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.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Efficient Box Approximation for Data-Driven Probabilistic Geofencing
Advanced Air Mobility (AAM) using electrical vertical take-off and landing (eVTOL) aircraft is an emerging way of air transportation within metropolitan areas. A key challenge for the success of AAM is how to manage large-scale flight operations with safety guarantees in high-density, dynamic, and uncertain airspace environments in real time. To address these challenges, we introduce the concept of a data-driven probabilistic geofence, which can guarantee that the probability of potential conflicts between eVTOL aircraft is bounded under data-driven uncertainties. To evaluate the probabilistic geofences online, Kernel Density Estimation (KDE) based on Fast Fourier Transform (FFT) is customized to model data-driven uncertainties. Based on the FFT-KDE values from data-driven uncertainties, we introduce an optimization framework of Integer Linear Programming (ILP) to find a parallelogram box to approximate the data-driven probabilistic geofence. To overcome the computational burden of ILP, an efficient heuristic algorithm is further developed. Numerical results demonstrate the feasibility and efficiency of the proposed algorithms.  more » « less
Award ID(s):
2138612
PAR ID:
10472746
Author(s) / Creator(s):
;
Publisher / Repository:
World Scientific
Date Published:
Journal Name:
Unmanned Systems
ISSN:
2301-3850
Page Range / eLocation ID:
1 to 12
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; (, Transport Economics and Management)
    Advanced Air Mobility (AAM) presents an emerging alternative to traditional car driving for commuting in metropolitan areas. However, its feasibility has not been thoroughly studied nor well understood at the operational level. Given that AAM has not been in place, this study explores the economic, energy, and environmental feasibility of AAM for commuting at an early stage of AAM deployment. We propose a time expanded network model to characterize the dynamics of eVTOL operations between a vertiport pair in different states: in-service flying, relocation flying, charging, and parking, while respecting various operational and commuter time window constraints. By jointly considering eVTOL flying with vertiport access and egress and using real-world data, we demonstrate an application of the model in the Chicago metropolitan area in the US. Different vertiport pairs and eVTOL aircraft models are investigated. We find substantial travel time saving if commuting by AAM. While vehicle operating cost will be higher using eVTOLs than using auto, the generalized travel cost will be less for commuters. On the other hand, with current eVTOL power requirement, the energy consumption and CO2 emissions of AAM will be greater than those of auto driving, with an important contributor being the significance presence of empty flights relocation. These findings, along with sensitivity analysis, shed light on future eVTOL development to enhance the competitiveness of AAM as a viable option for commuting. 
    more » « less
  2. ; ; (, Drones)
    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
  3. ; (, American Institute of Aeronautics and Astronautics)
    Urban air mobility (UAM) using unmanned aerial vehicles (UAV) is an emerging way of air transportation within metropolitan areas. For the sake of the successful operations of UAM in dynamic and uncertain airspace environments, it is important to provide safe path planning for UAVs. To achieve the path planning with safety assurance, the first step is to detect collisions. Due to uncertainty, especially data-driven uncertainty, it’s impossible to decide deterministically whether a collision occurs between a pair of UAVs. Instead, we are going to evaluate the probability of collision online in this paper for any general data-driven distribution. A sampling method based on kernel density estimator (KDE) is introduced to approximate the data-driven distribution of the uncertainty, and then the probability of collision can be converted to the Riemann sum of KDE values over the domain of the combined safety range. Comprehensive numerical simulations demonstrate the feasibility and eciency of the online evaluation of probabilistic collision for UAM using the proposed algorithm of collision detection. 
    more » « less
  4. ; ; (, Journal of Air Transport Management)
    Electric vertical takeoff and landing aircraft (eVTOLs) are gaining growing interest recently. However, limited attention has been paid to the prospect of using eVTOLs for package delivery. To fill this void, this paper explores the attractiveness of eVTOL-based package delivery in terms of cost, energy consumption, and CO2 emissions. Given that eVTOLs cannot take off/land at customer doorsteps, a two-leg system design is proposed and formulated as an optimization model. To implement the model, we consider multiple plausible eVTOL and ground vehicle types, their cost economics, and energy use and CO2 emission characteristics. Applying the model in the Chicago metro region, we find that the attractiveness of eVTOL-based package delivery depends critically on the eVTOL and ground vehicle types. With an appropriate eVTOL-ground vehicle combination, eVTOL-based delivery can be attractive compared to van-only delivery in terms of total shipping cost, but not necessarily so from the energy and mission perspectives. This highlights the need for future R&D to further enhance the energy efficiency of eVTOLs. When designing eVTOL-based package delivery systems, the importance to account for the potential interactions between eVTOL traffic and commercial air traffic should also be recognized. 
    more » « less
  5. ; ; (, American Society of Civil Engineers)
    T. Matthew Evans, Ph.D. Nina Stark (Ed.)
    Soil water characteristic curve (SWCC) which describes the relationship between water content and matric suction is important to analyzing unsaturated soil behavior. Because of the degree of uncertainty in field conditions due to climatic variability and soil heterogeneities, it becomes necessary to probabilistically characterize the SWCC. A satisfactory probabilistic characterization of field-based SWCCs requires a substantial data pair of water content and suction and their distribution characteristics. In this study, the kernel density estimate (KDE) approach was applied to water content and suction data measured from field-installed co-located sensors of a compacted clay bed to (1) determine the modality of water content and suction distribution and their constitutive relationship at variable weather conditions and (2) demonstrate the importance of probabilistic analysis of SWCC. The Gaussian function was used in the KDE analysis. A moisture sensor and soil water potential sensor were juxtaposed at 0.3 m depth of the 3 m × 3 m compacted clay bed to collect the water content and suction data and determine their distribution under the field condition. The density plots of both water content and suction at 0.3 m depth exhibited multimodal distribution due to the uneven distribution of climatic events. The KDE reasonably identified the air entry value, saturated moisture content, and residual moisture content in the field conditions, which were validated with field-based SWCC plots. The study showed that probabilistic analysis better interprets the realistic scenarios of field unsaturated soil behavior. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email