基于基础设施的车辆定位通过摄像头校准用于I2V通信警告警告.
Daniele Vignarca1, Michele Vignati1, Stefano Arrigoni1
1Department of Mechanical Engineering, Politecnico di Milano, 20156 Milan, Italy.
Sensors (Basel, Switzerland)
|August 26, 2023
概括
本研究引入了交叉路口与车辆 (I2V) 预警系统,使用路边摄像头用于交叉路口的车辆检测和跟踪. 它通过识别进入车辆的潜在障碍物来提高道路安全.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 运输工程 运输工程
背景情况:
- 对象检测和跟踪对于高级驾驶辅助系统 (ADAS) 和互联自动驾驶汽车 (CAV) 至关重要.
- 道路交叉点,特别是在城市地区,是交通事故的高风险区域.
- 现有的系统需要改进,以便在十字路口准确监控车辆.
研究的目的:
- 开发和评估一个十字路口到车辆 (I2V) 预警系统,以提高道路安全.
- 在十字路口检测和跟踪车辆,识别其他道路使用者的潜在障碍.
- 使用路边摄像头数据提供准确的车辆定位.
主要方法:
- 一个安装在路边装置 (RSU) 上的单个摄像头执行图像检测和跟踪.
- 一个本地化算法利用线性转换与内在的摄像机参数,高度和俯仰角.
- 车辆的位置是根据全球参考框架 (度和经度) 确定的.
主要成果:
- 定位算法实现了0.62米的平均误差.
- 检测可靠性显示出1.9%的低虚假阳性率.
- 错误检测率为3.6%.
结论:
- 拟议的I2V系统有效地检测和跟踪交叉路口的车辆.
- 定位算法为安全警告提供了准确的定位.
- 这项技术可以大大减少与十字路口有关的事故.
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