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Last Updated: Apr 25, 2025 | Study Period: 2024-2030
Individual car parts need to communicate with one another more and more as we move into higher-level autonomous vehicles.
True self-driving cars need to be able to brake, slow down, or detect threats from the outside. They also need to be able to connect those functions to make big, complicated decisions like when, how, and if they should slow down when they see a potential danger on the road and then start those functions in response.
Software functionality in modern automobiles has significantly increased over the past few years. Development and configuration become more difficult as a direct result of this expanding functionality. The number of software products will continue to rise, according to current research.
In addition, advanced driver assistance systems (ADAS) and autonomous functionality, such as driving or parking that is completely and completely automated, will be made available. System complexity increases as a result of the fact that many of these new functions require access to various communication domains within the vehicle.
The software architecture that has become the industry standard in the automotive industry, AUTOSAR, does not provide any methods for dealing with new challenges or reducing this level of complexity. In the RACE project, a solution to these changing systems is developed. This chapter introduces a centralized platform computer (CPC) based on the tried-and-true method used in automation and avionics.
The CPC provides interfaces for test and verification as well as a dependable communication infrastructure to smart sensors and actuators, establishing a generic safety-critical execution environment for applications. Support for Plug & Play is made possible by a centralized platform, which also significantly simplifies the integration and verification of new applications.
The Global automotive centralized car computer market accounted for $XX Billion in 2023 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2024 to 2030.
Customers of today expect new features from their automobiles. They want new personalization and "infotainment" options, for instance, as well as advanced autonomous driving features. Additionally, they want to incorporate digital services into an ecosystem for automobiles that extends far beyond the typical automobile to a smartphone-like experience.
The software architecture and electronics of the vehicle need to be altered in order to transition from a conventional vehicle to an automotive ecosystem, also known as a mobile smartphone. That means moving away from using scattered, embedded electronic control units (ECUs) and moving toward a domain-focused system with central vehicle controllers.
This requires more sophisticated software, including the use of Ethernet and scaled connectivity, a software abstraction layer, and other features. In addition, it signifies a rise in the utilization of more advanced microprocessors as opposed to embedded microcontrollers in order to increase performance, decrease power consumption, and centralized control.
As a result, OEMs and suppliers must switch their R&D procedures and operating models from hardware engineering to software and technology-driven systems engineering. Over-the-air (OTA) updates to fix bugs, update software features, improve customer experiences, or sell new features that weren't available when the vehicle was first sold will be commonplace in this new setting throughout the vehicle's life cycle.
This necessitates the establishment of R&D steering strategies that link software and hardware development throughout the vehicle's life cycle, as well as a shift in OEM and supplier development patterns toward cyclical, more integrated patterns.
One of the most notable partnership acquisitions was between Bosch and Renesas Electronics. The two companies agreed to collaborate on the development of automotive central computers, which will be used in connected and automated vehicles.
The collaboration will enable the companies to develop a platform that can support various electronic components and systems, as well as improve safety and efficiency. In addition, the collaboration will also enable the companies to develop a centralized car computer that can be used in a variety of different vehicles.
One of the most recent partnerships is between Tesla and Google, who have teamed up to create an AI-enabled infotainment system for Tesla vehicles. The Google Assistant, integrated into the Tesla operating system, will allow drivers to access various services, such as navigation and music streaming, without ever taking their eyes off the road.
Toyota has also joined forces with Microsoft to create a cloud-based platform for its vehicles. The platform will provide Toyota customers with access to a variety of services, such as real-time vehicle diagnostics, predictive maintenance, and over-the-air software updates.
This system will also enable Toyota to better monitor and analyze the data generated by its vehicles in order to improve the overall driving experience.
Volkswagen has also been busy partnering with various companies to develop its own centralized car computer. The company has teamed up with Nvidia to use its AI-powered Drive IX platform in order to make its vehicles more intelligent.
The platform will allow Volkswagen to better analyze the data generated by its cars and use that information to provide personalized experiences to customers.
Ford has partnered with IBM to use its Watson AI technology in its vehicles. The AI-enabled system will enable Ford to better predict and analyze how its vehicles are used, as well as make recommendations for maintenance and repair.
The system will also allow Ford to personalize its services for each customer, such as offering customized music playlists or providing real-time traffic information.
Another major partnership acquisition in the automotive centralized car computer market is between Continental and Nvidia. The two companies have agreed to collaborate on the development of a high-performance, AI-enabled car computer.
The computer will have a powerful GPU and will be able to process vast amounts of data very quickly. It will be used in both connected and automated vehicles, and will enable faster decision making and better driving performance.
Autoliv and NXP Semiconductors have agreed to collaborate on the development of advanced automotive computing systems. The systems will enable the companies to develop a powerful and efficient car computer that can be used in a variety of different vehicles.
| Sl no | Topic |
| 1 | Market Segmentation |
| 2 | Scope of the report |
| 3 | Abbreviations |
| 4 | Research Methodology |
| 5 | Executive Summary |
| 6 | Introduction |
| 7 | Insights from Industry stakeholders |
| 8 | Cost breakdown of Product by sub-components and average profit margin |
| 9 | Disruptive innovation in the Industry |
| 10 | Technology trends in the Industry |
| 11 | Consumer trends in the industry |
| 12 | Recent Production Milestones |
| 13 | Component Manufacturing in US, EU and China |
| 14 | COVID-19 impact on overall market |
| 15 | COVID-19 impact on Production of components |
| 16 | COVID-19 impact on Point of sale |
| 17 | Market Segmentation, Dynamics and Forecast by Geography, 2024-2030 |
| 18 | Market Segmentation, Dynamics and Forecast by Product Type, 2024-2030 |
| 19 | Market Segmentation, Dynamics and Forecast by Application, 2024-2030 |
| 20 | Market Segmentation, Dynamics and Forecast by End use, 2024-2030 |
| 21 | Product installation rate by OEM, 2023 |
| 22 | Incline/Decline in Average B-2-B selling price in past 5 years |
| 23 | Competition from substitute products |
| 24 | Gross margin and average profitability of suppliers |
| 25 | New product development in past 12 months |
| 26 | M&A in past 12 months |
| 27 | Growth strategy of leading players |
| 28 | Market share of vendors, 2023 |
| 29 | Company Profiles |
| 30 | Unmet needs and opportunity for new suppliers |
| 31 | Conclusion |
| 32 | Appendix |
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