note that in [6], only the upper bound p UB c is computed and the conflict probability estimate is set equal to such an upper bound without providing any accuracy. This prevents the possibility of implementing a guided refinement so as to achieve some desired quality of the estimate.…”