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首页> 外文期刊>IEEE sensors journal >Modeling the Quarter-Vehicle: Use of Passive Sensor Data for Road Condition Monitoring
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Modeling the Quarter-Vehicle: Use of Passive Sensor Data for Road Condition Monitoring

机译：建模四分之一车辆：使用被动传感器数据进行道路状况监控

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摘要

In recent years, automated driving has become one of the most important research fields in the automotive industry. A key component for a successful substitution of human driving by vehicles is a real-time model of the current environment including the traffic situation, the guide-way, and the road itself. We propose a solution for measuring road conditions within the spring-damper system of the vehicle. In this paper, we utilize a Vehicle Level Sensor (VLS) and an Acceleration Sensor (AS), both of which are standard components in modern vehicles, for road condition monitoring. Our model-based approach therefore consists purely of additional software. We present a calculation of the Quarter Vehicle Model (QVM) for road elevation measurements to enable each connected vehicle to provide valid data for a potential crowd-sensing approach, where every vehicle contributes past data and consumes data for upcoming segments. The generated data are capable of providing the environment model with real-time data. Our calculations are first validated in a laboratory setup, representing a down-scaled Quarter-Vehicle. The knowledge gained it then applied to a real vehicle. For this purpose, the measurement setup is explained, the model-based calculation and the parameters are adjusted, and the results are compared.
机译：近年来，自动化驾驶已成为汽车行业中最重要的研究领域之一。通过车辆成功替代人类驾驶的一个关键部件是当前环境的实时模型，包括交通状况，指导方式和道路本身。我们提出了一种用于测量车辆弹簧阻尼系统内的道路状况的解决方案。在本文中，我们利用车辆水平传感器（VLS）和加速度传感器（AS），这两者都是现代车辆中的标准组件，用于道路状况监测。因此，我们基于模型的方法纯粹是额外的软件。我们介绍了用于道路仰视测量的四分之一车辆模型（QVM），以使每个连接的车辆能够为潜在的人群感测方法提供有效数据，其中每个车辆都会为即将到来的段消耗数据并消耗数据。生成的数据能够使用实时数据提供环境模型。我们的计算首先在实验室设置中验证，代表了一个下缩放的四分之一车辆。所获得的知识然后施加到真正的车辆上。为此，解释了测量设置，调整了基于模型的计算和参数，并进行了比较结果。

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