Robustness of optimized collision avoidance logic to modeling errors

Kochenderfer, Mykel J.; Chryssanthacopoulos, James; Radecki, Peter

doi:10.1109/dasc.2010.5655381

Cited by 9 publications

(9 citation statements)

References 15 publications

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“…The evaluation simulations use the same intruder random turn rate model with standard deviation σ ψ that was used for value iteration. A robustness study using different models is not presented here, but previous research [13] suggests that this method will offer good performance when evaluated against both a range of noise parameters and structurally different models. The intruder initial position is randomly generated between 800 m and 1500 m from the center point of the encounter area at (500m, 500m) with an initial heading that is within 135 • of the direction from the initial position to the center point.…”

Section: Resultsmentioning

confidence: 99%

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Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming

Sunberg

Kochenderfer

Pavone

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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Safely integrating unmanned aerial vehicles into civil airspace is contingent upon development of a trustworthy collision avoidance system. This paper proposes an approach whereby a parameterized resolution logic that is considered trusted for a given range of its parameters is adaptively tuned online. Specifically, to address the potential conservatism of the resolution logic with static parameters, we present a dynamic programming approach for adapting the parameters dynamically based on the encounter state. We compute the adaptation policy offline using a simulation-based approximate dynamic programming method that accommodates the high dimensionality of the problem. Numerical experiments show that this approach improves safety and operational performance compared to the baseline resolution logic, while retaining trustworthiness.

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Section: Resultsmentioning

confidence: 99%

“…For example, the TRL could be extended to handle variable speed and altitude, but the policy that governs the TRL parameters could be optimized only on the most important dimensions of the model (e.g., the horizontal plane). See [13] for a similar successful example.…”

Section: A Model Assumptionsmentioning

confidence: 99%

Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming

Sunberg

Kochenderfer

Pavone

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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“…Finally, X t and h tÀ1 are passed through a sigmoid layer, and c t is passed through a tangent layer. The multiplication of the results of these two layers forms the output h t of the current LSTM module as shown in equation (7). Since they produce the output, these functions are called the output gate of the LSTM module.…”

Section: Lstm Network Structurementioning

confidence: 99%

“…4 Many researchers have been using this model in evaluating the performance of TCAS in new scenarios, 5,6 or studying new collision avoidance algorithms. 7,8 However, the major criticism of this model is that this model assumes pilot behavior is deterministic, that is, the response time delay and acceleration are fixed inspite of the different human pilot and different situation. Through analyzing radar data, researchers have already found that the deterministic pilot behavior model could not adequately describe realistic pilot behavior.…”

Section: Introductionmentioning

confidence: 99%

Predicting pilot behavior during midair encounters using long short-term memory network

Hu,

Wang

2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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Characterized by the wide use of advanced automation and the introduction of new operation concepts, the future air transportation system will be more complex. Advanced pilot behavior models with improved capability are required to support the design and analysis of the midair encounter situations in the future air transportation system. This paper first filters midair encounter data from Automatic Dependent Surveillance-Broadcast (ADS-B) observations. Based on the acquired midair encounter data, a comprehensive pilot behavior model is proposed based on a multi-layer Long Short-Term Memory (LSTM) network. The model is designed for the purpose of enhancing the predicting capability of pilot behaviors in both horizontal and vertical planes. Finally, the performance of the proposed model to predict pilot behavior in both horizontal and vertical planes is studied through evaluating against realistic midair encounter situations.

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“…The detailed introduction of each parameter in the simulation model is shown in Table 3. In order to generate a three-aircraft scenario, this paper adopts MIT Lincoln Laboratory's CASSATT to evaluate TCAS multi-aircraft conflict [26][27][28]. At first, we used the model to generate a pairwise conflict between two aircraft.…”

Section: Simulation Modelingmentioning

confidence: 99%

Graphical Modeling and Simulation for a Multi-Aircraft Collision Avoidance Algorithm based on Collaborative Decisions

2020

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The Traffic Alert and Collision Avoidance System (TCAS) is recognized worldwide as the last resort for avoiding midair collisions. The existing TCAS can solve pairwise conflict effectively, but cannot manage multi-aircraft conflict satisfactorily, and more seriously, can even trigger domino conflicts in some situation. In response to the increasingly frequent multi-aircraft conflicts, especially three-aircraft conflicts, it is necessary to improve the ability of TCAS. This paper studies the collision avoidance of multi-aircraft scenarios and innovatively proposes a collaborative optimization of a collision avoidance system (CAS) based on the state prediction of the aircraft. In the process, not only invading aircraft but also potential invading aircraft are considered in the plan for an optimal conflict resolution program. From the perspective of mathematics, the collaborative multi-aircraft conflict detection and resolution algorithm is described in detail in this paper. In the end, this paper conducts a comparative experiment to prove the feasibility of the algorithm in three-aircraft scenarios using InCAS software and Gmas simulation software based on graphical modeling of complex systems. The experimental results show that the CAS proposed in this paper can efficiently prevent the occurrence of domino conflicts and guide each aircraft to avoid conflict areas and return to their origin trajectories. In contrast, the existing TCAS will cause the target aircraft to intensify the conflict with the potential invading aircraft when avoiding intruder aircraft. The research greatly remedies the gaps in the area of multi-aircraft collision avoidance and greatly improves the ability and efficiency of TCAS.

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Robustness of optimized collision avoidance logic to modeling errors

Cited by 9 publications

References 15 publications

Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming

Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming

Predicting pilot behavior during midair encounters using long short-term memory network

Graphical Modeling and Simulation for a Multi-Aircraft Collision Avoidance Algorithm based on Collaborative Decisions

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