Impact of radio channel characteristics on the longitudinal behaviour of truck platoons in critical car-following situations

Salil Sharma, E. Al-khannaq, R. Riebl, W. Schakel, P. Knoppers, A. Verbraeck, J. V. Lint
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引用次数: 1

Abstract

Truck platooning is an application of cooperative adaptive cruise control (CACC) which relies on vehicle-to-vehicle communications facilitated by vehicle ad-hoc networks. Communication uncertainties can affect the performance of a CACC controller. Previous research has not considered the full spectrum of possible car-following scenarios needed to understand how the longitudinal behaviour of truck platoons would be affected by changes in the communication network. In this paper, we investigate the impact of radio channel parameters on the string stability and collision avoidance capabilities of a CACC controller governing the longitudinal behaviour of truck platoons in a majority of critical car-following situations. We develop and use a novel, sophisticated and open-source VANET simulator OTS-Artery, which brings microscopic traffic simulation, network simulation, and psychological concepts in a single environment, for our investigations. Our results indicate that string stability and safety of truck platoons are mostly affected in car-following situations where truck platoons accelerate from the standstill to the maximum speed and decelerate from the maximum speed down to the standstill. The findings suggest that string stability can be improved by increasing transmission power and lowering receiver sensitivity. However, the safety of truck platoons seems to be sensitive to the choice of the path loos model.
无线电信道特性对卡车排在关键车辆跟随情况下纵向行为的影响
卡车队列是一种协作式自适应巡航控制(CACC)的应用,它依赖于车辆自组织网络促进的车对车通信。通信不确定性会影响CACC控制器的性能。以前的研究并没有考虑到所有可能的汽车跟随场景,需要了解卡车排的纵向行为如何受到通信网络变化的影响。在本文中,我们研究了无线电信道参数对控制卡车队列纵向行为的CACC控制器在大多数关键车辆跟随情况下的串稳定性和避碰能力的影响。我们开发并使用了一种新颖的、复杂的、开源的VANET模拟器OTS-Artery,它在单一环境中为我们的研究带来了微观交通模拟、网络模拟和心理概念。研究结果表明,货车排在从静止加速到最高速度,从最高速度减速到静止的情况下,其管柱稳定性和安全性受到的影响最大。研究结果表明,可以通过提高发射功率和降低接收灵敏度来改善弦的稳定性。然而,卡车排的安全性似乎对路径模型的选择很敏感。
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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