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表紙：車両インテリジェンスシステムの世界市場-2023年～2030年
市場調査レポート
商品コード
1347993

車両インテリジェンスシステムの世界市場-2023年～2030年

Global Vehicle Intelligence Systems Market - 2023-2030
出版日: | 発行: DataM Intelligence | ページ情報: 英文 206 Pages | 納期: 約2営業日

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車両インテリジェンスシステムの世界市場-2023年～2030年
出版日: 2023年09月11日
発行: DataM Intelligence
ページ情報: 英文 206 Pages
納期: 約2営業日
ご注意事項 :
本レポートは最新情報反映のため適宜更新し、内容構成変更を行う場合があります。ご検討の際はお問い合わせください。
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概要

概要

世界の車両インテリジェンスシステム市場は、2022年に85億米ドルに達し、2023～2030年の予測期間中にCAGR 12.3％で成長し、2030年には232億米ドルに達すると予測されています。

主な成長要因のひとつは、安全性の重視です。AIやセンサー技術を利用した車線逸脱警告、自動緊急ブレーキ、歩行者検知などの先進運転支援の採用により、事故を未然に防ぎ、死亡事故を減らすことができます。様々な企業が、人間の介入なしにナビゲートする自動運転車の製造に投資し始めました。

IoTの導入が進むにつれて、車両間のコネクティビティや車両からインフラへのコネクティビティが高まり、車両がセンサーを通じて通信できるようになっています。コネクティビティは交通管理や衝突回避を改善し、全体的な効率を向上させます。シーメンスのレポートによると、交差点を通過する平均交通量は15%未満であり、交通密度は緩和されています。

予測期間中、北米は世界の車両インテリジェンスシステム市場の1/3以上を占める支配的な地域になると予想されています。同地域では、コネクテッドカーやVehicle-to-Everything通信システムの台頭により、車両が他の車両、インフラ、歩行者、交通管理システムと情報を交換できるようになり、その接続性により交通の流れが改善され、事故が減少し、全体的な交通安全が向上しています。

ダイナミクス

政府による先進技術の採用

政府はしばしば、インテリジェンスや自動化技術を搭載した車両を含む車両の安全規制や基準を実施しており、こうした規制は、衝突回避システム、自動ブレーキ、車線逸脱警告システムなどの車両インテリジェンスシステム・コンポーネントが、事故を減らし交通安全を向上させるための特定の安全基準を満たしていることを保証するものです。

例えば、2022年4月15日、インドの電子情報技術省は、インド都市向けインテリジェント交通システム・エンデバーPhase-II構想の一環として3つの革新的な製品を発表しました。これらの製品は、インド工科大学マドラス校先端コンピューティング開発センターと産業界の協力者であるマヒンドラ・アンド・マヒンドラ社との共同研究によって開発されました。

このシステムには、 促進要因の行動と車両周辺を監視するための車両搭載型センサーが組み込まれています。センサー・データをリアルタイムで解釈することで、 促進要因支援のための視覚的・音響的アラートを提供し、交通安全を強化します。

企業間の事業協力・提携

車両インテリジェンスシステムは、包括的なソリューションを構築するために、ソフトウェア、ハードウェア、専門知識の組み合わせを必要とすることが多いです。さまざまな企業と協力することで、さまざまなコンポーネントや技術を統合し、完全で堅牢なインテリジェンス・システムを実現することができます。コラボレーションは、異なるパートナーの強みを活用することで、カスタマイズされたソリューションの作成を可能にします。

新たな世界的協業の一環として、ウェイモとボルボ・カーズ・グループは2020年6月にライドヘイリング用の自動運転電気自動車の生産で協業することを決定しました。ウェイモは、自動運転" 促進要因"のための人工知能と、カメラ、ライダー、レーダーなどの特殊技術に注力します。ボルボは車両の設計と製造を行います。

