Optimal Dynamic Coverage Infrastructure for Large-Scale Fleets of Reconnaissance UAVs

Altshuler, Yaniv; Pentland, Alex; Bruckstein, Alfred M.

doi:10.1007/978-3-319-63604-7_8

Cited by 14 publications

(10 citation statements)

References 76 publications

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“…As the prediction of future ride-sharing potential is ultimately needed for optimization purposes (of the overall travel time, congestion or any other utilization metric) of a dynamic coverage problem, comparing the performance of any proposed method to the theoretical results that are available for various types of such decentralized collaborative coverage challenges (see [100][101][102][103][104][105] and specifically [106]) can also be of value.…”

Section: Summary and Future Workmentioning

confidence: 99%

Modeling and Prediction of Ride-Sharing Utilization Dynamics

Altshuler

Katoshevski

et al. 2019

Journal of Advanced Transportation

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The potential of an efficient ride-sharing scheme to significantly reduce traffic congestion, lower emission level, and drivers’ stress, as well as facilitating the introduction of smart cities has been widely demonstrated in recent years. Furthermore, ride sharing can be implemented within a sound economic regime through the involvement of commercial services that creates a win-win for all parties (e.g., Uber, Lyft or Sidecar). This positive thrust however is faced with several delaying factors, one of which is the volatility and unpredictability of the potential benefit (or utilization) of ride-sharing at different times, and in different places. Better understanding of ride-sharing dynamics can help policy makers and urban planners in increase the city’s “ride-sharing friendliness” either by designing new ride-sharing oriented systems, as well as by providing ride-sharing service operators better tools to optimize their services. In this work the following research questions are posed: (a) Is ride-sharing utilization stable over time or does it undergo significant changes? (b) If ride-sharing utilization is dynamic can it be correlated with some traceable features of the traffic? and (c) If ride-sharing utilization is dynamic can it be predicted ahead of time? We analyze a dataset of over 14 million taxi trips taken in New York City. We propose a dynamic travel network approach for modeling and forecasting the potential ride-sharing utilization over time, showing it to be highly volatile. In order to model the utilization's dynamics, we propose a network-centric approach, projecting the aggregated traffic taken from continuous time periods into a feature space comprised of topological features of the network implied by this traffic. This feature space is then used to model the dynamics of ride-sharing utilization over time. The results of our analysis demonstrate the significant volatility of ride-sharing utilization over time, indicating that any policy, design, or plan that would disregard this aspect and chose a static paradigm would undoubtably be either highly inefficient or provide insufficient resources. We show that using our suggested approach it is possible to model the potential utilization of ride sharing based on the topological properties of the rides network. We also show that using this method the potential utilization can be forecasting a few hours ahead of time. One anecdotal derivation of the latter is that perfectly guessing the destination of a New York taxi rider becomes nearly three times easier than rolling a “Snake Eyes” at a casino.

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Section: Summary and Future Workmentioning

confidence: 99%

Modeling and Prediction of Ride-Sharing Utilization Dynamics

Altshuler

Katoshevski

et al. 2019

Journal of Advanced Transportation

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“…There has been a considerable increase in the use of the small Unmanned Aerial Vehicles (UAVs) across different spectrums such as entertainment and logistics [1]. The reason for such a widespread adaption is because they are agile robots that can navigate at high speeds in complex environments otherwise inaccessible to humans [21].…”

Section: Introductionmentioning

confidence: 99%

Solving Vehicle Routing Problem for unmanned heterogeneous vehicle systems using Asynchronous Multi-Agent Architecture (A-teams)

Subramanian¹,

Mondal²,

Bhounsule³

2023

Preprint

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Fast moving but power hungry unmanned aerial vehicles (UAVs) can recharge on slow-moving unmanned ground vehicles (UGVs) to survey large areas in an effective and efficient manner. In order to solve this computationally challenging problem in a reasonable time, we created a two-level optimization heuristics. At the outer level, the UGV route is parameterized by few free parameters and at the inner level, the UAV route is solved by formulating and solving a vehicle routing problem with capacity constraints, time windows, and dropped visits. The UGV free parameters need to be optimized judiciously in order to create high quality solutions. We explore two methods for tuning the free UGV parameters: (1) a genetic algorithm, and (2) Asynchronous Multi-agent architecture (Ateams). The A-teams uses multiple agents to create, improve, and destroy solutions. The parallel asynchronous architecture enables A-teams to quickly optimize the parameters. Our results on test cases show that the A-teams produces similar solutions as genetic algorithm but with a speed up of 2-3 times.

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“…• UAV swarms: The multi-UAVs system is analyzed from the perspective of the formation configuration, which mainly emphasizes the external physical features of UAV networks. Analysis from this perspective makes the models more intuitive, so problems of transportation planning and control [8] are generally solved by this point of view.…”

Section: Introductionmentioning

confidence: 99%

Self-Organizing Relay Selection in UAV Communication Networks: A Matching Game Perspective

Liu

Wang

et al. 2019

IEEE Wireless Commun.

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For large unmanned aerial vehicle (UAV) networks, the timely communication is needed to accomplish a series of missions accurately and effectively. The relay technology will play an important role in UAV networks by helping drones communicating with long-distance drones, which solves the problem of the limited transmission power of drones. In this paper, the relay selection is seen as the entry point to improve the performance of self-organizing network with multiple optimizing factors. Different from the ground relay models, the relay selection in UAV communication networks presents new challenges, including heterogeneous, dynamic, dense and limited information characteristics. More effective schemes with distributed, fast, robust and scalable features are required to solve the optimizing problem. After discussing the challenges and requirements, we find that the matching game is suitable to model the complex relay model. The advantages of the matching game in selforganizing UAV communications are discussed. Moreover, we provide extensive applications of matching markets, and then propose a novel classification of matching game which focuses on the competitive relationship between players. Specifically, basic preliminary models are presented and some future research directions of matching game in UAV relay models are discussed. ). due to the limited transmission capacity, the heavy UAVto-infrastructure communication hardware and the unreliable communication [3], it is difficult for all UAVs to connect with the satellite. With large-scale deployment and intensive cooperation of UAVs, it is meaningful to discuss the internal communication [4] of UAVs. In more extreme cases, if satellite communications are disrupted, effective internal communications can guarantee the completion of the mission.In the internal communication, the technology of short haul communication is used. As shown in Fig. 1, due to the complexity of the spatial distribution, the UAV network needs to be divided into several coalitions to finish the comprehensive missions. Within the network, the internal communication of UAVs involves the control information exchange and the service information fusion. The information sharing mainly implements the information interaction among coalitions of UAVs, so as to configure the UAV coalitions and assign tasks. The information fusion mainly refers to the information exchange between the units within the UAVs, so drones can assess the overall situation and accomplish tasks.Because of the transmission power constraint of drones, it is difficult to achieve reliable communications among the whole UAV network. Some drones should be used as relay devices to improve the quality of the communication. However, the large scale of UAVs, the self-organization of UAV coalition and the intensive external interference make the relay selection of UAV communication more difficult. Considering the complexity of the UAV communication, this article mainly provides a new perspective of developing distributed and robust relay s...

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Optimal Dynamic Coverage Infrastructure for Large-Scale Fleets of Reconnaissance UAVs

Cited by 14 publications

References 76 publications

Modeling and Prediction of Ride-Sharing Utilization Dynamics

Modeling and Prediction of Ride-Sharing Utilization Dynamics

Solving Vehicle Routing Problem for unmanned heterogeneous vehicle systems using Asynchronous Multi-Agent Architecture (A-teams)

Self-Organizing Relay Selection in UAV Communication Networks: A Matching Game Perspective

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