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自动送货车辆行业（2022 年）
市场调查报告书
商品编码
1130739

自动送货车辆行业（2022 年）

Autonomous Delivery Vehicle Industry Report, 2022
出版日期: | 出版商: ResearchInChina | 英文 180 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

预计到 2025 年，中国户外自动送货车市场规模将达到约 170 亿元人民币。中国国家邮政局数据显示，2022年1-7月，中国快递企业共处理包裹608.7亿件，其中1-6月投递512.2亿件，同比增长3.7% ，7月份为96.5亿，增长8.0%）。企业正在推动成本节约和效率提升。

2021 年 5 月，中国在示范区的公共道路上清理了第一批自动驾驶送货车。 2022年上海疫情期间，500多辆自动送货车齐聚一堂，服务疫区。这样一来，通过对各种场景的适配和技术优化验证，自动送货车的应用范围越来越广。

本报告探讨自动送货车行业，重点研究中国和世界户外地面自动送货车、市场规模、行业趋势、发展、政策，我们提供简介等信息的大公司。

内容

第一章自动送货车辆

  • 定义和分类
  • 主要应用场景
  • 户外自动驾驶配送应用场景
  • 自动送货车系统配置
  • 自动送货车的主要传感器和功能
  • 用于自动送货车辆的线控底盘
  • 自动送货车计算平台
  • 自动驾驶交付产业链
  • 部分自动送货车的参数信息
  • 2022 年上半年新增自动配送产品
  • 自 2021 年至 2022 年上半年自动配送应用范围扩大
  • 自动交付商业化阶段
  • 自动送货车辆面临的挑战
  • 日本主要自动驾驶配送公司的发展情况
  • 国外主要自动驾驶车辆的商业化进展

第2章自主配送相关政策

  • 国内自动驾驶配送相关政策
  • 国外自主配送政策：美国
  • 国外自主配送政策：欧洲
  • 国外自主配送政策：日本

第三章：低速自主配送市场

  • 世界市场
    • 市场规模
    • 主要自动驾驶配送公司及其发展
  • 中国市场
    • 市场规模
    • 中国主要低速自动送货车公司的运营情况
    • 市场需求
    • 快递和即时配送的发展加速自动送货车的落地
  • 发展趋势
    • 自动送货车辆将取代人工加速
    • 自动送货车辆的成本正在迅速下降
    • 2023年自动送货车行业将进入高速发展期
    • 主动融资：为低速自动配送公司融资
    • 场景不断扩展，技术加速迭代
    • 更多汽车製造商进入自动驾驶行业

第 4 章。主要应用程序提供商的自动送货车辆布局

  • JD.com Logistics Technology
  • Meituan
  • Alibaba Autonomous Delivery
  • Overall Comparison of Autonomous Delivery of JD.com, Meituan, Ali Xiaomanlu

