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市場調查報告書

自動泊車輔助 (APA) 和自動代客泊車 (AVP) 行業(2021 年)

Automated Parking Assist (APA) and Automated Valet Parking (AVP) Industry Report, 2021

出版商 ResearchInChina 商品編碼 1005365
出版日期 內容資訊 英文 210 Pages
商品交期: 最快1-2個工作天內
價格
自動泊車輔助 (APA) 和自動代客泊車 (AVP) 行業(2021 年) Automated Parking Assist (APA) and Automated Valet Parking (AVP) Industry Report, 2021
出版日期: 2021年05月13日內容資訊: 英文 210 Pages
簡介

2020年我國搭載APA的乘用車保有量23.8萬輛,同比增長46.4%,搭載APA的比例比2019年提高4.28個百分點至12.3%。 2020 年 APA 安裝率總體呈現穩定增長,但由於 COVID-19 大流行導致乘用車銷量下降,2 月份有所下降。目前在售的兼容APA的車型大多是奔馳、寶馬、別克等海外品牌。

本報告考察了全球和中國自動泊車輔助(APA)和自動代客泊車(AVP)行業,包括技術、商業模式、產品和解決方案、為APA和AVP領先供應商的OEM停車,提供智能等信息主要公司的分析和簡介。

目錄

第 1 章自動泊車概念與技術

  • 自動泊車的概念和定義
    • 自動泊車輔助 (APA) 和自動代客泊車 (AVP) 的概念
    • AVP系統典型架構及分類
    • 博世定義的自動泊車等級和演變
    • ResearchInChina 定義的自動泊車的水平和演變
    • 停車場景介紹
    • APA、RPA、AVP傳感器配置及典型應用場景
    • AVP應用場景
    • AVP 標準和法規
  • 自動泊車系統配置及技術
    • 自動泊車系統配置
    • 自動泊車系統示意圖
    • 3 個 AVP 技術路線圖的比較
    • 主要AVP供應商的解決方案比較
    • 量產車停車智能對比
  • AVP系統發展趨勢
    • AVP 發展趨勢
    • 2020年APA/AVP主要供應商動態
    • OEM智能停車介紹(2020-2021)
    • 日本AVP申請進展

第二章自動停車市場

  • AVP 市場規模
  • APA安裝數量和安裝率(2019-2020)
  • APA月度安裝量及同比增速(2019-2020)
  • APA月度安裝率及同比增速(2019-2020)
  • 按價格劃分的APA安裝數量和安裝率(2019-2020)
  • 按國家/地區劃分的 APA 安裝數量和比率(2019-2020 年)
  • 按價格範圍劃分的 APA 安裝率(2019-2020 年)
  • APA安裝TOP15品牌(2019-2020)
  • APA 安裝的 TOP15 模型(2019-2020)
  • 按品牌和型號劃分的 APA 兼容型號排名(2020 年)
  • APA 兼容車型占汽車總銷量的百分比(2019-2020 年)
  • 中國 APA 和 AVP 安裝率(2014-2024E)

第三章 APS/AVP 技術提供商

  • 法雷奧
  • 博世
  • 現代摩比斯
  • 縱目科技
  • 優視科技
  • 百度
  • 全息
  • 洞察力
  • 動量
  • 斯昆辰科技
  • ForVision智能技術
  • 摩托維斯
  • 零最大值
  • 空間
  • TJD 停車場
  • 德賽SV
  • 智行者加
  • 靜車
  • 大疆汽車
  • 華為
  • 採埃孚
  • ihorseai

