SDVs, Connected and Autonomous Vehicles (CAVs), In-Car AI Assistants, V2X, Autonomy as a Service, Connected Vehicles, E/E Architecture, Intelligent Transportation Systems (ITS-G5), DSRC, C-V2X, Features as a Service, ADAS

 

The automotive industry is undergoing a foundational shift toward software-defined vehicles (SDVs), where functionality, value, and user experience are increasingly governed by software rather than hardware. IDTechEx's report, "Software-Defined Vehicles, Connected Cars, and AI in Cars 2026-2036: Markets, Trends, and Forecasts", offers a comprehensive analysis of this transformation, covering the evolution of in-vehicle electrical/electronic (E/E) architecture, connectivity platforms, feature monetization models, and long-term market forecasts. According to IDTechEx forecasts, Central Compute and quasi-zonal SDV platforms are set to generate around US$755 billion in hardware revenue by 2029, becoming the key source of value uplift for OEMs. SDV feature-related revenue is expected to grow at a 30-34% CAGR through 2035, driven by connectivity and autonomy-based service monetization.

 

 

 

Modern SDVs are defined by their ability to decouple hardware from software, supported by centralized computing platforms and over-the-air (OTA) update capabilities. This report classifies SDVs across five levels, from gateway-centric and domain-based systems to fully software-centric vehicles and provides a detailed breakdown of the key enabling components, including high-performance compute (HPC), zonal controllers, and service-oriented middleware.

 

The report analyzes flagship platforms such as BMW's Neue Klasse, Tesla's FSD-capable models, and emerging Chinese SDVs from BYD, NIO, and Li Auto. It also explains how these vehicles use technologies like TSN Ethernet, AI-enabled SoCs, and solid-state power distribution to reshape the EE landscape.

 

SDVs are not only a technical upgrade, they represent a shift in the business model. Automakers are increasingly embedding monetizable features in the vehicle, ranging from advanced driver assistance systems (ADAS) to infotainment, personalization, and even heating functions.

 

The report outlines how OEMs like BMW, Ford, and Mercedes-Benz are leveraging features-as-a-service (FaaS) and OTA updates to generate recurring revenue. It investigates subscription models, regional pricing strategies, and the impact of SDV features on customer retention and brand differentiation.

 

Case studies highlight real-world deployments, including BMW's Neue Klasse, and in-car payment platforms powered by Mastercard and JPMorgan Mobility Payments.

 

As vehicles become more autonomous and connected, V2X (Vehicle-to-Everything) technologies play an essential role in ensuring safety, coordination, and enhanced user experience. This report provides a deep dive into C-V2X, DSRC, and 5G-based communications, evaluating their performance, cost, and geographic adoption.

 

IDTechEx maps spectrum allocations and policy developments across key regions including China, the EU, the US, Japan, and South Korea. The report also profiles major V2X hardware providers and explains how onboard units (OBUs), roadside units (RSUs), and chipsets are integrated into SDV platforms.

 

The report also explores the integration of generative AI in SDVs, particularly in in-car assistants, personalized infotainment, and predictive diagnostics. With companies like Qualcomm, Nvidia, and Unity enabling on-device AI inference, new opportunities are emerging for OEMs to offer adaptive and immersive digital experiences.

 

Beyond voice control, the SDV cockpit is becoming a digital platform. Full-width screens, AI avatars, and customizable software skins are creating a new battleground for brand loyalty and user engagement.

 

This IDTechEx report provides 10-year market forecasts on the SDV market for the period 2026-2036, in both volume and market value. Forecasts include:

 

• Global SDV unit sales by architecture level (SDV-0 to SDV-5)
• Hardware revenue by SDV architecture, including central and zonal compute platforms
• Feature-related revenue growth driven by subscription and OTA models
• V2X radio access technology adoption by region
• V2V/V2I Vehicle Unit Sales Forecasting

Key Aspects

• Comparison of DSRC, ITS-G5, C-V2X, and 5G technologies
• Regional spectrum allocation and regulatory status
• In-depth review of SDV E/E architecture evolution and centralized computing trends
• Use cases for V2V and V2I in safety and sustainability
• Breakdown of hardware modules such as chipsets, onboard units, and roadside units

• Connectivity requirements by SAE Level (L2-L5)
• Mapping and localization technologies used in advanced ADAS and AV systems
• Teleoperation models and their relevance in early-stage autonomous deployments

• Global SDV sales forecast by level (SDV-0 to SDV-5), with Central Compute and Zonal Compute growth trajectories
• Hardware revenue forecast by SDV level, highlighting over US$1.57 trillion peak from SDV-3 by 2028
• Feature-related revenue forecast driven by subscriptions and over-the-air unlocks, reaching ~US$470B by 2035
• V2V/V2I forecast by region and radio access technology, with C-V2X adoption leading post-2025

