In 2010, Damian Harty was enjoying an especially rewarding time in his career as technical specialist in dynamics at Prodrive, the renowned UK engineering consultancy and motorsport preparation outfit. Having previously been involved in the development of the all-conquering Subaru Imprezas in the World Rally Championship, he had turned his attention to the new (and disappointingly short-lived) Mini Countryman WRC initiative. At that time, Harty wrote an article for Vehicle Dynamics International, ATTI’s former sister title, about the Mini’s development, in which he memorably noted, “There will always be a bigger rock. However much suspension travel there is, it will all get used up. Whatever loads are designed for, they will be exceeded.”

That there will always be a “bigger rock” neatly summarizes much of the difficulty of automotive testing, no matter which part of the vehicle is under consideration. Sixteen years later, during a chat with Harty, ATTI began by asking whether it is now easier than it was before to know where the limit of testing should lie. “I don’t think so, because the challenge is not so much about the vehicle itself, it’s about what the vehicle will encounter,” he replies. “And for as long as you have human drivers and, let’s say, imperfectly calibrated software drivers, it’s still difficult to anticipate the corner cases with which the vehicle will be presented.

“That was what I meant by ‘There will always be a bigger rock.’ So, the requirement to understand where we draw a line in the sand, and then what happens when we inevitably accidentally overshoot that line in the sand, still exists, I think.”

Harty notes that Sir Alec Issigonis, the designer of the original Mini, initially believed that the car’s combination of small size, light weight, front-wheel drive and hydrolastic suspension provided drivers with greater safety margins – but later realized that drivers would fully use up whatever margins you gave them.

“Someone will always go the other side of that line in the sand, so we still need to understand what happens there,” he continues. “We then try to make a value judgment about where we draw the line, such that, if you’re just below it then things emerge undamaged, or if you’re above it, things are damaged in a way that we can predict.

“A further difficulty is that you’re trying to stay inside the herd. If your line is drawn in more or less the same place as everyone else’s, then you’re probably okay. But if it is drawn a lot higher than everyone else’s, your products cost more than they need to; a lot lower than anyone else’s line and you will be on the receiving end of some pretty unpopular sentiment. I think that finding where to draw the line is no easier or more difficult than it ever was.”

A blend of human experience and previous data remains the key to determining how demanding a test should be, according to Harty. “One of the challenges that I understood very clearly in the powersports industry is that as your products improve, people move the line,” he observes. “The speed that people are willing to carry over a certain surface goes up, for example. As you make products better, people’s expectations increase. It’s not a static thing at all.” In short: the test engineer’s work is never done.

Recipe for success

Looking ahead to this year’s ATTI Awards, which will take place at Automotive Testing Expo Europe, Harty notes that test engineers are continuing to marry new techniques with established tools. For the latter, Isaac Newton’s F=ma remains his go-to for a back-to-basics understanding of what is happening to a vehicle, component or subassembly. He also expresses surprise at how little FEA has evolved in the past 30 years, computing power aside. For new methodologies, he highlights automotive software testing as an area where tools are advancing especially rapidly – but cautions that the industry’s understanding of how the product is being used, and therefore where the focus of testing should lie, is still evolving.

“Testing is about trying to find stuff before your customers do,” he explains. “The two areas where that’s most difficult tend to be durability and anything to do with software. The durability challenge is pretty much the same as it has always been. I think that for metallic components, we’re quite well served [with tools and knowledge]. But as soon as you switch to polymers or composites, for example, we’re grasping in the dark as to what they’ll do under repeated loading. That holds us back from using different materials for critical structural applications.

“Meanwhile, the scope for software is evolving all the time,” he continues. “When you put things in the hands of the public, you have the million-monkeys, million-typewriters problem, where they are generating scenarios that you maybe didn’t test for, so all the energy and effort is on the software side. Personally, I’m not so interested in whether the cellphone connectivity works properly or not, because it’s unlikely to be life threatening if you get that wrong. But there is a lot of functional stuff where many systems are interacting and there’s a whole load of corners to poke into. I feel like there is a lot of unmapped territory there that we’re still finding our way into as an industry.”

