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A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry

机译:基于光学相机通信与摄影测量相结合的车辆定位新方案

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The demand for autonomous vehicles is increasing gradually owing to their enormous potential benefits. However, several challenges, such as vehicle localization, are involved in the development of autonomous vehicles. A simple and secure algorithm for vehicle positioning is proposed herein without massively modifying the existing transportation infrastructure. For vehicle localization, vehicles on the road are classified into two categories host vehicles (HVs) are the ones used to estimate other vehicles’ positions and forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV transmits modulated data from the tail (or back) light, and the camera of the HV receives that signal using optical camera communication (OCC). In addition, the streetlight (SL) data are considered to ensure the position accuracy of the HV. Determining the HV position minimizes the relative position variation between the HV and FV. Using photogrammetry, the distance between FV or SL and the camera of the HV is calculated by measuring the occupied image area on the image sensor. Comparing the change in distance between HV and SLs with the change in distance between HV and FV, the positions of FVs are determined. The performance of the proposed technique is analyzed, and the results indicate a significant improvement in performance. The experimental distance measurement validated the feasibility of the proposed scheme.
机译:由于其巨大的潜在利益,对自动驾驶汽车的需求正在逐渐增加。然而,无人驾驶汽车的发展涉及诸如汽车本地化的若干挑战。本文提出了一种用于车辆定位的简单且安全的算法,而无需大量修改现有的运输基础设施。对于车辆定位,道路上的车辆分为两类:主车辆(HV)用于估计其他车辆的位置,而前进车辆(FV)是在HV前方移动的车辆。 FV从尾灯(或背光)传输调制数据,而HV的摄像机使用光学摄像机通信(OCC)接收该信号。另外,考虑路灯(SL)数据以确保HV的位置精度。确定HV位置可使HV和FV之间的相对位置变化最小。使用摄影测量法,FV或SL与HV摄像机之间的距离是通过测量图像传感器上的占用图像区域来计算的。将HV和SL之间的距离变化与HV和FV之间的距离变化进行比较,确定FV的位置。分析了所提出技术的性能,结果表明性能有了显着提高。实验距离测量验证了该方案的可行性。

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