表紙
市場調査レポート

自動運転車 (ロボットカー) の進化:自動車産業への今後の影響

The Autonomous Vehicle Revolution: How it Will Affect the Automotive Sector

発行 Autelligence 商品コード 325474
出版日 ページ情報 英文 185 Pages
納期: 即日から翌営業日
価格
本日の銀行送金レート: 1USD=102.95円で換算しております。
Back to Top
自動運転車 (ロボットカー) の進化:自動車産業への今後の影響 The Autonomous Vehicle Revolution: How it Will Affect the Automotive Sector
出版日: 2015年04月30日 ページ情報: 英文 185 Pages
概要

当レポートでは、自動運転車 (ロボットカー) の発展の経緯と見通しについて調査し、各種実現技術の動向、関連の法規制・リスク・訴訟問題、ビジネスモデル、バリューチェーンの開発、従来の自動車部品・システムへの影響、主要事業者のプロファイルなどをまとめています。

イントロダクション

  • イントロダクション
  • 消費者による受容

自動運転車 (ロボットカー) の進化

  • ドライバーレスの未来へ
  • ADAS:次レベルの実現

法規制・リスク・訴訟

  • 追突の頻度の削減
  • 賠償責任上の落し穴
  • 政策の視点から見るコストと利便性

実現技術

  • 通信
  • The Connected Vehicle Programme
  • CAR 2 CAR
  • オートモーティブネットワークの設計
  • ネットワークのタイプと設計
  • システムエンジニアリング
  • CAN
  • LIN
  • イーサネット
  • FlexRay
  • イーサネットかFlexRayか?
  • MOST
  • ソフトウェア
  • 増す複雑性との協調
  • AUTOSAR
  • GENIVI Alliance
  • AutoLinQ
  • Microsoft Auto
  • ElectroBit
  • JasPar
  • Robot Operating System (ROS)
  • ドメインコントローラーアプローチ
  • センサー
  • 赤外線
  • レーダー
  • ライダー
  • カメラシステム
  • 超音波センサー
  • 暗視強化
  • クラスタ型センサー・センサーモジュール・センサー融合
  • HMI (ヒューマンマシンインターフェース)/ドライバービークルインターフェース
  • マッピング&位置情報の取得

産業力学・ビジネスモデル

  • 増分的かディスラプティブか?
  • 自動車を所有するか時間を買うか?
  • バリューチェーンの開発

従来の自動車部品・システムへの影響

  • パワートレイン
  • シャーシシステム
  • 内装
  • 外装

付録:最近の発表・トライアル

企業プロファイル

  • アイシン精機
  • Apple
  • Baidu
  • BMW
  • Continental
  • Daimler
  • Delphi
  • デンソー
  • Ford
  • General Motors
  • Google
  • Hella
  • Here
  • Hyundai Motors
  • Jaguar Land Rover
  • Mobileye
  • Omron
  • Smarteye
  • トヨタ
  • TRW
  • Valeo
  • Velodyne
  • Visteon
  • Volkswagen
  • Volvo

図表

目次

Authoritative overview of the current state of the autonomous car and its impact on the automotive industry - innovations, technology, legislation, business models, and innovation and activity profiles of significant industry players, both OEMs, suppliers, and non-automotive.

The pace of progress to automate cars over the last few years has been startling. The way that consumers interact with cars as well as the way that they operate will transform most functions in road vehicles, in small as well as major ways - but it is not yet clear exactly how as Dieter Zetsche, chairman of Daimler and head of Mercedes-Benz Cars states, “Anyone who focuses solely on the technology has not yet grasped how autonomous driving will change our society”.

The “Digitales Testfeld Autobahn” in January 2015 was important for Germany (and Europe) to ensure that the European automotive industry does not become a follower and lose control of its destiny in the automotive marketplace. Europe needs to address and master new technology and its implications, in the face of innovation from outside and inside the industry in the United States and Asia, in an effort to maintain its leading position in automotive technology.

OEMs and suppliers throughout the automotive sector know that it is time for executives and companies in the industry to do their homework and think through the implications of this potentially revolutionary change that is the autonomous car. Whether fully driverless or not the technology has tremendous implications for the hardware and software that control the operations of the vehicle, the way they are specified and developed.

“Anyone who focuses solely on the technology has not yet grasped how autonomous driving will change our society” - Dieter Zetsche, chairman of Daimler and head of Mercedes-Benz Cars.

It has major implications for the way cars communicate with the outside world, with each other, and with the driver or occupants. It has implications for the functions that drivers and car owners expect on their vehicles.

And ultimately because it affects the way consumers interact with vehicles, it has implications for interior and exterior design, and in the end for all the major hardware areas of the vehicles - chassis, powertrain and transmission.

Report coverage:

  • Timeline for the development of innovations in the field of the autonomous car, to give a clear perspective on what has been happening.
  • Modifications and adaptation in mature areas of the vehicle technology, as well as disruptive new ideas.
  • Regulation, risk and litigation
  • Enabling technology
  • Automotive network design
  • Software, Sensors, Human/machine interface
  • Industry dynamics and business models
  • Profiles innovations and activities of a large number of the significant players - OEMS and suppliers - active in the field, including companies new to the automotive space.

