Az Android, a Google Cloud és a Nexus SDV segítségével a mesterséges intelligenciával meghatározott jármű építése

The automotive industry is transitioning from hardware-centric platforms to building their own sophisticated Software-Defined Vehicle (SDV) architectures. For OEMs, a vehicle is no longer just a means of transportation, but an intelligent, connected node within an AI-native ecosystem! Google’s Android and Google Cloud are at the forefront of this transition, offering solutions like Android’s open-source Automotive OS (AAOS) SDV and scalable infrastructure including AI integration tools. Valtech, a Google Cloud partner, uses Google technologies within its Nexus SDV platform, establishing a full end-to-end connected vehicle system. This enables true agentic mobility for automotive OEMs, providing a ready-to-use foundation for the next generation of connected vehicles. Let’s examine how this comes together. The vehicle side: AAOS SDV As the foundational in-vehicle platform, Google’s open-source AAOS SDV platform abstracts core functions into reusable services independent of physical hardware, establishing a modular Service-Oriented Architecture (SOA). By decoupling non-safety domains like climate control, lighting, and diagnostics from Electronic Control Units (ECUs), the AAOS SDV platform introduces dynamic runtime service discovery. This allows the SDV to easily discover what services are running (e.g., the odometer, HVAC, sunroof, motorized seats, electric windows, etc.) and their status. By leveraging the Android Cuttlefish emulator, engineering teams can build digital twins in the cloud, simulating high-frequency sensor streams to validate these decoupled services before physical silicon is ready. Valtech Nexus SDV utilizes this AAOS SDV middleware layer to discover, map, and manage vehicle resources, structuring and streaming high-frequency telemetry data directly into Bigtable. This contrasts with the prior state, where OEMs outsourced system software to various suppliers, each with their own pipelines, protocols, and data stored in separate silos. Crucially, this model decouples services from the heavy infotainment stack, allowing them to run independently, even when the vehicle is off and parked. This enables remote vehicle monitoring to remain active even when the primary infotainment system is powered down, ensuring continuous telemetry access without draining the vehicle’s 12V battery or main EV battery pack. This tight integration between the AAOS SDV platform and Nexus SDV enables a number of agentic AI and innovative first-party solutions. Unlike traditional sandboxed infotainment tools, multimodal AI agents can utilize the service discovery layer to safely interact with the physical car and process complex, intent-based requests. For example, an AI agent could automatically adjust climate zones, window actuators, or interior lighting based on a conversation with the driver, or in response to climate sensors. By linking this on-vehicle service layer managed by Nexus SDV with historical fleet telemetry stored in Bigtable, you deliver deeply integrated experiences that unlock new mobility solutions. Now let’s take a quick look at the Cloud side. The Google Cloud side: AI-native mobility Beyond SDV, we are rapidly moving toward AI-defined vehicles (AIDV), where AI is core to a vehicle’s operational logic. To be AI-native means being autonomous by design, with AI embedded at every architectural level. With this level of AI, the system can perceive environments, reason through complex scenarios using engines like Google Gemini, and proactively execute actions. For example, a Gemini-powered vehicle doesn’t just warn you that you’re low on power; it analyzes your schedule, traffic, and charger availability to suggest an optimized charging stop that pre-conditions the battery for maximum efficiency. This is the level of contextual understanding and proactive automation that characterizes AIDV. This contrasts with legacy architectures, which were not designed to capture the volume and variety of data coming from different systems across the vehicle. This can lead to data silos of isolated maintenance and safety information telematics. Moreover, because this data is fragmented, it can be very difficult to get cohesive value from the data across systems. An AI-native approach can help collapse these silos, providing a unified contextual understanding. This solves a primary OEM pain point: the massive complexity of managing high-bandwidth telemetry from multiple sources like SDV telematics. Bigtable: The data backbone for Automotive Telemetry Bigtable was purpose-built for the massive ingestion rates and sub-millisecond latency requirements, and serves as the data backbone for petabyte-scale automotive and manufacturing telemetry datasets. In fact, Bigtable is already being used to support business critical automotive telemetry solutions. Its flexible, sparse-row schema allows OEMs to evolve their data models without downtime, accommodating diverse sensor arrays — from high-frequency engine metrics to LiDAR point clouds — within a single, unified table structure. Then, by versioning time-series events in a way that is natively optimized for both massive writes and complex, multi-dimensional analytical lookups, Bigtable helps avoid the