J.D. Power研究：智能体验转向实用主义

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]