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世界および中国HDマップ産業:2019年~2020年

Global and China HD Map Industry Report, 2019-2020

発行 ResearchInChina 商品コード 929173
出版日 ページ情報 英文 260 Pages
納期: 即日から翌営業日
価格
本日の銀行送金レート: 1USD=109.83円で換算しております。
世界および中国HDマップ産業:2019年~2020年 Global and China HD Map Industry Report, 2019-2020
出版日: 2020年03月16日 ページ情報: 英文 260 Pages
概要

多くの自動車メーカーは、L3自動運転車分野に次々と参入しており、そのほとんどが2020年にL3モデルを発売する予定です。HDマップはL3自動運転車に不可欠であるため、HDマップ市場は急速な成長期を迎えています。

HDマップの進歩により、マッププロバイダーはデータサービスに目を向け、データ更新サービスの料金を定期的に得ています。 HDマップの単価は、従来のナビゲーションマップの少なくとも5倍(約200元/車両)であり、その後のサービス料金は年間100元程度です。2019年には、AutoNavi (amap.com) が、1台あたり年間100元以下の標準HDマップ料金を導入し、HDマップの普及を促進しました。

中国のHDマップ市場は2025年に90億元を超える規模になることが予測されます。

HDマップ市場はまだ立ち上がったばかりですが、2021年以降、ますます高度なコネクテッドビークル、またはICVにHDマップが搭載され、L3自動運転車が発売されると、この市場は活況は飛躍的に成長するでしょう。

当レポートでは、世界と中国のHDマップ産業について調査分析し、収集モードと技術分析、市場状況、産業チェーン、主要プロバイダーなど、体系的な情報を提供しています。

第1章 HDマップ産業

  • HDマップと技術の概念
  • HDマップの役割
    • 車両の位置情報
    • 経路計画と認識
    • 意思決定支援
    • シミュレーション用のHDマップ
    • V2XのHDマップ
    • HDマップアプリケーションの問題
  • HDマップの規格
    • 自動運転データリンクとエコシステム
    • マップ規格
  • HDマップの作成とメンテナンス
  • HDマップの市場規模
  • HDマップの競合パターン
  • HDマップ開発の課題
  • HDマップの開発動向

第2章 HDマップのサポート技術とデータ

  • HDマップのサポート技術
  • HDマップのデータ収集
  • MobileyeとHDマップ
  • Bosch HDマップテクノロジー
  • Qianxun SI
  • DMP (Dynamic Map Planning)

第3章 中国のマッププロバイダー

  • AutoNavi (amap.com)
  • Baidu Map
  • NavInfo
  • Tencent Map
  • Leador
  • eMapgo (EMG)
  • DiTu (Beijing) Technology
  • Momenta
  • Wuhan KOTEI Big Data Corporation
  • Jiangsu Zhitu Technology
  • JD Logistics
  • Photool Technology
  • Huawei Map
  • 中国マッププロバイダーのHDマップ開発ロードマップ
  • 主要3マッププロバイダーのHDマップ技術分析
  • 主要3マッププロバイダーのHDマップオーダー

第4章 国際マッププロバイダー

  • Here
  • TomTom
  • Waymo
  • ゼンリン
  • インクリメントP

第5章 HDマップのスターアップ企業

  • KuanDeng Technology
  • Deep Map
  • Civil Maps
  • lvl
  • Carmera
  • Wayz.ai
  • Ushr
  • DeepMotion
  • Mapbox
  • Dilu Technology
  • TrafficData
  • Netradyne

第6章 標準化団体

  • NDS
  • ADASIS
  • SENSORIS

第7章 結論

目次

HD map industry study: the HD map market is burgeoning with the roll-out of L3 autonomous vehicles.

The automakers (except Volvo, Ford and NIO that claimed a leap over L3) have set foot in L3 autonomous vehicle successively, and most of them are scheduled to launch L3 models in 2020.

As HD map is indispensable to an L3 self-driving car, the HD map market ushers in a period of rapid growth.

With the advances in HD map, the map providers are turning to the data services and getting data update service charges annually. HD map has a unit price at least five times higher than traditional navigation map (about 200 yuan/vehicle) and subsequent service fee stands at 100 yuan/year or so. In 2019, AutoNavi (amap.com) introduced the standard HD map fee below 100 yuan/year per vehicle, facilitating the prevalence of HD map.

As expected, the Chinese HD map market will be worth more than RMB9 billion in 2025.

The HD map market is now in its infancy and it has not been spawned yet, but the market will be booming after 2021 when more and more intelligent connected vehicles, or ICVs will be packed with HD map with the launch of L3 self-driving vehicle models. It can be seen from use of HD map in automakers' L3 self-driving cars to be soon mass-produced that the map leaders like Amap, Baidu Map, NavInfo and eMapgo stay ahead in HD map application.

In addition to HD map services for third parties, more companies applied in 2019 to be the eligible providers of electronic navigation mapping with class-A qualification, such as DiDi, Huawei and SF Express. JD.com is primarily focused on the maps for unmanned delivery vehicle often running on the non-motorway and JD thus needs to collect the HD map data about the non-motorway.

