skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


This content will become publicly available on June 30, 2026

Title: Privacy-Preserving Mechanisms for Coordinating Airspace Usage in Advanced Air Mobility
Advanced Air Mobility (AAM) operations are expected to transform air transportation while challenging current air traffic management practices. By introducing a novel market-based mechanism, we address the problem of on-demand allocation of capacity-constrained airspace to AAM vehicles with heterogeneous and private valuations. We model airspace and air infrastructure as a collection of contiguous regions (or sectors) with constraints on the number of vehicles that simultaneously enter, stay, or exit each region. Vehicles request access to airspace with trajectories spanning multiple regions at different times. We use the graph structure of our airspace model to formulate the allocation problem as a path allocation problem on a time-extended graph. To ensure that the cost information of AAM vehicles remains private, we introduce a novel mechanism that allocates each vehicle a budget of “air-credits” (an artificial currency) and anonymously charges prices for traversing the edges of the time-extended graph. We seek to compute a competitive equilibrium that ensures that: (i) capacity constraints are satisfied, (ii) a strictly positive resource price implies that the sector capacity is fully utilized, and (iii) the allocation is integral and optimal for each AAM vehicle given current prices, without requiring access to individual vehicle utilities. However, a competitive equilibrium with integral allocations may not always exist. We provide sufficient conditions for the existence and computation of a fractional-competitive equilibrium, where allocations can be fractional. Building on these theoretical insights, we propose a distributed, iterative, two-step algorithm that: (1) computes a fractional competitive equilibrium, and (2) derives an integral allocation from this equilibrium. We validate the effectiveness of our approach in allocating trajectories for the emerging urban air mobility service of drone delivery.  more » « less
Award ID(s):
2125913
PAR ID:
10627365
Author(s) / Creator(s):
; ; ; ; ; ; ;
Publisher / Repository:
Journal on Autonomous Transportation Systems
Date Published:
Journal Name:
ACM Journal on Autonomous Transportation Systems
Volume:
2
Issue:
4
ISSN:
2833-0528
Page Range / eLocation ID:
1 to 34
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Advanced air mobility (AAM) is an emerging sector in aviation aiming to offer secure, efficient, and eco-friendly transportation utilizing electric vertical takeoff and landing (eVTOL) aircraft. These vehicles are designed for short-haul flights, transporting passengers and cargo between urban centers, suburbs, and remote areas. As the number of flights is expected to rise significantly in congested metropolitan areas, there is a need for a digital ecosystem to support the AAM platform. This ecosystem requires seamless integration of air traffic management systems, ground control systems, and communication networks, enabling effective communication between AAM vehicles and ground systems to ensure safe and efficient operations. Consequently, the aviation industry is seeking to develop a new aerospace framework that promotes shared aerospace practices, ensuring the safety, sustainability, and efficiency of air traffic operations. However, the lack of adequate wireless coverage in congested cities and disconnected rural communities poses challenges for large-scale AAM deployments. In the immediate recovery phase, incorporating AAM with new air-to-ground connectivity presents difficulties such as overwhelming the terrestrial network with data requests, maintaining link reliability, and managing handover occurrences. Furthermore, managing eVTOL traffic in urban areas with congested airspace necessitates high levels of connectivity to support air routing information for eVTOL vehicles. This paper introduces a novel concept addressing future flight challenges and proposes a framework for integrating operations, infrastructure, connectivity, and ecosystems in future air mobility. Specifically, it includes a performance analysis to illustrate the impact of extensive AAM vehicle mobility on ground base station network infrastructure in urban environments. This work aims to pave the way for future air mobility by introducing a new vision for backbone infrastructure that supports safe and sustainable aviation through advanced communication technology. 