第四章OEM APA/AVP應用現狀及趨勢

  • 大眾
    • 智能停車的演進
    • 自動停車測試和停車支持服務
    • VW Touareg Autonomous Driving 自動泊車
  • 特斯拉
    • 特斯拉MODEL 3自動泊車功能
    • Tesla MODEL Y 自動泊車功能
    • 特斯拉智能召喚
  • 長安汽車
    • 停車場介紹
    • 自動泊車技術發展規劃
    • 智能停車技術演進
    • APA 6.0智能遠程泊車技術特點
  • 吉利
    • 自動泊車技術路線圖
    • 智能停車技術演進
    • 智能停車系統的特點
    • "爬行者" 智能停車系統
    • 自動停車操作模式
    • 自動停車+自動充電技術介紹
    • 吉利星月L 5G-AVP系統
    • 吉利5G-AVP 1km自動泊車技術
  • 小鵬汽車
    • 自動泊車技術路線圖
    • 智能停車技術演進
    • 小鵬G3全場景自動泊車
    • 小鵬P7手機泊車輔助
    • 小鵬P5停車場記憶停車
  • 上汽
    • 上汽榮威智能停車技術演進
    • 上汽榮威MARVEL X 最後一公里自動泊車系統
    • 上汽榮威MARVEL XAI 自學停車
    • 上汽榮威MARVEL R 一體化全自動泊車
    • 上汽通用五菱推廣 "自動泊車+共享出行" 運營模式
  • 奇瑞
    • APA/AVP進展
    • 奇瑞超越APA
    • Cherry EXEED APA 的特點
    • 使用Cherry EXEED APA的注意事項
  • 海關總署
    • 自動停車場維護計劃
    • 廣汽AION智能停車技術演進
    • 廣汽AION V智能遠程泊車特點
  • Weltmeister
    • 智能自動泊車的演進
    • Welt Meister W6 AVP
    • Weltmeister W6 Cloud AVP 應用場景
目錄

Intelligent parking research: mass adoption of AVP will begin in 2023.

Our Automated Parking Assist (APA) and Automated Valet Parking (AVP) Industry Report, 2021 combs through technology routes, business models, products and solutions of major APA and AVP suppliers, and parking intelligence of OEMs.

In 2020, the installation rate of APA reached 12.3%, 4.28 percentage points higher than a year ago.

According to ResearchInChina, in 2020, China had 2,308,000 passenger cars equipped with APA, an annualized upsurge of 46.4%, taking the installation rate of APA to 12.3%, up 4.28 percentage points versus 2019; in 2020, the installation rate of APA made a steady growth as a whole, but a decline in February due to the reduced passenger car sales caused by the COVID-19 pandemic.

Wherein, among APA-enabled models that sell well, most are foreign brands like Mercedes-Benz, BMW and Buick.

Fully automated parking assist (F-APA) and remote parking are major intelligent parking system solutions at present.

In OEM market, L3 memory parking and L4 APA capabilities begin to become available to mid-to-high-end and luxury models.

For AVP single vehicle intelligence technologies, memory parking is firstly landed; at the parking lot end, AVP is firstly used in P3 and P4 parking lots.

Automated valet parking (AVP) allows a user who gets off at the designated drop-off point to send a parking instruction via the mobile APP to his/her car which will then drive itself to the parking spot without manual operation and monitoring; as the user gives a pick-up instruction on the APP, the car following the instruction will automatically go to the designated pick-up point; if several cars receive the parking instruction at the same time, they will wait to enter the parking space one after another automatically.

The study shows that AVP that renders vehicles more intelligent can promote vehicle sales, cut down 30% operating cost for parking lots, reduce 10% invalid traffic time in parking lots, and save 10-15 minutes in vehicle pick-up and returning.

The AVP market accommodates large numbers of players which mainly provide three technology solutions: single vehicle intelligence, parking lot intelligence, and vehicle-parking lot cooperation. Of them, single vehicle intelligence primarily supplied by Baidu and ZongMu Technology are most often used by OEMs. In September 2020, at Auto China, the full-size E-HS9 SUV BEV of New Hongqi started pre-sale. This model packs AVP system from ZongMu Technology.

Baidu is a typical provider of AVP single vehicle intelligence solutions. The firm has planned the implementation route for AVP system from short distance to long distance, from easy to difficult. The memory parking (Home-AVP) is the first one to be landed.

