基于车辆通信的车辆队列预测框架

Varun Jain, Stephan Lapoehn, T. Frankiewicz, T. Hesse, M. Gharba, Sandip Gangakhedkar, K. Ganesan, Hanwen Cao, J. Eichinger, A. R. Ali, Yao Zou, Liang Gu
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引用次数: 13

摘要

与传感器系统的识别相比,车辆之间的信息传输延迟较低,这是车辆队列系统中V2V通信的主要优点之一。低延迟使得后续车辆能够在很短的时间内预测前车的轨迹并规划所需的控制动作。此外,在视场或天气条件不合适的情况下,视觉传感器的信息不可用或有限的情况下,可以有效地使用V2V。在本文中,我们提出了这样一个车辆队列系统,它只依赖于V2V通信,而不使用视觉传感器。我们还评估了通信延迟和可靠性对系统性能的影响。使用5G-V2X和802.11p通信的原型硬件进行的车辆测试显示了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction based framework for vehicle platooning using vehicular communications
One of the major advantages of V2V communication for vehicle platooning system is the low latency of message transfer between the vehicles as compared to the recognition by the sensor systems. The low latency allows the following vehicles to predict the trajectory of leading vehicle and plan the required control actions in a very short time. In addition, V2V can be effectively used in scenarios where the information from vision sensors in unavailable or limited due to field-of-view or unsuitable weather conditions. In this paper, we present such a vehicle platooning system that relies only on V2V communication, without use of vision sensors. We also evaluate the effect of communication latency and reliability on the performance of the system. Vehicle tests using prototype hardware for 5G-V2X and 802.11p communications show the effectiveness of the approach.
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