Probabilistic Planning and Risk Evaluation Based on Ensemble Weather Forecasting

Zhang, Bin; Tang, Liang; Roemer, Michael

doi:10.1109/tase.2017.2648743

Cited by 17 publications

(4 citation statements)

References 31 publications

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“…In [198], CWAM weather forecasts were employed in combination with Dijkstra's algorithm to minimize a combination of fuel burn and expected cost of deviation due to weather. In [199], the any-angle path planning field D * algorithm is applied in a receding horizon fashion in order to minimize a combination of flight time and accumulated probability of bad weather conditions along the route.…”

Section: Convective Environmentsmentioning

confidence: 99%

Robust aircraft trajectory planning under uncertain convective environments with optimal control and rapidly developing thunderstorms

González-Arribas

Soler

Sanjurjo-Rivo

et al. 2019

Aerospace Science and Technology

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The Air Traffic Management (ATM) system in the busiest airspaces in the world is currently being overhauled to deal with multiple capacity, socioeconomic, and environmental challenges. One major pillar of this process is the shift towards a concept of operations centered on aircraft trajectories (called Trajectory-Based Operations or TBO in Europe) instead of rigid airspace structures. However, its successful implementation (and, thus, the realization of the associated improvements in ATM performance) rests on appropriate understanding and management of uncertainty. Due to its complex socio-technical structure, the design and operations of the ATM system are heavily impacted by uncertainty, proceeding from multiple sources and propagating through the interconnections between its subsystems.One major source of ATM uncertainty is weather. Due to its nonlinear and chaotic nature, a number of meteorological phenomena of interest cannot be forecasted with complete accuracy at arbitrary lead times, which leads to uncertainty or disruption in individual air and ground operations that propagates to all ATM processes. Therefore, in order to achieve the goals of SESAR and similar programs, it is necessary to deal with meteorological uncertainty at multiple scales, from the trajectory prediction and planning processes to flow and traffic management operations. This thesis addresses the problem of single-aircraft flight planning considering two important sources of meteorological uncertainty: wind prediction error and convective activity. As the actual wind field deviates from its forecast, the actual trajectory will diverge in time from the planned trajectory, generating uncertainty in arrival times, sector entry and exit times, and fuel burn. Convective activity also impacts trajectory predictability, as it leads pilots to deviate from their planned route, creating challenging situations for controllers. In this work, we aim to develop algorithms and methods for aircraft trajectory optimization that are able to integrate information about the uncertainty in these meteorological phenomena into the flight planning process at both pre-tactical (before departure) and tactical horizons (while the aircraft is airborne), in order to generate more efficient and predictable trajectories.To that end, we frame flight planning as an optimal control problem, modeling the motion of the aircraft with a point-mass model and the BADA performance model. Optimal control methods represent a flexible and general approach that has a long history of success in the aerospace field. As a numerical scheme, we use direct methods, which can deal with nonlinear systems of moderate and high-dimensional state spaces in a computationally manageable way. Nevertheless, while this framework is well-developed in the context of deterministic problems, the techniques for the solution of practical ix x Abstract optimal control problems under uncertainty are not as mature, and the methods proposed in the literature are not applicable to the flight planning probl...

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Section: Convective Environmentsmentioning

confidence: 99%

Robust aircraft trajectory planning under uncertain convective environments with optimal control and rapidly developing thunderstorms

González-Arribas

Soler

Sanjurjo-Rivo

et al. 2019

Aerospace Science and Technology

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“…In recent years, unmanned aerial vehicles (UAVs) have experienced rapid development in both civilian and military sectors [ 1 , 2 , 3 ]. UAVs implement control through sensitive flight parameters such as launch force, flight attitude, altitude, speed, position, etc., ensuring the safety and efficient completion of tasks [ 4 , 5 , 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Research on UAV Flight Parameter Identification Method Based on Launch Force and Airspeed

Chen,

Li,

et al. 2024

Sensors

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Flight parameters are crucial criteria for UAV control, playing a significant role in ensuring the safe and efficient completion of missions. Launch force and airspeed information are key parameters in the early and middle stages of flight, serving as important data for monitoring the UAV’s flight status. In response to challenges such as weak launch force, low identification rates, small airspeed, and low recognition accuracy in UAVs, a method for identifying UAV flight parameters based on launch force and airspeed is proposed. From the aspect of launch force identification, a recognition method based on a low-g value accelerometer information source is proposed, utilizing a ‘multi-level time window + threshold’ approach. For airspeed identification, an optimization method for airspeed measurement under the Kalman filter architecture is introduced. A device for airspeed measurement based on pressure sensors is designed, and the recommended installation position is determined through simulation. Furthermore, the feasibility and robustness of the proposed launch force identification and airspeed measurement optimization methods are validated through simulation. Finally, the effectiveness of the design is verified through centrifuge and wind tunnel experiments. This research provides technical support for the identification of the launch force and airspeed measurement in UAVs.

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“…In B. Zhang and Roemer (2014); Zhang et al (2017), the authors introduced a probabilistic analysis of weather forecasting. The analysis is based on ensemble weather forecasting data provided by the Center for Analysis and Prediction of Storm (CAPS) Jung et al (2008).…”

Section: Introductionmentioning

confidence: 99%

“…The analysis is based on ensemble weather forecasting data provided by the Center for Analysis and Prediction of Storm (CAPS) Jung et al (2008). Additionally, Zhang et al (2017) presented a path planning algorithm to avoid the stochastic hazard, including a mission risk analysis. Nevertheless, additional efforts are needed in stochastic thunderstorm modeling and aircraft trajectory planning, e.g., considering the additional uncertainty introduced by the aircraft dynamic system.…”

Section: Introductionmentioning

confidence: 99%

On maximizing safety in stochastic aircraft trajectory planning with uncertain thunderstorm development

Hentzen

Kamgarpour

Soler

et al. 2018

Aerospace Science and Technology

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Dealing with meteorological uncertainty poses a major challenge in air traffic management (ATM). Convective weather (commonly referred to as storms or thunderstorms) in particular represents a significant safety hazard that is responsible for one quarter of weather-related ATM delays in the US. With commercial air traffic on the rise and the risk of potentially critical capacity bottlenecks looming, it is vital that future trajectory planning tools are able to account for meteorological uncertainty. We propose an approach to model the uncertainty inherent to forecasts of convective weather regions using statistical analysis of state-of-the-art forecast data. The developed stochastic storm model is tailored for use in an optimal control algorithm that maximizes the probability of reaching a waypoint while avoiding hazardous storm regions. Both the aircraft and the thunderstorms are modeled stochastically. The performance of the approach is illustrated and validated through simulated case studies based on recent nowcast data and storm observations.

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Probabilistic Planning and Risk Evaluation Based on Ensemble Weather Forecasting

Cited by 17 publications

References 31 publications

Robust aircraft trajectory planning under uncertain convective environments with optimal control and rapidly developing thunderstorms

Robust aircraft trajectory planning under uncertain convective environments with optimal control and rapidly developing thunderstorms

Research on UAV Flight Parameter Identification Method Based on Launch Force and Airspeed

On maximizing safety in stochastic aircraft trajectory planning with uncertain thunderstorm development

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