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Future Automotive Computing Architectures
Future Automotive Computing Architectures
Price: Starting at USD 3,000
Publish Date: 05 May 2021
Code: AN-5402
Research Type: Research Report
Pages: 49
Purchase
RELATED SERVICE:
Smart Mobility & Automotive
Report Detail
Table of Contents
Companies Mentioned
Related Research
Related Insights
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Table of Contents
Companies Mentioned
Related Research
Related Insights
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Actionable Benefits
Build or future-proof hardware and software solution strategies based on the expected evolution of ADAS and AV architecture.
Understand how to deploy and monetize from advanced AV functionalities within the current regulation with L2+ vehicles.
Assess the semiconductor components (CPU, GPU, FPGA, and ASIC NNA) and functional OTA software updates shipments and revenue opportunities until 2030.
Use the detailed assessment of key players, market share, and OEM releases as input for product planning.
Critical Questions Answered
How the hardware requirements differ in the different automated driving stages, from driver assistance to fully autonomous systems?
How will the transition from legacy to AV vehicle architecture take place?
What are the AI edge processing and networking requirements in L2+ and fully autonomous systems?
What are the semiconductor components (CPU, GPU, FPGA, and ASIC NNA) shipments and revenue opportunities for passenger vehicles and robotaxis?
What is the functional OTA software updates market opportunity per SAE level?
Research Highlights
In-depth analysis of the vehicle architecture evolution, from SAE Level 1 to 5.
A detailed assessment of the ADAS and AV hardware key players, partnerships, and carmakers releases.
Detailed hardware components forecasts per region and SAE level for passenger vehicles and robotaxis.
Functional OTA software update forecasts by SAE Level.
Who Should Read This?
Decision-makers and OEMs, and Tier 1s responsible for ADAS and Autonomous Technology deployments.
Product managers in silicon companies with dedicated automotive-grade SoCs.
Automotive product managers at networking semiconductor vendors.
Table of Contents
1. EXECUTIVE SUMMARY
1.1. Introduction
1.2. Transition from Legacy Platforms
1.3. Heterogeneous ADAS and AV Architecture
1.4. Convergence between ADAS and IVI functionalities
1.5. Open versus Turnkey Platforms
1.6. From Robotaxis to Passenger Vehicles
2. L2+ ADVANCED PARTIAL AUTOMATION WITHIN THE CURRENT REGULATION
2.1. Architecture Implications
2.2. Software development
2.3. Carmakers Using L2+ Capable Centralized Architecture
2.4. Concluding Remarks
3. OTA UPDATES
3.1. Archtecture Implications
3.2. Concluding Remarks
4. AI AND ML EDGE PROCESSING
4.1. CPU
4.2. GPUs
4.3. FPGA
4.4. ASIC NNA
4.5. Heterogeneous Compute
4.6. Vendors
5. NETWORKING
5.1. Ethernet
5.2. HDBaseT
6. ROBOTAXIS AND LONG TERM ARCHITECTURE CONSIDERATIONS
6.1. Architecture Implications
6.2. Concluding Remarks
7. EXPECTED ARCHITECTURE EVOLUTION
7.1. ADAS (L1 to L2)
7.2. L2+
7.3. L4 and L5
8. OTHER TRENDS AFFECTING ADAS/AD ARCHITECTURES
8.1. Electric Vehicles
8.2. Cockpit Domain Controller
9. ADAS/AV PLATFORM VENDOR PROFILES
9.1. Mobileye
9.2. NVIDIA
9.3. NXP
9.4. Qualcomm
9.5. Xilinx
9.6. Texas Instrument (TI)
10. FORECASTS
10.1. Passenger Vehicles
10.2. Robotaxis
10.3. Total Hardware Revenue: Passenger Vehicles and Robotaxis
Companies Mentioned
Ambarella, Inc.
Audi
Cadillac
Ford Motor Company
Geely Auto Group
Hailo
Harman
Imagination Technologies
Jam
Marvell
Mercedes-Benz
Mobileye
Motional
NIO
NVIDIA
NXP Semiconductors
Qualcomm Inc
Tesla
Texas Instruments Inc
Volvo
Xilinx, Inc.
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