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开发一个节能且具有成本效益的自动驾驶车辆研究平台。

Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform.

机构信息

Western Michigan University, 1903 W Michigan Ave., Kalamazoo, MI 49008, USA.

FEV North America Inc., 4554 Glenmeade Ln, Auburn Hills, MI 48326, USA.

出版信息

Sensors (Basel). 2022 Aug 11;22(16):5999. doi: 10.3390/s22165999.

Abstract

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.

摘要

商业化的自动驾驶汽车技术是汽车行业的主要目标,因此,世界各地的研究正在迅速扩展。然而,尽管研究活动水平很高,但详细描述开发自动驾驶汽车研究平台的简单且具有成本效益的方法的文献却很少。为了满足这一需求,我们介绍了为本地自动驾驶汽车试点计划开发的 2019 年起亚尼罗自动驾驶汽车的仪器和控制的方法和结果。该平台包括线控驱动执行套件、安波福电子扫描雷达、立体摄像机、MobilEye 计算机视觉系统、激光雷达、惯性测量单元、两个提供航向信息的全球定位系统接收器以及用于驾驶环境感知和路径规划的车载计算机。机器人操作系统软件用作仪器和自动驾驶应用算法之间的系统中间件。在选择、安装和集成这些组件后,我们的结果表明成功利用了所有传感器、线控功能、总额外功率消耗 242.8 瓦(典型值)和 118189 美元的总费用,与具有类似功能的其他商业上可用的系统相比,这是一个巨大的节省。这辆车仍然是我们主要的自动驾驶汽车研究和开发平台。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8c0/9416450/66a8feebe972/sensors-22-05999-g0A1.jpg

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