10 September 2026
Over the past few years, the regulatory landscape for advanced driver assistance systems (ADAS) and automated driving systems (ADS) has undergone substantial change. This evolution is not the result of a single new regulation but of a broader shift within the UN and EU frameworks, complemented by increasingly demanding consumer assessment programs.
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18 August 2026
Validation has become one of the biggest challenges in ADAS/AD development. The challenge is not only collecting high-quality data. Modern vehicle fleets can generate thousands of hours of recordings every week. The real challenge is transforming those recordings into trustworthy validation evidence quickly, repeatedly, and at scale.
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10 June 2026
Sensor models, physics engines, and scenario logic all depend on one thing being right first: the environment. At aiMotive, we've built a full in-house 3D content pipeline that feeds aiSim with everything it needs.
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4 June 2026
Training a reliable ADAS classifier starts long before model architecture – it starts with finding the right data. In this post, we walk through how aiMotive's aiData platform tackles one of the most underrated challenges in AD development: surfacing the specific, diverse, high-quality samples you actually need from a petabyte-scale dataset.
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12 March 2026
Modern AD development needs more than raw sensor recordings. To train, validate, and debug perception and planning logic, teams require a high-precision, machine-readable reference of the road environment. HD maps provide exactly this: a consistent, structured foundation for modern AD workflows.
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9 December 2025
Behind every autonomous driving breakthrough is a vehicle that has been carefully engineered, instrumented, and prepared for the kinds of tests that push technology forward.
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10 October 2025
As the automotive industry accelerates toward fully autonomous and software-defined vehicles (SDVs), the cost and complexity of software validation have become a central challenge. At aiMotive, we’re tackling this head-on with a GPU-accelerated, bit-accurate functional model of our aiWare NPU—designed to dramatically scale up Software-in-the-Loop (SiL) testing.
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2 October 2025
When it comes to ADAS development, high-quality annotated data is essential – but getting it shouldn’t be slow or expensive. Traditionally, manual annotation can cost millions of dollars annually and take months to process, delaying progress.
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8 August 2025
Developing automotive AI – whether for ADAS or automated driving – starts with one critical foundation: data. High-quality, precise, and well-documented data enables everything from neural network training, validation and simulation testing.
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12 February 2025
Why co-design of hardware, drivers, and application software is essential for cost-effective production solutions for embedded applications
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23 January 2025
The automotive industry is no stranger to challenges. Over the past few years, we've witnessed a significant downturn across global markets, driven by shifting consumer priorities, supply chain disruptions, and economic uncertainty.
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18 July 2024
Validating automated driving software requires millions of test kilometers. This not only implies long system development cycles with continuously increasing complexity, but it also brings with it the problem that real-world testing is resource intensive, and safety issues might arise as well.
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2 January 2024
In the dynamic landscape of automotive technology, the journey toward autonomy demands a profound shift in how we perceive and implement intelligence. At aiMotive, our dedication to innovation has led us to reimagine the very core of our approach.
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12 October 2023
In the rapidly evolving world of automated driving, adaptability is key. As our roadways become increasingly populated with vehicles of all shapes and sizes, seamlessly integrating automated driving systems in new fleets is paramount.
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27 June 2023
Artificial intelligence (AI) is transforming the automotive industry with automated and autonomous driving capabilities. As the European Union (EU) introduces new legislation in this field, it is crucial to understand its implications.
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14 June 2023
In the ever-evolving world of automated driving technology, simulation plays a crucial role in testing and validating new innovations. Today, we are thrilled to announce a groundbreaking development: aiSim, our in-house built simulator, now features the largest test track in Hungary, AVL ZalaZONE.
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10 May 2023
Carlos Tavares shares his experience of the test drive with aiDrive and its technologies during his visit to aiMotive premises. Stellantis recently acquired aiMotive, a leading developer of advanced artificial intelligence and automated driving software, to supercharge mid-term development of STLA AutoDrive, the Company’s automated driving tech platform.
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21 April 2023
The paper titled ‘aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perception’ by Tamás Matuszka et al. has been accepted to ICLR 2023 – the eleventh International Conference on Learning Representations. The workshop ‘Scene Representations for Autonomous Driving’ will cover the real-world impact of ML research on self-driving technology. The work of aiMotive researchers will be presented in Kigali, Rwanda, on May 5, 2023. The paper presents the publicly available aiMotive Multimodal Dataset and describes several 3D object detection baseline models trained on it.
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28 December 2022
aiMotive’s latest NPU is aimed at the next-gen automated driving workloads
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21 October 2022
aiMotive has developed a comprehensive tool for evaluation of NN algorithms, detection SW and automated driving software. It tracks development progress against requirements and provides real-time insights and gap analysis.
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5 October 2022
Data is critical to neural network (NN) development. Automatic annotation is the most effective and cheapest way to generate training and validation data from real-world recordings. But what about hard-to-capture scenarios or corner cases that hardly ever occur in real life? Automated driving systems still need to be aware of such events.
