Automobile manufacturers are at an inflection point in their business. They recognise driverless cars are gaining momentum but maintain an approach to engineering that is traditional and rooted in the past. With the help of Hungarian software solutions provider, aiMotive, car companies can energise the automotive sector with software focused on testing artificial intelligence-powered autonomous systems, making sure new vehicles are both reliable and safe.
By David Silverberg
Self-driven to safety
Driverless cars may not be a fantastical sci-fi dream for much longer. More automobile manufacturers are subscribing to the idea of autonomous driving, which is poised to revolutionise how the world experiences mobility. The rise of this innovation may crest the horizon sooner than we think: a scenario analysis by McKinsey estimates that 20% of passenger cars sold in 2030 will have advanced self-driving technologies, and by 2035, that figure could rise to 57%.
Earlier this year, autonomous driving afficionados were given a teaser of what the industry is capable of: a self-driving Maserati MC20 Coupe with set a new land speed record for autonomous vehicles, reaching 318 kilometres per hour during an event at the Kennedy Space Center.
Increasingly, automobile manufacturers are seeking ways to ensure those autonomous driving systems are reliable and safe. Software-driven scalable hardware leads to more robust autonomous driving, exemplified by testing how a driverless car responds to a host of environments and landscapes. Think of how an self-driving vehicle has to respond to snowy weather, encroaching bikes or a pedestrian suddenly crossing in front of the headlights; those events have to be analysed by software designed to ensure the AI-driven innovation under the hood can respond accurately and quickly.
To that end, Hungary-based aiMotive is on the path to setting the "gold standard" for how autonomous driving systems are tested and validated, says Bence Boda, marketing and communications director for the global firm.
aiMotive is regarded as a key player in developing technology for manufacturers interested in levelling up their autonomous driving capabilities, whether that comes in the form of an AI-powered software stack (aiDrive) or advanced simulation tools (aiSim). What has been a top-burner priority recently is a Eureka Network project testing verification methods for automated driving functions and environmental perception systems.
The goal of this project was to strengthen real-world testing and simulation methods in order to shorten the time-to-market of autonomous driving functions.
Learning from Apple’s ascension and drive
aiMotive’s origin story can be credited to founder and CEO László Kishonti, who worked in the telecommunications industry for years. He saw how software was critical to the market reach of major manufacturers such as Apple, evidenced by how the iPhone skyrocketed to worldwide adoption due to its robust software. An absence of this kind of progress plagued other manufacturers like Nokia and Research in Motion.
Kishonti recognised how software would become the key competitive edge for vehicles too, especially with automated driving innovations beginning to eke into the spotlight. He founded Hungarian SME, aiMotive, in 2015 to focus on developing AI-layered solutions for autonomous driving systems, a heady task considering how nascent the industry was at the time.
But the sector has matured in the past two years, and recent research supports its rise. The global autonomous vehicle market size is projected to grow from 1.8 trillion US dollars in 2023 to 13.6 trillion US dollars by 2030.
aiMotive’s products attracted the attention of major players in the automotive industry, so much so that Stellantis acquired the company in 2022. Acting as a subsidiary of Stellantis, known for brands such as Dodge, Maserati and Chrysler, aiMotive operates independently. Boda says that the freedom to develop products at their own rate is motivating, whilst its connection to Stellantis also supports the Hungarian SME with access to vast engineering resources.
At the heart of aiMotive’s business model is bridging the gap between theory and practice. “The rapidly evolving nature of the autonomous driving industry requires constant experimentation and adaptation,” says Boda. “By embedding R&D deep into our operations, we ensure our solutions remain cutting-edge and aligned with real-world demands.”
Invigorating the innovative solutions central to aiMotive requires branching in directions that give manufacturers confidence their autonomous driving systems are safe. Enter the Eureka-funded project in partnership with several organisations, which created cross-border testing regions to give manufacturers confidence their self-driving systems will rank high on a range of metrics.
Boda explains, “Automated driving systems rely heavily on sensors to ‘see’ and understand the world around them. Our project creates frameworks to verify that these sensors and the algorithms behind them are accurate, reliable and ready for real-world deployment.”
Brandishing autonomous driver’s reputation
The aiMotive project came at a time when safety was paramount for those closely following the autonomous driving sector. In a 2025 survey, more than three-quarters of drivers in the United States said they prioritise “advancements in safety systems as a top vehicle technology initiative.” Over the past decade, headlines of driverless cars causing accidents and injuries to pedestrians have soured the perception of a completely safe autonomous driving system, which may be a pipe dream considering how even today’s driver-equipped cars are not 100% safe, either.
Still, automobile manufacturers can read the tea leaves and envision a future where self-driving cars complement the human-driven cars on the road. It is a future paved by trailblazers like Tesla, Boda notes. He adds, “They have a more software-development approach to the auto industry while traditional manufacturers approach solutions through a mechanical-engineering lens. Those approaches are very different, and traditional manufacturers are struggling to shift to that software approach. That is why they often call on aiMotive for external help.”
Reaching that level of innovation does not happen overnight, nor does it evolve alone. Boda says, “The funding and collaborative framework provided by Eureka enabled us to tackle ambitious challenges and accelerate our R&D roadmap. Moreover, the projects helped strengthen our relationships with European partners, creating a foundation for future growth and cross-border collaboration.”
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