Future Automotive Computing Architectures

Price: Starting at USD 4,500
Publish Date: 05 May 2021
Code: AN-5402
Research Type: Research Report
Future Automotive Computing Architectures
RELATED SERVICE: Smart Mobility & Automotive
Actionable Benefits

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

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

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?

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