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@article{207394,
        author = {Gaddam Venkata Rao},
        title = {The Brain on Wheels: AI-Powered Digital Cockpits and the Future of Software-Defined Vehicles},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {909-920},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207394},
        abstract = {The automotive industry has been undergoing its most profound transformation since the introduction of the internal combustion engine. Software-Defined Vehicles (SDVs) are rapidly displacing hardware-centric architectures, placing artificial intelligence at the heart of the driving experience. Software-Defined Vehicles (SDVs) introduce centralized computing architectures where cockpit systems, Advanced driver assistant systems, Driver and Occupants monitoring, Infotainment, Connectivity, and cloud services operate as a unified intelligent platform. AI serves as the cognitive engine of this transformation, enabling contextual awareness, predictive interaction, personalized user experiences, autonomous assistance, and continues over-the-air evolution. This paper examines the architectural evolution of AI-powered digital cockpits and provides rigorous comparative analysis of the five dominant cockpit compute platforms — Qualcomm Snapdragon Auto, MediaTek Dimensity Auto, Telechips TCC Series, NVIDIA DRIVE, Renesas R-Car, TI TDA5, and NXP i.MX/S32 — across compute performance, AI capability, safety certification, connectivity and ecosystem maturity. We further analyze the convergence of large language models, sensor fusion, edge inference, machine learning deployment, human-machine interfaces, emerging innovations, and over-the-air update architecture within the modern SDV and outline the strategic roadmap for the next decade of automotive intelligence.},
        keywords = {AI Powered Digital Cockpits, Future of Software-defined Vehicles, AI Deep Dive on Embedded Edge Computing, Edge AI Automotive Use Cases, Silicon vendors deep-dive on AI workloads.},
        month = {August},
        }