Advanced Lane Finding Prototype Based on Autoware Platform

Marko Dragojevic, Stevan Stevic, Momcilo Krunic, N. Lukic
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Abstract

In order to achieve functionality of autonomous driving, modern vehicles must be aware of theirs surrounding in any given moment. Complex software modules within such systems oversee vehicle’s environment and use this environmental data to pinpoint vehicles position in the world. Often these perception modules process numerous calculations and fuse data acquired from different sensors to achieve, as precise as possible, understanding of vehicles environment. Alongside these highlevel data fusion modules, many modern vehicles have redundant subsystems that handle similar functionality but in smaller scale in order to achieve shorter “Sense-Plan-Act” loop. In this paper we will present prototype for Advance Lane Finding (ALF) application, which could be utilized as an enhancement of multiple ADAS systems. Proposed solution is implemented in C+ + programming language as a part of Autoware/ROS platform. Prototype’s performances are tested on Nvidia DRIVE PX2 hardware platform.
基于Autoware平台的高级寻道原型
为了实现自动驾驶的功能,现代车辆必须随时了解周围环境。这种系统内的复杂软件模块监控车辆的环境,并利用这些环境数据来确定车辆在世界上的位置。通常,这些感知模块处理大量计算并融合从不同传感器获取的数据,以尽可能精确地理解车辆环境。除了这些高级数据融合模块,许多现代车辆都有冗余的子系统来处理类似的功能,但规模较小,以实现更短的“感知-计划-行动”循环。在本文中,我们将介绍先进车道查找(ALF)应用的原型,该应用可以用作多个ADAS系统的增强。该方案采用c++编程语言作为Autoware/ROS平台的一部分实现。样机在Nvidia DRIVE PX2硬件平台上进行了性能测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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