Home-AVP: memory parking. From elevator to parking spot, learn one time; users summon or return cars outside using their mobile phones, and their cars can drive themselves;

Public-AVP: from any pick-up or drop-off point in the parking lot, users park their cars anywhere in the parking lot, and the cars will automatically find a parking space; the summoned cars will drive themselves to the place designated by users;

Urban-AVP: from pick-up or drop-off point at most 1km away from the parking space to the parking space, users can summon or return their cars at their will, and the cars will drive themselves.

Bosch is a typical parking lot intelligence solution provider. Together with Mercedes-Benz and the parking lot operator Apcoa, Bosch has deployed a set of AVP system for trial commercial operation at the car park P6 at Stuttgar Airport.

Vehicle-parking lot cooperation solution providers are led by Huawei. The solution is the hardest one to be commercialized for it is difficult to coordinate multiple stakeholders involved (e.g., property companies, independent parking solution providers, OEMs, and mobility platform operators).

The General Technical Requirements of Automated Valet Parking Systems firstly defines parking lot standards.

In current stage, AVP standards are mainly formulated by associations. To fill the gaps in AVP industry standards in China and deal with the challenge of AVP compatible with multiple solutions, China-SAE and China Communications Industry Association introduced the General Technical Requirements of Automated Valet Parking Systems (T/CSAE156-2020) in December 2020.

The standard covers the three technology routes: single vehicle intelligence, parking lot intelligence and vehicle-parking lot cooperation. It has four parts of content: system definition, security application scenarios, general technical requirements of the system, and general technical requirements of testing.

The General Technical Requirements of Automated Valet Parking Systems defines levels of intelligent parking lots: P0, P1, P2, P3, P4 and P5.

According to the table above, P2 parking lots meet the conditions needed by AVP single vehicle intelligence; P4 parking lots are basically qualified for being AVP parking lots at the strong end; P3 parking lots meet the conditions of AVP parking lots at the weak end, with most CVIS solutions deployed in P3 parking lots.

Most insiders argue that CVIS is the future of AVP. After exchanges with experts, we believe any technology roadmap needs a subject of responsibility for safety, that is, who takes charge of the safety of AVP system, vehicle end or parking lot end? We think the subject of responsibility at the strong end should be parking lot operators and AVP technology providers, and at the weak end, the OEMs and AVP technology providers.

Application of AVP in P2 parking lots needs L4 intelligent vehicles which are however unlikely to be mass-produced shortly (before 2025). Even if P2 parking lots are built, there will be few vehicles available. So before 2025, parking lots (P3/P4) that support CVIS solutions have plenty of room for growth.

As a substandard of the General Technical Requirements of Automated Valet Parking Systems, the Technical Requirements of Automated Valet Parking Maps and Positioning is under discussion and expected to be drafted in December 2021. The study of other AVP substandards such as AVP parking lot communications, AVP test and memory parking is in the pipeline.

OEMs step up R&D of intelligent parking systems for mass production

OEMs are accelerating R&D of intelligent parking systems for mass production by way of independently developing or seeking external collaborations. Some OEMs like Weltmeister have achieved AVP for L4 automated driving in designated scenarios through working with Baidu; Geely with 5G-AVP technology enabling 1km autonomous parking will step into exploration of intelligent cloud based AVP; with a plan of trying to equip some of its models with memory parking function in late 2020, GAC has installed AVP function in some high-end and luxury models in 2021H1; Great Wall Motor and Baidu Apollo have worked together on mass production of AVP, and announced to spawn AVP-enabled vehicles in 2021.

There is a common belief that the pace of AVP system testing will quicken to gear up for use in vehicles between 2021 and 2022, and the mass adoption of AVP system will begin in 2023.