Harty believes that help in finding such corner cases will be one area in which AI will benefit the testing industry. “One of the things I like about AI is that it’s like talking to someone who isn’t necessarily all that clever but is hugely widely read. For the corner cases, I think it will be easier to poke more deeply into the corners, find and flag an issue, and specifically test for it.”

No two the same

Knowing what to test for will remain an issue for test engineers more generally, he believes, and will continue to be a moving target as customers exploit the margins to which Issigonis referred. Harty has been reminded of this in his recent work with TVS, India’s largest motorcycle manufacturer, rekindling a working relationship that began in the 1990s.

“For me, the biggest misconception about testing is the illusion that we really know what people are going to do with our products,” he confirms. “I think people underestimate how much of an honest best guess is used in all sorts of testing. There’s an erroneous belief in precision that’s misplaced when it comes to putting products out in the wild and understanding what people are going to do with them.

“When I began working with TVS in the 1990s, the engineers talked about how one product, a 50cc moped, was used as a load carrier. I did not understand what they meant: after all, it has a 50cc, two-stroke engine that makes just over one horsepower and can barely do 30mph [50km/h]! But when I came to India, I saw endless examples of multiple sheets of 8 x 4ft [2.4 x 1.2m] plywood, bags of concrete and more, all piled up in incredibly imaginative ways on mopeds with someone walking beside them, using the engine to just walk the load to where they wanted to go. I had no conception that the product could be used like that, but these engineers understood their market. The load case for the pedals was not a human, it was as many sheets of 8×4 ply as you could balance on it – a very different number of kilograms.

“That is an example of the sort of thinking that is quite difficult, especially if you’re coming up with a novel product,” he concludes. “It’s hard to imagine how people might conceive of using your product. That, I think, will continue to keep us interested and amused going forward.

“There is a glorious quote from Douglas Adams in Mostly Harmless: ‘A common mistake that people make when trying to design something completely foolproof is to underestimate the ingenuity of complete fools.’ He’s saying that whatever you think, there’s no guarantee that’s how everyone else will think. It’s a fascinating idea.”

This article was first published in the June 2026 edition of Automotive Testing Technology International

The results of this year’s Automotive Testing Technology International Awards will be announced at Automotive Testing Expo Europe next week – secure your ticket now!

As cellular networks transition away from legacy 2G and 3G infrastructure, auto makers face mounting pressure to deliver compliant Next-Generation eCall (NG-eCall) implementations that utilize packet-switched 4G and 5G networks. Because regional network modernization moves at varying speeds, vehicles must operate reliably across mixed-network environments. According to Keysight, its certified Hybrid eCall solution addresses this challenge directly, enabling in-vehicle systems (IVS) to dynamically switch between legacy and NG-eCall systems based on real-world network availability.

Building on Keysight’s previously achieved EN 17240 validation, this new certification ensures continuous alignment with evolving international standards.

Lourdes Sánchez, connectivity director at DEKRA, said, “At DEKRA, we are committed to supporting the automotive industry in the transition toward next-generation emergency communications through testing and certification services aligned with the latest European standards. Our collaboration with Keysight in validating its Hybrid eCall capabilities according to EN 18052:2025 has enabled the verification of critical aspects related to interoperability, reliability and regulatory readiness, helping accelerate the adoption of safer and more connected vehicle solutions for the future.”

The certification covers a range of critical real-world testing scenarios, including emergency call setup to validate rapid and stable connections across evolving network infrastructures, minimum set of data (MSD) transmission to ensure accurate delivery of vehicle location and telemetry data to emergency responders, voice communication to verify clear and uninterrupted call quality under realistic network conditions, and network fallback to confirm reliable operation when transitioning between NG-eCall and legacy network environments.

