The automotive human-machine interfaces market size is expected to see rapid growth in the next few years. It will grow to $36.29 billion in 2028 at a compound annual growth rate (CAGR) of 11.7%. The growth in the forecast period can be attributed to energy-efficient vehicles, environmental sustainability focus, continuous evolution of smart cities, regulatory compliance and safety standards, ergonomics and design aesthetics.. Major trends in the forecast period include touchscreen displays and gesture recognition, voice-activated controls and natural language processing, personalization and user profiles, connected car features and cloud-based services, haptic feedback and tactile controls, focus on driver monitoring systems (dms), artificial intelligence (ai) integration.
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Segmentation & Regional Insights
The automotive human-machine interfaces market covered in this report is segmented –
1) By Product: Central Display, Voice Control System, Steering Mounted Control, Instrument Cluster, Head-Up Display, Rear Seat Entertainment, Multifunction Switch
2) By Technology: Visual Interface, Acoustic Interface, Other Technologies
3) By Access: Standard HMI, Multimodal HMI
4) By Function type: Primary, Secondary
5) By End User: Passenger Vehicle, Commercial Vehicle
North America was the largest region in the automotive human-machine interfaces market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the automotive human-machine interfaces market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Major Driver Impacting Market Growth
The increasing trend toward connected and autonomous vehicles is driving the automotive human-machine interface market. An autonomous vehicle is capable of operating on its own without the assistance of a human driver, and a connected car has wireless network connectivity capabilities to connect to adjacent devices. The automotive human-machine interface systems are widely used in these vehicles to provide users with a more interactive and efficient experience. For instance, according to TechCrunch, a US-based online newspaper focusing on high tech and startup companies, in 2022, there were over 1,400 self-driving cars in the US which are being tested by over 80 companies. Furthermore, according to Policy Advice, a US-based website devoted to helping everyday people make, save, and grow money, in the next two decades, 55% of small enterprises anticipate having a fully autonomous fleet. Therefore, the rise in autonomous and connected vehicles will propel the automotive human-machine interface market.
Key Industry Players
Major companies operating in the automotive human-machine interfaces market report are Continental AG, Visteon Corporation, Valeo India Pvt. Ltd., Panasonic Corporation, Denso Corporation, YAZAKI Corporation, Harman International, Robert Bosch GmbH, Clarion Company Limited, Alpine Electronics Inc., Magneti Marelli SPA, Nuance Communications Inc, Socionext Inc., Tata Group, Synaptics Incorporated, Nippon Seiki Company Limited, Luxoft Holding Inc., Aptiv PLC, Delphi Technologies PLC, Elektrobit Automotive GmbH, Valeo S.A., EAO AG, Nuance Communications Inc., Alpine Electronics Inc., Altran Technologies SA, Pioneer Corporation, Garmin Ltd., TomTom International BV, Yazaki Corporation, Faurecia S.A.
The automotive human-machine interfaces market report table of contents includes:
1. Executive Summary
2. Automotive Human-Machine Interfaces Market Characteristics
3. Automotive Human-Machine Interfaces Market Trends And Strategies
4. Automotive Human-Machine Interfaces Market – Macro Economic Scenario
5. Global Automotive Human-Machine Interfaces Market Size and Growth
……………….
31. Global Automotive Human-Machine Interfaces Market Competitive Benchmarking
32. Global Automotive Human-Machine Interfaces Market Competitive Dashboard
33. Key Mergers And Acquisitions In The Automotive Human-Machine Interfaces Market
34. Automotive Human-Machine Interfaces Market Future Outlook and Potential Analysis
35. Appendix
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