For parking business models, parking lot operators, OEMs and AVP solution providers make profits by charging AVP subscription fee or pay-per-use billing. Parking lot operators also make benefits with value-added services derived from intelligent parking systems. An example is Bosch which combines electric vehicle automatic charging, autonomous washing of vehicles and express delivery to provide complete solutions for parking lot operators.

Table of Contents

1 Automated Parking Concept and Technologies

  • 1.1 Concept and Definition of Automated Parking
    • 1.1.1 Concepts of Automated Parking Assist (APA) and Automated Valet Parking (AVP)
    • 1.1.2 Typical Architecture and Classification of AVP System
    • 1.1.3 Bosch-defined Levels and Evolution of Automated Parking
    • 1.1.4 ResearchInChina-defined Levels and Evolution of Automated Parking
    • 1.1.5 Introduction to Parking Scenarios
    • 1.1.6 Sensor Configurations of APA, RPA and AVP and Typical Application Scenarios
    • 1.1.7 AVP Application Scenarios
    • 1.1.8 AVP Standards and Regulations
  • 1.2 Composition and Technologies of Automated Parking System
    • 1.2.1 Composition of Automated Parking System
    • 1.2.2 Schematic Diagram of Automated Parking System
    • 1.2.3 Comparison of Three AVP Technology Roadmaps
    • 1.2.4 Comparison of Solutions between Major AVP Providers
    • 1.2.5 Comparison of Degree of Parking Intelligence between Some Mass-produced Models
  • 1.3 Development Trends of AVP System
    • 1.3.1 Development Trends of AVP
    • 1.3.2 Dynamics of Major Suppliers in APA/AVP in 2020
    • 1.3.3 Intelligent Parking Deployments of OEMs, 2020-2021
    • 1.3.4 Japan's Progress in AVP Application

2 Automated Parking Market

  • 2.1 AVP Market Size
  • 2.2 Installations and Installation Rate of APA, 2019-2020
  • 2.3 Monthly Installations of APA and YoY Growth, 2019-2020
  • 2.4 Monthly Installation Rate of APA and YoY Growth, 2019-2020
  • 2.5 Installations and Installation Rate of APA by Price, 2019-2020
  • 2.6 Installations and Installation Rate of APA by Country, 2019-2020
  • 2.7 Installation Rate of APA by Price Range, 2019-2020
  • 2.8 TOP15 Brands by Installations of APA, 2019-2020
  • 2.9 TOP15 Models by Installations of APA, 2019-2020
  • 2.10 Ranking of APA-enabled Models by Brand/Model, 2020
  • 2.11 APA-enabled Models as a Percentage of Total Vehicle Sales, 2019-2020
  • 2.12 Installation Rates of APA & AVP in China, 2014-2024E

