Overcoming Autoware-Ubuntu Incompatibility in Autonomous Driving Systems-Equipped Vehicles: Lessons Learned

2024-10-09

arXiv.org

AI Summary

As drive-by-wire vehicles evolve toward full autonomy, critical challenges arise in wireless perception assistance, sensor synchronization, real-time performance, and software compatibility. Method: This study systematically addresses full-stack compatibility issues—specifically Python version conflicts, CUDA driver integration, source compilation, and simulation execution—when deploying Autoware.AI on a Chrysler Pacifica platform running Ubuntu 20.04 and ROS Noetic. We employ multi-version Python management, Docker-based containerized debugging, and Gazebo+RViz co-simulation. Contribution/Results: We propose the first Autoware–Ubuntu–ROS compatibility governance paradigm tailored for real-vehicle deployment, yielding a reusable, code-level remediation protocol and a standardized environment configuration checklist. Our approach enables stable onboard deployment and end-to-end functional validation of Autoware.AI, reducing environment setup time by over 70%.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Machine Learning: Hardware-aware ML
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

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.

Problem

• Transitioning Drive-by-Wire systems to autonomous driving platforms
• Addressing software incompatibility and sensor synchronization challenges
• Developing robust positioning and perception capabilities for autonomy

Innovation

• Framework for DBW-to-ADS transition using Chrysler Pacifica
• Offline autonomous operations with LiDAR and camera data
• Solutions for sensor synchronization and real-time perception