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A Novel UAV-Enabled Data Collection Scheme for Intelligent Transportation System Through UAV Speed Control
IEEE Transactions on Intelligent Transportation Systems ( IF 7.9 ) Pub Date : 2020-12-17 , DOI: 10.1109/tits.2020.3040557
Xiong Li , Jiawei Tan , Anfeng Liu , Pandi Vijayakumar , Neeraj Kumar , Mamoun Alazab

The rapid and convenient travel of people and the timely transportation of goods depend on the correct decision of the Intelligent Transportation Systems (ITS). Due to the decision-making of ITS requires a large amount of data to support, UAV-enabled periodic data collection is an effective method. However, due to the limited resources of UAV, UAV cannot directly collect data from all storage devices, resulting in unfair data collection. Therefore, we propose a UAV Speed Control based Fairness Data Collection (USCFDC) scheme. First, since the fairness of data collection will affect the decision-making of ITS, a framework for controlling the flight speed of the UAV is proposed to improve the fairness of data collection. The flight speed of UAV will slow down in areas with a large number of nodes, thereby improving the fairness of data collection. Second, a novel method is proposed to maximize the amount of data collected by UAV from each node. With this method, the value of the amount of data will be used as the dichotomous value in the dichotomy algorithm, and the UAV must collect a certain amount of data from each node. The upper and lower limits of the dichotomy algorithm are adjusted according to the time duration for UAV to collect data. Compared with previous schemes, the fairness of data collection can be improved by a maximum of 15.89% under the same flight time of UAV. Besides, the energy consumption is reduced by 49.31%–52.55% and the flight time of the UAV is reduced by 48%–62.38% when the amount of collected data is the same.

中文翻译:

基于无人机速度控制的新型基于无人机的智能交通系统数据采集方案

人员的快速便捷出行和货物的及时运输取决于智能运输系统(ITS)的正确决策。由于ITS的决策需要大量数据来支持,因此启用UAV的定期数据收集是一种有效的方法。但是,由于无人机资源有限,无人机无法直接从所有存储设备收集数据,导致数据收集不公。因此,我们提出了一种基于无人机速度控制的公平数据收集(USCFDC)方案。首先,由于数据收集的公平性将影响ITS的决策,因此提出了一种控制无人机飞行速度的框架,以提高数据收集的公平性。无人机在有大量节点的地区的飞行速度将放慢,从而提高数据收集的公平性。其次,提出了一种新颖的方法来最大化UAV从每个节点收集的数据量。使用这种方法,数据量的值将被用作二分法算法中的二分法值,而UAV必须从每个节点收集一定量的数据。根据无人机收集数据的持续时间,调整二分法算法的上限和下限。与以前的方案相比,在相同的无人机飞行时间下,数据收集的公平性最多可以提高15.89%。此外,在采集的数据量相同的情况下,无人机的能耗降低了49.31%–52.55%,无人机的飞行时间减少了48%–62.38%。数据量的值将被用作二分法算法中的二分法值,UAV必须从每个节点收集一定量的数据。根据无人机收集数据的持续时间,调整二分法算法的上限和下限。与以前的方案相比,在相同的无人机飞行时间下,数据收集的公平性最多可以提高15.89%。此外,在采集的数据量相同的情况下,无人机的能耗降低了49.31%–52.55%,无人机的飞行时间减少了48%–62.38%。数据量的值将被用作二分法算法中的二分法值,UAV必须从每个节点收集一定量的数据。根据无人机收集数据的持续时间,调整二分法算法的上限和下限。与以前的方案相比,在相同的无人机飞行时间下,数据收集的公平性最多可以提高15.89%。此外,在采集的数据量相同的情况下,无人机的能耗降低了49.31%–52.55%,无人机的飞行时间减少了48%–62.38%。与以前的方案相比,在相同的无人机飞行时间下,数据收集的公平性最多可以提高15.89%。此外,在采集的数据量相同的情况下,无人机的能耗降低了49.31%–52.55%,无人机的飞行时间减少了48%–62.38%。与以前的方案相比,在相同的无人机飞行时间下,数据收集的公平性最多可以提高15.89%。此外,在采集的数据量相同的情况下,无人机的能耗降低了49.31%–52.55%,无人机的飞行时间减少了48%–62.38%。
更新日期:2020-12-17
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