Publications

Authors: Ellis L. Thompson, Yan Xu and Peng Wei

Link:https://arxiv.org/abs/2305.13996

Conference: ITSC 2023

Abstract: In the UAM space, strategic deconfliction provides an all-essential layer to airspace automation by providing safe, preemptive deconfliction or assignment of airspace resources to airspace users pre-flight. Strategic deconfliction approaches provide an elegant solution to pre-flight deconfliction operations. This overall creates safer and more efficient airspace and reduces the workload on controllers. In this research, we propose a method that constructs routes between start and end nodes in airspace, assigns a contract of operational volumes (OVs) and ensures that these OVs are sufficiently deconflicted against static no-fly zones and OVs of other airspace users. Our approach uses the A* optimal cost path algorithm to generate the shortest routes between the origin and destination. We present a method for generating OVs based on the distribution of aircraft positions from simulated flights; volumes are constructed such that this distribution is conservatively described.

Bibtex Citation:

Authors: Ellis L. Thompson, Yan Xu and Peng Wei

Link: https://arxiv.org/abs/2301.12961

Conference: ICUAS 2023

Abstract: Strategic pre-flight functions focus on the planning and deconfliction of routes for aircraft systems. The urban air mobility concept calls for higher levels of autonomy with onboard and en route functions but also strategic and pre-flight systems. Existing endeavours into strategic pre-flight functions focus on improving the route generation and strategic deconfliction of these routes. Introduced with the urban air mobility concept is the premise of operational volumes. These 4D regions of airspace, describe the intended operational region for an aircraft for finite time. Chaining these together forms a contract of finite operational volumes over a given route. It is no longer enough to only deconflict routes within the airspace, but to now consider these 4D operational volumes. To provide an effective all-in-one approach, we propose a novel framework for generating routes and accompanying contracts of operational volumes, along with deconfliction focused around 4D operational volumes. Experimental results show efficiency of operational volume generation utilising reachability analysis and demonstrate sufficient success in deconfliction of operational volumes.

Bibtex Citation:

Authors: Ellis L. Thompson, Abenezer Taye, James Ashby, Gerald Fattah, Peng Wei, Timothy Bonin, James Jones, Marcos Quinones-Grueiro and Guatam Biswas

Link: https://arc.aiaa.org/doi/abs/10.2514/6.2023-3964

Conference: AIAA AVIATION 2023

Abstract: The Advanced Air Mobility (AAM) concept envisions small unmanned aerial systems (UASs) and some larger electric vertical take-off and landing (eVTOL) vehicles operating in close proximity to one another within populated areas. As such it is important to assess the feasibility of a mission before departure. This includes both the aircraft's ability to maneuver to each waypoint safely, as well as ensuring that the aircraft can perform the mission given some initial State of Charge (SoC). Both of these performance related assessments can be affected by the presence of wind by either observing deviations from the prescribed flight plan or an increase in anticipated power consumption, draining the battery. In this paper we outline two systems developed to probabilistically evaluate the feasibility of a flight for a small UAS octocopter in the presence of wind. Designed in two parts, the first evaluates flight plan conformance identifying regions of deviation above a provided threshold. The second evaluates mission feasibility based on battery performance and yields a probability of completion given the remaining state of charge.

Bibtex Citation:

Authors: Ellis L. Thompson, Abenezer G. Taye, Wei Guo, Peng Wei,Marcos Quinones, Ibrahim Ahmed, Gautam Biswas, Jesse Quattrociocchi, Steven Carr, Ufuk Topcu, James C. Jones and Marc W. Brittain

Link: https://doi.org/10.2514/6.2022-3539

Conference: AIAA AVIATION 2023

Abstract: In this research, we have identified and surveyed three categories of hazards for advancedair mobility (AAM): (i) adverse weather with a special focus on winds, (ii) eVTOL vehicleand component level faults/degradation, and (iii) AAM corridor incursion by non-cooperativeaircraft. While these categories of hazards may be independent of one another as first ordereffects, their collective impact on safety is also an important factor. This paper is the firstpublication from the NASA funded project named “Demonstration of the In-Time Learning-Based Safety Management for Scalable Heterogeneous AAM Operations”. Our research teamproposes the design, development and demonstration of an in-time learning-based aviationsafety management system (ILASMS) for scalable heterogeneous AAM operations. We proposethree core functions (F1-mission level, F2-vehicle level, and F3-airspace level) in the ILASMS,to address these hazards. This survey paper will identify possible hazards that will define thefunction groups design requirements and specifications. We will perform system validation andscenario demonstrations with use case simulations and sub-scale flight tests.

Bibtex Citation:

Authors: Pouria Razzaghi, Amin Tabrizian, Wei Guo, Shulu Chen, Abenezer Taye, Ellis L. Thompson, Alexis Bregeon, Ali Baheri and Peng Wei

Link: https://arxiv.org/abs/2211.02147

Abstract: Compared with model-based control and optimization methods, reinforcement learning (RL) provides a data-driven, learning-based framework to formulate and solve sequential decision-making problems. The RL framework has become promising due to largely improved data availability and computing power in the aviation industry. Many aviation-based applications can be formulated or treated as sequential decision-making problems. Some of them are offline planning problems, while others need to be solved online and are safety-critical. In this survey paper, we first describe standard RL formulations and solutions. Then we survey the landscape of existing RL-based applications in aviation. Finally, we summarize the paper, identify the technical gaps, and suggest future directions of RL research in aviation.

Bibtex Citation: