A method of vehicle networking environment information sharing based on distributed fountain code

Jianhang Liu , Xinyao Wang , Haibin Zhai , Shibao Li , Xuerong Cui , Qian Zhang
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Abstract

The exchange of perceptual information between autonomous vehicles could significantly improve driving safety. In general, obtaining more information means driving more safely. However, Frequent information sharing consumes a significant amount of channel bandwidth resources, which will reduce transmission efficiency and increase delay, especially in crowded cities. This paper presents a novel method of motion prediction compensation to solve this problem. Firstly, we propose a distributed fountain coding scheme to improve transmission efficiency and reduce vehicles’ delay in acquiring peripheral information. Secondly, we design a mobile prediction model and information transmission control algorithm to reduce traffic while ensuring information reliability. The simulation results show that the prediction accuracy of this method is above 94 %, the information transmission is reduced by more than 50 %, and the vehicle perception rate is increased by 34 %.

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基于分布式喷泉代码的车联网环境信息共享方法
自动驾驶车辆之间的感知信息交流可以大大提高驾驶安全性。一般来说,获得更多信息意味着驾驶更安全。然而,频繁的信息共享会消耗大量的信道带宽资源,从而降低传输效率并增加延迟,尤其是在拥挤的城市中。本文提出了一种新颖的运动预测补偿方法来解决这一问题。首先,我们提出了一种分布式喷泉编码方案,以提高传输效率,减少车辆获取周边信息的延迟。其次,我们设计了一种移动预测模型和信息传输控制算法,在保证信息可靠性的同时减少交通流量。仿真结果表明,该方法的预测准确率在 94 % 以上,信息传输量减少了 50 % 以上,车辆感知率提高了 34 %。
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