Over the last few years, the concept of incorporating aerial vehicles into the urban environment for diverse purposes has attracted ample interest and investment. These purposes cover a broad spectrum of applications, from larger vehicles designed for passenger transport, to package delivery and inspection/surveillance missions performed by small unmanned drones. While these Advanced Air Mobility (AAM) operations have the potential to alleviate bottlenecks arising from saturated surface transportation networks, there are a number of challenges that need to be addressed to make these operations safe and viable. One challenge is predicting weather effects within the urban environment with the required level of spatiotemporal fidelity, which current operational weather models fail to provide due to the use of coarse grid spacings (a few kilometers) constrained by the predictive performance limitations of traditional computer architectures. Herein, we demonstrate how FastEddy®, a microscale model that exploits the accelerated nature of graphics processing units for high‐performance computing, can be used to understand and predict urban weather impacts from seasonal, day‐to‐day, diurnal, and sub‐hourly scales. To that end, we efficiently perform more than 50 telescoped simulations of microscale urban effects at street‐scale (5 m grid spacing) driven by realistic weather over a 20 km2region centered at the downtown area of Dallas, Texas. Our analyses demonstrate that urban‐weather interactions at the street‐scale are complex and tightly connected, which is of utmost relevance to AAM operations. These demonstrations reveal the capability of such models to provide real‐time weather hazard avoidance products tailored to capture microscale urban effects.
This content will become publicly available on May 1, 2024
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- Award ID(s):
- 2148178
- NSF-PAR ID:
- 10490260
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Drones
- Volume:
- 7
- Issue:
- 5
- ISSN:
- 2504-446X
- Page Range / eLocation ID:
- 319
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
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
-
As city populations continue to rise, urban air mobility (UAM) seeks to provide much needed relief from traffic congestion. UAM is enforced by electrical vertical takeoff and landing (eVTOL) vehicles, which operate out of a vertiport, akin to the relationship between planes and airports. The vertiport has an air traffic controller (ATC) tasked with managing each eVTOL, ensuring they reach their destinations on time and safely. This task allocation problem can be difficult due to inadvertent issues such as mechanical failure, inclement weather, collisions, among other uncertainties that may arise. This paper provides a novel solution to this Urban Air Mobility - Vertiport Schedule Management (UAM-VSM) problem through the utilization of graph convolutional networks (GCNs). GCNs allow us to add abstractions of the vertiport space and eVTOL space as graphs, and aggregate information for a centralized ATC agent to help generalize the environment. We use Unreal Engine combined with Airsim for high fidelity simulation. The proposed GRL agent will be trained in an environment without extra uncertainties and then tested with and without those uncertainties. The performance will be examined side by side with a random and first come first serve (FCFS) baseline.more » « less
-
This paper addresses the proposed air corridor planned to be established between the University of North Texas (UNT) and Choctaw Nation of Oklahoma (CNO), a model for accessible Advance Air Mobility (AAM) service. The National Aeronautics and Space Administration (NASA) defines AAM as “safe, sustainable, affordable, and accessible aviation for transformational local and intra-regional missions" [1] and AAM missions as rural and urban operations that occur below ranges of 300 nautical miles, including passenger carrying and cargo delivery technologies.more » « less
-
null (Ed.)Intelligent Transportation Systems (ITS) aim at integrating sensing, control, analysis, and communication technologies into travel infrastructure and transportation to improve mobility, comfort, safety, and efficiency. Car manufacturers are continuously creating smarter vehicles, and advancements in roadways and infrastructure are changing the feel of travel. Traveling is becoming more efficient and reliable with a range of novel technologies, and research and development in ITS. Safer vehicles are introduced every year with greater considerations for passenger and pedestrian safety, nevertheless, the new technology and increasing connectivity in ITS present unique attack vectors for malicious actors. Smart cities with connected public transportation systems introduce new privacy concerns with the data collected about passengers and their travel habits. In this paper, we provide a comprehensive classification of security and privacy vulnerabilities in ITS. Furthermore, we discuss challenges in addressing security and privacy issues in ITS and contemplate potential mitigation techniques. Finally, we highlight future research directions to make ITS more safe, secure, and privacy-preserving.more » « less
