Traffic Management for Urban Air Mobility

Bharadwaj, Suda; Carr, Steven; Neogi, Natasha A.; Poonawala, Hasan A.; Chueca, Alejandro Barberia; Topcu, Ufuk

doi:10.1007/978-3-030-20652-9_5

Cited by 8 publications

(4 citation statements)

References 20 publications

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“…In this paper, we employ a hierarchical decomposition of the UAM operations space motivated by the physical and geographical infrastructure required to field the system. Such an architecture has been studied in [2,3] and allows for scalable air traffic management. UAM vehicles take off and land from a landing pad, called a vertipad, which includes the final approach and takeoff (FATO) area.…”

Section: Settingmentioning

confidence: 99%

Minimum-Violation Traffic Management for Urban Air Mobility

Bharadwaj

Wongpiromsarn

Neogi

et al. 2021

Lecture Notes in Computer Science

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Urban air mobility (UAM) refers to air transportation services in and over an urban area and has the potential to revolutionize mobility solutions. However, due to the projected scale of operations, current air traffic management (ATM) techniques are not viable. Increasingly autonomous systems are a pathway to accelerate the realization of UAM operations, but must be fielded safely and efficiently. The heavily regulated, safety critical nature of aviation may lead to multiple, competing safety constraints that can be traded off based on the operational context. In this paper, we design a framework which allows for the scalable planning of a UAM ATM system. We formalize safety oriented constraints derived from FAA regulations by encoding them as temporal logic formulae. We then propose a method for UAM ATM that is both scalable and minimally violates the temporal logic constraints. Numerical results show that the runtime for our proposed algorithm is suitable for very large problems and is backed by theoretical guarantees of correctness with respect to given temporal logic constraints.

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Section: Settingmentioning

confidence: 99%

Minimum-Violation Traffic Management for Urban Air Mobility

Bharadwaj

Wongpiromsarn

Neogi

et al. 2021

Lecture Notes in Computer Science

Self Cite

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“…This necessitates a method that can use traffic information gained at runtime to adjust behavior for improved performance and safety. Previous approaches implement runtime safety enforcement [8]- [11], but cannot handle more general specifications.…”

Section: Given the Probability Of The Human's Location Based Onmentioning

confidence: 99%

“…Proof. The upper bound on C * (p) follows from (8). Consider the collection of polytopes T i constructed using the first N hyperplanes in ( 6) and (7).…”

Section: Theoremmentioning

confidence: 99%