Raw like sushi. How to handle automotive SENSOR RAW DATA and refine it into a SPECIALITY

In the webinar series "The Data Sushi Lessons" this was shown by b-plus together with the partners Bertrandt, Deutronic, IBM, Incenda AI and Zukunft Mobility (ZF).

The exquisite components for development tools of autonomous driving and ADAS functionalities were explained to the visitors in presentations and Q&As. Because just like sushi, the individual "ingredients" and the processing of measurement data for test systems have an enormous impact on the quality of the final product.

The speakers presented how raw sensor data is acquired, stored, processed, replayed and simulated into valid test data. They also demonstrated other process steps in raw data management such as precise test vehicle setup and advanced fleet management.



See the videos of the event in the internal section.

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The agenda...

…or should we rather say menu?

Johannes Zangerle
b-plus technologies GmbH



Johann Führmann
b-plus automotive GmbH



The ingredients for a "smart ADAS/AD meal”

3 Main Takeaways

  • Essential building blocks for smart data handling
  • Use of data already during recording
  • How Measurement data can be extracted directly from the ECU?

Data is the central element in advancing autonomous driving. They accompany the development and validation process in various forms (e.g. raw data, metadata) starting with the first bit, still in the sensor itself or from the ADAS control unit. In order to be profitably further processed, reliably high quality and, in particular, temporal synchronization are essential.

Unlike in the past, this further processing already begins in the vehicle. Our lessons follow this data path from the source to the data center memory and beyond.

Our first "ingredient" is therefore the extraction of data from the ECU software and a flexible path directly into the measurement technology by means of the Measurement Data Service.


Julian Kapitel
Bertrandt AG



Development, design and assembly of ADAS/AD test carriers

3 Main Takeaways

  • Sensor integration and overall system development
  • Vehicle assembly and subsystems such as HMI, power supply and cooling
  • Operational safety, operator models and off-vehicle topics such as analytics

The complexity of autonomous systems and the associated sensor technology e.g. Cameras, Radars and Lidars is increasing continuously. Therefore, the complexity and scope of measurement data involved in the development and application of future systems must be managed accordingly. A powerful and reliable measurement technology is a prerequisite for the development and validation of systems and is a critical and safety-relevant part of autonomous mobility. It is also decisive how well this measurement technology is integrated in the overall vehicle system. A powerful energy supply, a safe and user-friendly operating concept (HMI), and reliable cooling of the measurement equipment are key factors for reliable performance, ensuring a high quality result.

b-plus and Bertrandt have developed and built a latest generation technology test carrier together; MAX. In this presentation, Julian Kapitel has been taking the audience through the entire history of the development and assembly of such a technology carrier.

Maria Wurm
b-plus automotive GmbH



How your use of meta data can increase the efficiency of test fleets

3 Main Takeaways

  • Capture metadata + raw data together
  • Use metadata for AI-based analysis of test drives
  • Plan and execute further test drives in a targeted manner

Aiming to get its customers safely into series production, b-plus automotive shows how metadata in combination with a holistic management approach can increase the efficiency of a test fleet. Beginning with the preparation, the realisation and the evaluation of test drives, a comprehensive best-practice workflow is showcased. It improves the development process qualitatively and quantitatively.

The use of meta information along the development process reduces the workload and speeds up the cycle from harvesting data during test drives and analyzing raw data.     

Tobias Wanzke
Deutronic GmbH



The power supply of the vehicle electrical system and ADAS in EVs – The High-Voltage converter as a central interface

3 Main Takeaways

  • HV-DC-DC-Converter provides useful data during test & validation
  • Saving of expensive measurement electronics
  • Optimization and monitoring of the energy supply of the electrical system

In addition to the powertrain's electrification, tomorrow's mobility will be defined above all by the self-driving vehicle. Due to their large number of sensors and processing hardware, advanced driver-assistance systems (ADAS) require enormous amounts of electrical energy. A central role for the energy supply of ADA systems in electric vehicles is played by the high-voltage converter, which provides essential data mainly in the test and validation phase of vehicles. This data is used to hedge the vehicle electrical system and the sustainable improvement and optimization of individual components.

The speakers from b-plus, Bertrandt, Deutronic, IBM, Incenda.ai and Zukunft Mobility (ZF) are experts when it comes to pioneering future mobility. The single presentations gave interesting and inspiring insights in the toolchain for ECU development. In total, they showed us a holistic approach on pushing autonomous driving.

