China Automotive Multimodal Interaction Development Research Report, 2025
Research on Automotive Multimodal Interaction: The Interaction Evolution of L1~L4 Cockpits
ResearchInChina has released the "China Automotive Multimodal Interaction Development Research Report, 2025". This report comprehensively sorts out the installation of Interaction Modalities in automotive cockpits, multimodal interaction patents, mainstream cockpit interaction modes, application of interaction modes in key vehicle models launched in 2025, cockpit interaction solutions of automakers/suppliers, and integration trends of multimodal interaction.
I. Closed-Loop Evolution of Multimodal Interaction: Progressive Evolution of L1~L4 Intelligent Cockpits
According to the "White Paper on Automotive Intelligent Cockpit Levels and Comprehensive Evaluation" jointly released by the China Society of Automotive Engineers (China-SAE), five levels of intelligent cockpits are defined: L0-L4.
As a key driver for cockpit intelligence, multimodal interaction capability relies on the collaboration of AI large models and multiple hardware to achieve the fusion processing of multi-source interaction data. On this basis, it accurately understands the intentions of drivers and passengers and provides scenario-based feedback, ultimately achieving natural, safe, and personalized human-machine interaction. Currently, the automotive intelligent cockpit industry is generally in the L2 stage, with some leading manufacturers exploring and moving towards the L3.
The core feature of L2 intelligent cockpits is "strong perception, weak cognition". In the L2 stage, the multimodal interaction function of cockpits achieves signal-level fusion. Based on multimodal large model technology, it can "understand users' ambiguous intentions" and "simultaneously process multiple commands" to execute users' immediate and explicit commands. At present, most mass-produced intelligent cockpits can enable this.
In the case of Li i6, it is equipped with MindGPT-4o, the latest multimodal model which boasts understanding and response capabilities with ultra-long memory and ultra-low latency, and features more natural language generation. It supports multimodal "see and speak" (voice + vision fusion search: allowing illiterate children to select the cartoons they want to watch by describing the content on the video cover); multimodal referential interaction (voice + gesture: ① Voice reference to objects: while issuing commands, extend the index finger: pointing left can control the window and complete vehicle control. ② Voice reference to personnel: passengers in the same row can achieve voice control over designated personnel through gesture and voice coordination, e.g., pointing right and saying "Turn on the seat heating for him").
The core feature of L3 intelligent cockpits is "strong perception, strong cognition". In the L3 stage, the multimodal interaction function of cockpits achieves cognitive-level fusion. Relying on large model capabilities, the cockpit system can comprehensively understand the complete current scenario and actively initiate reasonable services or suggestions without the user issuing explicit commands.
The core feature of L4 intelligent cockpits is "full-domain cognition and autonomous evolution", creating a "full-domain intelligent manager" for users. In the L4 stage, the application of intelligent cockpits will go far beyond the tool attribute and become a "digital twin partner" that can predict users' unspoken needs, have shared memories, and dispatch all resources for users. Its core experience is: before the user clearly perceives or expresses the need, the system has completed prediction and planning and entered the execution state.
II. Multimodal AI Agent: Understand What You Need and Predict What You Think
AI Agent can be regarded as the core execution unit and key technical architecture for the specific implementation of functions in the evolution of intelligent cockpits from L2 to L4. By integrating voice, vision, touch and situational information, AI Agent can not only "understand" commands, but also "see" the environment and "perceive" the state, thereby integrating the original discrete cockpit functions into a coherent, active and personalized service process.
Agent applications under L2 can be regarded as "enhanced command execution", which is the ultimate extension of L2 cockpit interaction capabilities. Based on large model technology, the cockpit system decomposes a user's complex command into multiple steps and then calls different Agent tools to execute them. For example, a passenger says: "I'm tired, help me buy a cup of coffee." The large model of the L2 cockpit system will understand this complex command and then call in sequence:
1.Voice Agent: Parse user needs in real time;
2.Food Ordering Agent: Recommend the best options according to user preferences, real-time location, and restaurant business status;
3.Payment Agent: Automatically complete unconscious payment;
4.Delivery Agent: Dynamically plan the food delivery time combined with vehicle navigation data (e.g., "food arrives when the car arrives", ensuring that the food is delivered synchronously when the user reaches the destination).
Currently, Agent applications are essentially responses and executions to a user's explicit and complex commands. The cockpit system does not do anything "actively", and it just "completes the tasks assigned by the user" more intelligently.
Case (1): IM Motors released the "IM AIOS Ecological Cockpit" jointly developed with Banma Zhixing. This cockpit is the first to implement Alibaba's ecosystem services in the form of AI Agent, creating a "No Touch & No App" human-vehicle interaction mode. The "AI Food Ordering Agent" and "AI Ticketing Agent" functions launched by the IM AIOS Ecological Cockpit allow users to complete food selection/ticketing and payment only through voice interaction without needing manual operation.
Case (2): On August 4, 2025, Denza officially launched the "Car Life Agent" intelligent service system at its brand press conference, which is first equipped on two flagship models, Denza Z9 and Z9GT. The "Car Life Agent" supports voice food ordering and enables payment by face with face recognition technology. After completing the order, the system will automatically plan the navigation route, forming a seamless experience of "demand-service-closed loop".
