面向无人机辅助车联网的并行任务传输与处理优化策略

doi:10.16182/j.issn1004731x.joss.23-1322

系统仿真学报 ›› 2025, Vol. 37 ›› Issue (3): 635-645.doi: 10.16182/j.issn1004731x.joss.23-1322

• 论文 • 上一篇

面向无人机辅助车联网的并行任务传输与处理优化策略

杨超¹, 郑瑞群¹, 李圳¹, 张鸿薇¹, 唐燕群², 李东泽³

^1.广东工业大学自动化学院，广东广州 510006
^2.中山大学电子与通信工程学院，广东深圳 518107
^3.军事科学院国防科技创新研究院，北京 100091

收稿日期:2023-11-03 修回日期:2023-12-19 出版日期:2025-03-17 发布日期:2025-03-21
通讯作者: 李东泽
第一作者简介:杨超(1985-)，男，副教授，博士，研究方向为智能交通系统。
基金资助:
国家自然科学基金联合基金(U1911401);广东省自然科学基金面上项目(2024A1515012745);深圳市科技重大专项(KJZD 20240903102000001)

Parallel Task Transmission and Processing Optimization Scheme for UAV-assisted Internet of Vehicles

Yang Chao¹, Zheng Ruiqun¹, Li Zhen¹, Zhang Hongwei¹, Tang Yanqun², Li Dongze³

^1.School of Automation, Guangdong University of Technology, Guangzhou 510006, China
^2.School of Electronics and Communications, SUN YAT-SEN University, Shenzhen 518107, China
^3.National Innovation Institute of Defense Technology, Academy of Military Science, Beijing 100091, China

Received:2023-11-03 Revised:2023-12-19 Online:2025-03-17 Published:2025-03-21
Contact: Li Dongze

摘要/Abstract

摘要：

在构建无人机辅助车联网过程中，为解决无人机有限的能量与计算能力导致现有的平铺式逐个服务点的覆盖策略效率较低的问题，基于无人机的可视距通信和快速移动的特点，提出一种并行的计算任务传输与处理优化策略。无人机在获得计算任务后直接飞往下一个服务点，在飞行的过程中同时进行任务处理，无人机的飞行轨迹和任务调度策略被联合优化。设计了一种双层优化求解算法，重点考虑了待处理任务的优先级。仿真结果表明：并行任务传输与处理优化策略在无人机的服务能效和任务处理效率上优于传统的平铺式无人机覆盖策略，更加适合智能交通系统的应用需求。

关键词: 车联网, 无人机, 路径规划, 任务调度

Abstract:

To address the increasing of computation demands of internet of vehicles (IoV) users due to the sudden traffic congestion, unmanned aerial vehicles (UAVs) are introduced to the intelligent transportation systems (ITS) to construct an UAV-assisted IoV network. The UAV limited energy and computing resources lead to the current traditional UAV coverage strategy with one by one less efficiency. We propose a parallel task transmission and processing optimization strategy, considering the line-of-sight communication links and fast moving characteristics of UAV. After receiving the tasks from vehicles in the service point, UAV can fly to the next point and perform task processing while flying, both the UAV flight trajectory and task scheduling strategies are optimized jointly. We design a two-layer optimization solution algorithm, the prioritization of pending tasks is considered mainly. A set of simulation results show that, compared with the traditional UAV coverage strategy, the proposed parallel task transmission and processing scheme is more suitable for ITS application requirements, in terms of UAV service energy efficiency and task processing efficiency.

Key words: Internet of vehicles, UAV, flight trajectory optimization, task scheduling

中图分类号:

TP273

杨超,郑瑞群,李圳等 . 面向无人机辅助车联网的并行任务传输与处理优化策略[J]. 系统仿真学报, 2025, 37(3): 635-645.

Yang Chao,Zheng Ruiqun,Li Zhen,et al . Parallel Task Transmission and Processing Optimization Scheme for UAV-assisted Internet of Vehicles[J]. Journal of System Simulation, 2025, 37(3): 635-645.

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面向无人机辅助车联网的并行任务传输与处理优化策略

Parallel Task Transmission and Processing Optimization Scheme for UAV-assisted Internet of Vehicles

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