1.1. What is a software-defined vehicle?

1.2. What's required for an SDV

1.3. Software-Defined Vehicle Level Guide

1.4. SDV Level Chart: Major OEMs compared

1.5. SDV Level Guide Explained

1.6. SDV feature layer

1.7. Mainstream OEMs and Representative Models/Platforms

1.8. SDV E/E Architecture - Microcontroller Unit

1.9. SDV E/E Architecture players

1.10. SDV Conclusions and Key Takeaways (1)

1.11. SDV Conclusions and Key Takeaways (2)

1.12. Over-the-Air updates and diagnostics

1.13. Software-Defined Vehicle Forecast (Units)

1.14. SDV Forecast (Hardware Revenue)

1.15. What is a Connected Vehicle?

1.16. Connected Vehicles Key Terminology

1.17. Radio Access Technologies Compared

1.18. The Connected Vehicle Supply Chain

1.19. V2X Chipsets - Comparison

1.20. Radio Access Technologies Compared

1.21. Radio Access Technologies Compared

1.22. Example V2V/V2I use cases summarised

1.23. V2X Regional Regulatory Status

1.24. V2V/V2I Uptake Forecasting

1.25. V2V/V2I Radio Access Technology Forecast

1.26. Why 5G Matters for Autonomy

1.27. Company Profiles

1.28. Access More With an IDTechEx Subscription

 

