Air-ground trajectory synchronization &amp;#x2014; Metrics and simulation results

Chan, D.; Brooksby, G.; Hochwarth, Joachim; Klooster, Joel K.; Torres, S.

doi:10.1109/dasc.2011.6095977

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…The synchronization of aircraft's trajectories could be considered as a representation of predicted results (Klooster et al, 2010) and could be further optimized by integrating flight plans, aircraft intentions (Frontera et al, 2017), and behavior models (Poles et al, 2010). Moreover, Chan et al (2011) synchronized trajectories by integrating the data from the air and ground. However, unlike CVs in urban traffic, aircraft's trajectories are constrained by the flight plan.…”

Section: Related Workmentioning

confidence: 99%

Heterogeneous data‐based spatiotemporal trajectory synchronization for virtual–real interactive testing

Qiu

Shangguan

Cai

et al. 2022

Computer aided Civil Eng

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Virtual–real interactive testing (VRIT) is a practical approach to assessing the safety and intelligence of connected vehicles. Under this testing scheme, state consistency between physical and virtual spaces must be guaranteed. This paper proposes a multispace synchronization framework to ensure the desired interactive performance of VRIT systems. According to this framework, the synchronization process is decomposed into tracking and extensional periods. In addition, the heterogeneous data collected from physical and virtual spaces are divided into three layers. Each layer has a specific priority in the generation of the tracking trajectory. Furthermore, an extensional trajectory is integrated based on the proposed filtering mechanism, which improves the synchronization accuracy under high latency conditions. Finally, numerical experiments are conducted to demonstrate the superiority of the proposed method and to illustrate how the key parameters affect the system performance.

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Section: Related Workmentioning

confidence: 99%

Heterogeneous data‐based spatiotemporal trajectory synchronization for virtual–real interactive testing

Qiu

Shangguan

Cai

et al. 2022

Computer aided Civil Eng

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“…If the quadratic is constrained so that its minimum point is reached at a speed that coincides with the speed corresponding to the minimum cost, v min , then to compute the quadratic coefficients it is only needed to specify the minimum cost point (C min , v min ), and a second point anywhere along the cost curve (C 1 ,v 1 ): equations (4), (5) and (6).…”

Section: Figure 4 Linear Segmentation (Dotted Line) Of Cost Curvesmentioning

confidence: 99%

“…To test and evaluate the use of cost coefficients in ground DSTs we have developed under the JSRI a test infrastructure consisting of a fast-time Matlabbased simulation environment that integrates real world trajectory predictors used in FMS and ATC systems along with trajectory management and ranking tools [4], [6]. Coupled with realistic scenarios, this environment will allow us to quantify the benefits expected from the concept.…”

Section: Use Of Cost Data In Trajectory Managementmentioning

confidence: 99%

“…By leveraging GE's FMS and aircraft/avionics expertise with Lockheed Martin's ATC domain expertise, including the FAA's En Route Automation Modernization (ERAM), and the Common Automated Radar Terminal System (Common ARTS), the JSRI aims to explore and evaluate trajectory synchronization and negotiation concepts that bring airspace operations closer to the businessoptimal goal in a safe and efficient manner [3][4][5][6]. This paper describes a user-preference-driven trajectory management concept developed under the JSRI.…”

Section: Introductionmentioning

confidence: 99%

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Trajectory management driven by user preferences

Torres¹,

Martin²,

Klooster³

et al. 2011

2011 IEEE/AIAA 30th Digital Avionics Systems Conference

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The evolution of the Traffic Flow Management (TFM) and Air Traffic Control (ATC) systems towards Trajectory Based Operations (TBO) is constrained by the need to support a mixed fleet of aircraft for the foreseeable future. Trajectory synchronization and negotiation in particular are key enablers of TBO that need to take into account both the advanced capabilities in existing and future Flight Management Systems (FMS), and the limitations in performance and capabilities of legacy aircraft. Trajectory management systems will have to address the challenges imposed by this reality. Lockheed Martin and General Electric (GE) have established a Joint Strategic Research Initiative (JSRI) to develop technologies that can efficiently address the challenges of trajectory management. In this paper, we describe a user preference driven trajectory management concept that was developed under the JSRI. The idea consists of providing flight-specific cost information to Decision Support Tools (DST) used by controllers for strategic conflict resolution and schedule management. The cost of operating a flight may be decomposed into the cost of fuel and other direct and time related costs (such as crew pay, aircraft maintenance, or connecting passengers). In current operations, there is no practical mechanism to make this information known to the ground automation (or the controller) which needs to make changes to the business trajectory; moreover, much of this information is considered proprietary or sensitive by the operators, making it difficult or impossible to determine the true cost impact of modifications to the reference business trajectory. However, it is precisely the overall cost of operations that should be driving the decision process. A mechanism has been developed to extract the effective operating cost from the FMS and to make that information available to ground DSTs. Cost information is encoded in coefficients that do not reveal operator specific business strategies that may be considered proprietary. This enables the ground controller (and DSTs) to make an informed decision that may increase the likelihood of operators business objectives being accommodated, and would allow operators to better inform ATC's decisions such that the impact on the business objectives are minimized when changes are required. The encoding of cost information is made in a compact way so that communication band-width requirements are reasonable.

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