White paper library
The Apex.AI MQTT Connector
The white paper discusses the importance of software-defined vehicles being connected to the cloud and the need for secure and reliable data exchange in various applications, offering the MQTT connector as a solution.
Key takeaways:
MQTT Connector for software-defined vehicles: Explore how to enhance your software-defined vehicles with Apex.AI's MQTT connector, enabling secure and efficient connections to the cloud for real-time telemetry, remote control, and seamless data exchange.
MQTT's versatility: Learn how MQTT, initially designed for IoT, has gained widespread adoption in the automotive and industrial sectors. Simplify your message exchange processes, allowing your developers to concentrate on content rather than intricate network details.
Quality of Service and security: Discover how MQTT offers versatile Quality of Service options tailored to different message types, ensuring the reliable delivery of critical data. Explore its robust security features, including TLS connections and X.509 certificates, safeguarding sensitive user data and vehicle control commands.
Safe calibration of automated driving sensor suites
Discover the future of automated driving calibration in this white paper authored by Stefan Milz, Jack Borer, and Florian Wandling. Dive into the world of sensor fusion and calibration, where safety is paramount, and learn about cutting-edge technologies that ensure reliable sensor performance.
Key takeaways:
Safety by design: Uncover how sensor redundancy and ASIL decomposition create a foundation for safer automated driving by minimizing the risk of errors.
Continuous online calibration: Explore the innovative concept of Continuous Online Extrinsic Calibration (COEC) that eliminates the need for artificial targets, ensuring precise calibration during vehicle operation.
Real-world integration: See the practical side of calibration with real-world demonstrations, proving the robustness of calibration methods in diverse driving scenarios, even in challenging conditions.
A middleware journey from microcontrollers
to microprocessors
More and more modern automotive systems move to powerful, centralized POSIX systems instead of AUTOSAR Classic-based microcontrollers. Porting established software architectures leads to systems that suffer from poor performance.
Your takeaways from this white paper:
Where AUTOSAR Classic and ROS 2 differ in execution and communication.
The pitfalls that lead to poor performance.
The mechanisms provided by Apex.OS and Apex.Middleware to address the performance issues.
Apex.Grace Executor — An execution management framework
Learn about executors, why they are needed, and how they can be used in modern, complex, real-time systems such as software-defined vehicles.
Your takeaways from this white paper:
How Apex.Grace’s design goals support developers.
How the Apex.Grace Executor handles complex execution graphs through four illustrative use cases.
How the Apex.Grace Executor achieves the determinism required by real-world applications.
AUTOSAR adaptive on zero-copy steroids
Discover how the inter-process communication for Automotive ECUs can be realized with the open-source middleware Eclipse iceoryx™, and more on the extensions provided with Apex.Middleware that enables the usage of iceoryx in safety-critical systems.
Your takeaways from this white paper:
How iceoryx has evolved to an open-source middleware during the AUTOSAR Adaptive standardization.
How iceoryx can be integrated into automotive communication stacks.
The benefits of iceoryx and the extensions made to it in Apex.Middleware.
Real-time LIDAR object detection on embedded hardware — from open-source projects to production-grade implementation
Learn how our partner driveblocks benefits from the lower and more predictable latency on their LIDAR perception stack by integrating with Apex.OS.
Your takeaways from this white paper:
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How driveblocks’ LIDAR perception stack built on top of Apex.OS can outperform others.
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Why Apex.OS - a fork from ROS 2 is the perfect match for the task of lowering data transport latency.
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What implementations on Apex.OS and Apex.Middleware leads to lower latency.