In the next level of intelligent cockpits, Agent applications will change from "you say, I do" to "I watch, I guess, I suggest, let's do it together". Users do not need to issue any explicit commands. They just sigh and rub their temples, and the system can comprehensively judge data from "camera" (tired micro-expressions), "biological sensors" (heart rate changes), "navigation data" (continuous driving for 2 hours), and "time" (3 pm (afternoon sleepiness period)) via the large model to know that "the user is in the tired period of long-distance driving and has the need to rest and refresh". Based on this, the system will take the initiative to initiate interaction: "You seem to need a rest. There is a service zone* kilometers ahead with your favorite ** coffee. Do you need me to turn on the navigation? At the same time, I can play refreshing music for you." After the user agrees, the system then calls navigation, entertainment and other Agent tools.
Automotive AIOS Research Report, 2026
Automotive AIOS Research: Mass Production Solutions Are Implemented
Mass Production Solutions Are Implemented on A Small Scale.
In 2026, AIOS starts small-scale implementation, helping to improve v...
Automotive Telematics Service Provider (TSP) Research Report, 2026
TSP Research: Leading providers collectively turn to AI agents to provide all-scenario active services
Telematics Service Providers (TSPs) are the core hub of the telematics industry chain, connectin...
Automotive Smart Interior Research Report, 2026
Smart Interior Research: As Technologies like Interactive Starlight Headliner, Hidden Display and Surface Projection Are Launched, Automotive Interiors Become Ever More Intelligent
The Automotive Sma...
Research Report on AI Applications in Cockpits, 2026
AI Application in Cockpits: AI Services Become More Comprehensive, Convenient, and Refined.
In the first half of 2026, cockpit AI functions underwent initial upgrades across multiple dimensions, inc...
Software-Defined Vehicles in 2026: OEM Software Development and Supply Chain Deployment Strategy Research Report
Research on OEMs’ Software Strategies: R&D Focus, Development Strategies and Supplier Building Models of 30 OEMs
In this paper, we adopt a research framework covering 13 subsystems and 48 sub-di...
Passenger Car Chassis Domain Control and Chassis Cross-Domain Integration Research Report, 2026
Chassis Control Research: Mass Production of Full Chassis-by-Wire Solutions Starts
1. A Cluster of Full Chassis-by-Wire Solutions Make Their Debut, and EMB Enters Mass Production and Adoption for the...
Central Domain Control (Powertrain, Chassis, Body) and Motion Controller Research Report, 2026
Central Domain Control and Motion Control Research: XYZ Coordinated Control and Full X-by-Wire Actuation System
With the gradual penetration of L3+ autonomous driving, the chassis control system is ...
48V Low-voltage Power Distribution Network (PDN) Architecture and Supply Chain Panorama Research Report, 2026
Research on 48V Low-Voltage Power Distribution Network （PDN): An Active 48V Supply Chain, with Priority Deployment in High-Power Scenarios Such as Steer-by-Wire Chassis
The automotive 48V low-voltage...
AI-Defined Vehicle (AIDV) OEMs' Deployment Strategies Research Report, 2026
AIDV Research: Deployment Strategies of 22 OEMs
The AI-Defined Vehicle (AIDV) OEMs' Deployment Strategies Research Report, 2026, released by ResearchInChina, analyzes the AI deployment strategies of ...
OEMs’ Passenger Car Model Planning Research Report, 2026
Vehicle Model Planning Research: Chinese OEMs Launch Sub-Brands Intensively, While Multinational OEMs Apply the Brakes to Electrification Strategies
ResearchInChina released the OEMs’ Passenger Car M...
Autonomous Driving Simulation and World Model Research Report, 2026
Autonomous driving simulation research: "Simulation test + world model"-driven test system has become R&D infrastructure.
The "Autonomous Driving Simulation and World Model Research Report, 2026"...
Cockpit-Driving Integration Central Domain Controller SoC and AI Supercomputing Architecture Research Report, 2026
Cockpit-Driving integration and AI supercomputing research: The One Chip solution is rapidly installed in vehicles, and AI supercomputing architectures are moving towards full-domain integration.
AI ...
Intelligent Driving End-to-End Large Model Research Report, 2026
Research on Intelligent Driving Large Models: A Critical Period for Technological Competition and Paradigm Integration
As autonomous driving technology rapidly iterates from L2 to L3?L4, intelligent...
Automotive Digital Key Industry Trend Report, 2026
Digital Key Research: Automotive BLE, UWB and SLE Hardware Layout
The Automotive Digital Key Industry Trend Report, 2026, released by ResearchInChina, analyzes and predicts the digital key market, co...
Monthly Report on Automotive New Technology (May 2026)
UHD gaze technology, full-color LiDAR, UWB, etc. promote the upgrade of intelligent driving perception capabilities
This report is published once a month and is available for annual subscription.The...
In-Cabin Monitoring Systems (DMS, OMS, etc.) Research Report, 2026
In-Cabin Monitoring System Research: DMS to Become Mandatory in 2027, Expected to be Installed in Over 14 Million Vehicles
ResearchInChina released the In-Cabin Monitoring Systems (DMS, OMS, etc.) Re...
Automotive Service-Oriented Architecture (SOA) and Cross-Domain Middleware Industry Report, 2026
Research on automotive SOA and cross-domain middleware: The era of AI atomic services and AI cross-domain fusion agents is coming.
Automotive SOA evolves towards AI + full SOA servitization Driv...
Automotive Display, Center Console and Cluster Industry Report, 2026
Automotive Display Research: Multi-Screen Application Slows Down, While OLED and MiniLED Are Introduced in Vehicles Quickly
In 2026, automotive displays will no longer excessively pursue the number a...