汽車多模式互動開發市場機會、成長動力、產業趨勢分析及 2025 - 2034 年預測

2024 年，全球汽車多模態互動開發市場規模達 28 億美元，預計到 2034 年將以 21% 的複合年成長率成長，達到 184 億美元。這得益於下一代汽車對智慧用戶介面的強勁需求以及互聯出行解決方案的廣泛應用。隨著汽車創新的加速，多模式互動正成為車載技術的核心，而人機之間的無縫通訊定義了未來的出行方式。對個人化、增強安全性和直覺控制的日益成長的需求正在重塑駕駛員與車輛的互動方式。人工智慧、先進的感測器整合和即時資料處理正在融合，以創建高度自適應的車載環境。隨著自動駕駛、智慧城市生態系統和數位互聯的轉變，汽車製造商競相嵌入能夠提供自然、反應迅速的使用者體驗的系統。全球各地的汽車製造商和技術供應商都在大力投資研發，以完善人機協同，確保車輛不僅能準確回應，還能預測駕駛者的需求。多模式互動——涵蓋語音、觸摸、手勢和情緒檢測——將大規模重新定義駕駛的便利性和安全性。

在全球範圍內，出行計畫和數位轉型專案正在推動智慧交通基礎設施的投資，旨在降低駕駛複雜性。各國政府正大力支持人機介面 (HMI) 技術的進步，以提升交通管理、安全性和駕駛滿意度。語音指令、手勢辨識和臉部認證等非接觸式系統日益普及，這正在徹底改變車載體驗。汽車製造商正在迅速採用能夠理解駕駛員行為、環境和情緒的自適應系統，並將多模式技術整合到自動駕駛和半自動駕駛平台中。亞洲正將自己定位為強大的催化劑，為在不斷擴張的市場中部署下一代互動出行解決方案提供監管激勵和政策支援。

以組件計算，軟體平台細分市場在2024年佔據47.4%的佔有率，預計到2034年將以21.8%的複合年成長率成長。人工智慧功能日益複雜，推動了對高階演算法、語音辨識工具和情境感知介面的需求。軟體平台是多模式系統的大腦，支援跨通路通訊、無線更新，並支援高度客製化的駕駛環境。城市地區和互聯出行生態系統正迎來旨在建立可擴展智慧互動框架的投資激增。

按車型分類，乘用車在2024年佔據市場主導地位，市佔率達76.4%。這得益於產量的提升、人機介面（HMI）系統的強勢整合，以及消費者對高階科技駕駛體驗日益成長的需求。電動車的蓬勃發展以及高級駕駛輔助系統 (ADAS) 的普及，正推動著汽車製造商整合多模式解決方案，以提升舒適性、安全性和直覺式操控性。

2024年，美國汽車多模態互動開發市場佔63%的市場佔有率，貢獻了7.934億美元的市場規模。這一成長得益於美國先進的汽車研發現狀系統、對自動駕駛汽車專案的強勁投資，以及科技公司和汽車製造商之間的深度合作。在聯邦政府和私人資金的支持下，美國各地城市正積極地成為尖端人機互動技術的實際測試平台。

引領市場的主要參與者包括華為、地平線、德賽西威、Cerence、博泰、百度、騰訊、安波福、科大訊飛和大陸集團。各公司正透過策略合作夥伴關係、與人工智慧開發商成立合資企業、加強研發力度以及開發自主研發的人工智慧平台來鞏固其市場地位。對區域擴張、使用者體驗在地化以及雲端智慧整合的重視，持續推動整個領域的創新。

目錄

第1章：方法論與範圍

第2章：執行摘要

第3章：行業洞察

• 產業生態系統分析
• 供應商格局
  • 零件製造商
  • 技術提供者
  • 軟體開發者
  • 最終用途
• 川普政府關稅的影響
  • 貿易影響
    • 貿易量中斷
    • 報復措施
  • 對產業的影響
    • 供應方影響（原料）
      • 主要材料價格波動
      • 供應鏈重組
      • 生產成本影響
    • 需求面影響（客戶成本）
      • 價格傳導至終端市場
      • 市佔率動態
      • 消費者反應模式
  • 受影響的主要公司
  • 策略產業反應
    • 供應鏈重組
    • 定價和產品策略
    • 政策參與
  • 展望與未來考慮
• 利潤率分析
• 技術與創新格局
• 專利分析
• 重要新聞和舉措
• 監管格局
• 衝擊力
  • 成長動力
    • 自動駕駛和半自動駕駛汽車的興起
    • 越來越關注車載安全（DMS、ADAS）
    • OEM和一級供應商對智慧座艙系統的投資
    • 持續的技術進步
  • 產業陷阱與挑戰
    • 開發和整合成本高
    • 使用者體驗設計的複雜性
• 成長潛力分析
• 波特的分析
• PESTEL分析

