基于轨迹的车联网人群感知任务分配

Xu Xiaoyu, Zhiqing Huang, Zhuying Lin
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引用次数: 3

摘要

人群感知是车联网的核心特征之一,利用车联网进行人群感知有利于感知任务的合理分配。本文主要研究了车联网人群感知任务分配问题,提出了一种基于轨迹的车联网人群感知任务分配方案。在有限的预算约束下,参与者的运动轨迹作为时空可用性的指标。根据最小覆盖问题的求解思路,选择最小参与车辆数量,实现对目标区域的覆盖。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trajectory-Based Task Allocation for Crowd Sensing in Internet of Vehicles
Crowd sensing is one of the core features of internet of vehicles, the use of internet of vehicles for crowd sensing is conducive to the rational allocation of sensing tasks. This paper mainly studies the problem of task allocation for crowd sensing in internet of vehicles, proposes a trajectory-based task allocation scheme for crowd sensing in internet of vehicles. With limited budget constraints, participants' trajectory is taken as an indicator of the spatiotemporal availability. Based on the solution idea of the minimal-cover problem, select the minimum number of participating vehicles to achieve the coverage of the target area.
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