2.1.1. What is a software-defined vehicle?

2.1.2. Why is there this hype? (1)

2.1.3. Why is there this hype? (2)

2.1.4. Software-Defined Vehicle Level Guide

2.1.5. SDV Level Chart: Major OEMs compared

2.2. SDV Service and Applications

2.2.1. Connectivity as a Service

2.2.2. SDV for Insurance (Allianz)

2.2.3. In-vehicle payments

2.2.4. Infotainment hardware

2.2.5. Infotainment (1)

2.2.6. Infotainment (2)

2.2.7. Hardware as a Service (HaaS)

2.2.8. Over-the-Air updates

2.2.9. Over-the-Air diagnostics

2.2.10. Autonomy as a Service (AaaS)

2.2.11. Personalization

2.3. SDV Service and Applications Hardware

2.3.1. SDV Hardware Requirements

2.3.2. Communication

2.3.3. Compute

2.3.4. Screens to facilitate connected features (1)

2.3.5. Screens to facilitate connected features (2)

2.3.6. Automotive transparent antennas

2.3.7. Selling a Chinese SDV in Europe - BYD

2.4. SDV Service Software Case Study

2.4.1. Ford

2.4.2. MG (SAIC)

2.4.3. Volkswagen

2.4.4. BMW (1) - Connected Drive Portal

2.4.5. BMW (2) - SDV Monetization

2.4.6. BMW (3) - Connected Package

2.4.7. BMW (4) - International Strategy

2.4.8. SDV E/E Architecture Introduction

2.4.9. Smart Cockpit Software Architecture

2.4.10. Vehicle Control Software Architecture

2.5. SDV E/E Architecture

2.5.1. Paradigm Shift in Automotive E/E Architectures

2.5.2. SDV E/E Architecture players

2.5.3. Optical Fiber Emerges as a Successor to Traditional Ethernet

2.5.4. Intel

2.5.5. Qualcomm

2.5.6. Black sesame (1)

2.5.7. Black sesame (2)

2.5.8. Unity

2.6. Centralized Computing with Zonal Control

2.6.1. SDV E/E Architecture - OEM Level Zonal Control Architecture (1)

2.6.2. SDV E/E Architecture - OEM Level Zonal Control Architecture (2)

2.6.3. SDV E/E Architecture - Tier 1 Level Zonal Control Architecture (1)

2.6.4. SDV E/E Architecture - Tier 1 Level Zonal Control Architecture (2)

2.6.5. SDV E/E Architecture - Tier 1 Level Zonal Control Architecture (3)

2.7. MCU in Zonal Architecture

2.7.1. SDV E/E Architecture - Microcontroller Unit

2.7.2. Infineon - AURIX TC4x

2.7.3. Infineon - Flex Modular Zone

2.7.4. NXP: S32 CoreRide Platform

2.7.5. Renesas: RH850/U2x and Zone-ECU Virtualization Platform

2.7.6. STMicroelectronics: Stellar and STM32A

2.7.7. Intel: ACU U310

2.8. OEMs' in-house SDV E/E Architecture

2.8.1. Mainstream OEMs and Representative Models/Platforms

2.8.2. BMW --- Neue Klasse (1)

2.8.3. BMW --- Neue Klasse (2)

2.8.4. BMW --- Neue Klasse SDV platform in China (1)

2.8.5. BMW --- Neue Klasse SDV platform in China (2)

2.8.6. Tesla

2.8.7. VW.OS EEA

2.8.8. OPPO Volkswagen

2.8.9. Rivian Volkswagen

2.8.10. Toyota Arene OS

2.8.11. Stellantis

2.8.12. AWS SDV

2.8.13. Xpeng

2.8.14. Mercedes

2.9. Generative AI for SDVs

2.9.1. What is a Generative AI?

2.10. In-vehicle generative AI

2.10.1. Smart Cockpit

2.10.2. Spike the personal assistant (AWS & BMW)

2.10.3. A personalized digital assistant (AWS)

2.11. Generative AI for automakers

2.11.1. Generative AI for Automotive Design

2.11.2. Vizcom (powered by Nvidia)

2.11.3. Microsoft - AI for automotive

2.11.4. Microsoft - M365 Copilot

2.11.5. Digital Twins and Simulated Autonomy

2.11.6. Nvidia Digital Twins and Simulated Autonomy

2.11.7. SDV-related Regulations

2.12. Conclusion

2.12.1. SDV Conclusions and Key Takeaways (1)

2.12.2. SDV Conclusions and Key Takeaways (2)

 

