B-AWARE: 5G自动驾驶车辆的阻塞感知RSU调度

IF 2.8 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI:10.1145/3609133
Matthew Szeto, Edward Andert, Aviral Shrivastava, Martin Reisslein, Chung-Wei Lin, Christ Richmond
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引用次数: 0

摘要

5G毫米波(mmWave)技术由于能够实现Gbps范围内的数据速率,因此对联网自动驾驶汽车(cav)具有很大的前景。然而,毫米波的波束形成开销高,并且需要视距(LOS)来保持强连接。在车辆到基础设施(V2I)的场景中,自动驾驶汽车连接到路边单元(rsu),这些缺点变得明显。由于车辆是动态的,因此存在很大的链接阻塞可能性。这些阻塞对车辆上运行的连接应用程序(如协作感知和远程驾驶员接管)是有害的。现有的RSU选择方案仅基于信号强度和车辆轨迹进行决策,不足以防止链路阻塞。许多现代自动驾驶汽车的运动规划算法通常使用其他车辆的近期路径规划,要么通过车辆之间的明确通信,要么通过预测。在本文中,我们利用其他车辆近期路径计划的知识,进一步改进了自动驾驶汽车的RSU关联机制。我们将RSU关联算法转化为以最大化总通信带宽为目标的最短路径问题来解决RSU关联算法。我们使用城市交通模拟(SUMO)和自动驾驶智能车辆数字孪生(DRIVE)在12个高速公路和城市街道场景中评估了我们名为B-AWARE的方法,这些场景具有不同的交通密度和RSU位置。模拟显示,B-AWARE在平均情况下可将潜在数据量提高1.05倍,在最佳情况下可将潜在数据量提高1.28倍。但更令人印象深刻的是,与最先进的方法相比,B-AWARE在无连接情况下的平均时间减少了42%,在最佳情况下减少了60%。这是B-AWARE减少近100%堵塞的结果。
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B-AWARE: Blockage Aware RSU Scheduling for 5G Enabled Autonomous Vehicles
5G Millimeter Wave (mmWave) technology holds great promise for Connected Autonomous Vehicles (CAVs) due to its ability to achieve data rates in the Gbps range. However, mmWave suffers from a high beamforming overhead and requirement of line of sight (LOS) to maintain a strong connection. For Vehicle-to-Infrastructure (V2I) scenarios, where CAVs connect to roadside units (RSUs), these drawbacks become apparent. Because vehicles are dynamic, there is a large potential for link blockages. These blockages are detrimental to the connected applications running on the vehicle, such as cooperative perception and remote driver takeover. Existing RSU selection schemes base their decisions on signal strength and vehicle trajectory alone, which is not enough to prevent the blockage of links. Many modern CAVs motion planning algorithms routinely use other vehicle’s near-future path plans, either by explicit communication among vehicles, or by prediction. In this paper, we make use of the knowledge of other vehicle’s near future path plans to further improve the RSU association mechanism for CAVs. We solve the RSU association algorithm by converting it to a shortest path problem with the objective to maximize the total communication bandwidth. We evaluate our approach, titled B-AWARE, in simulation using Simulation of Urban Mobility (SUMO) and Digital twin for self-dRiving Intelligent VEhicles (DRIVE) on 12 highway and city street scenarios with varying traffic density and RSU placements. Simulations show B-AWARE results in a 1.05× improvement of the potential datarate in the average case and 1.28× in the best case vs. the state-of-the-art. But more impressively, B-AWARE reduces the time spent with no connection by 42% in the average case and 60% in the best case as compared to the state-of-the-art methods. This is a result of B-AWARE reducing nearly 100% of blockage occurrences.
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来源期刊
ACM Transactions on Embedded Computing Systems
ACM Transactions on Embedded Computing Systems 工程技术-计算机:软件工程
CiteScore
3.70
自引率
0.00%
发文量
138
审稿时长
6 months
期刊介绍: The design of embedded computing systems, both the software and hardware, increasingly relies on sophisticated algorithms, analytical models, and methodologies. ACM Transactions on Embedded Computing Systems (TECS) aims to present the leading work relating to the analysis, design, behavior, and experience with embedded computing systems.
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