Exploring the influence AI will wield in propelling the inaugural software-defined vehicle to the market
The automotive sector is already firmly advancing towards introducing software-defined vehicles (SDVs) in the nearby future. Nevertheless, there exist several obstacles to surmount. This is especially pertinent for the more traditional automotive manufacturers, who are contending with outdated technology, infrastructure, and mindset. In contrast, emerging players in regions like China, unencumbered by these legacies, are spearheading the transition towards a software-defined era by adopting best practices derived from their more established competitors.
AI is poised to play a pivotal role in propelling SDVs forward and will ultimately expedite the process. Nonetheless, at present, the industry must dedicate time and resources to comprehend the ramifications and implementation of AI.
Generative AI is set to serve as a potent catalyst for entrenched car manufacturers as they shift towards delivering SDVs to the market. An array of advantages includes heightened efficiency. AI excels at replicating our guidance, making it adept at aiding in laborious tasks such as generating and intelligently filling a template configuration file with parameter data. It also promotes superior design and refinement. By scrutinizing data and opting for the most suitable parameters, generative AI can offer insights and recommendations for optimized functionalities in SDVs, resulting in superior, more efficient vehicles with improved performance and safety features. For instance, an AI-based model for a Battery Management System could increase the vehicle’s range and enhance its resistance to adverse weather conditions.
In this manner, generative AI could potentially bridge the divergence between legacy automakers and the software-led future by expediting development, refining designs, and expediting testing cycles.
AI finds numerous and diverse applications within the SDV, where it will eventually impact everything from car maintenance and driver support to delivering intuitive personalized aid. This encompasses functionalities like sophisticated driver assistance and leveraging AI for fully autonomous autopilot capabilities, enabling steering, navigation, route planning, and parking across virtually all scenarios. It also plays a key role in monitoring vehicle health to detect potential issues, enhance safety, and decrease the likelihood of delays.
Personalized in-vehicle encounters will leverage AI’s capacities, such as aligning route planning with the driver’s timetable and assimilating driver preferences like locations, temperatures, or even audio entertainment choices. AI will also empower the driver to dictate an email or message and send it after learning the appropriate tone from the user. It further reinforces security, ranging from biometric owner identification to distinguishing suspicious activities and thwarting cyber threats.
The obstacle to surmount revolves around where the AI capabilities should reside, in the cloud or within the vehicle itself. Although the cloud may appear to be the logical option due to computational needs, the vehicle would need constant, uninterrupted connectivity to the cloud at all times. At present, this cannot be guaranteed, with little indication of it becoming feasible. Consequently, incorporating processing capabilities within the vehicle itself appears to be the more feasible choice.
The potential for AI within SDVs is rapidly expanding, with the SDV market projected to reach nearly US$250bn by 2032, presenting a substantial opportunity for the automotive sector. The key to transforming this into reality will involve furnishing the platform and the AI-driven software without compromising on vehicle design safety.
The viewpoints expressed here are those of the author and may not reflect the stances of Automotive World Ltd.
Przemek Krokosz serves as a Senior Solution Architect at Mobica
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