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Multiple Model Method for Aircraft Conflict Detection and Resolution in Intent and Weather Uncertainty

机译：飞机冲突检测和分辨率的多种式模型方法，在意图和天气不确定性

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摘要

This paper presents a novel multiple model (MM) method for aircraft conflict detection and resolution (CDR) in intent andweather uncertainty for the next generation air transportation system. It is based on probabilisticMMaircraft trajectory prediction. Conflict detection is performed through the use of predicted probability of conflict (PC). An improved algorithm for estimating PC is proposed and compared with a commonly used method. Conflict resolution (CR) is formulated as a stochastic model predictive control (MPC) problem subject to a constraint on the predicted PC to guarantee safety of the optimized CR trajectories. The cost function to be minimized is tailored to the CR problem and includes the cost of performing evasive maneuvers as well as the average cost incurred by extra travel distance to the destination due to the maneuvers. An efficient algorithm for finding the optimal path (maneuver sequence), with respect to the maneuver cost, is proposed and extended to an overall CDR optimization algorithm for the total cost, in order to produce optimized conflict-free CR trajectories. The proposed search algorithm is essentially a generalization of an optimal list Viterbi algorithm (for unconstrained minimization through a trellis) to the constrained case of our MPC-based CDR problem. The capability and computational efficiency of the proposed MM-CDR method (including PC prediction, optimal search, and overall CDR) are evaluated via comprehensive simulation of a large variety of unmanned aerial vehicle "sense-and-avoid" encounter scenarios, and are compared with existing methods in the literature.
机译：本文提出了一种新型多种模型（MM）用于飞机冲突检测和分辨率（CDR）的方法，用于下一代空运系统的意图。它是基于概率的轨道轨迹预测。通过使用预测冲突（PC）的概率来执行冲突检测。提出了一种改进的估计PC算法，并与常用方法进行比较。冲突分辨率（CR）被制定为随机模型预测控制（MPC）问题，受预测PC的约束，以保证优化的CR轨迹的安全性。要最小化的成本函数是根据CR问题量身定制的，并且包括执行逃避演动的成本以及由于演习，以额外的行程距离发生的平均成本。提出了一种有效地查找最佳路径（机动序列）的高效算法，并扩展到总成本的总CDR优化算法，以便生产优化的无冲突CR轨迹。所提出的搜索算法基本上是最佳列表Viterbi算法的推广（通过格子通过格子的无疑最小化）到基于MPC的CDR问题的受限情况。通过全面模拟各种无人的空中车辆“感觉 - 避免”遇到场景，通过综合模拟来评估所提出的MM-CDR方法（包括PC预测，最佳搜索和整体CDR）的能力和计算效率。比较与文献中的现有方法。

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