Assessing the impact of communication delays for Autonomous Intersection Management systems

IF 5.8 2区 计算机科学 Q1 TELECOMMUNICATIONS
Michael I.-C. Wang , Charles H.-P. Wen , H. Jonathan Chao
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引用次数: 0

Abstract

Communication is essential for Cooperative Intelligent Transportation Systems (C-ITS) to achieve better road efficiency, especially for Autonomous Intersection Management (AIM) which coordinates vehicles to pass the intersection safely and efficiently. Communication delays cause severe safety crises (i.e., collisions) and vehicular-performance degradation regarding intersection capacities and vehicular delays. Targeting the delays, network researchers have been working on low-latency communication technologies, and C-ITS researchers have proposed delay-tolerant AIM systems to avoid collisions in intersections. The impacts of communication delays are observed and discussed in the literature; however, models and assessments of the delay requirements for AIM are needed to provide insights for future network and C-ITS research. Here, we model the impact of communication delays on vehicular performance at an autonomous intersection and validate the models with the simulation results from over two million experiments, two types of multi-lane intersections (a typical 4-legged intersection and a roundabout), and four AIM systems. The simulations are conducted with SUMO simulator and AIM systems, where communication delays are inserted into the message exchanges during the simulation. The models are represented in linear, quintic, and cubic polynomials, showing that communication delay between 0 to 100 milliseconds is linearly related to vehicular performance in terms of intersection capacity and vehicular delay. According to the models, we show that by reducing communication delay from 100 to 10 milliseconds, the capacity degradation can be reduced from 7-10% to 0.7-1.0%. Moreover, communication delays must be less than 247 milliseconds to allow AIM systems to outperform traditional traffic lights.

评估自主交叉口管理系统通信延迟的影响
通信对于协同智能交通系统(C-ITS)实现更高的道路效率至关重要,尤其是对于协调车辆安全高效通过交叉路口的自主交叉路口管理(AIM)而言。通信延迟会导致严重的安全危机(即碰撞),并在交叉路口通行能力和车辆延迟方面造成车辆性能下降。针对延迟问题,网络研究人员一直在研究低延迟通信技术,而 C-ITS 研究人员则提出了容错 AIM 系统,以避免交叉路口发生碰撞。文献中对通信延迟的影响进行了观察和讨论;但是,需要对 AIM 的延迟要求进行建模和评估,以便为未来的网络和 C-ITS 研究提供见解。在此,我们建立了通信延迟对自主交叉路口车辆性能影响的模型,并通过两百多万次实验、两种类型的多车道交叉路口(典型的四脚交叉路口和环形交叉路口)以及四个 AIM 系统的仿真结果对模型进行了验证。模拟是通过 SUMO 模拟器和 AIM 系统进行的,在模拟过程中会在信息交换中插入通信延迟。模型以线性、五次多项式和三次多项式表示,表明 0 至 100 毫秒之间的通信延迟与交叉口容量和车辆延迟方面的车辆性能呈线性关系。根据这些模型,我们可以看出,将通信延迟从 100 毫秒减少到 10 毫秒,通行能力下降率可从 7%-10%减少到 0.7%-1.0%。此外,通信延迟必须小于 247 毫秒,AIM 系统才能优于传统交通信号灯。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Vehicular Communications
Vehicular Communications Engineering-Electrical and Electronic Engineering
CiteScore
12.70
自引率
10.40%
发文量
88
审稿时长
62 days
期刊介绍: Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier. The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications: Vehicle to vehicle and vehicle to infrastructure communications Channel modelling, modulating and coding Congestion Control and scalability issues Protocol design, testing and verification Routing in vehicular networks Security issues and countermeasures Deployment and field testing Reducing energy consumption and enhancing safety of vehicles Wireless in–car networks Data collection and dissemination methods Mobility and handover issues Safety and driver assistance applications UAV Underwater communications Autonomous cooperative driving Social networks Internet of vehicles Standardization of protocols.
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