第4章：競爭格局

• 介紹
• 公司市佔率分析
• 競爭定位矩陣
• 戰略展望矩陣

第5章：市場估計與預測：按組件，2021 - 2034 年

• 主要趨勢
• 硬體
• 軟體
• 服務

第6章：市場估計與預測：依車型，2021 - 2034 年

• 主要趨勢
• 搭乘用車
  • 掀背車
  • 轎車
  • 越野車
• 商業的

第7章：市場估計與預測：依互動，2021 - 2034 年

• 主要趨勢
• 語音辨識
• 手勢識別
• 臉部辨識
• 觸控式介面
• 其他

第8章：市場估計與預測：按地區，2021 - 2034 年

• 主要趨勢
• 北美洲
  • 美國
  • 加拿大
• 歐洲
  • 英國
  • 德國
  • 法國
  • 義大利
  • 西班牙
  • 俄羅斯
  • 北歐人
• 亞太地區
  • 中國
  • 印度
  • 日本
  • 韓國
  • 澳新銀行
  • 東南亞
• 拉丁美洲
  • 巴西
  • 墨西哥
  • 阿根廷
• MEA
  • 阿拉伯聯合大公國
  • 沙烏地阿拉伯
  • 南非

第9章：公司簡介

• ADAYO
• AISpeech
• Aptiv
• ArcSoft Technology
• Baidu
• Banma Network
• Cerence
• Cipia Vision
• Continental
• Desay SV
• Hikvision
• Horizon Robotics
• Huawei
• iFlytek
• Joyson Electronics
• Shenzhen Minieye Intelligent Technology (MINIEYE)
• Shanghai PATEO Electronic Equipment Manufacturing
• SenseTime
• Tencent
• ThunderSoft

The Global Automotive Multimodal Interaction Development Market was valued at USD 2.8 billion in 2024 and is estimated to grow at a CAGR of 21% to reach USD 18.4 billion by 2034, driven by the surging demand for intelligent user interfaces in next-gen vehicles and the widespread adoption of connected mobility solutions. As automotive innovation accelerates, multimodal interaction is becoming the centerpiece of in-vehicle technology, where seamless communication between humans and machines defines the future of mobility. The growing need for personalization, enhanced safety, and intuitive control is reshaping how drivers interact with vehicles. Artificial intelligence, advanced sensor integration, and real-time data processing are all converging to create highly adaptive in-vehicle environments. With the shift toward autonomous driving, smart city ecosystems, and digital connectivity, automakers are racing to embed systems that deliver a natural, responsive user experience. Around the globe, automotive manufacturers and tech providers are investing heavily in R&D to refine human-machine synergy, ensuring vehicles not only respond accurately but also anticipate driver needs. Multimodal interaction-spanning voice, touch, gesture, and emotion detection-is poised to redefine driving convenience and safety at scale.

Globally, mobility initiatives and digital transformation programs are pushing investments in smart transport infrastructure aimed at reducing driving complexities. Governments are endorsing advancements in human-machine interface (HMI) technologies to boost traffic management, safety, and driver satisfaction. The growing transition toward touchless systems, including voice commands, gesture recognition, and facial authentication, is transforming in-vehicle experiences. Automakers are rapidly embracing adaptive systems that understand driver behavior, environment, and emotions, integrating multimodal technologies into both autonomous and semi-autonomous platforms. Asia is positioning itself as a strong catalyst, offering regulatory incentives and policy support for deploying next-generation interactive mobility solutions across expanding markets.

Based on components, the software platforms segment held a 47.4% share in 2024 and is anticipated to grow at a CAGR of 21.8% through 2034. The rising complexity of AI-powered features is fueling the demand for advanced algorithms, speech recognition tools, and context-aware interfaces. Software platforms serve as the brain of multimodal systems, enabling cross-channel communication, delivering over-the-air updates, and supporting highly customized driving environments. Urban areas and connected mobility ecosystems are seeing a surge in investments aimed at building scalable, intelligent interaction frameworks.

By vehicle type, passenger vehicles dominated the market in 2024 with a 76.4% share, propelled by rising production rates, strong integration of HMI systems, and escalating consumer demand for sophisticated, tech-driven driving experiences. The boom in electric vehicles and the adoption of advanced driver-assistance systems (ADAS) are driving OEMs to integrate multimodal solutions that enhance comfort, safety, and intuitive control.

The United States Automotive Multimodal Interaction Development Market held a 63% share in 2024, contributing USD 793.4 million. This growth stems from the country's advanced automotive R&D ecosystem, robust investments in autonomous vehicle initiatives, and deep collaboration between tech firms and automakers. Cities across the U.S. are actively serving as real-world test beds for cutting-edge HMI technologies backed by federal initiatives and private funding.

Key players leading the market include Huawei, Horizon Robotics, Desay SV, Cerence, PATEO, Baidu, Tencent, Aptiv, iFlytek, and Continental. Companies are strengthening their market presence through strategic partnerships, joint ventures with AI developers, expanded R&D efforts, and proprietary AI platform developments. Emphasis on regional expansion, localization of user experiences, and integration of cloud-based intelligence continues to drive innovation across the space.

