双向长期短期内存应用于自动驾驶汽车在互联网上的自适应流
Chenn-Jung Huang1, Kai-Wen Hu2, Hao-Wen Cheng1
1Department of Computer Science & Information Engineering, National Dong Hwa University, Shoufeng, Hualien County 974301, Taiwan.
Biomimetics (Basel, Switzerland)
|October 27, 2023
概括
这项研究介绍了自动驾驶汽车乘客的6G驱动带宽管理算法,提高了在高峰交通期间的流媒体性能. 新系统将可访问的带宽平均提高55%.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 电信 电信服务 电信服务 电信服务
背景情况:
- 相互连接的自动驾驶汽车网络面临拥堵,特别是在高峰交通时段.
- 有限的研究解决了将6G等先进的无线技术集成到连接的车辆网络中的问题.
- 自动驾驶汽车的乘客需要强大的流媒体应用程序性能,而网络拥堵会给这种性能带来挑战.
研究的目的:
- 引入一种新的带宽管理算法,专门设计用于自动驾驶汽车中的流媒体应用程序.
- 为高速,广泛覆盖的车辆网络利用6G无线技术.
- 为应对网络拥堵中提供无流媒体服务的挑战.
主要方法:
- 开发一个量身定制的带宽管理算法,包括带宽继电器和视频剪辑预加载.
- 利用车辆到车辆 (V2V) 通信来协助带宽分配策略.
- 在各种网络条件下基于模拟验证算法的有效性.
主要成果:
- 拟议的算法成功地满足了自动驾驶汽车乘客的各种流媒体应用程序的带宽需求.
- 在用户需求高峰时期,带宽可用性显著增加.
- 实现了用户可访问带宽的平均提高55%.
结论:
- 开发的基于6G的带宽管理算法有效地提高了自动驾驶汽车的流媒体服务.
- 这种方法对在连接的自动驾驶汽车网络中有效管理带宽分配复杂性具有前景.
- 验证了先进无线技术的可行性,以改善车载娱乐和连接.
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