市場調查報告書

汽車自我學習型人工智能:分析、預測

Executive Analysis of Self-learning Artificial Intelligence in Cars, Forecast to 2025

出版商 Frost & Sullivan 商品編碼 373327
出版日期 內容資訊 英文 79 Pages
商品交期: 最快1-2個工作天內
價格
汽車自我學習型人工智能:分析、預測 Executive Analysis of Self-learning Artificial Intelligence in Cars, Forecast to 2025
出版日期: 2016年09月19日內容資訊: 英文 79 Pages
簡介

本報告提供車載用的自我學習型人工智能的市場調查,自我學習型汽車概要,優點及缺點,自我學習型AI的汽車的用途,技術必要條件,運行原理,各種進入經營者的技術策略,利用案例方案,市場規模,未來展望,成長機會等彙整資料。

第1章 摘要整理

  • 摘要整理:主要調查結果
  • 4等級的自我學習
  • 自我學習型汽車的演進
  • 自我學習技術的主要OEM策略
  • OEM比較分析
  • 自我學習的商機
  • 成長推動因素
  • 阻礙成長要素
  • 地區分析、引進/發展發展藍圖
  • 摘要整理:主要調查結果、未來展望

第2章 調查範圍、目的、背景、手法

第3章 定義

第4章 自我學習型汽車:概要

  • 自我學習概要:主要調查結果
  • 汽車的自我學習技術的需求
  • 自我學習型汽車:優點及缺點
  • 自我學習型汽車的資料支援
  • 汽車自我學習技術的用途
  • 技術必要條件
  • 自我學習型汽車的運行原理
  • 三大課題

第5章 主要進入經營者的技術策略

  • 技術策略:主要調查結果
  • 價值鏈內的技術企業
  • OEM群組及技術企業的聯盟
  • 13家OEM公司對自我學習技術的焦點
  • 自我學習技術策略:豐田
  • 自我學習技術策略:Ford
  • 自我學習技術策略:Volkswagen
  • OEM比較分析
  • 電子產品企業的技術策略:概要
  • 電子產品企業的策略:比較
  • 自我學習技術策略:NVIDIA
  • 技術企業的策略:概要
  • 技術企業的策略:比較
  • 自我學習技術策略:Cloudmade
  • 經營模式

第6章 利用案例方案

  • 利用案例方案:主要調查結果
  • 利用案例方案:用戶的愛好 (第1級)
  • 利用案例方案:近距離視野 (第2級)
  • 利用案例方案:高度自主性地圖 (第3級)
  • 利用案例方案:新的行動服務 (第4級)

第7章 自我學習:預測、市場規模

  • 自我學習型汽車的預測 (第1級&2)
  • 自我學習型汽車的預測 (第3級&4)

第8章 總論、未來展望

  • 技術的展望
  • 總論、未來展望:So-what分析
  • 主要調查結果、未來展望
  • 成長機會
  • 總論
  • 總論-三大預測
  • 免責聲明

第9章 附錄

目錄
Product Code: K053-18

Investments Worth $7.1 Billion to Develop 12 Use Cases across 3 Broad Applications by 2025

Scope of the report

The research report includes the following segments:

Product scope: Self-learning AI in cars - Autonomous Cars, Virtual Assistance in Cars, new revenue streams through data analytics and licensing, and HAD mapping Geographic scope: North America, Europe, China, and Japan

End-user scope: Automotive Industry Participants

Drivers and restraints, a detailed discussion of the four levels of evolution of self-learning cars, discussion of technology trends of key OEMs, and use case scenarios have also been provided for self-learning cars market.

What makes our reports unique?

We provide one of the longest market segmentation chains in this industry.

We conduct detailed market positioning, product positioning, and competitive positioning. Entry strategies, gaps, and opportunities are identified for all the stakeholders.

Comprehensive market analysis for the following sectors:

Pharmaceuticals, medical devices, biotechnology, semiconductor and electronics, energy and power supplies, food and beverages, chemicals, advanced materials, industrial automation, and telecom, and IT. We also analyze retailers and super-retailers, technology partners, and research and development (R&D) companies.

