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A Car2X sensor model for virtual development of automated driving

机译:自动驾驶虚拟开发的CAR2X传感器模型

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Automated driving requires a reliable digital representation of the environment, which is achieved by various vehicle sensors. Wireless devices for communication between vehicles and infrastructure (Car2X communication) provide additional data beyond the vehicle's sensor range. In order to reduce the amount of on-road testing, there has been an increased use of numerical simulation in the development of automated driving functions, which demands accurate simulation models for the sensors involved. The present research deals with the development of Car2X sensor models for conceptual, automated driving investigations based on relatively simple yet computationally efficient mathematical models featuring parameters derived from on-road hardware testing. For analysis purposes, variations in range and reliability in different driving situations were measured and depicted in Google Earth. For the sensor model, a combination of geometric and stochastic models was chosen. The modeling is based on a link budget calculation that considers system and path losses, where wave propagation is described using Nakagami probability density functions. For intersections, an additional term is added to account for the path loss with geometric parameters of the intersection. After model parametrization, an evaluation was conducted. In addition, as a sample case, Car2X was added to an adaptive cruise control, and the improved functionality was demonstrated using vehicle dynamics simulation. This extended adaptive cruise control used information from the indicator of surrounding vehicles to react faster to lane changes by these vehicles.
机译:自动驾驶需要由各种车辆传感器实现的环境的可靠数字表示。用于车辆和基础设施之间的通信(CAR2X通信)的无线设备提供超出车辆的传感器范围的额外数据。为了减少通道测试量,在自动化驾驶功能的开发中使用数值模拟的使用增加了,这需要对所涉及的传感器进行准确的仿真模型。本研究涉及基于相对简单但计算的有效数学模型的概念性,自动化驾驶调查的Car2x传感器模型的开发,其特征在于源自通道硬件测试。出于分析目的,测量并在谷歌地球中测量并描绘了不同驾驶情况下的范围和可靠性的变化。对于传感器模型,选择了几何和随机模型的组合。建模基于链接预算计算,其考虑系统和路径损耗,其中使用Nakagami概率密度函数描述波传播。对于交叉点,添加了一个附加术语以解释具有交叉点的几何参数的路径损耗。在模型参数化之后,进行了评估。另外,作为样品盒,将Car2x添加到自适应巡航控制中,并且使用车辆动力学模拟证明了改进的功能。这种扩展的自适应巡航控制从周围车辆的指示器中使用了信息,以通过这些车辆更快地反应道路。

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