技術進歩

自律走行技術の開発は、車両インテリジェンスシステムの成長の主要な原動力です。各社は、運転支援から完全な自動運転車までの自動化レベルに取り組んでいます。自律走行車には、センサー、AIアルゴリズム、精密なマッピング技術の高度な組み合わせが必要です。クラウドコンピューティングソフトウェアは、車両がクラウドからデータにアクセスして処理することを可能にし、遠隔診断やソフトウェア更新などのサービスを可能にします。

例えば、コネクテッド・ビークル・プラットフォーム企業のシブロスは2023年8月16日、組込みシステム・プロバイダーのアイウェーブ・システムズと提携し、さまざまな車両アーキテクチャに対応するソフトウェア定義の車両イノベーションを加速させます。SibrosのOver-the-Airプラットフォームは、iWaveのRugged Telematics Deviceに統合され、自動車、産業車両、オフロード車、大型車の組み込みインテリジェンスを可能にします。

誤動作と複雑な製造工程

車両インテリジェンスシステムは、ソフトウェア、センサー、通信ネットワークに大きく依存しています。これらのコンポーネントに不具合や故障が生じると、安全上のリスクや事故、システムエラーにつながる可能性があります。こうしたインテリジェンスシステムの信頼性と安全性を確保することは、極めて重要な課題です。自動車がより接続され、ソフトウェアに依存するようになると、サイバーセキュリティの脅威にさらされやすくなります。ハッカーが車両システムに不正アクセスする可能性があり、安全性とプライバシーのリスクにつながります。

車両インテリジェンスシステムの実装には、センサー、プロセッサー、通信インフラを含む複雑なシステムが必要であり、この複雑さが製造コストと整備コストの上昇につながり、普及を妨げる可能性があります。V2X通信など、車両インテリジェンスシステムの機能の多くは、スマート道路や通信ネットワークのような堅牢なインフラに依存しています。このようなインフラの欠如は、これらのシステムの潜在能力を十分に発揮する妨げとなる可能性があります。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

  • 影響要因
    • 促進要因
      • 政府による先端技術の採用
      • 企業間の事業協力・提携
      • 技術進歩
    • 抑制要因
      • 誤作動と複雑な製造工程
    • 機会
    • 影響分析

第5章 産業分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 価格分析
  • 規制分析
  • ロシア・ウクライナ戦争の影響分析
  • DMIの見解

第6章 COVID-19分析

第7章 コンポーネント別

  • センサー
  • アナログIC
  • プロセッサー
  • メモリ

第8章 ADAS（先進運転支援システム）・ドライバーモニタリングシステム（DMS）別

  • アダプティブクルーズコントロール（ACC）システム
  • 死角検知システム
  • 駐車支援システム
  • 渋滞支援システム
  • 眠気モニタリング

第9章 道路状況把握システム別

  • 車線維持システム
  • 標識検知システム
  • ナイトビジョンシステム
  • 歩行者検知システム

第10章 車両別

  • 乗用車
  • 商用車

第11章 地域別

  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • イタリア
    • ロシア
    • その他欧州
  • 南米
    • ブラジル
    • アルゼンチン
    • その他南米
  • アジア太平洋
    • 中国
    • インド
    • 日本
    • オーストラリア
    • その他アジア太平洋
  • 中東・アフリカ

第12章 競合情勢

  • 競合シナリオ
  • 市況/シェア分析
  • M&A分析

第13章 企業プロファイル

  • Continental AG
    • 企業概要
    • 製品ポートフォリオと説明
    • 財務概要
    • 主な動向
  • Denso Corporation
  • Delphi Automotive
  • Robert Bosch GmbH
  • Autoliv Inc.
  • Mobileye
  • Intel
  • Nvidia
  • Tesla
  • BMW AG

第14章 付録

目次
Product Code: ICT6855

Overview

Global Vehicle Intelligence Systems Market reached US$ 8.5 billion in 2022 and is expected to reach US$ 23.2 billion by 2030, growing with a CAGR of 12.3% during the forecast period 2023-2030.

One of the major growth factors is the emphasis on safety. Adoption of advanced driver assistance like lane departure warning, automatic emergency braking and pedestrian detection using AI and sensor technologies that prevent from accidents and reduce fatalities. Various companies began investing in manufacturing self-driven cars that navigate without human intervention.