Thomas Goetzl, vice president and general manager of Keysight’s Automotive & Energy Solutions, added, “The automotive industry is at a critical juncture as cellular infrastructure evolves. Auto makers need proven, reliable testing methodologies to avoid compliance bottlenecks and deployment delays. Achieving this DEKRA certification underscores our commitment to delivering real-world-ready solutions, giving manufacturers the confidence to scale their connected vehicle platforms globally while meeting the highest safety standards.”

Keysight will demonstrate its Hybrid eCall and NG‑eCall testing at the ETSI NG‑eCall Plugtests 2026.

In related news, Hyundai Mobis joins S-Core project to advance SDV software platform development

To this end, the company has joined the Software Defined Vehicle (SDV) Working Group under the Eclipse Foundation and will participate in the S-Core project to develop an SDV software platform in earnest.

The S-Core project is a global initiative launched primarily by European companies in late 2024 to standardize foundational technologies such as software platforms and middleware. It is the first open-source-based software platform development project to meet ASIL-B, the automotive industry’s functional safety standard.

Currently, a total of 13 companies are participating in the project and prioritizing the implementation of core technologies required for SDVs, as standardized foundational technologies are essential for accelerating the development of applications such as autonomous driving. Under the common objective, participating companies are also working to prevent redundant investments while improving system stability.

The most distinctive feature of the S-Core project is that it applies an open-source development approach, previously used primarily in the IT industry, to the mobility sector. Participating companies disclose some of their software technologies, enabling developers around the world to freely use and improve them.

Another reason companies disclose coding technologies that constitute intellectual property is the potential to create both tangible and intangible added value. By encouraging more developers to use their software, companies can increase the likelihood of their technologies becoming global standards.

The technology Hyundai Mobis plans to disclose is a so-called ‘container solution’ that minimizes interference between software within the Linux operating system. The technology effectively creates partitions between a wide range of software in SDVs, packaging them individually so they can operate quickly without affecting one another.

The container solution is known to be more than 10 times faster than existing technologies in automotive controller environments. The company has also secured an always-on integrity assurance function to prevent software tampering caused by external intrusions and other risks.

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The release extends the capabilities of Candera CGI Studio across the entire workflow from design and validation to deployment, and enables development teams to create and scale modern user interface concepts more efficiently across industries, hardware platforms and a wide range of use cases.

“With Candera CGI Studio 3.16, HMI development gets smarter and faster, combining AI-assisted tools, flexible workflows, and broad platform support,” said Roland Winkler, senior product development manager at Candera.

Improvements and updates

The Scene Composer experience has been enhanced with a new View Editor that simplifies automotive HMI workflows by allowing developers to preview scene combinations and manage transitions within a structured framework.

An Embedded Player enables seamless switching between design and runtime simulation inside Scene Composer, while a standalone Player remains available.

Multi View in the Scene Editor adds up to four synchronized views with selectable camera angles, improving inspection of complex 3D interfaces and enabling quick switching between single and multi-view modes.

Localization and documentation workflows are improved with built-in XLIFF 2.0 support. Developers can import, merge, edit and export localized text in a standard XML-based format, making CGI Studio easier to integrate into existing localization toolchains.

The new AI Docs Agent provides in-workflow support by delivering tailored answers in any language, helping users find information more quickly and reducing day-to-day friction. Each response also includes direct links to relevant Candera CGI Studio documentation, enabling users to access source material immediately.

Solution templates and advanced 3D

Another highlight of Candera CGI Studio 3.16 is the expansion of ready-to-use automotive HMI templates. The new In-Vehicle Infotainment (IVI) template includes building blocks for navigation, weather, media, phone, HVAC and digital twin scenarios. It supports both 2D and 3D use cases, with advanced visualizations and customizable application screens.

The new Instrument Cluster Solution Template integrates advanced driver assistant system functions such as adaptive cruise control (ACC), lane departure detection (LDD) and side assist alongside essential dashboard elements like speed gauge, media, telltales, time, odometer, temperature and turn-by-turn guidance. These templates help teams accelerate prototyping and shorten time to value.