3 APS/AVP Technology Providers

  • 3.1 Valeo
    • 3.1.1 Parking Business
    • 3.1.2 Evolution of Parking Technology
    • 3.1.3 Automated Parking Development Roadmap
    • 3.1.4 Park4U and Cyber Valet Services
    • 3.1.5 New-generation Park4U® Charge Automated Parking System
    • 3.1.6 Layout of Automated Parking in China
  • 3.2 Bosch
    • 3.2.1 ADAS/Parking Product Layout
    • 3.2.2 Automated Parking Planning
    • 3.2.3 Automated Parking Technology Roadmap
    • 3.2.4 Automated Parking Business Model
    • 3.2.5 L2 Automated Parking Technology and Supported Models
    • 3.2.6 AVP System Architecture, AVP Safety and Security Concepts
    • 3.2.7 AVP Solution Cooperated with Daimler
    • 3.2.8 AVP Solution Cooperated with Ford
    • 3.2.9 AVP Partners
    • 3.2.10 AVP Customers
  • 3.3 Hyundai Mobis
    • 3.3.1 AVPS
    • 3.3.2 AVP and Wireless Charging
  • 3.4 ZongMu Technology
    • 3.4.1 Profile
    • 3.4.2 Automated Parking Development Roadmap
    • 3.4.3 Automated Parking Technology Roadmap
    • 3.4.4 Automated Parking Business Model
    • 3.4.5 AVP/HPP System Architecture
    • 3.4.6 Evolution of Automated Parking System
    • 3.4.7 Features of Second-generation Automated Parking System
    • 3.4.8 L3 Parking Platform
    • 3.4.9 L4 Automated Parking System Services and Products
    • 3.4.10 Partners
    • 3.4.11 Customers
  • 3.5 Uisee Technology
    • 3.5.1 Profile
    • 3.5.2 Automated Parking Technology Roadmap and Progress
    • 3.5.3 Application of AVP Technology
    • 3.5.4 Partners
  • 3.6 Baidu
    • 3.6.1 Apollo AVP
    • 3.6.2 Automated Parking Development Roadmap
    • 3.6.3 Automated Parking Technology Roadmap
    • 3.6.4 Core of Automated Parking Technology
    • 3.6.5 Features of Automated Parking Technology
    • 3.6.6 Automated Parking Safety Framework and Partners
    • 3.6.7 Cooperated with Weltmeister on Implementation of Automated Parking Technology
    • 3.6.8 Baidu Cloud AVP Cloud Automated Parking System
  • 3.7 Holomatic
    • 3.7.1 Profile
    • 3.7.2 Features of HoloParking
    • 3.7.3 Automated Parking Business Model and Technology Roadmap
    • 3.7.4 Dynamics
  • 3.8 Intesight
    • 3.8.1 Profile
    • 3.8.2 Parking System Development Plan
    • 3.8.3 Fully Automated Parking System
    • 3.8.4 AVP System
  • 3.9 Momenta
    • 3.9.1 Profile
    • 3.9.2 Autonomous Driving Priority Scenarios and Technology Roadmap
    • 3.9.3 Mpilot Parking Automated Parking Technology Roadmap
    • 3.9.4 Mpilot Parking Automated Parking Solution Sensor Configuration
    • 3.9.5 Mpilot Parking Intelligent Parking Development Roadmap
  • 3.10 SKunchen Technology
    • 3.10.1 Profile
    • 3.10.2 Autonomous Driving Location Product Roadmap
    • 3.10.3 UWB-based AVP Application Solutions
    • 3.10.4 Automated Parking Business Model
    • 3.10.5 AVP Cooperation Projects
  • 3.11 ForVision Intelligent Technology
  • 3.12 Motovis
    • 3.12.1 Profile
    • 3.12.2 Automated Parking Technology Roadmap
    • 3.12.3 V-SLAM-based Automated Parking Technology
    • 3.12.4 APA and AVP Solutions
    • 3.12.5 Remote Automated Parking Technology
    • 3.12.6 Latest Cooperation Dynamics in Automated Parking
  • 3.13 Nullmax
    • 3.13.1 Profile
    • 3.13.2 Automated Parking Technology Roadmap
    • 3.13.3 Features of Automated Parking Solution
    • 3.13.4 Strategic Cooperation
  • 3.14 SPACE
    • 3.14.1 Profile
    • 3.14.2 Vehicle-Parking Lot-Cloud Cooperation AVP Module Architecture and Development Plan
    • 3.14.3 Evolution of AVP for Low-speed Autonomous Driving System
    • 3.14.4 Cross-border Strategic Cooperation in Automated Parking
  • 3.15 TJD Parking
    • 3.15.1 Profile
    • 3.15.2 Build a New Internet Intelligent Parking Ecosystem
    • 3.15.3 Deployments in Automated Parking
  • 3.16 Desay SV
    • 3.16.1 Deployments in Automated Parking
    • 3.16.2 Parking Intelligence Plan
  • 3.17 Idriverplus
    • 3.17.1 Profile
    • 3.17.2 Enhanced Vision Labeled AVP System Solution
    • 3.17.3 AVP Solution
    • 3.17.4 Advantages of Enhanced Vision Labeled AVP System Solution
  • 3.18 CalmCar
    • 3.18.1 Profile
    • 3.18.2 Automated Parking Solution
    • 3.18.2 Parking Lot AVP Solution
  • 3.19 DJI Automotive
    • 3.19.1 Profile
    • 3.19.2 Parking System Application Scenarios
    • 3.19.3 Comparison of DJI Intelligent Parking Solutions
    • 3.19.4 DJI Intelligent Parking System Configurations
  • 3.20 Huawei
    • 3.20.1 Development History and Technology Roadmap of Automated Parking Project
    • 3.20.2 Follow-up Plan for Automated Parking Project
    • 3.20.3 AVP Intelligent Parking Solution
    • 3.20.4 Development Roadmap of AVP
  • 3.21 ZF
    • 3.21.1 Development History of Automated Parking
    • 3.21.2 Automated Parking Technology Roadmap
  • 3.22 ihorseai