The rise in adoption of IoT has led to an increase in vehicle connectivity which enables vehicles to communicate through sensors in which there is vehicle-to-vehicle connectivity and vehicle-to-infrastructure connectivity. As the connectivity will improve traffic management and collision avoidance and improve overall efficiency. According to the report by Siemens, there is less than 15% of average traffic through the intersection and there is ease of traffic density.

During forecast period, North America is expected to be the dominant region in the global vehicle intelligence systems market covering more than 1/3rd of the market. The region has a rise of connected vehicles and Vehicle-to-Everything communication systems that enable vehicles to exchange information with other vehicles, infrastructure, pedestrians and traffic management systems and his connectivity improves traffic flow, reduces accidents and enhances overall road safety.

Dynamics

Adoption of Advanced Technologies by Government

Governments often implement safety regulations and standards for vehicles, including those equipped with intelligence and automation technologies and these regulations ensure that vehicle intelligence systems components, such as collision avoidance systems, automated braking and lane departure warning systems, meet specific safety criteria to reduce accidents and improve road safety.

For instance, on 15 April 2022, the Ministry of Electronics and Information Technology in India launched three innovative products as part of the Intelligent Transportation System Endeavor for Indian Cities Phase-II initiative and these products were developed through a collaboration between the Centre for Development of Advanced Computing, the Indian Institute of Technology Madras and industrial collaborator Mahindra and Mahindra.

The system incorporates vehicle-borne sensors to monitor the driver's behavior and vehicle surroundings. It delivers visual and acoustic alerts for driver assistance by interpreting sensor data in real-time, enhancing road safety.

Collaboration and Partnership Between Companies

Vehicle Intelligence Systems often require a combination of software, hardware and specialized expertise to create comprehensive solutions. Collaborating with different companies allows for the integration of various components and technologies to deliver complete and robust intelligence systems. Collaboration enables the creation of customized solutions by leveraging the strengths of different partners.

As part of a new worldwide collaboration, Waymo and the Volvo Cars Group decided to collaborate on the production of a self-driving electric vehicle for ride-hailing in June 2020. Waymo will focus on artificial intelligence and particular technology, like as cameras, lidar and radar, for the self-driving "driver." Volvo will design and build the vehicles.

Technology Advancement

The development of autonomous driving technology is a major driver of vehicle intelligence systems growth. Companies are working on levels of automation ranging from driver assistance to full self-driving vehicles. Autonomous vehicles require a sophisticated combination of sensors, AI algorithms and precise mapping technology. Cloud computing software allows vehicles to access and process data from the cloud, enabling services like remote diagnostics and software updates.

For instance, on 16 August 2023, connected vehicle platform company Sibros partnered with embedded systems provider iWave Systems to accelerate software-defined vehicle innovation for various vehicle architectures. Sibros' over-the-air platform will be integrated into iWave's Rugged Telematics Device to enable embedded intelligence in automotive, industrial, off-road and heavy-duty vehicles.

Malfunction and Complex Manufacturing

Vehicle intelligence systems heavily rely on software, sensors and communication networks. Any malfunction or failure in these components could lead to safety risks, accidents or system errors. Ensuring the reliability and safety of these intelligence systems is a critical challenge. As vehicles become more connected and reliant on software, they become susceptible to cybersecurity threats. Hackers potentially gain unauthorized access to vehicle systems, leading to risks of safety and privacy.

Implementing vehicle intelligence systems requires intricate systems, including sensors, processors and communication infrastructure and this complexity can lead to higher manufacturing and maintenance costs, which might deter widespread adoption. Many vehicle intelligence systems functionalities, such as V2X communication, depend on robust infrastructure like smart roads and communication networks. The lack of such infrastructure can hinder the full potential of these systems.

Segment Analysis

The global vehicle intelligence systems market is segmented based component, advanced driver assistance and driver monitoring systems, road scene understanding, Vehicle and region.