The update enhances 3D capabilities with full glTF 2.0 support and features such as clear coat rendering. It also adds HDR rendering with tone mapping and automated import of image-based lighting cube maps for global illumination. Together, these improvements enable more realistic HMI visuals across automotive, industrial and embedded applications.

Engine and platform improvements

On the platform side, Candera CGI Studio 3.16 expands deployment flexibility with native rendering support for Apple iOS, enabling developers to build applications for Apple devices using Xcode and Metal.

The release also introduces Vulkan support as a modern graphics backend for 3D GPUs, improving CPU and GPU efficiency on Linux and Android platforms.

Another key addition is Software Rendering, which enables Candera CGI Studio 3.16 to run on platforms without a GPU. This enables platform-independent rendering across a wide range of targets, including ESP32-S3, ESP32-P4, Traveo II Body MCU, Raspberry Pi Pico and Linux-based systems. The renderer supports transformations, blending and visual effects while achieving up to 60 FPS depending on the platform and configuration, with low memory requirements.

Additional engine optimizations round out the release. Candera CGI Studio 3.16 now supports the new Monotype Spark Engine, designed for low memory usage and high performance. The update also includes newer versions of FreeType and HarfBuzz, delivering significant cache improvements for more efficient text rendering.

Candera CGI Studio 3.16 also streamlines behavior configuration through automatic code-size optimization using the SC plugin and CMake integration. These improvements help developers reduce memory footprint, improve performance and simplify overall project setup and configuration.

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AGL SoDeV is an open-source reference platform for building software-defined vehicles. It combines the AGL Unified Code Base (UCB) with Linux containers, VirtIO, the Xen hypervisor, Zephyr RTOS and other Linux Foundation projects in a single pre-integrated package that runs on automotive systems-on-a-chip (SoCs), on virtual machines or in the cloud. SoDeV enables auto makers and suppliers to decouple software development from hardware availability, accelerating SDV time-to-market.

As the automotive industry moves toward software-defined vehicles (SDVs), demand is increasing for shared, open-source software platforms. AGL brings together auto makers, Tier 1 suppliers and technology companies to develop and maintain a common software stack to reduce fragmentation, shorten development timelines and support innovation across vehicle systems.

The addition of EMQ, Lineo Solutions, MediaTek, VA Linux Systems Japan and Very Good Ventures expands AGL’s expertise across areas including automotive semiconductors, connectivity, Linux engineering, in-vehicle user interfaces and embedded software tools that support large-scale SDV development.

“We’re excited to welcome these new members to the AGL community, each of which brings distinct and valuable expertise to the table,” said Dan Cauchy, executive director of Automotive Grade Linux. “The ecosystem around our SoDeV reference platform continues to grow, reflecting the breadth of innovation that open-source collaboration makes possible. The automotive industry is undergoing a fundamental shift to software-defined vehicles, and AGL is proud to be at the center of it.”

Available in latest AGL software release

An initial version of the AGL SoDeV reference platform is available in the latest AGL UCB software release, Ultimate Unagi, enabling developers to build and test an SDV system on Renesas Sparrow Hawk reference boards and cloud-based processor environments.

Announced in December 2025, the AGL SoDeV Reference Platform combines the AGL Unified Code Base (UCB) with multiple open-source projects hosted by the Linux Foundation to support the consolidation of ECUs, hardware abstraction through virtualization, and cloud integration for software-defined vehicles.

“The AGL platform represents exactly the kind of production-focused, community-driven approach to SDV software that our customers and partners need,” added Masahiro Sano, the chairman and CEO of Lineo Solutions.

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Advanced driver assistance systems bring increasingly sophisticated software into vehicles. Functions such as lane keeping, adaptive cruise control, automated emergency braking and sensor fusion rely on complex algorithms operating under tight real-time constraints. Consequently, automotive development organizations invest substantial effort to ensure that application software and hardware platforms comply with functional safety standards such as ISO 26262.

