The fourteenth edition of Roland Berger’s Automotive Disruption Radar finds that one country is now leading and reshaping the automotive industry.
Autonomous driving: Why automakers need to partner with chipmakers
By Stefan Riederle and Sebastian Braun
As AI is key to autonomous driving, only deep collaboration with tech leaders can ensure its successful deployment
Autonomous driving is here. Whether sharing a Waymo driverless cab in Los Angeles or riding an Apollo Go robotaxi in Wuhan, the technology is a reality. With the concept proven, automakers are now shifting focus from development to deployment. Yet executing this rollout at scale and pace will mean securing ready access to the core technologies behind autonomous driving (AD), especially artificial intelligence (AI) and high-performance computing. How can they achieve this? We believe that close partnerships between OEMs and technology leaders, especially chipmakers, are the key to success. In our article “AI in the driving seat: Why only deep collaboration between automakers and tech leaders can ensure success in autonomous driving” we assess the growing trend toward these partnerships, examine the importance of AI in AD and outline an approach to form value-adding relationships with chipmakers.
Recent announcements of partnerships between OEMs and chipmakers highlight how autonomous driving is increasingly being shaped by closer collaboration across computing, software, data and deployment. The tie-up between NVIDIA and Mercedes-Benz, for example, goes far beyond a traditional supplier relationship, encompassing joint R&D in vehicle intelligence, simulation environments and industrialized deployment processes. Meanwhile, the deal between NVIDIA and the ride-hailing provider Bolt aims to build a whole autonomous vehicle open-source platform that combines the chipmaker’s computing, simulation and software stack with Bolt’s large-scale, real-world carsharing fleet and ride-hailing data.
Why AI and partnerships are the key to scaling autonomous driving
"The AI-driven transformation is accelerated when OEMs co-develop with chipmakers across the full lifecycle."
Such close collaborations are integral to mastering autonomous systems, which require seamless coordination between sensors, computing hardware, AI models and real-time data processing. But are OEMs building the right capabilities and partnerships to deploy autonomous technology at scale?
Automakers require three key AI, computing and software capabilities to achieve scale:
Advanced perception: AI enables vehicles to interpret complex environments, recognize objects and anticipate hazards.
Real-time decision making: High-performance computing platforms process vast amounts of data in milliseconds, allowing for safe and efficient navigation.
Adaptive learning: AI models continuously improve through data-driven training, enhancing performance over time.
However, AI only becomes scalable when it is productized on the right computing foundation. This is where chipmakers come in. Their platforms define what is technically and economically feasible, setting the boundaries for what automakers can achieve and facilitating integrated hardware-software stacks. By embedding AI across all stages of the value chain, automotive players can:
Transform operations: Streamline development, testing and deployment of autonomous systems.
Bolster competitiveness: Shorten development cycles for autonomous driving functions, industrialize software updates and bring differentiated autonomous driving/advanced driver assistance systems (ADAS) capabilities to market faster than competitors.
"Develop a comprehensive AI and autonomy strategy that covers computing platforms, model architectures, tooling and safety concepts."
Improve efficiency and performance: Reduce validation effort through simulation and AI-enabled testing, optimize in-vehicle compute costs and improve system safety and driving performance.
How to build a strategic partnership
In short, treating computing as a late-stage procurement choice is no longer viable; deep, early-stage collaboration is the new standard. The full article uses the results of the latest Roland Berger Automotive Disruption Radar to further reinforce why collaborations are a prerequisite for future scale. For example, the article highlights the strong progress made in AD across major markets, especially with regard to technology, and notes the strong global uptick in venture capital investments. In addition, it outlines a set of recommendations on how OEMs can build strategic partnerships with tech leaders, including on co-designing a full end-to-end AI/autonomy stack.
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