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23 September 2022
The paper titled 'A Novel Neural Network Training Method for Autonomous Driving Using Semi-Pseudo-Labels and 3D Data Augmentations' written by Tamás Matuszka and Dániel Kozma has been accepted to the 14th Asian Conference on Intelligent Information and Database Systems (Category B in the 2021 CORE conference rankings) and will be published in Springer's Lecture Notes in Artificial Intelligence. The work will be presented in Ho Chi Minh City, Vietnam, on November 28-30, 2022.
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25 August 2022
Annotation is the most expensive element of training data generation, so truly automatic annotation remains the holy grail of automated driving development – aside from the ability to generate synthetic data that is indistinguishable from real data.
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28 July 2022
Our newest product, aiData, became available to selected partners a few months ago. The product includes five tools that can help partners and customers, ranging from data capture to data processing. In this blog series, we will take a closer look at these tools, starting with aiRec, responsible for data recording.
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21 July 2022
Safety is the most critical element of automated driving — check out our aiDrive safety report which was recently revised to provide a deeper understanding of the wide range of processes we use to ensure safe testing and operation of our solutions.
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14 January 2022
The latest generation of our automated driving full software stack, aiDrive 3.0, has just been released, featuring our in-house model-space based perception, which is the most solid foundation for automated driving solutions.
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24 November 2021
The world's first ISO26262 certified virtual validation suite, aiSim, has integrated ROS2, making it instantly compatible with one of the most popular prototyping frameworks for advanced driver-assistance systems and automated driving solutions.
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20 October 2021
Bernhard Bihr joined aiMotive in the summer of 2020. With his over 30 years of automotive experience, his goal is to support aiMotive's development efforts.
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7 October 2021
A 2020 survey showed that most respondents would be more comfortable letting a robot perform surgery on them than sitting in a car with autonomous tech in it. Would you?
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27 July 2021
Lately, attention is turning towards self-driving cars again. Some people envision driverless vehicles in the next couple of years; others struggle with the idea to trust a "robot" with their life. While some fear artificial intelligence with evil intentions, it might be time to wonder what are the ultimate goals that drive us and the teams at the heart of the AD and ADAS industry forward?
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15 July 2021
The aiSim team adapted the Hardware-In-the-Loop testing approach with a unique spin on the concept that allows for testing complete automated driving systems with live simulated sensor data without any prerecorded footage. In this post, I will provide some insights into the benefits and challenges of introducing this powerful and exciting new feature to aiSim.
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15 June 2021
Technology leadership claims can often be “economical” with the truth, and this is particularly true for NPUs (Neural Processor Units). However, over-stated performance can lead to procurement decisions that fall short of expectations. The result is engineering targets missed, deadlines not met, and R&D costs escalating. For its aiWare NPU, AImotive focuses on benchmarking NPU efficiency to provide the best information for AI engineers. Many other NPU suppliers quote raw TOPS and hardware utilization as a measure of performance. What’s the difference, and why does it matter?
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3 June 2021
Joining AImotive with decades of automotive experience, our new Chief Commercial Officer has been at the heart of the automotive industries transition towards ever-higher levels of automation. Arnaud Lagandré brings a solution-focused attitude and in-depth cultural knowledge to AImotive. However, it's best to let people speak for themselves. We sat down with Arnaud to learn more about him and his motivation behind joining AImotive.
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20 May 2021
Simulating the sensor modalities used in automated driving efficiently and accurately is an immense challenge. The best solutions is to rely on GPU-accelerated raytracing techniques and the efficient distribution of tasks. Today, the Vulkan API is the only tool that can support such a system – that’s why we’ve integrated it into aiSim.
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17 May 2021
Laszlo Kishonti sees a potential opening for aiMotive as non-traditional players look to enter the battery-electric market. In order to move quickly and be competitive, they’ll need to rely on companies like his for advanced technology, he believes.
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6 May 2021
In 2020 aiMotive's aiSim™ simulator was certified to TCL 3 according to ISO 26262:2018 by TÜV-Nord. This made it the world's first ISO26262-certified comprehensive automated driving simulator for the development of automated driving solutions. Let’s go a layer deeper and see what’s under the hood: what makes aiSim's rendering engine special and unique.
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11 March 2021
Is the future electric, self-driving or both? The answer is complex and influenced just as much by long-term industry trends, regulation and consumer demands, as how quickly the technology develops. Let’s take a closer look.
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28 January 2021
For embedded applications, the biggest challenge is taking a concept from a prototype in the lab to a production-ready solution: a product that is robust over lifetime, certified to all the relevant standards, tested to ensure it always works, and cost-engineered to make sure it delivers a profit. You need tools designed to help engineers do that job as flexibly as possible.
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12 January 2021
Delivering automated driving and driver assistance functions for a brand-new vehicle designed from scratch is a huge opportunity. We can fine-tune the sensor setup, the processing platform, the vehicle signals, and find ways to integrate all of them in the vehicle as seamlessly as possible while maximizing the value offered to the driver.
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13 November 2020
Apple’s recent announcement of the new M1 chip powering their latest Macs, following many years of successful deployment of their Ax chips powering their smartphones and tablets, demonstrates their use of hardware closely coupled to their software to maximize their product leadership. But why do they invest so much in their hardware platform?