Yet one critical layer of the software stack often receives far less attention: the compilers and libraries that silently transform our software code into reliable, high-performance executable behavior. These tools operate largely out of sight, but they play a decisive role in determining how ADAS software performs on the road. In fact, no ADAS function can exist without them.

The silent force behind ADAS software 

Compilers translate high-level source code into machine instructions, while standard libraries provide essential functionality for numerical computation, data handling and timing. Together, they form the foundation on which application software is built, and their correctness is often taken for granted throughout the development lifecycle.

In practice, this assumption can be risky. Even when application code complies with coding guidelines and the target hardware is safety-certified, deficiencies in the toolchain can still undermine system behavior. These issues typically do not originate in the application logic itself, but in lower layers that are difficult to observe directly.

Unseen risks in the toolchain 

Compiler optimization is a prominent example. Optimization is essential for meeting performance and power consumption requirements in automotive systems, but it also introduces significant complexity. Changes in optimization paths can alter control flow, numerical precision or timing in ways that are not apparent from source code inspection. As a result, a compiler update or a change in optimization options may introduce new behaviors (and even errors) while the application code remains unchanged.

Standard libraries present similar risks. Library functions are widely assumed to be robust and well tested, yet they are subject to implementation choices and corner cases like any other software. In ADAS, where libraries are statically or tightly linked into the final executable, subtle deviations from expected behavior can propagate directly into system-level effects.

Because these problems originate below the application layer, they are not easily detected using conventional testing approaches. Integration testing may expose symptoms, but it rarely provides systematic coverage of toolchain behavior. As a result, determining whether the root cause lies in the application logic, the compiler or a library implementation can require extensive investigation. When such issues surface late in development, the associated cost and disruption can be substantial. Even more concerning, if they remain undetected until deployment, they may manifest as safety-critical failures, with potentially severe consequences.

Ensuring reliability through verification 

Managing these risks requires systematic verification of compilers and libraries. This involves demonstrating conformance to relevant programming language standards and consistent behavior across configurations, optimization levels and target platforms.

Structured test suites are central to this effort. By exercising both front-end language features and back-end optimization paths, they can reveal defects that would otherwise remain latent. Problems are not confined to parsing or semantic analysis; changes deep within the optimization pipeline or the code generator can also introduce unintended effects. Comprehensive testing helps surface these issues early, before they impact product development.

Supporting qualification and long-term confidence 

Beyond identifying defects, verification provides the objective evidence needed to support tool qualification. The ISO 26262 safety standard for automotive software requires confidence in the correct operation of the compiler and evidence that the standard library meets the requirements on which the application relies. By testing the compiler against the programming language specification, it is possible to verify that source code is translated into machine code in a well-defined and predictable manner. Likewise, requirements-based testing of the standard library demonstrates that its functionality conforms to the requirements relied upon by the software. Together, these activities provide objective evidence that the generated object code faithfully represents the source code.

Furthermore, the goal of qualification is not to prove that the compiler or library is completely free of errors – an unrealistic expectation for any complex software tool. Instead, the objective is to understand their limitations and known deviations, and to manage them in a controlled way so that they do not compromise functional safety. This understanding is captured in a safety manual that complements the verification results and defines the constraints, assumptions and usage rules for the compiler and library, ensuring they can be applied safely within the software development process.

This approach also supports long-term maintainability. Automotive platforms often have lifecycles spanning decades, during which compilers and libraries inevitably evolve. Systematic validation of updates enables controlled transitions without the need to re-qualify entire systems from scratch.

This benefit has been demonstrated in practice, where early identification of compiler issues has significantly reduced the effort associated with toolchain updates. By understanding tool behavior upfront, organizations can make informed decisions about changes and avoid costly surprises later.