Table of Contents

Chapter 1 Methodology & Scope

• 1.1 Research design
  • 1.1.1 Research approach
  • 1.1.2 Data collection methods
• 1.2 Base estimates and calculations
  • 1.2.1 Base year calculation
  • 1.2.2 Key trends for market estimates
• 1.3 Forecast model
• 1.4 Primary research & validation
  • 1.4.1 Primary sources
  • 1.4.2 Data mining sources
• 1.5 Market definitions

Chapter 2 Executive Summary

• 2.1 Industry 360⁰ synopsis, 2021 - 2034

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Supplier landscape
  • 3.2.1 Component manufacturers
  • 3.2.2 Technology providers
  • 3.2.3 Software developers
  • 3.2.4 End use
• 3.3 Impact of Trump administration tariffs
  • 3.3.1 Trade impact
    • 3.3.1.1 Trade volume disruptions
    • 3.3.1.2 Retaliatory measures
  • 3.3.2 Impact on industry
    • 3.3.2.1 Supply-side impact (raw materials)
      • 3.3.2.1.1 Price volatility in key materials
      • 3.3.2.1.2 Supply chain restructuring
      • 3.3.2.1.3 Production cost implications
    • 3.3.2.2 Demand-side impact (Cost to customers)
      • 3.3.2.2.1 Price transmission to end markets
      • 3.3.2.2.2 Market share dynamics
      • 3.3.2.2.3 Consumer response patterns
  • 3.3.3 Key companies impacted
  • 3.3.4 Strategic industry responses
    • 3.3.4.1 Supply chain reconfiguration
    • 3.3.4.2 Pricing and product strategies
    • 3.3.4.3 Policy engagement
  • 3.3.5 Outlook & future considerations
• 3.4 Profit margin analysis
• 3.5 Technology & innovation landscape
• 3.6 Patent analysis
• 3.7 Key news & initiatives
• 3.8 Regulatory landscape
• 3.9 Impact forces
  • 3.9.1 Growth drivers
    • 3.9.1.1 Rise of autonomous and semi-autonomous vehicles
    • 3.9.1.2 Increasing focus on in-vehicle safety (DMS, ADAS)
    • 3.9.1.3 OEM and Tier-1 investment in intelligent cockpit systems
    • 3.9.1.4 Ongoing technological advancements
  • 3.9.2 Industry pitfalls & challenges
    • 3.9.2.1 High development & integration cost
    • 3.9.2.2 Complexity in user experience design
• 3.10 Growth potential analysis
• 3.11 Porter's analysis
• 3.12 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

• 4.1 Introduction
• 4.2 Company market share analysis
• 4.3 Competitive positioning matrix
• 4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2034 ($Bn)

• 5.1 Key trends
• 5.2 Hardware
• 5.3 Software
• 5.4 Services

Chapter 6 Market Estimates & Forecast, By Vehicle, 2021 - 2034 ($Bn)

• 6.1 Key trends
• 6.2 Passenger cars
  • 6.2.1 Hatchback
  • 6.2.2 Sedan
  • 6.2.3 SUV
• 6.3 Commercial

Chapter 7 Market Estimates & Forecast, By Interaction, 2021 - 2034 ($Bn)

• 7.1 Key trends
• 7.2 Speech recognition
• 7.3 Gesture recognition
• 7.4 Facial recognition
• 7.5 Touch-based interfaces
• 7.6 Others

Chapter 8 Market Estimates & Forecast, By Region, 2021 - 2034 ($Bn)

• 8.1 Key trends
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
• 8.3 Europe
  • 8.3.1 UK
  • 8.3.2 Germany
  • 8.3.3 France
  • 8.3.4 Italy
  • 8.3.5 Spain
  • 8.3.6 Russia
  • 8.3.7 Nordics
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 India
  • 8.4.3 Japan
  • 8.4.4 South Korea
  • 8.4.5 ANZ
  • 8.4.6 Southeast Asia
• 8.5 Latin America
  • 8.5.1 Brazil
  • 8.5.2 Mexico
  • 8.5.3 Argentina
• 8.6 MEA
  • 8.6.1 UAE
  • 8.6.2 Saudi Arabia
  • 8.6.3 South Africa

Chapter 9 Company Profiles

• 9.1 ADAYO
• 9.2 AISpeech
• 9.3 Aptiv
• 9.4 ArcSoft Technology
• 9.5 Baidu
• 9.6 Banma Network
• 9.7 Cerence
• 9.8 Cipia Vision
• 9.9 Continental
• 9.10 Desay SV
• 9.11 Hikvision
• 9.12 Horizon Robotics
• 9.13 Huawei
• 9.14 iFlytek
• 9.15 Joyson Electronics
• 9.16 Shenzhen Minieye Intelligent Technology (MINIEYE)
• 9.17 Shanghai PATEO Electronic Equipment Manufacturing
• 9.18 SenseTime
• 9.19 Tencent
• 9.20 ThunderSoft