无校准的路边BEV感知与V2X启用的车辆位置辅助
Wei Zhang1, Yilin Gao1, Zhiyuan Jiang1
1Information and Communication Engineering, Shanghai University, Shanghai 200444, China.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
本研究介绍了一种用于自动驾驶的新型无校准路边鸟视感知系统 (BEV). 它使用路边摄像头和蜂车辆到一切 (C-V2X) 通信来提高环境意识.
科学领域:
- 计算机视觉 计算机视觉
- 自主驾驶系统 自主驾驶系统
- 机器人技术 机器人技术 机器人技术
背景情况:
- 自动驾驶系统需要全面的环境意识,通常通过基于车辆的鸟视角 (BEV) 感知来实现.
- 现有的方法依赖于精确的摄像头校准或深度估计,这可能会引入不准确性.
- 路边感知提供了一个补充的方法来增强情境意识.
研究的目的:
- 为自动驾驶开发一个无校准的路边BEV感知架构.
- 提高BEV感知对现实世界通信和定位不确定性的稳定性.
- 通过使用相关数据集,与现有方法对拟议的架构进行评估.
主要方法:
- 利用路边高架摄像头和车辆位置通过蜂车辆到一切 (C-V2X) 通信传输.
- 开发了一种无校准的方法,独立于相机内在参数.
- 通过注入随机坐标噪声和变化的数据比例,模拟了诸如C-V2X延迟,数据包丢失和定位噪声等实际问题.
主要成果:
- 与基于校准和无校准的基线相比,拟的架构在路边BEV感知方面表现出卓越的性能.
- 该系统有效地处理C-V2X通信和车辆定位固有的不确定性.
- 对DAIR-V2X数据集的实验验证证证了拟议方法的有效性.
结论:
- 一个新的,无校准的路边BEV感知架构增强了自动驾驶能力.
- C-V2X集成系统为环境意识提供了强大的解决方案,减轻了常见的现实世界数据问题.
- 这种方法为提高自动驾驶汽车的安全性和可靠性提供了一个有希望的方向.
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