AUTOFRAME -- A Software-driven Integration Framework for Automotive Systems
Sven Kirchner, Nils Purschke, Chengdong Wu, Muhammed Aqib Khan, Divye Dixit, Alois C. Knoll
TL;DR
The paper addresses the rising complexity of automotive software by proposing AUTOFRAME, a modular, hardware-agnostic deployment framework that centralizes computation through a hardware abstraction layer (HAL) and dynamic software deployment. It decouples software from hardware via a vehicle configuration schema, modular application blocks, and Docker-based deployment, enabling scalable, safe operation across diverse hardware layouts. The evaluation in CARLA demonstrates practical integration of lane detection, motion planning, and vehicle control, validating the framework’s ability to adapt to different vehicle configurations and hardware setups. This work advances SDV development by providing a cohesive, extensible blueprint for centralized architectures that can streamline development, maintenance, and updates in real-world automotive systems.
Abstract
The evolution of automotive technologies towards more integrated and sophisticated systems requires a shift from traditional distributed architectures to centralized vehicle architectures. This work presents a novel framework that addresses the increasing complexity of Software Defined Vehicles (SDV) through a centralized approach that optimizes software and hardware integration. Our approach introduces a scalable, modular, and secure automotive deployment framework that leverages a hardware abstraction layer and dynamic software deployment capabilities to meet the growing demands of the industry. The framework supports centralized computing of vehicle functions, making software development more dynamic and easier to update and upgrade. We demonstrate the capabilities of our framework by implementing it in a simulated environment where it effectively handles several automotive operations such as lane detection, motion planning, and vehicle control. Our results highlight the framework's potential to facilitate the development and maintenance of future vehicles, emphasizing its adaptability to different hardware configurations and its readiness for real-world applications. This work lays the foundation for further exploration of robust, scalable, and secure SDV systems, setting a new standard for future automotive architectures.