Dr. Thomas Herpel
Zukunft Mobility GmbH



HIL-based Validation of Automotive Radar ECUs by Data Re-Injection

Wednesday, February 10th, 15:10 CET

3 Main Takeaways

  • ADAS require intensive validation with established test methods and novel approaches
  • Performance and modularity of test systems is a crucial aspect for serial testing
  • There is rarely a single „off-the-shelf“ solution - specific requirements lead to specific test system architectures

ADAS require extensive validation at various development levels. Hardware-in-the-loop tests of ECUs are an established test method, allowing for assessment of the robustness and performance on the target platform. The radar ECUs developed by ZF are intensively tested at early development stages by re-injection of real radar data in order to achieve maximum functional reliability and quality. High data rates, electrical robustness and exact synchronization are important parameters for the test.

In the presentation, the HIL system developed by Zukunft Mobility GmbH has been presented, in which the B-HIL from b-plus plays a central role for data re-injection.

Johann Führmann
b-plus automotive GmbH



End-to-end integration of a Repro HiL environment

Wednesday, February 10th, 16:10 CET

3 Main Takeaways

  • Advantages of a consistent HiL strategy
  • Open- / closed loop – what’s the difference?
  • Integration approach for CI systems

Thinking backwards: Testreports of the validation of ADAS/AD sensors and ECUs are “the reason” for huge challenges in the area of Hardware-in-the-loop. Not only for the 24/7 validation in HiL farms it is worthwhile to reprocess the data, but already at the beginning of the development at the developer’s desk. Using recorded data from end-to-end, removes a lot of hurdles by design.

Frank Kraemer



AI and Big Data Management for Autonomous Driving (AD) in 2021

Wednesday, February 10th, 16:40 CET

3 Main Takeaways

  • Technology for high-performance data management
  • Scalable, flexible and cost optimized Data Management
  • Remove data-related bottlenecks

Advanced driver-assistance systems (ADAS) suites have revolutionized the auto industry, but they have also generated a great deal of complexity, new technologies, and costs. AD providers use artificial intelligence (AI) as one key component. Researchers and developers who can deliver insights faster while managing rapid infrastructure growth will be the industry leaders. Following the process of data acquisition from test drives via ingest to the data centre and processing of big data, many challenges occur. To handle this unstructured data, seamless scaling systems and toolsets are necessary from the sensor to the data centre with storage and computing systems.

This presentation provided a case study of how synchronized data capturing in test drives, big data computing, storage and archiving are integrated in today’s AD development workflow.

Bernhard Pfeffer
b-plus technologies GmbH



Data Enrichment and Intelligent Recording Based on AI Methods

Wednesday, February 10th, 17:10 CET

3 Main Takeaways

  • Understand the advantages of intelligent recording
  • Get an overview of AI methods in use at b-plus
  • Get an insight on how b-plus products support ML applications

It’s all known that there’s the need to record a huge amount of data for the development of nowadays and future vehicles. Therefore, it’s increasingly important to carefully choose the “relevant” data, in order to efficiently develop and test complex automated driving functions.

Pre-Processing the data with AI methods in parallel to raw data recording can give precious insights to what is being recorded, and therefore increase efficiency. This presentation gave a short overview about AI methods that are in use at b-plus for the purpose of data enrichment.

Marius Reuther
Incenda AI GmbH



Intelligent Data Quality Assurance

Wednesday, February 10th, 17:40 CET

3 Main Takeaways

  • Data quality already begins during the data recording
  • Incenda AI’s algorithms detect data essential for HQ datasets
  • A pre-selection reduces overall effort and increases efficiency

The behaviour of Artificial-Intelligence-Based systems highly depends on the quality of the training data. Therefore, all the processes relevant for the data acquisition must face comprehensive quality assurance – data quality already starts during the data collection. In the Data Garage project, Incenda AI teams up with b-plus tackling this challenge. Incenda AI’s intelligent algorithms pre-select data during the collection process and on runtime directly on MAX, the Test Demo Car of b-plus. A perfect basis of a high-quality dataset.

The speakers from b-plus, Bertrandt, Deutronic, IBM, Incenda.ai and Zukunft Mobility (ZF) are experts when it comes to pioneering future mobility. The single presentations give interesting and inspiring insights in the toolchain for ECU development. In total, they show us a holistic approach on pushing autonomous driving. After each talk, you’ll get the chance to meet the speakers and our product experts.

Speakers & Partners










You would like to know more?

If the Data Sushi Lessons did not satisfy your thirst for knowledge or rather hunger for information, feel free to contact us!

We are looking forward to examine your use case and to work out an individual solution with you.

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