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1. Simulation of Real-time Routing for UAS traffic Management with Communication and Airspace Safety Considerations

   https://doi.org/10.1109/DASC43569.2019.9081675  

   Jin, Zhao ; Zhao, Ziyi ; Luo, Chen ; Basti, Franco ; Solomon, Adrian ; Gursoy, M. Cenk ; Caicedo, Carlos ; Qiu, Qinru ( September 2019 , Proceedings of 38th Digital Avionics Systems Conference)

   Small Unmanned Aircraft Systems (sUAS) will be an important component of the smart city and intelligent transportation environments of the near future. The demand for sUAS related applications, such as commercial delivery and land surveying, is expected to grow rapidly in next few years. In general, sUAS traffic routing and management functions are needed to coordinate the launching of sUAS from different launch sites and determine their trajectories to avoid conflict while considering several other constraints such as expected arrival time, minimum flight energy, and availability of communication resources. However, as the airborne sUAS density grows in a certain area, it is difficult to foresee the potential airspace and communications resource conflicts and make immediate decisions to avoid them. To address this challenge, we present a temporal and spatial routing algorithm and simulation platform for sUAS trajectory management in a high density urban area that plans sUAS movements in a spatial and temporal maze taking into account obstacles that are either static or dynamic in time. The routing allows the sUAS to avoid static no-fly areas (i.e. static obstacles) or other in-flight sUAS and areas that have congested communication resources (i.e. dynamic obstacles). The algorithm is evaluated using an agent-based simulation platform. The simulation results show that the proposed algorithm outperforms other route management algorithms in many areas, especially in processing speed and memory efficiency. Detailed comparisons are provided for the sUAS flight time, the overall throughput, conflict rate and communication resource utilization. The results demonstrate that our proposed algorithm can be used to address the airspace and communication resource utilization needs for a next generation smart city and smart transportation. 

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2. Advanced Air Mobility Operation and Infrastructure for Sustainable Connected eVTOL Vehicle

   https://doi.org/10.3390/drones7050319  

   Al-Rubaye, Saba ; Tsourdos, Antonios ; Namuduri, Kamesh ( May 2023 , 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.

    

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3. VLC-Enabled Human-Aware Building Management System

   Y, Kalay ; H, Sathyanarayanan ; D, Schaumann ; A, Wang ; G, Chen ; R, G ( July 2020 , Proc. 22nd International Conference on Human-Computer Interaction (HCII2020))

   null ; null (Ed.)

   “Smart” buildings that can sense and detect people’s presence have been in use for the past few decades, mostly using technologies that trigger reactive responses such as turning on/off heating/ventilating, lighting, security, etc. We argue that to be considered truly smart, buildings must become “aware” about the locations and activities of their inhabitants so they can proactively engage with the occupants and inform their decision making with respect to which actions to execute, by whom and where. To help assess the potential impact of “aware” buildings on their occupants, we are developing a multi-agent simulation-powered building management system that can sense human and building assets, extrapolate patterns of utilization, simulate what-if scenarios and suggest changes to user activities and resource allocation to maximize specific Key Performance Indicators (KPIs). The system is able to evaluate the implications of potential conflict resolution strategies and account for individual and collaborative activities of different types of users in semantically rich environments. Sensing in our case is based on Visible Light Communication (VLC) technology, embedded in a building’s LED lighting system. It can detect the actors, where they are located and what they do. To understand what happens in each space at any given time the information derived from the VLC system is combined with models of users’ activity schedules, profiles, and space affordances. We demonstrate our approach by hypothetically applying it to a Cardiac Catheterization Laboratory (CCL). The CCL is high-intensity hospital unit, second only to the Emergency Department in terms of the urgency of the cases it must handle. An aware building will help both patients and staff to allocate their (always scarce) resources more efficiently, saving time and alleviating stress. 

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4. On the Elliptic Curve Cryptography for Privacy-Aware Secure ACO-AODV Routing in Intent-Based Internet of Vehicles for Smart Cities

   https://doi.org/10.1109/TITS.2020.3008361  

   Safavat, Sunitha ; Rawat, Danda B. ( June 2020 , IEEE Transactions on Intelligent Transportation Systems)

   null (Ed.)

   Internet of Vehicles (IoV) in 5G is regarded as a backbone for intelligent transportation system in smart city, where vehicles are expected to communicate with drivers, with road-side wireless infrastructure, with other vehicles, with traffic signals and different city infrastructure using vehicle-to-vehicle (V2V) and/or vehicle-to-infrastructure (V2I) communications. In IoV, the network topology changes based on drivers' destination, intent or vehicles' movements and road structure on which the vehicles travel. In IoV, vehicles are assumed to be equipped with computing devices to process data, storage devices to store data and communication devices to communicate with other vehicles or with roadside infrastructure (RSI). It is vital to authenticate data in IoV to make sure that legitimate data is being propagated in IoV. Thus, security stands as a vital factor in IoV. The existing literature contains some limitations for robust security in IoV such as high delay introduced by security algorithms, security without privacy, unreliable security and reduced overall communication efficiency. To address these issues, this paper proposes the Elliptic Curve Cryptography (ECC) based Ant Colony Optimization Ad hoc On-demand Distance Vector (ACO-AODV) routing protocol which avoids suspicious vehicles during message dissemination in IoV. Specifically, our proposed protocol comprises three components: i) certificate authority (CA) which maps vehicle's publicly available info such as number plates with cryptographic keys using ECC; ii) malicious vehicle (MV) detection algorithm which works based on trust level calculated using status message interactions; and iii) secure optimal path selection in an adaptive manner based on the intent of communications using ACO-AODV that avoids malicious vehicles. Experimental results illustrate that the proposed approach provides better results than the existing approaches. 

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5. Risk-Aware Resource Management in Public Safety Networks

   https://doi.org/10.3390/s19183853  

   Vamvakas, Panagiotis ; Tsiropoulou, Eirini Eleni ; Papavassiliou, Symeon ( September 2019 , Sensors)

   null (Ed.)

   Modern Public Safety Networks (PSNs) are assisted by Unmanned Aerial Vehicles (UAVs) to provide a resilient communication paradigm during catastrophic events. In this context, we propose a distributed user-centric risk-aware resource management framework in UAV-assisted PSNs supported by both a static UAV and a mobile UAV. The mobile UAV is entitled to a larger portion of the available spectrum due to its capability and flexibility to re-position itself, and therefore establish better communication channel conditions to the users, compared to the static UAV. However, the potential over-exploitation of the mobile UAV-based communication by the users may lead to the mobile UAV’s failure to serve the users due to the increased levels of interference, consequently introducing risk in the user decisions. To capture this uncertainty, we follow the principles of Prospect Theory and design a user’s prospect-theoretic utility function that reflects user’s risk-aware behavior regarding its transmission power investment to the static and/or mobile UAV-based communication option. A non-cooperative game among the users is formulated, where each user determines its power investment strategy to the two available communication choices in order to maximize its expected prospect-theoretic utility. The existence and uniqueness of a Pure Nash Equilibrium (PNE) is proven and the convergence of the users’ strategies to it is shown. An iterative distributed and low-complexity algorithm is introduced to determine the PNE. The performance of the proposed user-centric risk-aware resource management framework in terms of users’ achievable data rate and spectrum utilization, is achieved via modeling and simulation. Furthermore, its superiority and benefits are demonstrated, by comparing its performance against other existing approaches with regards to UAV selection and spectrum utilization. 

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