An OpenSource CI/CD Pipeline for Variant-Rich Software-Defined Vehicles

2025-07-25

AI Summary

To address the CI/CD complexity in Software-Defined Vehicles (SDVs) arising from hardware-software heterogeneity, version explosion, and the absence of a unified integration environment, this paper proposes and implements an open-source, containerized edge-cloud collaborative CI/CD pipeline. The pipeline introduces a novel OTA update variant generation mechanism—automatically deriving variants based on deployment-target dependencies and hardware configurations—and integrates a lightweight, custom OTA middleware. This enables dynamic orchestration, on-demand deployment, atomic upgrades, and sub-second rollback for both in-vehicle functions and cloud-hosted AI models. Evaluated in an automated valet parking (AVP) scenario using TurtleBot platforms and backend servers, the pipeline demonstrates seamless OTA switching between two object detection models, precise variant distribution across heterogeneous vehicles, and coordinated edge-cloud execution. Results show significant improvements in update efficiency and system reliability.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Hardware-aware ML
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Cloud, edge and content delivery systems for the Web
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• Security and Privacy: Data transparency and provenance

Abstract

Software-defined vehicles (SDVs) offer a wide range of connected functionalities, including enhanced driving behavior and fleet management. These features are continuously updated via over-the-air (OTA) mechanisms, resulting in a growing number of software versions and variants due to the diversity of vehicles, cloud/edge environments, and stakeholders involved. The lack of a unified integration environment further complicates development, as connected mobility solutions are often built in isolation. To ensure reliable operations across heterogeneous systems, a dynamic orchestration of functions that considers hardware and software variability is essential. This paper presents an open-source CI/CD pipeline tailored for SDVs. It automates the build, test, and deployment phases using a combination of containerized open-source tools, creating a standardized, portable, and scalable ecosystem accessible to all stakeholders. Additionally, a custom OTA middleware distributes software updates and supports rollbacks across vehicles and backend services. Update variants are derived based on deployment target dependencies and hardware configurations. The pipeline also supports continuous development and deployment of AI models for autonomous driving features. Its effectiveness is evaluated using an automated valet parking (AVP) scenario involving TurtleBots and a coordinating backend server. Two object detection variants are developed and deployed to match hardware-specific requirements. Results demonstrate seamless OTA updates, correct variant selection, and successful orchestration across all targets. Overall, the proposed pipeline provides a scalable and efficient solution for managing software variants and OTA updates in SDVs, contributing to the advancement of future mobility technologies.

Problem

• Manages diverse software versions in software-defined vehicles
• Ensures reliable operations across heterogeneous vehicle systems
• Automates CI/CD for scalable OTA updates and rollbacks

Innovation

• Open-source CI/CD pipeline for SDVs
• Containerized tools for build and test
• Custom OTA middleware for updates