Multicommodity Eulerian-Lagrangian Large-Capacity Cell Transmission Model for En Route Traffic

Sun, Dong; Bayen, Alexandre M.

doi:10.2514/1.31717

Cited by 104 publications

(71 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous studies focused on a simple graph comprising a small number of nodes, and very little is known about the dynamics on complex networks. Note that Sun and Bayen [36] applied this cell transmission model to air traffic in a different manner, in which nodes correspond to discretized aviation routes.…”

Section: Model a Problem Formulationmentioning

confidence: 99%

Potential global jamming transition in aviation networks

Ezaki

Nishinari

2014

Phys. Rev. E

View full text Add to dashboard Cite

In this paper, we propose a nonlinear transport model for an aviation network. The takeoff rate from an airport is characterized by the degree of ground congestion. Due to the effect of surface congestion, the performance of an airport deteriorates because of inefficient configurations of waiting aircraft on the ground. Using a simple transport model, we performed simulations on a U. S. airport network and found a global jamming transition induced by local surface congestion. From a physical perspective, the mechanism of the transition is studied analytically and the resulting aircraft distribution is discussed considering system dynamics. This study shows that the knowledge of the relationship between a takeoff rate and a congestion level on the ground is vital for efficient air traffic operations.

show abstract

Section: Model a Problem Formulationmentioning

confidence: 99%

Potential global jamming transition in aviation networks

Ezaki

Nishinari

2014

Phys. Rev. E

View full text Add to dashboard Cite

show abstract

“…Among the more notable models to appear in the literature are the initial Eulerian model 27 , an aggregate stochastic dynamic model that accounts for the inherent departure time uncertainty at airports 28, and a multi -commodity large-capacity cell transmission model. 29 These models have been shown to accurately forecast the demand in both sectors and centers over a time horizon that supports strategic traffic flow planning,…”

Section: Demand Estimationmentioning

confidence: 94%

Integrated Traffic Flow Management Decision Making

Grabbe

Sridhar

Mukherjee

2009

AIAA Guidance, Navigation, and Control Conference

View full text Add to dashboard Cite

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the num ber of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

show abstract

“…Safety constraints increase the complexity of the problem. There are a range of ways in which the system can be modeled, ranging from discrete models, which require the solution of large integer programs [8,9], to continuous, flow-based, Eulerian models, which can often be solved using linear programs, but lose individual, flight-scale characteristics [7,51,62,90]. Both approaches hold promise at different time-scales, and research into the tradeoffs between the approaches for tactical and strategic decision-making is needed.…”

Section: Large-scale Real-time Optimization Algorithmsmentioning

confidence: 99%

Challenges in Aerospace Decision and Control: Air Transportation Systems

Balakrishnan

Clarke

Féron

et al. 2015

Advances in Control System Technology for Aerospace Applications

View full text Add to dashboard Cite

The Next Generation Air Transportation System (NextGen) is the FAA's vision of how the nation's aviation system will operate in 2025 and beyond [40]. In 2004, the National Airspace System (NAS) was already operating near capacity, and demand was expected to grow two-to threefold over the following 20 years. The NextGen initiative was established in 2003 in order to meet the challenges presented by the predicted increase in demand. It represents a substantial and long-term change in the management and operation of the US air transportation system, and involves both the leveraging of existing technologies and the development of new ones. This includes satellite-based navigation and control of aircraft, advanced digital communications, advanced infrastructure for greater information sharing, and enhanced connectivity between all components of the air transportation system. The overarching objectives of NextGen are to improve the safety, speed and efficiency, and to mitigate the environmental impacts of air transportation, while accommodating increased demand.

show abstract

Multicommodity Eulerian-Lagrangian Large-Capacity Cell Transmission Model for En Route Traffic

Cited by 104 publications

References 26 publications

Potential global jamming transition in aviation networks

Potential global jamming transition in aviation networks

Integrated Traffic Flow Management Decision Making

Challenges in Aerospace Decision and Control: Air Transportation Systems

Contact Info

Product

Resources

About