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Development of Leading IC Brands in Smart Vehicle Applications

  • Report

  • 23 Pages
  • January 2021
  • Region: Global
  • Market Intelligence & Consulting Institute (MIC)
  • ID: 5238463

Due to the growing maturity of IoV (Internet of Vehicles) and active safety technology such as advanced driver assistance systems, several leading IC brands have jumped on the bandwagon. Given the unique characteristics of the supply chain and strict requirements for safety and reliability in the automotive industry, most of these IC brands have chosen to work with leading carmakers to reduce entry barriers. Developing their own technology and ecosystems has thus become an important strategy for both parties. This report analyzes the product development and strategies of leading brands, including Intel, Nvidia, Qualcomm, and MediaTek, in the smart vehicle market.

List of Topics

  • Development of four leading IC brands in smart vehicles, including Intel, Nvidia, Qualcomm, and MediaTek
  • Overview of the strategies of these IC brands’ new product development that solve challenges and create opportunities

Table of Contents

1. Current Status of Smart Vehicles

2. Intel in Smart Vehicle Applications
2.1 Mobileye EyeQ Chips
2.2 Cooperation with Transportation Operators
2.3 Increased Focus on Image Sensing
2.4 Expansion into MaaS (Mobility-as-a-Service) Market

3. Nvidia in Smart Vehicle Applications
3.1 Chips and Platforms for Self-driving Cars
3.2 Cooperation with Carmakers

4. Qualcomm in Smart Vehicle Applications
4.1 C-V2X Chips
4.2 Snapdragon Ride Platform

5 MediaTek in Smart Vehicle Applications
5.1 Telematics System
5.2 Smart Cockpit System
5.3 Vison-based ADAS
5.4 Automotive mmWave Radar

6. Conclusion

List of Companies

List of Tables
Table 1 Evolution of EyeQ Chips
Table 2 Nvidias Platforms for Self-driving Vehicles
Table 3 MediaTeks Products for Smart Vehicles

List of Figures
Figure 1 Self-driving Car Services Co-developed by Mobileye and Moovit
Figure 2 The Nvidia DRIVE Ecosystem
Figure 3 Support Enabled by the Snapdragon Ride Platform



Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • Audi
  • BMW
  • Bosch
  • Buggy TLC Rentals
  • Canoo
  • Champion Motors
  • Continental AG
  • Didi Chuxing Technology
  • Eonite Perception
  • Faraday Future
  • Ford
  • General Motors
  • Gett
  • Here
  • Intel
  • Lyft
  • MediaTek
  • Mercedes-Benz
  • Mobileye
  • Moovit
  • Nvidia
  • NXP
  • Optimus Ride
  • Pony.ai
  • Qualcomm
  • RATP
  • SAIC Motor
  • Telsa
  • TuSimple
  • Uber
  • Volkswagen
  • XPen Motors
  • Zoo


Primary research with a holistic, cross-domain approach

The exhaustive primary research methods are central to the value that the analyst delivers. A combination of questionnaires and on-site visits to the major manufacturers provides a first view of the latest data and trends. Information is subsequently validated by interviews with the manufacturers' suppliers and customers, covering a holistic industry value chain. This process is backed up by a cross-domain team-based approach, creating an interlaced network across numerous interrelated components and system-level devices to ensure statistical integrity and provide in-depth insight.

Complementing primary research is a running database and secondary research of industry and market information. Dedicated research into the macro-environmental trends shaping the ICT industry also allows the analyst to forecast future development trends and generate foresight perspectives. With more than 20 years of experience and endeavors in research, the methods and methodologies include:


  • Component supplier interviews
  • System supplier interviews
  • User interviews
  • Channel interviews
  • IPO interviews
  • Focus groups
  • Consumer surveys
  • Production databases
  • Financial data
  • Custom databases


  • Technology forecasting and assessment
  • Product assessment and selection
  • Product life cycles
  • Added value analysis
  • Market trends
  • Scenario analysis
  • Competitor analysis