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11 November 2020
At AImotive, we heavily rely on perfecting simulation testing for our automated driving development efforts. This push has led to the creation of aiSim, the world’s first ISO 26262-certified simulator for automated driving systems. However, not even the best simulation can substitute the real world...
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2 November 2020
In five years, AImotive has created what no company has done before: the world’s first automotive grade, ISO26262-certified simulator, aiSim. However, it is not enough to have high-fidelity vehicle dynamics, realistic sensor models and last but not least realistic traffic simulation....
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21 September 2020
When considering hardware platforms for executing high performance NNs (Neural Networks), automotive system designers frequently determine the total compute power by simply adding up each NN’s requirements...
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8 September 2020
Efficiency has always been at the core of everything we do at AImotive, which is why we realized early on that the quality of data collection is more important than its quantity, and that there are much smarter methods than standard data collection practices.
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17 August 2020
The unprecedented situation that has developed as a result of the current COVID-19 outbreak has brought a new range of challenges to the fore in automotive software development. At AImotive, we are relying on...
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11 August 2020
To build a scalable technology platform for automated driving, we need to focus on safety throughout our development cycle. We have created a public Safety Report to show the framework of our approach to safety in ADAS.
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5 August 2020
At AImotive we are working to catalyze the mass deployment of automated driving solutions. In order to make these accessible to all, we still have to overcome several obstacles with our partners.
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21 May 2020
Solving continuous integration – continuous deployment (CICD) development for safety critical automotive software is a complex challenge. While simulation is a vital aspect of the solution, simply having a simulator is not everything. At AImotive, we have created a unique CICD development pipeline, that relies on simulated and real-world data to ensure safe development.
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11 February 2020
To get ADAS right, you have to start with the hardware. You can create the most advanced perception, robust decision making, detailed planning algorithms, but without a robust, reliable hardware platform with sufficient guaranteed performance, any deployment strategy will simply fail.
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9 August 2019
First came computer vision and traditional algorithms, then supervised-learning artificial intelligence. Yet we continue to find limitations in what machines can do. A novel approach is to train AI as we would train a pet, or even, as we often learn ourse
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1 August 2019
Guidelines for software devs and safety drivers to mitigate personal liability. The question of personal liability in automated driving development is surprisingly common, as everyone is aware of the risks involved. At the first AImotive Meetup in Bud
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18 July 2019
Scenarios are the base of simulation testing for automated driving systems, just as simulation testing is the base of safe automated driving. However, until recently moving scenarios from one simulator to another was almost impossible. This has to change.
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2 July 2019
Higher levels of autonomy will require dedicated chips built for self-driving. However, developing hardware platforms requires unique expertise of a kind that most traditional automotive OEMs don’t have.
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17 May 2019
Currently, many AVs use a powerful central compute platform, but as the technology, safety standards, and regulations mature even these platforms cannot deliver the performance needed. Distributed processing offers some answers, especially for AVs.
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30 April 2019
The proliferation of increasingly advanced automated driving technologies poses a new challenge for the automotive industry. One, that traditional safety standards are not equipped to solve.
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12 April 2019
Many believe that Neural Network (NN) hardware accelerators are great for anything using NNs. However, NN training is very different to NN inference as happens in applications like autonomous vehicles (AVs). This blog explains the differences, and why aiW
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19 March 2019
First people thought self-driving was a sprint race, now many think it’s a marathon. However, it’s turning out to be an ultra-marathon relay. No one can solve the challenges of self-driving alone: the future to automation lies in collaboration.
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28 February 2019
What’s the problem?Creating production-ready, compute-intensive AI-enabled hardware platforms for automotive is becoming one of the most innovative, dynamic and creative areas for the semiconductor industry.
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15 February 2019
No single sensor can handle the whole of self-driving, however, when utilizing sensor fusion the strengths and weaknesses of different sensor types have to be considered.
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31 January 2019
The future of automated driving lies in collaboration. However, this has its different forms and levels. The way forward is paved with standardization, modular software architectures, and flexible designs.
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3 January 2019
Much has changed in the autonomous industry over the past year, and even bigger changes are coming in 2019.
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19 December 2018
Automotive simulation has a specific set of demands. Meeting them is no simple task.
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29 November 2018
Simulation is a game changer in autonomous technology, but more has to be done.
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22 November 2018
The demand for ever more advanced high-performance real-time compute processing hardware is increasing rapidly across the automotive industry.
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16 October 2018
As computer systems became more complex the question arose: centralize all resources, or distribute processing?
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1 October 2018
It may sound trivial, but getting a self-driving system to understand its own movement is no easy task.
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30 August 2018
Our Lead AI research scientist, Viktor Gyenes explores how the newly released NNEF™ standard has changed our everyday work at AImotive.
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16 August 2018
Self-driving is one of the greatest challenges of our age. For the first time, we have the technological background, spatial and temporal resolution for a robotic system to fully understand its surroundings.
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12 July 2018
Functional safety is, without a doubt, the most crucial factor in safety-critical environments such as automotive development. Not only because you gain the trust of customers but because you would put the health and safety of test drivers and more import
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