Core Insights - The research conducted by J.D. Power, Tongji University HVR Lab, and XAI Lab reveals that the average score for smart cockpit models in 2025 is 622 points out of 1000, with some models nearing 700 points, showcasing excellence in HMI multimodal interaction and AI capabilities [1][3] Group 1: Research Methodology - The 2025 China Smart Cockpit Research employs an innovation index scoring model, divided into HMI performance index (50%) and AI performance index (50%), ensuring comprehensive and accurate assessments through user satisfaction scores [3] - The study indicates a shift in smart cockpit development from "digital redundancy" to "pragmatism," focusing on the depth of user experience rather than the breadth of functions [3] Group 2: User Interaction Preferences - User interaction is returning to a rational balance, with touch controls remaining dominant (importance mean 4.17/5) while the demand for physical buttons is nearly as strong (4.11/5), indicating a need for a stable balance between touch, physical buttons, and multimodal collaboration [4] - The application ecosystem is perceived as more tool-oriented than social, with users prioritizing functionalities like "charging services" (importance mean 4.23/5) and "vehicle health management" (importance mean 4.24/5) over social interaction [4] Group 3: AI Functionality and User Expectations - AI experiences are shifting from "showy" to "trustworthy," with users valuing AI functionalities that enhance travel efficiency and safety, such as "smart traffic navigation" (importance mean 4.27/5) and "health monitoring" (importance mean 4.22/5) [5] - Concerns about reliability and safety have led 56.5% of users to reduce their use of AI vehicle control functions, highlighting the need for the industry to improve AI capabilities in complex scenarios [5] Group 4: Competitive Landscape - Data quality and scenario definition are becoming core competitive advantages as the industry faces functional homogenization, shifting competition from "model scale" to "data quality, scenario granularity, and depth of adaptation" [6] - The depth of user experience is emerging as a key factor in purchasing decisions, with increased willingness to pay for comfort features like smart seats and audio systems, indicating a transition from passive tools to proactive cognitive partners in smart vehicles [6]

Core Insights - The report indicates that by 2025, the focus of smart cockpit competition will shift from "breadth of functionality" to "depth of experience," moving from "digital redundancy" to "pragmatism" [1] Group 1: Evolution of Smart Cockpits - The early "functional cockpit" centered around rich online services, while the subsequent "perceptual cockpit" integrated multi-modal interaction and perception technologies for natural interaction and task automation [1] - The industry has now entered the "cognitive cockpit" phase, enabled by the deep application of large model technology, which allows for precise understanding of user behavior and preferences, leading to proactive personalized service delivery [1] Group 2: Interaction Design - Touch controls remain mainstream, but there is a nearly equal demand for physical buttons, with 25.3% of users viewing the lack of dedicated buttons for common functions as an interaction flaw, indicating the irreplaceable nature of physical feedback in high-pressure driving scenarios [2] - Future interaction design must find a stable balance between touch, physical buttons, and multi-modal collaboration [2] Group 3: Application Ecosystem - Although 80.2% of users frequently use automotive apps, their needs are primarily tool-oriented, with "charging services" and "vehicle health management" significantly outpacing "social interaction" and "marketplace services" [3] - There is a misalignment between automakers' direction to develop apps as social platforms and users' demand for immediate utility, suggesting that ecosystem development should focus on essential scenarios [3] Group 4: AI Experience - Users currently prioritize AI functions that enhance travel efficiency and safety, such as "smart traffic navigation" and "health monitoring," with 56.5% reducing AI vehicle control usage due to reliability and safety concerns [4] - The industry needs to overcome challenges in complex scenarios, multi-modal collaboration, and intent correction to transition AI from "showcase intelligence" to "stable and trustworthy intelligence" [4] Group 5: Competitive Landscape - As large model capabilities become widespread, the industry is experiencing a trend of functional homogenization, shifting competition from "model scale" to "data quality, scene granularity, and depth adaptation" [5] - Automakers must build an integrated capability of "scene-data-model" to achieve differentiated experiences in real-world usage scenarios, with user willingness to pay for comfort features like smart seats and audio systems increasing [5] - The interaction paradigm of smart vehicles is rapidly transitioning from "passive response tools" to "proactive cognitive partners," integrating sensor data, user habits, and contextual needs to anticipate and provide services [5]