Recently, 5G and beyond 5G (B5G) systems, Ultrareliable Low Latency Network (URLLC) represents the key enabler for a range of modern technologies to support Industry 4.0 applications, such as transportation and healthcare. Real-world implementation of URLLC can help in major transformations in industries like autonomous driving, road safety, and efficient traffic management. Furthermore, URLLC contributes to the objective of fully autonomous cars on the road that can respond to dynamic traffic patterns by collaborating with other vehicles and surrounding environments rather than relying solely on local data. For this, the main necessity is that how information is to be transferred among the vehicles in a very small time frame. This requires information to be transferred among the vehicles reliably in extremely short time duration. In this paper, we have implemented and analyzed the Multiaccess Edge Computing- (MEC-) based architecture for 5G autonomous vehicles based on baseband units (BBU). We have performed Monte Carlo simulations and plotted curves of propagation latency, handling latency, and total latency in terms of vehicle density. We have also plotted the reliability curve to double-check our findings. When the RSU density is constant, the propagation latency is directly proportional to the vehicle density, but when the vehicle density is fixed, the propagation latency is inversely proportional. When RSU density is constant, vehicle density and handling latency are strictly proportional, but when vehicle density is fixed, handling latency becomes inversely proportional. Total latency behaves similarly to propagation latency; that is, it is also directly proportional.

中文翻译：

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B5G 超可靠低延迟网络，实现高效安全的自主智能车联网

最近，在 5G 和 5G (B5G) 系统之后，超可靠低延迟网络 (URLLC) 代表了一系列现代技术的关键推动因素，以支持工业 4.0 应用，例如运输和医疗保健。URLLC 的实际实施可以帮助自动驾驶、道路安全和高效交通管理等行业的重大转型。此外，URLLC 有助于实现道路上完全自动驾驶汽车的目标，该汽车可以通过与其他车辆和周围环境协作而不是仅依赖本地数据来响应动态交通模式。为此，主要的必要性是如何在非常短的时间范围内在车辆之间传输信息。这需要在极短的时间内在车辆之间可靠地传输信息。在本文中，我们已经为基于基带单元 (BBU) 的 5G 自动驾驶汽车实施并分析了基于多接入边缘计算 (MEC) 的架构。我们已经执行了蒙特卡罗模拟并绘制了传播延迟、处理延迟和车辆密度方面的总延迟曲线。我们还绘制了可靠性曲线以再次检查我们的发现。当 RSU 密度恒定时，传播延迟与车辆密度成正比，但当车辆密度固定时，传播延迟成反比。当 RSU 密度恒定时，车辆密度和操控延迟严格成正比，但当车辆密度固定时，操控延迟成反比。总延迟的行为类似于传播延迟；也就是说，它也是成正比的。