Table of Contents

Introduction

  • Introduction
  • Consumer acceptance

The evolution of the autonomous car

  • Towards a driverless future
  • ADAS: Enabling the next level

Regulation, risk and litigation

  • Reducing crash frequency
  • The liability trap
  • Cost and convenience from a policy perspective

Enabling Technology

  • Communications
  • The Connected Vehicle Programme
  • CAR 2 CAR
  • Automotive network design
  • Network types and design
  • Systems Engineering
  • CAN
  • LIN
  • Ethernet
  • FlexRay
  • Ethernet or FlexRay?
  • MOST
  • Software
  • Coping with growing complexity
  • AUTOSAR
  • GENIVI Alliance
  • AutoLinQ
  • Microsoft Auto
  • ElectroBit
  • JasPar
  • Robot Operating System (ROS)
  • Domain Controller approach
  • Sensors
  • Infrared
  • Radar
  • Lidar
  • Camera systems
  • Ultrasonic sensors
  • Night vision enhancement
  • Clustered sensors, sensor modules and sensor fusion
  • Human machine interface/ driver vehicle interface
  • Mapping and position acquisition

Industry dynamics and business models

  • Incremental or disruptive?
  • Owning a car or buying time?
  • Value chain development

Effects on traditional vehicle components and systems

  • Powertrain
  • Chassis systems
  • Interior
  • Exterior

Appendix - Tables of recent announcements and trials

Company Profiles

  • Aisin Seiki
  • Apple
  • Baidu
  • BMW
  • Continental
  • Daimler
  • Delphi
  • Denso
  • Ford
  • General Motors
  • Google
  • Hella
  • Here
  • Hyundai Motors
  • Jaguar Land Rover
  • Mobileye
  • Omron
  • Smarteye
  • Toyota
  • TRW
  • Valeo
  • Velodyne
  • Visteon
  • Volkswagen
  • Volvo

Table of tables

  • Table 1: US National Highway Traffic Safety Administration (NHTSA) definition of automation levels
  • Table 2: Bus and communication standards comparison
  • Table 3: The role of digital mapping in providing sensor type information for ADAS systems
  • Table 4: Key operational and investment considerations for stakeholders within the autonomous vehicle value chain
  • Table 5: Strategic considerations for key stakeholders in the autonomous vehicle value chain
  • Table 6: Recent OEM and supplier announcements and NHTSA level
  • Table 7: Summary of autonomous vehicle technology trials announced 2013 - 2015

Table of figures

  • Figure 1: When will each OEM bring an automated car to market
  • Figure 2: Comparison between autonomous car level classifications
  • Figure 3: Various predictions about autonomous car availability
  • Figure 4: Automated driving requires systems expertise
  • Figure 5: Consumer levels of trust for automated vehicles
  • Figure 6: ADAS overall market value by system type
  • Figure 6: Legal situation for driverless cars within the US
  • Figure 7: Electrical power requirements versus time
  • Figure 8: Examples of automotive sensor applications
  • Figure 9: Market segmentation development for in-vehicle networks
  • Figure 10: Cost versus speed for automotive communication standards
  • Figure 11: Uses for the various communication standards
  • Figure 12: A schematic representation of the FlexRay architecture
  • Figure 13: A MOST Infotainment system in a heterogeneous networking environment
  • Figure 14: AUTOSAR software architecture showing components and interfaces
  • Figure 15: AUTOSAR membership
  • Figure 16: Typical existing automotive domain characteristics
  • Figure 17: Domain requirements for autonomous driving
  • Figure 18: High level architecture building blocks for autonomous vehicles
  • Figure 19: High performance domain control ECUs can simplify overall network complexity
  • Figure 20: Estimated sensor market size ($ billion)
  • Figure 21: A slip control system ECU with integrated inertial control sensors
  • Figure 22: Fusing multiple sensor information for driver assistance systems
  • Figure 23: A schematic showing the operation of Delphi's electronic scanning radar
  • Figure 24: Volvo XC90 features Delphi's RACam system, enabling a wide range of active safety features
  • Figure 25: Evolution of Bosch radar sensors
  • Figure 26: Relative importance of technologies in autonomous cars
  • Figure 27: A Bosch schematic representation of its stereo camera system
  • Figure 28: Bosch stereo video sensor package
  • Figure 29: BMW X5 night vision display
  • Figure 30: Hella's active night vision system
  • Figure 31: Image showing pedestrian using visual and IR
  • Figure 32: Image showing highlighted animals
  • Figure 33: Mercedes-Benz Active Night View Assist with Spotlight Function
  • Figure 34: Audi Night Vision system
  • Figure 35: The effects of low and high spatial resolution (4 GHz vs 79GHz)
  • Figure 36: Progress towards a global harmonized 79Hz radar frequency
  • Figure 37: Aggregate volume for radar sensors supplied by Bosch
  • Figure 38: Top four HMI research questions in need of investigation
  • Figure 39: High definition mapping from Nokia HERE
  • Figure 40: A schematic of the map integration concept developed by the MAPS&ADAS sub-project
  • Figure 41: Shares of the autonomous car value chain
  • Figure 42: Potential commercial risks and opportunities with autonomous vehicles
  • Figure 44: Powertrain development roadmap to 2050
  • Figure 45: Chassis systems evolution
  • Figure 46: Interior connectivity
  • Figure 47: Mercedes-Benz F015 concept interior
  • Figure 48: Mercedes-Benz F015 concept interior
  • Figure 49: Mercedes-Benz F015 concept exterior
  • Figure 50: Mercedes-Benz F015 concept exterior
Back to Top