Autonomous vehicles have been rapidly developed as demand that provides safety and efficiency in transportation systems. As autonomous vehicles are designed based on open-source operating and computing systems, there are numerous resources aimed at building an operating platform composed of Ubuntu, Autoware, and Robot Operating System (ROS). However, no explicit guidelines exist to help scholars perform trouble-shooting due to incompatibility between the Autoware platform and Ubuntu operating systems installed in autonomous driving systems-equipped vehicles (i.e., Chrysler Pacifica). The paper presents an overview of integrating the Autoware platform into the autonomous vehicle's interface based on lessons learned from trouble-shooting processes for resolving incompatible issues. The trouble-shooting processes are presented based on resolving the incompatibility and integration issues of Ubuntu 20.04, Autoware.AI, and ROS Noetic software installed in an autonomous driving systems-equipped vehicle. Specifically, the paper focused on common incompatibility issues and code-solving protocols involving Python compatibility, Compute Unified Device Architecture (CUDA) installation, Autoware installation, and simulation in Autoware.AI. The objective of the paper is to provide an explicit and detail-oriented presentation to showcase how to address incompatibility issues among an autonomous vehicle's operating interference. The lessons and experience presented in the paper will be useful for researchers who encountered similar issues and could follow up by performing trouble-shooting activities and implementing ADS-related projects in the Ubuntu, Autoware, and ROS operating systems.

翻译：自动驾驶车辆作为提升交通系统安全性与效率的需求载体，其研发进程正快速推进。由于自动驾驶车辆通常基于开源操作系统与计算架构进行设计，目前已有大量资源致力于构建由Ubuntu、Autoware及机器人操作系统（ROS）组成的操作平台。然而，针对自动驾驶系统车辆（如克莱斯勒Pacifica）中Autoware平台与Ubuntu操作系统之间的兼容性问题，尚缺乏明确的故障排查指导方案。本文基于在解决兼容性问题过程中积累的经验，系统阐述了将Autoware平台集成至自动驾驶车辆接口的总体框架。故障排查流程围绕解决自动驾驶系统车辆中Ubuntu 20.04、Autoware.AI与ROS Noetic软件的兼容性及集成问题展开。具体而言，本文重点探讨了涉及Python兼容性、统一计算设备架构（CUDA）安装、Autoware部署以及Autoware.AI仿真的常见兼容性问题及其代码级解决方案。本文旨在通过系统化、细节化的呈现方式，阐明如何应对自动驾驶车辆操作接口间的兼容性挑战。文中总结的经验教训可为遭遇类似问题的研究人员提供参考，帮助其在Ubuntu、Autoware与ROS操作系统环境中开展故障排查工作，并推进自动驾驶系统相关项目的实施。