Aerospace and Automotive Hardware Tested in the Loop

Welcome to the event where technology meets reality! This time we will dive together into automotive and aerospace testing.

Doc. Ing. Peter Chudý, Ph.D., MBA from FIT VUT in Brno will be the first to give his presentation and will speak on the subject of Hardware in the loop in aerospace. Hardware in the loop simulations are indisputably perceived as an integral part of the avionics design and development process. This paper describes the simulation process which has been employed to test a digital autopilot for a light sport aircraft. Simulation processes have been performed on two different ground testing levels. The first setting consisted of a laboratory grade verification phase which supported the initial functional estimate of the designed and implemented autopilot features. The subsequent testing level already included the embedded autopilot system installation on board of the test aircraft. The initial hardware in the loop simulation was performed at the light aircraft simulation lab SimStar at the Brno University of Technology. The aim of the ground simulations was to verify and ground test the operational suitability of the designed autopilot flight control system elements. The implemented flight control system hardware units have been connected into the simulation network using the CANaerospace communication protocol for both testing scenarios. Simulations focused on the real time automatic flight modes operational scenarios. Both of the simulation scenarios confirmed the anticipated performance of the autopilot design features.

The second speaker will be Diego Carvalho, Engineering Software Design Leader, who will be speaking on development Valeo automotive cameras. In this session, will be presented the cameras standardized Software and Hardware framework used across the verification and validation workflow. Starting from camera testing through in-vehicle recording ending by Simulation ending with Replay HIL.

The last, but no less important speaker will be Rostislav Halaš from National Instruments, who will talk about the Evolution of NI ADAS validation toolchain. As part of his presentation, we will focus on the importance of connecting test methodologies throughout the In-Vehicle Data Record, Replay, and Hardware-in-the-Loop (HIL) test, with a deeper dive into the latest advancements in simulation HIL and direct image injection techniques and new technologies such as RDMA supporting this evolution.

Artificial Intelligence in Automotive Industry + video

For the new year, on the first day of February, we had another technical evening. This time we discussed in depth about artificial intelligence and its use in the automotive sector.

Sara Polak was the first to give her presentation.
And what did she talk about?
She called her presentation: From pyramids to robots
Are we living in a sustainable social structure? Is there such a thing as a collapse of civilizations, or are we merely undergoing a constant transformation accompanied by ever better technology? Is it possible that our evolutionary nature lies not in large, complex social groupings, but in decentralized tribes, and this makes any civilization unsustainable in the long term? Come on a trip through time from pyramids to robots and immerse yourself in research on the simulation of complex social systems to better understand the anatomy of the civilization we live in and better prepare ourselves for the future.

The next presenter was Antonín Vobecký. He is one of the few people involved in artificial intelligence and machine learning at Valeo within
Antonín explained to us the work he presented together with his team at ECCV in Israel, dealing with the partial automation of the annotation process. This process is important part for training ADAS (advanced driver-asistence systems) for autonomous cars, and its automation appears to be a great saving of time and money. In his work, he investigated whether it is possible to learn pixel-wise semantic image segmentation of urban scenes without the need for any manual annotation, only from raw unedited data collected by cars equipped with cameras and LiDAR sensors while driving in the city.

The last but not less important speaker was Petr Cezner. After five years as a research software engineer, he decided to focuse on Machine Learning. For that occasion, he also changed employer, from 2022 he works at DataSentics as a Machine Learning Engineer.
His presentation led us through a computer vision algorithm for quality control. Quality control is an essential part of each manufacturing process and historically had to be always done manually with qualified personnel. Deep learning has introduced a huge improvement in automatizing this task in recent years, resulting in faster production and in cost savings. We talked about neural networks for 2D sensors, 3D data, thermal cameras and IoT sensors or how you should choose between classification, segmentation or anomaly detection. We also discussed how it is solved currently, which cloud or on-prem solutions are used and how is this field expected to change in future.

How to test and validate autonomous systems for various forms of mobility + video

At another of the Valeo Technical Evenings, we walked about testing of the autonomous systems. Whether it means public transportation or passenger cars, it is necessary to prepare them for the future and, when the time comes, only reliable transport solutions will be put into operation.