4 Application Status and Trends of APA/AVP of OEMs

  • 4.1 Volkswagen
    • 4.1.1 Evolution of Intelligent Parking
    • 4.1.2 Automated Parking Test and Parking Supporting Services
    • 4.1.3 Automated Parking for VW Touareg Autonomous Driving
  • 4.2 Tesla
    • 4.2.1 Tesla MODEL 3 Automated Parking Function
    • 4.2.2 Tesla MODEL Y Automated Parking Function
    • 4.2.3 Tesla Smart Summon
  • 4.3 Changan Automobile
    • 4.3.1 Deployments in Parking
    • 4.3.2 Development Plan for Automated Parking Technology
    • 4.3.3 Evolution of Intelligent Parking Technology
    • 4.3.4 Features of APA6.0 Intelligent Remote Parking Technology
  • 4.4 Geely
    • 4.4.1 Automated Parking Technology Roadmap
    • 4.4.2 Evolution of Intelligent Parking Technology
    • 4.4.3 Features of Intelligent Parking System
    • 4.4.4 "Creeper" Intelligent Parking System
    • 4.4.5 Automated Parking Operation Mode
    • 4.4.6 Introducing Automated Parking + Automatic Charging Technology
    • 4.4.7 Geely Xingyue L 5G-AVP System
    • 4.4.8 Geely 5G-AVP 1km Automated Parking Technology
  • 4.5 Xiaopeng Motors
    • 4.5.1 Automated Parking Technology Roadmap
    • 4.5.2 Evolution of Intelligent Parking Technology
    • 4.5.3 Xpeng G3 All-Scenario Automated Parking
    • 4.5.4 Xpeng P7 Mobile Parking Assist
    • 4.5.5 Xpeng P5 Parking Lot Memory Parking
  • 4.6 SAIC
    • 4.6.1 Evolution of SAIC Roewe Intelligent Parking Technology
    • 4.6.2 SAIC Roewe MARVEL X Last-mile Automated Parking System
    • 4.6.3 SAIC Roewe MARVEL X AI Self-learning Parking
    • 4.6.4 SAIC Roewe MARVEL R Integrated Fully Automated Parking
    • 4.6.5 SAIC-GM-Wuling Promotes the "Automated Parking + Shared Mobility" Operation Model
  • 4.7 Chery
    • 4.7.1 Progress in APA/AVP
    • 4.7.2 Chery EXEED APA
    • 4.7.3 Features of Chery EXEED APA
    • 4.7.4 Precautions for Chery EXEED APA
  • 4.8 GAC
    • 4.8.1 Automated Parking Development Plan
    • 4.8.2 Evolution of GAC AION Intelligent Parking Technology
    • 4.8.3 Features of GAC AION V Intelligent Remote Parking
  • 4.9 Weltmeister
    • 4.9.1 Evolution of Intelligent Automated Parking
    • 4.9.2 Weltmeister W6 AVP
    • 4.9.3 Application Scenarios of Weltmeister W6 Cloud AVP