Speed up data-driven ADAS/AD function development

The central challenge in ADAS/AD function development is ensuring safety and reliability in complex driving environments while achieving robust performance across diverse scenarios. This makes the development of such functions resource-intensive.

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As automation in vehicles increases, the system assumes greater responsibility for vehicle dynamics, which reduces the driver's workload but also heightens technological complexity. This complexity escalates from level 2 to level 3 and peaks at level 5, where advanced algorithms, sophisticated sensor fusion techniques, and complex decision-making processes are required to autonomously manage a wide range of scenarios, including unpredictable ones.

Paving the way to autonomous mobility

The evolution of driver assistance and autonomous driving leads to challenges with high impact on the development and deployment of ADAS/AD systems.

Functional safety

To ensure fail-safe functionality, level 3 and above systems must have a comprehensive understanding of their operational limitations and the ability to execute safe maneuvers or initiate a safe stop when faced with uncertainties.

High-speed data processing

Modern autonomous driving systems generate and process vast amounts of data from multiple sensors and sources. These need to be processed with low latency for real-time decision making and control, enabling ADAS/AD systems to process and react to data in a timely manner.

Test and validation

The complexity and open-world nature of ADAS/AD systems require innovative validation approaches that go beyond traditional testing methods and use re-computation to diagnose potential issues and refine algorithms.

The shift from assistance to automation

The picture shows a diagram in which the VDA levels of automation are explained with reference to system responsibilities and driver responsibilities.

The overlay shows that from level 3 the safety requirements as well as the performance requirements and the system complexity increase by leaps and bounds.

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Automation levels according to VDA (German Association of the Automotive Industry)

Safety levels driving complexity and performance requirements

Fast, cost-efficient, data-driven development of ADAS/AD functions

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ADAS/AD Measurement solution

The ADAS/AD Measurement solution for assisted and automated driving control units (ADCUs) and sensors offers high performance and scalable tools for data acquisition and processing, which can be efficiently integrated into existing development environments. It features internal ADCU and sensor data measurement, lossless compression, and enhanced performance via an accelerator card for efficient data handling and hardware-in-the-loop (HiL) replay readiness.

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ADAS/AD Middleware solution

The ETAS Middleware solution for developing modern ADAS/AD systems supports software and hardware architecture modelling and high-performance communication. The solution consists of multiple tools, ECU software libraries and a robust API for the ADAS/AD development cycle. Drive fidelity facilitates advanced debugging through forensic re-compute and massive reduction of physical test miles through reproducible simulation-based validation.

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Cybersecurity solutions

ADAS/AD functions are vulnerable to cyberattacks due to their reliance on complex software and extensive connectivity. These systems require constant data exchange with external sources, such as cloud services and other vehicles, increasing the risk of unauthorized access. Additionally, the integration of numerous sensors and communication interfaces creates multiple entry points for potential attackers, making robust cybersecurity measures essential to protect these advanced technologies.

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“How to master safe ADAS/AD development”

Our white paper shows the progression from driver assistance to full automation, highlighting the step-by-step incorporation of ADAS/AD technology in vehicles. It stresses the significance of fail-safe architectures and questions conventional validation approaches. It also introduces re-computation as a validation method and outlines the AD cycle as an organized framework for building dependable ADAS/AD systems.

Read our paper and learn how to tackle the challenges of developing safe ADAS/AD functions.

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