构建车联网信息物理系统逻辑视图的质量-成本权衡：一种深度强化学习方法
Quality-Cost Trade-off on Constructing Logical Views for Vehicular Cyber-Physical Systems: A Deep Reinforcement Learning Approach
AI总结：
本文针对车联网信息物理系统逻辑视图构建中的质量与成本平衡问题，提出基于分布式深度确定性策略梯度的优化方法，通过联合决策感知与上传参数实现视图质量最大化与成本最小化。
摘要：
随着感知技术、车联网（V2X）通信和边缘计算范式的发展，车联网信息物理系统（VCPS）正在成为实现未来智能交通系统（ITS）的最基础平台。特别是，基于异构信息感知和上传在边缘节点构建逻辑视图对VCPS的实现至关重要。然而，在时效性和准确性方面质量更高的视图可能需要更高的感知和上传成本。鉴于此，本文致力于在构建VCPS逻辑视图的质量与成本之间取得平衡。具体而言，我们首先推导了基于多类M/G/1优先级队列的信息感知模型和基于可靠性保证的车到基础设施（V2I）通信的数据上传模型。在此基础上，我们同时设计了两个指标，即视图年龄（AoV）和视图成本（CoV）。然后，我们构建了一个双目标问题，以最大化AoV并最小化CoV。进一步，我们提出了一种分布式分布式深度确定性策略梯度（D4PG）解决方案，用于确定感知信息、频率、上传优先级、传输功率和V2I带宽。最后，我们建立了仿真模型并进行了全面的性能评估，仿真结果确凿地证明了所提方案的优越性。
英文摘要：
With the development of sensing technologies, vehicle-to-everything (V2X) communications, edge computing paradigm, vehicular cyber-physical systems (VCPS) are emerging as the most fundamental platform for realizing future intelligent transportation systems (ITSs). In particular, the construction of logical views at the edge nodes based on heterogeneous information sensing and uploading are critical to the realization of VCPS. However, a higher-quality view in terms of timeliness and accuracy may require higher cost on sensing and uploading. In view of this, this paper is dedicated to striking a balance between the quality and the cost for constructing logical views of VCPS. Specifically, we first derive an information sensing model based on multi-class M/G/1 priority queue and a data uploading model based on reliability-guaranteed vehicle-to-infrastructure (V2I) communications. On this basis, we design two metrics, namely, age of view (AoV) and cost of view (CoV), simultaneously. Then, we formulate a bi-objective problem to maximize the AoV and minimize the CoV. Further, we propose a distributed distributional deep deterministic policy gradient (D4PG) solution to determine sensing information, frequency, uploading priority, transmission power, and V2I bandwidth. Finally, we build a simulation model and give a comprehensive performance evaluation, and the simulation results conclusively demonstrate the superiority of the proposed solution.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