Key Questions Answered

  • What are self-learning cars? Who are the key industry participants applying this technology?
  • Where are the growth opportunities in the value chain? What are the roadmaps to reach a self-learning car?
  • What is the strategy of various industry participants, and what are the use case scenarios? Is self-learning car the best route to a self-driving car?
  • What are the new business models evolving around self-learning cars? Who are the key industry participants that will benefit from Self Learning Technology adaption?
  • How are new partnerships evolving and disrupting the traditional supply chain in the automotive industry?

Table of Contents

1. EXECUTIVE SUMMARY

  • 1. Executive Summary-Key Findings
  • 2. Four Levels of Self Learning
  • 3. Self-learning Cars Evolution
  • 4. Self-learning Cars Evolution (continued)
  • 5. Self-learning Cars Evolution (continued)
  • 6. Self-learning Cars Evolution (continued)
  • 7. Key OEMs Strategy on Self Learning Technology
  • 8. Key OEMs Strategy on Self Learning Technology (continued)
  • 9. Key OEMs Strategy on Self Learning Technology (continued)
  • 10. Comparative Analysis of OEMs
  • 11. Self Learning Revenue Opportunities
  • 12. Drivers
  • 13. Restraints
  • 14. Regional Analysis and Adoption/Rollout Roadmap
  • 15. Executive Summary-Key Findings and Future Outlook

2. RESEARCH SCOPE, OBJECTIVES, BACKGROUND, AND METHODOLOGY

  • 1. Research Scope
  • 2. Research Aims and Objectives
  • 3. Research Methodology
  • 4. Key Questions This Study Will Answer
  • 5. Research Background
  • 6. Key OEM Groups Analyzed in this Study

3. DEFINITIONS

  • 1. Defining a Self-learning Car
  • 2. Three Levels of AI to Disrupt the Automotive Industry
  • 3. Deep Neural Networks to Drive Self-learning AI
  • 4. Evolution of Self-learning Cars in 4 Levels
  • 5. Self Learning is not Autonomous-It is Beyond

4. SELF-LEARNING CARS-OVERVIEW

  • 1. Overview of Self Learning-Key Findings
  • 2. Need for Self Learning Technology in Cars
  • 3. Self-learning Cars-Advantages and Limitations
  • 4. Self-learning Cars will Scale with Data
  • 5. Applications of Self Learning Technology in Cars
  • 6. Technology Requisites
  • 7. Working Principle of Self-learning Cars
  • 8. Three Big Challenges

5. KEY PARTICIPANTS TECHNOLOGY STRATEGIES

  • 1. Technology Strategies-Key Findings
  • 2. Technology Companies in the Value Chain
  • 3. OEM Groups are Partnering with Tech Companies
  • 4. 13 OEMs Focus on Self Learning Technology
  • 5. Toyota Strategy on Self Learning Technology
  • 6. Ford Strategy on Self Learning Technology
  • 7. Volkswagen Strategy on Self Learning Technology
  • 8. Comparative Analysis of OEMs
  • 9. Electronic Companies Technology Strategy-Overview
  • 10. Electronic Companies Strategy-Comparison
  • 11. NVIDIA Strategy on Self Learning Technology
  • 12. NVIDIA Strategy on Self Learning Technology (continued)
  • 13. Technology Companies Strategy-Overview
  • 14. Technology Companies Strategy-Comparison
  • 15. Cloudmade Strategy on Self Learning Technology
  • 16. Business Models

6. USE CASE SCENARIOS

  • 1. Use Case Scenario-Key Findings
  • 2. Use Case Scenarios-User Preferences (Level 1 Self Learning)
  • 3. Use Case Scenarios-Near Field Vision (Level 2 Self Learning)
  • 4. Use Case Scenarios-Highly Autonomous Maps (Level 3 Self Learning)
  • 5. Use Case Scenarios-New Mobility Services (Level 4 Self Learning)

7. SELF LEARNING-FORECASTING AND MARKET SIZING

  • 1. Self-learning Cars-Forecast (Level 1 & Level 2)
  • 2. Self-learning Cars-Forecast (Level 3 & Level 4)

8. CONCLUSIONS AND FUTURE OUTLOOK

  • 1. Technology Outlook
  • 2. Conclusions and Future Outlook-So-what Analysis
  • 3. Key Findings and Future Outlook
  • 4. 5 Growth Opportunities
  • 5. Key Conclusions
  • 6. The Last Word-3 Big Predictions
  • 7. Legal Disclaimer

9. APPENDIX

  • 1. Methodology
  • 2. Abbreviations and Acronyms Used