The first speaker was Jan Zahradník and he talked about autonomous and highly automated cars that represent a big part of the next automotive revolution. In order to secure their safety and the effectiveness of their functionalities, these cars go through a very thorough validation regime. The regime involves collecting big amounts of data on the roads and test tracks, processing the data and extracting system performance KPIs, all the way up to system homologation and certification for certain levels of automation.
In addition, virtual validation is becoming instrumental in order to train the algos and cover corner cases that cannot be safely achieved by real world testing. The combination of virtual/real world validation can cover a full range of system functionality and safety requirements including FuSa and SOTIF. The robustness of the tool chain and model correlation with real world data is key for guaranteeing the performance and reliability of the system. Defining, selecting and processing the right data becomes a big challenge with the increasing complexity of the systems and the tighter regulatory requirements.
The topic of the day was narrowed down to “How to Define A Validation Methodology and Tool Chain for Level 3 and Beyond Systems”
The foundations of the System Validation Platform at Valeo were: Automation, Standardization, Virtual Validation, Big Data Management, Tool Chain Validation and Advanced System Validation.

Next guest was Michal Pochmon, technical director and head of implementation at Škoda Digital, who talked about the future of trams and their autonomy. He started with the recapitulation of the actual state of anticollision system in Skoda Group. We deeply analyzed the vision for the future development of the autonomous trams. The anticollision system for trams is one of the leading funcionality that is fundamental in the time of increasing density of the traffic in the bigger cities. We talked about phases and ways of testing. We did not miss the simulator and future validation possibilities.

Our meet up was concluded by Tomáš Svoboda from CTU. He addressed the problem of weakly supervised learning. Complete data annotation needed for machine learning algorithms, think about labeling each pixel in images; cannot keep pace with the testing and validation demands. Instead of complete data annotation, one could leverage some external weakly related source. This talk focused on exploiting recorded vehicle trajectories. He showed how to incorporate kinematic constraints to supervise a learnable terrain predictor. In the second part, he discussed with us the ideas for incorporating a dynamic model.

PCB Design and Industrialization for ADAS + video

PCBs became the central topic of the Valeo Technical Evening.
This abbreviation, which means Printed Circuit Boards, is inextricably linked with every electronic device. Firstly, together with Miroslav Purnoch, hardware engineer from Valeo Prague R&D center, we went through the nooks and crannies of each circuit or resistor, its meaning and resulting functionality in driver assistance systems. We had a look at the steps of the development process and the tools used to design, simulate and test prototypes of printed circuit boards. What are the specifics of high frequency PCB materials for automotive radar sensors? We answered this and more on our last meetup.
Later, Jiří Zvolánek presented you some of the advanced PCB technologies such as HDI microvia technology, 3D flex-rigid technology and PCBs with embedded components, on which Würth Elektronik GmbH & Co. KG works.
Finally, we listened to a short introductive presentation of Valeo’s PCB expert, Paul-Henry Morel, who shared a broader view of mass circuit board production. We discussed in more detail the challenges and possible future development of this discipline in the field of automotive.
Jan Kostecky , the Process Engineers’ Team leader, together with his colleagues gave us a 10 minutes inside look into the planned production of PCB at Valeo Rakovník Site.

Detection of dirty/blocked sensors Meetup + video

How to detect the dirty sensors on a car? Algorithms for blockage detection – automotive radar and camera

Has it already happened that your car showed a message like “Adaptive cruise control is switched off, radar is blocked”? Have you already thought about how important is having clear sensors that care about adaptive cruise control, lane departure warning or other smart functions in your car? And how important is it for the future autonomous cars that will not need the driver behind the steering wheel?

Valeo’s department of Radars finished the development of a new algorithm that recognizes any sign of blockage of the sensor. Naiallen Carvalho, one of the developers of the algorithm, explained how it works, how a signal from the sensor looks when blocked and how to perceive if the sensor is still able to detect the objects.

Valeo department of Artificial Intelligence concentrates on the dirt or water blocking cameras for a long time. David Hurych talked about how to identify the water drops on a camera lens and how the developers continue to enhance the system.

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