Standard libraries follow similar principles. When assessing a new library implementation, behavioral comparison against a known baseline helps ensure that replacements do not introduce unintended or system-relevant changes.

The role of collaboration 

ADAS development involves many stakeholders: software engineers, functional safety engineers, validation teams and certification bodies. Ensuring that compilers and libraries behave as expected requires collaboration across all these roles.

Verification cannot be treated as an isolated activity, it must be an integral part of a broader safety strategy. When toolchain behavior is well understood and documented, communication between teams becomes clearer, assumptions are explicit and decisions can be justified with evidence rather than intuition.

Strong partnerships between tool providers, system integrators and safety experts further support this process. By sharing knowledge and aligning on verification practices, organizations can reduce duplication of effort and improve overall confidence in their development environment.

Conclusion 

Compilers and libraries may operate invisibly, but their impact on ADAS safety is substantial. Treating them as implicit assumptions rather than explicit verification targets introduces avoidable risk. As ADAS functionality grows increasingly complex, this risk will only increase.

By recognizing the role of the toolchain early and subjecting it to the same rigor as application software, automotive developers can build a stronger foundation for safety. Verification and qualification of compilers and libraries are not optional extras; they are essential steps to ensure that software behaves as intended – from code to road.

A feature in the next issue of Automotive Testing Technology International will investigate the challenges of continuous testing for software, the stages of a typical DevOps pipeline, how companies are measuring software readiness, and more. Read the March 2026 edition here. 

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The hub is expected to employ around 200 technical specialists that will be responsible for enhancing the MyToyota and LexusLink+ applications, which are used by more than two million European customers to access remote vehicle functions, battery‑charge monitoring and a wide range of ownership‑convenience services. The team will also contribute to the development of the cloud infrastructure that enables connected services for Toyota and Lexus vehicles in Europe, while additionally providing cybersecurity support.

“Toyota has been present in Poland for 35 years and this project strengthens Toyota’s commitment in this market,” said Thierry Boitel, vice president of research and development, Toyota Motor Europe. “Poland was selected as the location for the Toyota Digital Hub due to its strong pool of highly skilled specialists and the presence of leading technical universities.”

The establishment of the Toyota Digital Hub marks a further investment by Toyota in Wrocław. Since 2015, the Shared Services Centre has operated in the city, providing accounting and tax advisory services for all Toyota units in Europe.

“The Toyota Digital Hub is set to play an important role in Europe by expanding Toyota’s software development capabilities and positioning Toyota Motor Europe as a trusted partner in future global software‑defined vehicle development,” said Luis Lopes, vice president information and technology, Toyota Motor Europe.

“The decision to locate Toyota Digital Hub in Poland confirms our country’s strong investment appeal and its solid position as a hub for modern technologies,” said Andrzej Domański, Polish minister of finance and economy.

Recent news, Pony AI launches self-improving physical AI engine PonyWorld 2.0

During the pilot, ALLO demonstrated its ability to improve inbound logistics planning performance across TME’s complex European logistics network, reduce planning cycle times and support TME’s carbon neutrality objectives.

“The results of our pilot with Agillence have exceeded expectations,” said Jean-Christophe Deville, vice president of supply chain at TME. “ALLO has proven to be a strategic asset in our pursuit of a sustainable, cost-efficient logistics network across Europe. We are confident that this long-term partnership will continue to drive meaningful progress toward our carbon neutrality goals while delivering real operational value.”

“We are pleased to formalize our long-term relationship with Toyota Motor Europe,” said Srini Paruchuri, vice president of customer strategy and solutions at Agillence. “This partnership is a testament to the power of ALLO in addressing the unique logistics complexities of large-scale European automotive operations. We look forward to deepening our collaboration with TME as they continue to lead the industry in sustainable supply chain practices.”

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To address this, Pony.ai has launched PonyWorld 2.0, the latest upgrade to its proprietary world model and a major advancement in the core training system behind its autonomous driving stack. The key advancement is its ability to identify its own weaknesses and guide targeted improvements. The upgrade introduces three core capabilities: self-diagnosis, targeted data collection in areas where performance is still limited and more efficient training focused on the most challenging cases.