    more » « less
  2. Advanced air mobility (AAM) has introduced a new mode of air transportation that can be integrated, providing services including air taxis, which can quickly transport people and cargo from one place to another. However, urban airspace is already congested with commercial air traffic, so there is a need for an efficient and autonomous airspace management system. Establishing structured air corridors and enabling UAS-to-UAS (U2U) communications are essential to achieve autonomy. Air corridors are designated airspace primarily reserved for AAM traffic, which will streamline the movement of unmanned aircraft systems (UAS). Meanwhile, U2U communications facilitate efficient collision avoidance strategies (CAS). A key aspect of this system is the development of CAS, which requires advanced communication protocols to monitor traffic patterns and detect potential collisions. This paper explores designing and implementing CAS using U2U communications. Use cases for U2U communications include merging, minimum separation, information relay, collaborative sensing, and rerouting. All these use cases demand real-time solutions for managing traffic conflicts involving multiple UAS. The CAS discussed in this paper utilizes U2U communications to mitigate the risk of collisions in the airspace and demonstrates how U2U communications can assist in efficient AAM traffic management through simulations. 
    more » « less
  3. With the advancing development of Advanced Air Mobility (AAM), there is a collaborative effort to increase safety in the airspace. AAM is an advancing field of aviation that aims to contribute to the safe transportation of goods and people using aerial vehicles. When aerial vehicles are operating in high-density locations such as urban areas, it can become crucial to incorporate collision avoidance systems. Currently, there are available pilot advisory systems such as Traffic Collision and Avoidance Systems (TCAS) providing assistance to manned aircraft, although there are currently no collision avoidance systems for autonomous flights. Standards Organizations such as the Institute of Electrical and Electronics Engineers (IEEE), Radio Technical Commission for Aeronautics (RTCA), and General Aviation Manufacturers Association (GAMA) are working to develop cooperative autonomous flights using UAS-to-UAS Communication in structured and unstructured airspaces. This paper presents a new approach for collision avoidance strategies within structured airspace known as “digital traffic lights”. The digital traffic lights are deployed over an area of land, controlling all UAVs that enter a potential collision zone and providing specific directions to mitigate a collision in the airspace. This strategy is proven through the results demonstrated through simulation in a Cesium Environment. With the deployment of the system, collision avoidance can be achieved for autonomous flights in all airspaces. 
    more » « less
  4. Abstract Urban air mobility (UAM) is an emerging air transportation mode to alleviate the ground traffic burden and achieve zero direct aviation emissions. Due to the potential economic scaling effects, the UAM traffic flow is expected to increase dramatically once implemented, and its market can be substantially large. To be prepared for the era of UAM, we study the fair and risk‐averse urban air mobility resource allocation model (FairUAM) under passenger demand and airspace capacity uncertainties for fair, safe, and efficient aircraft operations. FairUAM is a two‐stage model, where the first stage is the aircraft resource allocation, and the second stage is to fairly and efficiently assign the ground and airspace delays to each aircraft provided the realization of random airspace capacities and passenger demand. We show that FairUAM is NP‐hard even when there is no delay assignment decision or no aircraft allocation decision. Thus, we recast FairUAM as a mixed‐integer linear program (MILP) and explore model properties and strengthen the model formulation by developing multiple families of valid inequalities. The stronger formulation allows us to develop a customized exact decomposition algorithm with both benders and L‐shaped cuts, which significantly outperforms the off‐the‐shelf solvers. Finally, we numerically demonstrate the effectiveness of the proposed method and draw managerial insights when applying FairUAM to a real‐world network. 
    more » « less
  5. We consider the problem of fairly allocating a set of indivisible goods among n agents. Various fairness notions have been proposed within the rapidly growing field of fair division, but the Nash social welfare (NSW) serves as a focal point. In part, this follows from the ‘unreasonable’ fairness guarantees provided, in the sense that a max NSW allocation meets multiple other fairness metrics simultaneously, all while satisfying a standard economic concept of efficiency, Pareto optimality. However, existing approximation algorithms fail to satisfy all of the remarkable fairness guarantees offered by a max NSW allocation, instead targeting only the specific NSW objective. We address this issue by presenting a 2 max NSW, Prop-1, 1/(2n) MMS, and Pareto optimal allocation in strongly polynomial time. Our techniques are based on a market interpretation of a fractional max NSW allocation. We present novel definitions of fairness concepts in terms of market prices, and design a new scheme to round a market equilibrium into an integral allocation in a way that provides most of the fairness properties of an integral max NSW allocation. 
    more » « less