Adoption of Sensors for Navigation Purposes

During the forecast period, sensors are expected to hold majority of the global market share holding around 30.3% of the market. Sensors contribute majorly to vehicle safety by enabling real-time data access and the implementation of ADAS that use sensors to detect objects, pedestrians and other vehicles. It is also utilized to give a 360-degree view of the surroundings of the car, helping drivers to make better decisions.

On 24 February 2023, Mercedes-Benz and Google announced a partnership that will enhance its vehicle with advanced features and software systems. It also plans to integrate "supercomputers" into its vehicles. Mercedes-Benz partnered with Google for navigation services. Google Maps will be integrated into Mercedes-branded navigation systems, offering drivers real-time traffic information, automatic rerouting and the ability to access Level 3 autonomous driving mode.

Geographical Penetration

Rising Demand for Optimizing Traffic Flow and Collaborations in Asia-Pacific

Asia-Pacific is the fastest growing region in the global vehicle intelligence systems market covering about 1/4th of the market. The region is undergoing rapid urbanization and increasing traffic congestion and these features have a strong demand for vehicle intelligence system technology that optimizes traffic flow, improved road safety and it enhances overall transportation efficiency.

Automotive manufacturers, technology companies and startups are forming partnerships and collaborations that accelerate the development and deployment of intelligence systems. For instance, on 7 August 2023, Great Wall Motor, China's largest sport-utility vehicle assembler, partnered with Baidu, a search and AI giant, to integrate Baidu's AI-powered chatbot tool called Ernie Bot into its vehicles and this partnership aims to enhance the conversation and interaction between drivers and their vehicles.

Competitive Landscape

The major global players in the market include: Continental AG, Denso Corporation, Delphi Automotive, Robert Bosch GmbH, Autoliv Inc., Mobileye, Intel, Nvidia, Tesla and BMW AG.

COVID-19 Impact Analysis

The pandemic disrupted global supply chains, leading to shortages of components and parts needed for manufacturing vehicle intelligence systems and this resulted in delays in production and slowed down the rollout of new vehicles with advanced technologies. Many companies faced challenges in conducting research and development activities due to lockdowns, travel restrictions and remote work arrangements and this could have delayed the progress of new technologies and innovations in vehicle intelligence systems.

The pandemic hindered the ability to conduct real-world testing and validation of vehicle intelligence systems. Restrictions on movement and social distancing measures impacted the collection of data needed to refine and improve these systems. The pandemic led to fluctuations in market demand for vehicles. Economic uncertainty and changing consumer preferences impacted the adoption of advanced technologies, including vehicle intelligence systems.

Some companies temporarily shifted their focus from developing new technologies to addressing immediate challenges posed by the pandemic and this could have redirected resources away from the advancement of vehicle intelligence systems. Remote work arrangements affected collaboration among teams working on vehicle intelligence systems. Developing and integrating complex technologies requires close coordination, which could have been challenging in a remote work environment.

AI Impact

AI is a core technology in enabling autonomous driving capabilities. AI-powered intelligence systems, like computer vision and sensor fusion, allows vehicles to understand and interpret their surroundings. Machine learning algorithms help vehicles make real-time decisions based on complex data inputs from cameras, lidars, radars and other sensors. AI algorithms lead to analyze data from sensors and cameras to provide features like adaptive cruise control, lane-keeping assistance and parking assistance.

AI can analyze data from various vehicle sensors to predict and identify potential mechanical issues before they lead to breakdowns and this predictive maintenance approach reduces downtime, increases vehicle longevity and improves overall operational efficiency. AI-powered NLP enables voice recognition and natural language understanding in vehicles. Drivers and passengers can interact with infotainment systems, navigation and other features using voice commands, making the in-car experience more intuitive and hands-free.

For instance, on 21 August 2023, UAE-based electric car manufacturer NWTN introduced the Rabdan Muse, a luxury smart passenger vehicle, featuring advanced technology suitable for both business and family travel. Unveiled at the Pebble Beach Concours d'Elegance in California, the Muse offers autonomous driving capabilities, AI integration and personalized lifestyle features.

