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Highlights

The AUTOSAR Adaptive Platform introduces a standardized approach for the Application Layer middleware within the automotive industry. This layer, analogous to the Classic Platform’s Runtime Environment (RTE), operates on top of a POSIXcompliant operating system like PSE51. This operating system runs on a machine (equivalent to the BSW layer in Classic AUTOSAR), which can be either native hardware
or virtualized using a hypervisor on High-Performance Computing (HPC) platforms.

The core purpose of Adaptive AUTOSAR is to address the growing performance demands in areas like Advanced Driver-Assistance Systems (ADAS)/Autonomous Driving (AD), Vehicle-to-Everything (V2X) communication, and secure over-the-air
(OTA) updates during runtime.

Within this framework, Adaptive Applications function as individual POSIX processes. These applications interact with Application Programming Interfaces (APIs) to access Functional Clusters and Adaptive Platform Services provided by the AUTOSAR Runtime
for Adaptive Applications (ARA). This standardized approach facilitates the development and deployment of complex automotive software applications.

Problem Statement

A Chinese Tier 1 supplier encountered several challenges when developing an AP Stack that adheres to AUTOSAR AP specifications and achieves desired performance levels. The customer aimed to build its own AP Stack solution based on the AP Communication Management (AP CM) functional cluster within the AUTOSAR Adaptive Platform Demonstrator (APD) provided by the AUTOSAR Consortium. It also required a gap analysis to identify discrepancies between the customer’s implementation and the official AP CM specifications. The analysis would encompass both static and dynamic behavior at the unit and integration levels.

Solution

Constructing an AP Stack that aligns with specifications while meeting performance criteria is a complex task that demands significant resources. Also, the market offers a limited selection of AP Stack solutions that fulfill stability, safety, and security requirements, often at high costs. To overcome these challenges, following solution was proposed and implemented:

Automated Unit Testing: GoogleTest was employed to create unit tests encompassing all AP CM specification items. These tests were seamlessly integrated within the AP stack build environment using Yocto layers, Docker, and CMake, enabling efficient and automated testing.

Mastery of Communication Management Design Patterns: In-depth knowledge of communication managementspecific design patterns, including proxy-skeleton, service-oriented, and remote procedure call (RPC) architectures, was leveraged. A detailed test plan and specification were established, along with a custom mocking framework built upon GoogleTest and Google Mock (GMock) for enhanced testing capabilities.

Code Generation and Design Support: Critical AP CM specification items and corresponding design elements were identified for potential code generation. The solution provided end-to-end support for the communication management functional cluster’s detailed design. This included deriving designs from AP software specifications and facilitating the creation of the ARXML metamodel, a key component for automated code generation.

Deployment and Testing Integration: Yocto layers and Bitbake recipes were configured to embed test scripts and executables within the final AUTOSAR Adaptive Platform Demonstrator (APD) image. This image was then executed on the QEMU emulator, a virtual machine environment, built using Bitbake. This approach streamlined the deployment and execution of tests within the target environment.

By implementing this solution, the project successfully addressed the challenges associated with developing a robust and high-performing AP Stack while ensuring adherence to AUTOSAR AP specifications.

Results

The BSW layer underwent rigorous testing, culminating in the delivery of a comprehensive set of artifacts. This included detailed coverage reports, traceability matrices, test results, test cases, defect reports, and summary reports. Additionally, a thorough overview of the entire unit testing process was provided. These deliverables demonstrate a firm commitment to quality assurance throughout the software development lifecycle, guaranteeing the robustness and reliability of the tested BSW components.

The project successfully executed unit tests for over 32 AUTOSAR BSW modules. This encompassed a wide range of components, including the Communication Stack (Com Stack), safety-critical components, the Memory Stack, and the Diagnostic Stack. This extensive testing effort involved meticulous analyses and validation procedures, ensuring the robustness, safety, and reliability of the BSW modules under test.

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