Since 2020, Pony.ai has developed PonyWorld not as a basic synthetic data simulation tool, but as a full reinforcement learning system spanning cloud-based training and in-vehicle deployment. As the system has matured, improving the Virtual Driver has increasingly depended on enhancing the world model that trains it, particularly its ability to accurately represent real-world dynamics and interactions.

“PonyWorld 2.0 is an important step toward a more self-improving approach to autonomous driving development,” said Dr Tiancheng Lou, founder and CTO of Pony.ai. “As AI systems become more capable, they can play a larger role not only in learning to drive, but also in guiding their own improvement – making L4 development more scalable over time.”

PonyWorld 2.0 is already being applied across Pony.ai’s L4 driverless fleet and R&D system.

After validating robotaxi unit economics in two major Chinese cities with its seventh-generation fleet, the company is accelerating commercialization across China and international markets, targeting over 3,000 vehicles and 20 cities globally by year-end, nearly half overseas.

New training for scalable autonomy

As driverless operations grow from hundreds of vehicles to thousands and beyond, it becomes both harder and more important to keep improving safety and performance without regression.

Pony.ai defines a true world model as more than a tool for generating virtual scenarios. It must establish what good driving means, accurately model the physical world and replicate realistic interactions between the AI driver and other road users across both edge cases and normal traffic.

PonyWorld 2.0 is designed to make that process more efficient. A structured intention layer enables the model to form an internal representation of why it made a decision, making large-scale self-diagnosis possible. The system can review its own decisions, compare intent with outcomes and identify the types of scenarios where additional learning is needed. It can then generate targeted data-collection tasks for human teams, which gather the relevant real-world samples, feed them back into the cloud, and help recalibrate the world model for more precise training.

In the early stages of autonomous driving, progress depended heavily on human engineers to design rules, label data and decide what to train next. PonyWorld 2.0 points to a different model. As AI systems become more capable, they can take over more of their own improvement cycle, while human engineers increasingly serve as operators of a directed data-collection loop shaped by the system’s own learning needs.

Pony.ai believes PonyWorld 2.0’s approach, combining high-accuracy world modeling, self-diagnosis and targeted improvement, could apply to broader physical AI systems that must learn safely and efficiently in real-world environments, extending beyond autonomous driving.

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To address this, OmniTrust and Synopsys have partnered to help development teams identify and fix critical security issues earlier in the embedded systems lifecycle by enabling secure boot validation within virtual ECU (vECU) environments.

The collaboration aims to close this gap between software and hardware by bringing security validation into the early stages of development. By combining Synopsys’s vECU solutions with OmniTrust’s embedded trust capabilities, teams can run production firmware in virtual environments and validate both expected and tampered scenarios long before hardware is ready.

This approach enables developers to observe and test secure boot behavior as part of standard software workflows, including automated regression testing. As a result, teams can detect vulnerabilities sooner, reduce integration risks and accelerate time to market.

OmniTrust provides core embedded security capabilities such as secure boot policy validation, firmware signature verification and cryptographic trust anchor management. When integrated into Synopsys’s virtual development environments, these capabilities enable developers to treat security enforcement as a continuous, testable part of modern software development.

“As automotive architectures become increasingly software-defined, automotive companies must integrate security validation as part of their software development,” said Marc Serughetti, vice president, product management and markets group, Synopsys. “Our collaboration with OmniTrust enables development teams to leverage electronics digital twins and integrate trust validation into their software development before hardware is available. Our joint customers can accelerate time to market and innovation with greater confidence in the security of their systems.”

“Secure boot and firmware authenticity are essential for system integrity, yet often checked later in development,” said Albert Rooyakkers, SVP of business development at OmniTrust. “Synopsys virtual ECUs enable early security validation, automated testing and authenticated software deployment in production.”

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