Russia- Ukraine War Impact

The conflict may disrupt supply chains that provide critical components and materials for VIS manufacturing and this could lead to shortages and delays in production, affecting the availability of vehicles equipped with advanced intelligence systems. Companies in the region directly affected by the conflict may face challenges in conducting research and development activities. Resources that would have been allocated to innovation and technology advancement could be diverted to address more immediate concerns related to the conflict.

The geopolitical tensions and economic instability resulting from the conflict could create uncertainty in the market and this uncertainty might impact consumer demand for vehicles and their associated technology, including VIS. Governments and industries in the affected regions might need to prioritize resources for national security and recovery efforts and this could result in reduced investments and attention allocated to the development and deployment of VIS.

By Component

  • Sensor
  • Analog ICs
  • Processor
  • Memory

By Advanced Driver Assistance and Driver Monitoring Systems

  • Adaptive Cruise Control System
  • Blind Spot Detection System
  • Park Assist System
  • Traffic Jam Assit Systems
  • Drowsiness Monitoring

By Road Scene Understanding

  • Road/Lane Tracking System
  • Road Sign Detection System
  • Night Vision System
  • Pedestrian Detection System

By Vehicle

  • Passenger Cars
  • Commercial Vehicles

By Region

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Russia
    • Rest of Europe
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia-Pacific
    • China
    • India
    • Japan
    • Australia
    • Rest of Asia-Pacific
  • Middle East and Africa

Key Developments

  • On 12 April 2023, BYD, a prominent global manufacturer of new energy vehicles introduced its first self-developed intelligent body control system, known as the DiSus Intelligent Body Control System and this system represents a significant milestone for BYD, solidifying its pioneering position in the industry.
  • On 28 June 2023, ZTE Corporation and Tianyi Transportation Technology unveiled the industry's first 5G+ intelligent connected vehicle system with Vehicle-Road-Cloud integration at the Mobile World Congress Shanghai 2023 and this collaboration aims to enhance the capabilities of autonomous driving through comprehensive whole-road perception and collaborative decision-making.
  • On 4 July 2023, Antolin is spearheading the GENIUS project, an innovative venture in Artificial Intelligence aimed at enhancing the user experience during journeys. the GENIUS project will employ sensors within the vehicle cabin, connected to intelligent systems, to interpret users' cognitive and emotional states.

Why Purchase the Report?

  • To visualize the global vehicle intelligence systems market segmentation based on component, advanced driver assistance and driver monitoring systems, road scene understanding, vehicle and region, as well as understand key commercial assets and players.
  • Identify commercial opportunities by analyzing trends and co-development.
  • Excel data sheet with numerous data points of vehicle intelligence systems market-level with all segments.
  • PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
  • Product mapping available as excel consisting of key products of all the major players.

The global vehicle intelligence systems market report would provide approximately 69 tables, 70 figures and 206 pages.

Target Audience 2023

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Component
  • 3.2. Snippet by Advanced Driver Assistance and Driver Monitoring Systems
  • 3.3. Snippet by Road Scene Understanding
  • 3.4. Snippet by Vehicle
  • 3.5. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Adoption of Advanced Technologies by Government
      • 4.1.1.2. Collaboration and Partnership Between Companies
      • 4.1.1.3. Technology Advancement
    • 4.1.2. Restraints
      • 4.1.2.1. Malfunction and Complex Manufacturing
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory Analysis
  • 5.5. Russia-Ukraine War Impact Analysis
  • 5.6. DMI Opinion

6. COVID-19 Analysis

  • 6.1. Analysis of COVID-19
    • 6.1.1. Scenario Before COVID
    • 6.1.2. Scenario During COVID
    • 6.1.3. Scenario Post COVID
  • 6.2. Pricing Dynamics Amid COVID-19
  • 6.3. Demand-Supply Spectrum
  • 6.4. Government Initiatives Related to the Market During Pandemic
  • 6.5. Manufacturers Strategic Initiatives
  • 6.6. Conclusion

