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市場調查報告書

大型卡車的ADAS (先進駕駛輔助系統)

Advanced Driver Assistance Systems in Heavy Duty Trucking

出版商 Frost & Sullivan 商品編碼 590286
出版日期 內容資訊 英文 61 Pages
商品交期: 最快1-2個工作天內
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大型卡車的ADAS (先進駕駛輔助系統) Advanced Driver Assistance Systems in Heavy Duty Trucking
出版日期: 2017年10月31日 內容資訊: 英文 61 Pages
簡介

本報告提供大型卡車的ADAS (先進駕駛輔助系統) 技術趨勢調查,彙整市場定義和概要,各種硬體設備感測器套件趨勢,軟體及ECU的整合相關趨勢,電器及電子架構趨勢,車隊(編隊)管理和保險·賠償責任相關趨勢等各種安全技術趨勢·展望與其影響等資料。

第1章 摘要整理

  • 自動駕駛功能發展路程
  • 集中型處理
  • 48v的需求:自動駕駛對E/E架構的影響
  • 保險和資料利用
  • 賠償責任的變化

第2章 調查範圍·調查目的·背景·調查手法

第3章 硬體設備感測器套件

  • 安全技術的演進及其意義
  • 感測系統的錯誤
  • 光學感應技術趨勢
  • 雷達技術趨勢
  • LiDAR和設定
  • 典型傳感器套件ADAS應用的數據融合
  • ACC (主動車距控制巡航系統)的藍圖
  • LDW (車道偏離警告) 藍圖
  • BSD (死角檢測) 藍圖

第4章 軟體及ECU的整合

  • 處理能力
  • 分散式處理
  • 集中型處理
  • 安全性網域ECU
  • 汽車網路方案
  • 價值鏈分析

第5章 電子架構的演進

  • 目前電器及電子生態系統概要
  • 48v系統設計
  • 第一波和第二波技術的頂層分析
  • 48v的需求:自動駕駛對E/E架構的影響

第6章 對車隊(編隊)所有者來說的優點

  • 缺乏幹練的司機
  • 追尾事故的影響:北美
  • 追尾事故的影響:歐洲
  • 保險和資料利用
  • 降低追尾事故技術和保險費的影響
  • 賠償責任的變化

第7章 成長機會·推薦行動

  • 成長機會:附加價值服務·聯盟
  • 成功與成長的策略性要求

第8章 總論·未來展望

  • 總論
  • 總論:三大預測
  • 免責聲明

第9章 附錄

第10章 關於FROST & SULLIVAN

目錄
Product Code: K154-18

Next Generation of Truck Safety Advancement to be Enhanced by Faster Data Processing, System Integration, and Truck Digitization

Driver and technician shortage has emerged as the most important top-of-mind issue for fleet managers. This, coupled with concerns on economic outlook and operating margins, is predicating several choices that fleet managers are making with regards to advanced truck technologies. Potential benefits of safety, technology and lower operating costs will spur growth of autonomous trucking given issues to be resolved over liability, regulations and labor. Fleets involved in crashes are facing high-dollar jury verdicts currently with worsening severity of jury awards; in addition to this, safety profile of a fleet is focused more in a crash case than specifics of the accident. Access to data from safety systems will protect fleets from false claims and also aid in reducing insurance premiums owing to lower risk of accidents. Therefore, increased opportunities exist for prospective industry participants in integrating safety and fuel efficiency benefits across various technology platforms. Performing real-time computing for advanced safety technologies' sensor data input will require sophisticated and reliable hardware platform with sufficient high performance computing abilities; cloud platform is expected to aid in functionalities such as distributed computing and distributed storage for deep learning model training and HD map production.

The technical challenges of autonomous systems, in addition to the need for all digital components to communicate with each other continuously are expected to create gaps in the market for Tier 1 suppliers and semiconductor companies. Moreover, unfiltered, unbiased raw data will be preferred over traditional distributed processing in the future owing to the enhanced ability of the model to generate a complete view of the truck's environment through centralized processing. In the domain of in-vehicle networks, the demand for connectivity will force OEMs to look into new network technology such as Ethernet that can handle quick, large-volume, high-speed data transmissions to enable effective coordinated control across multiple functional domains in autonomous trucks. The inclusion of crash mitigating technologies and onboard cameras as standard features in trucks is expected to significantly reduce risk of collision, thereby reducing premiums. While insurance premium parameters are largely calculated based on fleet- or driver-related data, vehicle-related data such as autonomous driving algorithms, cybersecurity, and logic robustness are expected to feature in the calculations; liability for crashes is expected to shift to truck manufacturers.

The aim of this research service is to provide a strategic overview of the heavy-duty truck safety technologies enabling autonomous driving, including analysis of key market trends, and technology trends, and integration of electronic architecture for autonomous driving.

Table of Contents

1. EXECUTIVE SUMMARY

  • Functional Path Towards Autonomous Driving
  • Centralized Processing
  • Need for 48V-Impact of Automated Driving on E/E Architecture
  • Insurance and Use of Data
  • Changing Liability

2. RESEARCH SCOPE, OBJECTIVES, BACKGROUND, AND METHODOLOGY

  • Research Scope
  • Research Aims and Objectives
  • Key Questions this Study Will Answer
  • Research Background
  • Research Methodology

3. HARDWARE SENSOR SUITE

  • Safety Technology Evolution and Implications
  • Errors in Sensing Systems
  • Optical Sensor Technology Trends
  • Radar Technology Trends
  • Configurations with LiDAR
  • Data Fusion on Typical Sensor Suite for ADAS Application
  • Adaptive Cruise Control (ACC) Roadmap
  • Lane Departure Warning (LDW) Roadmap
  • Blind Spot Detection (BSD) Roadmap

4. INTEGRATION OF SOFTWARE AND ECU

  • Processing Power
  • Processing Power (continued)
  • Distributed Processing
  • Centralized Processing
  • Safety Domain ECU
  • In-vehicle Network Scenario
  • Value Chain Analysis

5. EVOLUTION OF ELECTRIC ARCHITECTURE

  • Overview of the Current Electrical and Electronic Ecosystem
  • 48V System Design
  • Top Level Analysis of First and Second Wave Technologies
  • Need for 48V-Impact of Automated Driving on E/E Architecture

6. BENEFITS TO FLEET OWNERS

  • Shortage of Skilled Drivers
  • Impact of Collisions-North America
  • Impact of Collisions-Europe
  • Insurance and Use of Data
  • Impact of Crash Mitigating Technologies on Premiums
  • Changing Liability

7. GROWTH OPPORTUNITIES AND COMPANIES TO ACTION

  • Growth Opportunity-Value-add Services and Partnerships
  • Strategic Imperatives for Success and Growth

8. CONCLUSIONS AND FUTURE OUTLOOK

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

9. APPENDIX

  • Acronyms Used

10. THE FROST & SULLIVAN STORY

  • The Frost & Sullivan Story
  • Value Proposition-Future of Your Company & Career
  • Global Perspective
  • Industry Convergence
  • 360° Research Perspective
  • Implementation Excellence
  • Our Blue Ocean Strategy
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