A LiDAR Error Model for Cooperative Driving Simulations

Michele Segata, R. Cigno, R. Bhadani, Matt Bunting, J. Sprinkle
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引用次数: 8

Abstract

Cooperative driving and vehicular network simulations have done huge steps toward high realism. They have become essential tools for performance evaluation of any kind of vehicular networking application. Yet, cooperative vehicular applications will not be built on top of wireless networking alone, but rather fusing together different data sources including sensors like radars, LiDARs, or cameras. So far, these sensors have been assumed to be ideal, i.e., without any measurement error. This paper analyzes a set of estimated distance traces obtained with a LiDAR sensor and develops a stochastic error model that can be used in cooperative driving simulations. After implementing the model within the Plexe simulation framework, we show the impact of the model on a set of cooperative driving control algorithms.
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协同驾驶仿真激光雷达误差模型
协同驾驶和车辆网络模拟已经朝着高真实感迈出了巨大的一步。它们已经成为任何一种车联网应用性能评估的重要工具。然而,协作式车载应用不会仅仅建立在无线网络之上,而是将不同的数据源融合在一起,包括雷达、激光雷达或摄像头等传感器。到目前为止,这些传感器被认为是理想的,即没有任何测量误差。本文分析了激光雷达传感器获得的一组估计距离轨迹,并建立了可用于协同驾驶仿真的随机误差模型。在Plexe仿真框架内实现该模型后,我们展示了该模型对一组协同驾驶控制算法的影响。
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