7. By Component

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 7.1.2. Market Attractiveness Index, By Component
  • 7.2. Sensor*
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. Analog ICs
  • 7.4. Processor
  • 7.5. Memory

8. By Advanced Driver Assistance and Driver Monitoring Systems

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Advanced Driver Assistance and Driver Monitoring Systems
    • 8.1.2. Market Attractiveness Index, By Advanced Driver Assistance and Driver Monitoring Systems
  • 8.2. Adaptive Cruise Control System*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. Blind Spot Detection System
  • 8.4. Park Assist System
  • 8.5. Traffic Jam Assit Systems
  • 8.6. Drowsiness Monitoring

9. By Road Scene Understanding

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Road Scene Understanding
    • 9.1.2. Market Attractiveness Index, By Road Scene Understanding
  • 9.2. Road/Lane Tracking System*
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Road Sign Detection System
  • 9.4. Night Vision System
  • 9.5. Pedestrian Detection System

10. By Vehicle

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Vehicle
    • 10.1.2. Market Attractiveness Index, By Vehicle
  • 10.2. Passenger Cars*
    • 10.2.1. Introduction
    • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 10.3. Commercial Vehicles

11. By Region

  • 11.1. Introduction
    • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 11.1.2. Market Attractiveness Index, By Region
  • 11.2. North America
    • 11.2.1. Introduction
    • 11.2.2. Key Region-Specific Dynamics
    • 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Advanced Driver Assistance and Driver Monitoring Systems
    • 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Road Scene Understanding
    • 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Vehicle
    • 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.2.7.1. U.S.
      • 11.2.7.2. Canada
      • 11.2.7.3. Mexico
  • 11.3. Europe
    • 11.3.1. Introduction
    • 11.3.2. Key Region-Specific Dynamics
    • 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Advanced Driver Assistance and Driver Monitoring Systems
    • 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Road Scene Understanding
    • 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Vehicle
    • 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.3.7.1. Germany
      • 11.3.7.2. UK
      • 11.3.7.3. France
      • 11.3.7.4. Italy
      • 11.3.7.5. Russia
      • 11.3.7.6. Rest of Europe
  • 11.4. South America
    • 11.4.1. Introduction
    • 11.4.2. Key Region-Specific Dynamics
    • 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Advanced Driver Assistance and Driver Monitoring Systems
    • 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Road Scene Understanding
    • 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Vehicle
    • 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.4.7.1. Brazil
      • 11.4.7.2. Argentina
      • 11.4.7.3. Rest of South America
  • 11.5. Asia-Pacific
    • 11.5.1. Introduction
    • 11.5.2. Key Region-Specific Dynamics
    • 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Advanced Driver Assistance and Driver Monitoring Systems
    • 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Road Scene Understanding
    • 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Vehicle
    • 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.5.7.1. China
      • 11.5.7.2. India
      • 11.5.7.3. Japan
      • 11.5.7.4. Australia
      • 11.5.7.5. Rest of Asia-Pacific
  • 11.6. Middle East and Africa
    • 11.6.1. Introduction
    • 11.6.2. Key Region-Specific Dynamics
    • 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Advanced Driver Assistance and Driver Monitoring Systems
    • 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Road Scene Understanding
    • 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Vehicle

12. Competitive Landscape

  • 12.1. Competitive Scenario
  • 12.2. Market Positioning/Share Analysis
  • 12.3. Mergers and Acquisitions Analysis

13. Company Profiles

  • 13.1. Continental AG*
    • 13.1.1. Company Overview
    • 13.1.2. Product Portfolio and Description
    • 13.1.3. Financial Overview
    • 13.1.4. Key Developments
  • 13.2. Denso Corporation
  • 13.3. Delphi Automotive
  • 13.4. Robert Bosch GmbH
  • 13.5. Autoliv Inc.
  • 13.6. Mobileye
  • 13.7. Intel
  • 13.8. Nvidia
  • 13.9. Tesla
  • 13.10. BMW AG

LIST NOT EXHAUSTIVE

14. Appendix

  • 14.1. About Us and Services
  • 14.2. Contact Us