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Disruptive Technologies with Innovative Business Models Driving Platform and Architecture Strategies for AVs, 2020

  • Report

  • 66 Pages
  • September 2020
  • Region: Global
  • Frost & Sullivan
  • ID: 5174510

Growth Potential Enhanced by 4-layered Platform Approach Toward CASE

The automotive industry is at a tipping point, with traditional business models being disrupted, changing the market dynamics, increasing urbanization and congestion, tighter emission and safety regulations, evolving consumer expectations for digital features, and focus on user safety. The ecosystem is evolving at a rapid pace, not only through the emergence of new business models, but also on the technological front.

Traditionally, most OEMs and Tier-I suppliers have been taking the siloed approach for developments in connected, autonomous, and electric vehicles. However, this approach of singular focus is not viable for the long term. OEMs will need strategies that explore the benefits of developing applications focused on the convergence of the 3 technology pillars. To cope with this transition, automakers will need to realign their value proposition around these emerging dynamics and rethink their physical and digital platform strategies to harness the value of myriad types of data.

Powertrain electrification is among the most important strategies of every OEM to achieve the long-term vision of carbon-neutral mobility. OEMs are also aiming to create a consolidated chassis platform, which will be modular enough to handle multiple segments of vehicles. These factors will force the OEMs to shift from well-established legacy chassis platforms to multi-energy platforms (MEPs) and modular and dedicated electric platforms. OEMs are also focused on strengthening their E/E architecture, which can handle humongous data sizes from continuously evolving sensor suite and processing software. The rise of data ingestion per vehicle has called in the significance of cloud computation as on-premise servers become incapable.

The study covers the key platforms that OEMs need to focus on, as they shift their strategy to data-centric revenue models from traditional vehicle-centric business models. As every OEM strategizes their individual path toward CASE convergence, the expected evolution of the platforms are explored, along with major industry partnerships.

Key Issues Addressed

  • How is the automotive industry shifting, and what are the implications of that shift on traditional OEM strategies?
  • Which are the 4 key platforms that OEMs need to focus on to align their strategy with future CASE convergence?
  • How is the chassis platform evolving, as the industry gears up for electrification and adding redundancies for L4 and L5 autonomy?
  • How will development toward higher-level autonomy affect the in-vehicle electronics and software, and how will the industry cope with increasing data?
  • What are specific OEMs and developers strategizing for the 4 key platforms?

Table of Contents

1. Executive Summary
  • Platform Components
  • Chassis Platform
  • Electronic Platform
  • Software Platform
  • Cloud Platform
  • Partnership Strategies across Platforms
  • Key Conclusions

2. Research Scope and Objectives
  • Research Scope
  • Key Questions this Study will Answer

3. Definitions
  • Vehicle Segmentation
  • Standards for Autonomous Driving
  • Electric Vehicle (xEV) in Scope

4. Industry Overview
  • Shifting Landscape of the Automotive Industry
  • Industry Optimizations Due to Shifting Landscape
  • Key Challenges for OEMs with Traditional Development
  • Platform-based Approach Toward CASE

5. Vehicle and Chassis Platform
  • Future Autonomous Vehicle Platforms
  • Modular and Skateboard Platforms
  • Key Platforms
  • OEMs’ Strategy - BEVs on Skateboard Platform

6. Electronic Platform
  • Evolution of E/E Architecture
  • Evolution of Sensor Hardware
  • Role of Sensor Data Fusion by Level of Automation
  • EV Power Components
  • OEM E/E Architecture Strategies
  • EV Battery and Motor Strategy

7. Software Platform
  • Key In-vehicle Software Enabling AD
  • Software-Hardware Decoupling
  • AI-based Software Vs. Conventional Software
  • Role of Machine Learning
  • Implementation of Machine Learning
  • Autonomous Driving Software Platforms

8. Cloud and Edge Computing Platform
  • Data Storage and Computing for AVs
  • Edge Vs. Cloud Computing
  • Cloud-Edge Computation Models
  • Cloud Storage and Computation
  • OEM Cloud Strategy

9. CASE Convergence
  • CASE Convergence
  • Implications of CASE Convergence

10. Growth Opportunities and Companies to Action
  • Growth Opportunity - Investments and Partnerships from OEMs/TSPs
  • Strategic Imperatives for Success and Growth

11. Key Conclusions
  • Key Conclusions
  • The Last Word - 3 Big Predictions
  • Legal Disclaimer

12. Appendix
  • Market Engineering Methodology
  • Abbreviations and Acronyms Used
  • List of Exhibits