data overload typical of legacy systems. Meanwhile, features like Continuous Materialized Views (CMV) allow for pre-calculating key metrics, such as average battery temperature or fleet-wide torque distributions, directly within the storage layer, minimizing computational overhead. Bigtable’s integration with Agent Development Kit (ADK) further bridges the gap between data and action by giving AI agents access to data. This kit combined with Bigtable’s integrations with frameworks like Apache Spark help monitor the firehose of live telemetry data and trigger automated workflows in real time, e.g., logging mission-critical alerts, initiating proactive over-the-air (OTA) software adjustments, or pre-ordering replacement parts, the moment specific degradation patterns are detected. Bringing it all together: Nexus-SDV platform The Nexus SDV platform is built on Google Cloud and integrated with AAOS SDV, supporting the future of connected vehicles. By providing a standardized data foundation, Nexus empowers automotive OEMs to go beyond building infrastructure from scratch and start focusing on unique brand experiences. Nexus SDV uses Google components like Gemini Enterprise Agent Platform, Bigtable, and BigQuery. Setting up Nexus SDV is quick, automated and transparent. OEMs can create brand-specific customer experiences in the vehicle, as well as in other customer touch points such as the UI screen, mobile app, or service centers. The connection to the vehicle is accomplished by leveraging the open source Synadia NATS interface. This integration with the vehicle is facilitated through simple Cloud and vehicle SDKs, for service discovery on both sides. Nexus SDV is optimized for AAOS SDV, but can integrate with any vehicle framework. Security is woven into the Nexus architecture via a Defense-in-Depth model. Mutual TLS (mTLS) and Google Cloud Certificate Authority Service (CAS) provide vehicles with a cryptographically secure identity. Network isolation is maintained through Private GKE clusters, while the Secure AI Framework (SAIF) helps ensure data privacy throughout the machine learning lifecycle, protecting sensitive user data and OEM intellectual property. Together, the quick setup and integration time coupled with a standardized data foundation and built-in state-of-the-art security leads to an immediate and measurable business impact for the car manufacturer. Let’s put it all together and look at a use case in more detail… Predictive maintenance By moving from reactive to predictive maintenance, OEMs can reduce warranty costs, improve customer loyalty, and ensure higher vehicle uptime. The challenge: Traditional scheduled maintenance is often inefficient, leading to unnecessary service visits or unexpected vehicle breakdowns that incur significant costs for both OEMs and owners. By moving to a proactive, AI-driven approach, Nexus SDV, Bigtable, and ADK transform this experience. The process begins by taking the firehose of vehicle telemetry data —monitoring engine RPM, vibration, fluid levels, brake pressure, and more — ingesting it and storing it directly into Bigtable. To enable real-time anomaly detection, agentic AI can monitor telemetry streams as they arrive. Bigtable CMVs pre-calculate rolling aggregations such as average engine vibration or sudden fluctuations in battery temperature profiles. AI models consuming these live aggregates can then detect subtle deviations from normal parameters, identifying early signs of engine wear or accelerated battery degradation long before a warning light appears on the dashboard. Once an anomaly is detected by specialized AI models, the system shifts into the agentic reasoning and action phase. A Gemini-powered engine assesses the severity and context of the data, considering factors like mileage, model, make, service history, and upcoming trips. Based on this intelligent assessment, the system can proactively notify the driver via the AAOS infotainment system, suggests an optimized service appointment at a nearby dealership, or can even trigger an automated parts order to ensure everything is ready upon arrival. The AI model works against false negatives to protect customer sentiment or erosion of confidence, while the solution as a whole ensures higher vehicle uptime, transforming maintenance from a reactive burden into a brand-defining service experience. Get started The AI-native Nexus SDV platform with AAOS SDV is available today, providing a sophisticated, end-to-end connected vehicle ecosystem designed to meet the extreme scale and analytical rigors of modern mobility. By adopting this unified, open-source architecture, OEMs can transcend the limitations of legacy infrastructure and redirect their resources toward the development of high-impact, brand-defining features. Nexus SDV takes the connected vehicle service into the agentic era, where vehicles are no longer merely connected, but serve as intelligent, proactive partners in the driving experience. Give it a try today. Learn more If you’d like to learn more about Nexus SDV platform, AAOS SDV and Bigtable contact us today at nexus-sdv@google.com. AAOS SDV is available in the Android Automotive 26Q2 release. Nexus SDV documentation can be found here. Go here to learn more about Bigtable as the time-series database for automotive telemetry.