HD map is used mainly in the three including mobility service market, enclosed areas and parking areas. As concerns mobility service, the map providers like Baidu have tried mobility services such as RoboTaxi in China and beyond. In respect of enclosed area, SAIC has conducted a trial project "5G+L4 self-driving heavy truck" at the Shanghai Yangshan Deepwater Port. What's more, AVP (automated valet parking) remains a hotspot over the past two years, and the map providers like Baidu and eMapgo have already launched the map solutions for automated parking.

HD map is not only for autonomous vehicle but serves as a stimulus to the development of intelligent connected roads. In September 2019, the State Council put forward the importance of smart connected road construction in the Program of Building National Strength in Transportation. At the same time, China Highway and Transportation Society (CHTS) also issued the Levels of Intelligent Connected Roads and Interpretations. It is now at the L1 in China.

In the next three years, a total of about RMB75 billion will be invested to build intelligent road projects in China. HD map will be an integral part of smart road and will be onto the cloud as a platform. Moreover, it offers a unified space benchmark for roads. HD map is also an important carrier of smart road toll collection by service.

HD map is an emerging industry and is still short of unified industrial criteria, and the map vendors still apply de facto standard. An industrial standard will not be developed until the massive use of HD map in self-driving cars. China Autonomous Driving Map Working Group plans to nail down all kinds of autonomous driving map related standards and testing standards in 2022.

Table of Contents

1 HD Map Industry

  • 1.1 Concept of HD Map and Technologies
    • 1.1.1 Concept of HD Map and Technologies
    • 1.1.2 HD Map Composition
    • 1.1.3 HD Map Format
    • 1.1.4 ADAS MAP
    • 1.1.5 HAD MAP
    • 1.1.6 HD Map for L4
    • 1.1.7 Dynamic Map
    • 1.1.8 Static Map
  • 1.2 Role of HD Map
    • 1.2.1 Vehicle Positioning
    • 1.2.2 Path Planning and Perception
    • 1.2.3 Decision Aid
    • 1.2.4 HD Map for Simulation
    • 1.2.5 HD Map for V2X
    • 1.2.6 Difficulties in HD Map Application
  • 1.3 Standards on HD Map
    • 1.3.1 Autonomous Driving Data Link and Ecosystem
    • 1.3.2 Map Standards
  • 1.4 Production and Maintenance of HD Map
    • 1.4.1 Production Process
    • 1.4.2 Data Production of Static Map
    • 1.4.3 Data Update of Dynamic Map
    • 1.4.4 Tools for Acquisition of Dynamic Map
    • 1.4.5 Maintenance of HD Map
  • 1.5 HD Map Market Size
  • 1.6 Competitive Pattern of HD Map
  • 1.7 Challenges for Development of HD Map
    • 1.7.1 Mapping Costs of HD Map
    • 1.7.2 Technical Complexity
    • 1.7.3 Frequency of HD Map Updates
  • 1.8 Development Trend of HD Map
    • 1.8.1 From Professional Mapping to Crowdsourcing Update
    • 1.8.2 Elimination of Perceptual Error
    • 1.8.3 Diversified Competition
    • 1.8.4 HD Map Gets Used Increasingly with Mass Production of L3 Autonomous Vehicle
    • 1.8.5 Facilitate the Development of Intelligent Roads

2 HD Map Supporting Technologies and Data

  • 2.1 HD Map Supporting Technology
  • 2.2 Data Acquisition of HD Map
  • 2.3 Mobileye and HD Map
  • 2.4 Bosch HD Map Technology
  • 2.5 Qianxun SI
  • 2.6 Dynamic Map Planning

3 Chinese Map Providers

  • 3.1 AutoNavi (amap.com)
  • 3.2 Baidu Map
  • 3.3 NavInfo
  • 3.4 Tencent Map
  • 3.5 Leador
  • 3.6 eMapgo (EMG)
  • 3.7 DiTu (Beijing) Technology
  • 3.8 Momenta
  • 3.9 Wuhan KOTEI Big Data Corporation
  • 3.10 Jiangsu Zhitu Technology
  • 3.11 JD Logistics
  • 3.12 Photool Technology
  • 3.13 Huawei Map
  • HD Map Development Roadmap of Chinese Map Providers
  • HD Map Technology Analysis of Three Leading Chinese Map Providers
  • HD Map Orders of Three Leading Chinese Map Providers

4 Foreign Map Providers

  • 4.1 Here
  • 4.2 TomTom
  • 4.3 Waymo
  • 4.4 Zenrin
  • 4.5 Increment P

5 HD Map Starups

  • 5.1KuanDeng Technology
  • 5.2 Deep Map
  • 5.3 Civil Maps
  • 5.4 lvl 5
  • 5.5 Carmera
  • 5.6 Wayz.ai
  • 5.7 Ushr
  • 5.8 DeepMotion
  • 5.9 Mapbox
  • 5.10 Dilu Technology
  • 5.11 TrafficData
  • 5.12 Netradyne

6 Standardization Organizations

  • 6.1 NDS
  • 6.2 ADASIS
  • 6.3 SENSORIS

7 Conclusions

  • HD Map Market Players
  • Comparison between Foreign HD Map Companies
  • Comparison between Chinese HD Map Companies (I)
  • Comparison between Chinese HD Map Companies (II)
  • HD Map Business Model
  • Applied Scenarios of HD Map