走向协作自动驾驶:模拟平台和端到端系统
概括
协作自动驾驶通过优化信息共享来提高安全性. 本研究介绍了V2Xverse模拟和CoDriving系统,提高驾驶性能和减少碰撞.
科学领域:
- 自动驾驶自动驾驶的自动驾驶
- 机器学习 机器学习
- 通信系统 通信系统
背景情况:
- 车辆到一切辅助的自动驾驶 (V2X-AD) 显示出对更安全的道路的承诺.
- 目前的V2X-AD研究缺乏对基础设施和通信资源利用进行性能提升的探索.
- 需要协作自动驾驶系统来优化信息共享.
研究的目的:
- 开发一个模拟平台 (V2Xverse),用于生成数据和测试V2X-AD系统.
- 引入一个综合系统 (CoDriving),集成V2X通信,以提高自动驾驶.
- 为提高性能和效率,提出和评估一项新的以驾驶为导向的沟通策略.
主要方法:
- 开发了V2Xverse,这是一个具有数据生成方案,全系统部署代码库和闭环性能评估的模拟平台.
- 推出了CoDriving,一个端到端的系统,将V2X通信与使用稀疏的感知线索来补充驾驶关键区域的新战略相结合.
- 使用V2Xverse进行了全面的基准测试,以分析模块化和闭环驾驶性能.
主要成果:
- 与最先进的方法相比,共同驾驶显著提高了62.49%的驾驶分数.
- 共同驾驶极大降低了53.50%的行人碰撞率.
- 在动态通信限制下,共同驾驶证明了持续的性能优越性.
结论:
- V2Xverse平台为协作自动驾驶研究和开发提供了一个完整的管道.
- 协同驾驶系统有效地整合了V2X通信,提高了驾驶性能和通信效率.
- 建议的以驾驶为导向的沟通策略在提高V2X-AD.安全性和优化资源利用方面是有效的.
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