3.1.1. V2X Acronyms

3.1.2. What is a Connected Vehicle?

3.1.3. Why V2X

3.1.4. Radio Access Technologies Compared (1)

3.1.5. Connected Vehicles Key Terminology

3.1.6. Radio Access Technologies Compared (2)

3.1.7. Radio Access Technologies Compared

3.1.8. Radio Access Technologies Compared

3.1.9. 3GPP 5G Interpretation

3.1.10. Policy Interpretation: Integrated Vehicle-Road-Cloud Development in China

3.1.11. 3GPP Automotive Roadmap

3.1.12. Regulatory Status: DSRC vs C-V2X (1)

3.1.13. Regulatory Status: DSRC vs C-V2X (2)

3.1.14. Regulatory Status: DSRC vs C-V2X (3)

3.1.15. V2X Low Latency (PC5) use cases

3.1.16. V2X High Data Rate (Uu) use cases

3.1.17. Connected Vehicle Cybersecurity

3.1.18. C-V2X roadmap (third edition)

3.2. V2V and V2I Use Cases for Safety and Sustainability

3.2.1. What is V2V and V2I?

3.2.2. Day 1/Day 2/Day 3

3.2.3. How V2V and V2I works:

3.2.4. V2X applications Launch Timeline and Standard

3.3. Current 'Day 1' V2V/V2I dependent use cases

3.3.1. V2V/V2I-required use cases (1)

3.3.2. V2V/V2I-required use cases (2)

3.3.3. V2V/V2I-required use cases (3)

3.3.4. V2V/V2I-required use cases (4)

3.4. Current use cases that benefit from V2V/V2I

3.4.1. V2V/V2I-beneficial use cases

3.4.2. V2V/V2I-beneficial use cases

3.4.3. Example V2V/V2I use cases summarised

3.5. Case Studies and the 5GAA

3.5.1. ZTE 5G and C-V2X use cases

3.5.2. 5G for Autonomous Vehicles: 5GAA

3.5.3. 5GAA C-V2X overview

3.5.4. Q&A with 5G Automotive Association (5GAA) director (1)

3.5.5. Q&A with 5G Automotive Association (5GAA) director (2)

3.5.6. Q&A with 5G Automotive Association (5GAA) director (3)

3.5.7. C-V2X: Automated valet parking in a 5G network (1)

3.5.8. C-V2X: Automated valet parking in a 5G network (2)

3.6. V2X ITS Hardware

3.6.1. V2X Hardware: What's in a V2X module

3.6.2. V2X Hardware: Key terms explained

3.6.3. Telematics Control Unit

3.6.4. The Connected Vehicle Supply Chain

3.6.5. V2V/V2I Supply Chain

3.6.6. V2X Chipsets - Comparison

3.6.7. V2X Chipsets: Qualcomm

3.6.8. V2X Chipsets: NXP & Huawei

3.6.9. V2X Chipsets: Autotalks

3.6.10. V2X Chipsets: Marvell and Morningcore

3.6.11. V2X Modules - Comparison

3.6.12. V2X Modules - Comparison (2)

3.6.13. V2X Modules - Comparison (3)

3.6.14. LG Innotek Modules

3.6.15. Alps Alpine Modules

3.6.16. Rolling Wireless Modules

3.6.17. V2X Hardware: RSUs

3.6.18. Murata Modules

3.6.19. Quectel Modules

3.6.20. Cohda Wireless Modules, OBUs, & RSUs

3.6.21. Commsignia Modules, OBUs, & RSUs

3.6.22. V2X Hardware: RSUs and OBUs

3.6.23. Black Sesame RSUs

3.6.24. Black Sesame RSUs

3.6.25. Siemens RSUs

3.6.26. Huawei RSUs

3.6.27. AI-enhanced roadside unit (RSU) for future mobility (2)

3.6.28. Intelligent RSU for C-V2X side link positioning

3.6.29. V2X Software

3.6.30. V2X micromobility solutions

3.6.31. Connected Vehicle Conclusion and Thoughts

4. AUTONOMOUS VEHICLE CONNECTIVITY

4.1.1. Why Automate Cars?

4.1.2. The Automation Levels in Detail

4.1.3. Functions of Autonomous Driving at Different Levels

4.1.4. Roadmap of Autonomous Driving Functions in Private Cars

4.1.5. Typical Sensor Suite for Autonomous Cars

4.1.6. Evolution of Sensor Suites from Level 1 to Level 4

4.1.7. Autonomous driving technologies

4.1.8. Why is cellular connectivity important for AVs

4.1.9. Connected aspects of Autonomous Vehicles

4.1.10. 4G compared to 5G

4.1.11. 4G compared to 5G visualized

4.1.12. Why 5G Matters for Autonomy

4.1.13. Why V2X Sidelink Matters for Autonomy (1)

4.1.14. Why V2X Sidelink Matters for Autonomy (2)

4.1.15. Level 2 Requirements

4.1.16. Level 3 Requirements

4.1.17. Level 4 (Private) Requirements

4.1.18. Level 4 (Robotaxi) Requirements

4.1.19. Autonomy Levels Requirements compared

4.2. Mapping and Localization

4.2.1. What is Localization?

4.2.2. Localization: Absolute vs Relative

4.2.3. Lane Models: Uses and Shortcomings

4.2.4. HD Mapping Assets: From ADAS Map to Full Maps for Level-5 Autonomy

4.2.5. Many Layers of an HD Map for Autonomous Driving

4.2.6. HD Map as a Service

4.2.7. Who are the Players?

4.2.8. Mapping Business Models

4.2.9. Vertically Integrated Mappers

4.2.10. HD Mapping with Cameras

4.2.11. HD Mapping with Cameras

4.2.12. DeepMap

4.2.13. Civil Maps

4.2.14. Semi- or Fully Automating the Data-to-Map Process

4.2.15. Radar Mapping

4.2.16. Radar Localization: Navtech

4.2.17. Radar Localization: WaveSense

4.3. Teleoperation

4.3.1. Enabling Autonomous MaaS

4.3.2. Three Levels of Teleoperation

4.3.3. How remote assistance works - Zoox

4.3.4. Remote assistance

4.3.5. Remote Control

4.3.6. Where is teleoperation currently used?

4.3.7. Players

4.3.8. MaaS vs Independent solution providers

4.3.9. Ottopia's Advanced Teleoperation (1)

4.3.10. Ottopia's Advanced Teleoperation (2)

4.3.11. Phantom Auto's Teleoperation as Back-Up for AVs

4.3.12. Phantom Auto Gaining Momentum in Logistics

4.3.13. Halo - Subverting Autonomy

5. FORECASTS

5.1. Forecasting Content

5.2. Forecasting Methodology

5.3. Software-Defined Vehicle Level Guide

5.4. SDV Forecast Methodology

5.5. SDV Global Total Vehicle Sales Forecast (Units)

5.6. SDV Global Total Vehicle Sales Forecast (Units)

5.7. SDV Forecast Methodology

5.8. SDV Global Vehicle Revenue Forecast (Hardware Revenue)

5.9. SDV Forecast (Hardware Revenue)

5.10. SDV Feature Revenue Forecast Methodology

5.11. SDV Feature Revenue Forecast Methodology

5.12. SDV Feature-related Revenue Forecast (Global Revenue)

5.13. SDV Feature Forecast (Global Revenue)

5.14. V2V/V2I Uptake Forecasting

5.15. V2V/V2I Radio Access Technology Forecast

5.16. V2V/V2I Vehicle Unit Sales Forecasting

5.17. V2V/V2I Unit Sales Forecasting

 

6.1. ADASTEC

6.2. AiDEN: Enabling Services on Connected Cars

6.3. AUO

6.4. Autocrypt

6.5. Black Sesame

6.6. Continental

6.7. Cruise

6.8. Ethernovia: Automotive Ethernet

6.9. Innovate UK

6.10. JPMorgan Mobility Payments Solutions: In-Vehicle Payments

6.11. Mobileye

6.12. Monumo: Artificial Intelligence for Motor Development

6.13. NXP Semiconductors

6.14. PIX Moving

6.15. PreAct Technologies: Software-Defined Sensors

6.16. Qualcomm: Sense ID

6.17. Recogni ? Neural Network Accelerated Autonomous Car Computing

6.18. TCL Technology

6.19. Visionox

6.20. Waymo: Autonomous Trucking

6.21.Zelostech