第五章中国主要低速自动送货车厂商

  • Unity Drive
    • 个人资料
    • 发展历程
    • 主要产品
    • 远程驾驶舱
    • TaaS 系统
    • 技术优势
    • 操作示例
    • 合作伙伴
  • Go Further.AI
    • 个人资料
    • 发展历程
    • 码头物流自动驾驶送货车 "Juedi"
    • 无人物流车 "Fanyu"
    • 工厂材料自动驾驶汽车
    • 微服务机器人
    • 无人驾驶核心套件
    • 自动驾驶车辆运营基础架构
    • 自动驾驶汽车应用场景
    • 运营实例：终端物流自主配送
    • 操作示例：社区业务场景
    • 运行示例：工业 4.0 场景
    • 生产状态
  • White Rhino Zhida
    • 个人资料
    • 自动送货车的配置
    • 核心技术
    • 自动送货车落地典型案例
  • Neolix
    • 个人资料
    • 自动送货车的技术优势
    • 自动送货车场景落地 - 整体
    • 自动送货车场景落地
    • 自动送货车场景落地案例
    • 自动送货车的运行配置条件
    • 自动送货车辆的运营和销售流程
    • 合作伙伴
  • Uisee Technology
    • 个人资料
    • 发展历程
    • 产品体系
    • 自主机场行李物流车
    • 工厂自主物流车
    • L4 级自动驾驶解决方案 UiBox
    • 自动送货车落地案例
    • 核心技术
    • 阴影模式
    • 发展计划和战略
  • Haomo.ai
    • 个人资料
    • 发展历程
    • 低速自动送货车
    • 小摩托登陆
    • L4级低速自动送货车製造基地
    • 小摩托码头物流发货记录
    • 其他投资业绩
  • MOVE-X
    • 个人资料
    • 发展历程
    • 自动送货车
    • RC ONE 参数
    • 自动送货车的应用
    • 量产 L4 级自动驾驶配送车製造测试基地
  • Idriverplus
    • 个人资料
    • 发展历程
    • 低速智能汽车主要产品
    • 自动驾驶配送及物流车应用实例
    • 数据驱动的自动驾驶量产解决方案
  • CYBER-AI
    • 个人资料
    • 核心团队成员
    • CYBER-EXP-01 自动驾驶汽车
    • CYBER-EXP-01 自动驾驶汽车硬件配置
    • 网络VCU
    • 合作伙伴
  • Candela (Shenzhen) Technology
    • 个人资料
    • 室内/室外产品
    • 码头配送自主物流车
    • 阳光户外自主物流车应用实例
    • 场景操作流程
    • 生产状态
  • Ant Ranger Technology
    • 个人资料
    • 自主物流车
  • Whale Dynamic
    • 个人资料
    • 乘用车技术向高速公路级自动驾驶汽车的迁移
    • 自动送货车
    • L4 解决方案合作伙伴
  • Hunan Apollo Intelligent Transportation
    • 个人资料
    • 自动驾驶研发中心
    • 自动送货车BOBO*GO
    • 自动送货车落地案例
  • Jushi Technology
    • 个人资料
    • 发展历程
    • 核心技术
    • QBOX 自动驾驶汽车
    • 自动驾驶汽车应用实例
  • Excelland AI
    • 个人资料
    • 发展历程
    • 产品矩阵
    • 户外自动送货车
    • 应用示例
  • Pudu Technology
    • 个人资料
    • 产品矩阵
    • 四足步行机器人
  • Nuro
    • 个人资料
    • 发展历程
    • 自动送货车辆的演变
    • 自动送货车 R2
    • 与BYD R3合作
简介目录
Product Code: FZQ003

Research on autonomous delivery: the cost declines, and the pace of penetration and deployment in scenarios accelerate.

Autonomous delivery contains outdoor autonomous delivery (including ground-based delivery and drone delivery) and indoor robot delivery. This report focuses on researching outdoor ground-based autonomous delivery vehicles.

1. The autonomous delivery industry has transitioned from test run to large-scale operation.

In May 2021, the first batch of autonomous delivery vehicles in China was allowed to run on public roads in demonstration areas. During the epidemic in Shanghai in 2022, more than 500 autonomous delivery vehicles were assembled to serve the affected areas. After going through adaptation to different scenarios and technical optimization and verification in this period of time, autonomous delivery vehicles are finding ever wider application. Autonomous express delivery, autonomous takeaway delivery, supermarket delivery and autonomous retail have penetrated scenarios like communities, industrial parks, college campuses, smart scenic spots, AI parks and business districts.

In Neolix's case, as of July 2022 its autonomous vehicles have successfully been used in over 100 scenarios in 40 cities of 13 countries, delivering more than 2 million orders to over 300,000 users. The company has delivered and deployed a total of more than 1,000 vehicles. In the meantime, Unity Drive's products have landed in over 100 large- and medium-sized cities and run in over 150 parks across China. As of July 2022, GoFurther.AI's intelligent autonomous delivery vehicles have delivered 1.3 million parcels.

As concerns application, as of May 2022, JD Logistics has had nearly 400 intelligent delivery vehicles operated normally in over 25 cities across China, including Beijing, Tianjin and Changshu. During 2022-2023, JD will push on with research and development and put into use thousands of intelligent delivery vehicles for a wider coverage of autonomous delivery. In more than 200 colleges and universities in China, Cainiao has introduced more than 500 Xiaomanlu autonomous vehicles to serve millions of teachers and students, realizing normal operation.

Companies' quicker pace of carrying out their large-scale implementation plans has a strong bond with maturing autonomous delivery vehicle technology and declining vehicle cost.

2. The partnerships between industry chain companies expand, and the cost of autonomous delivery vehicles dwindles.

In April 2022, Haomo.AI introduced Little Magic Camel, an intelligent vehicle packing 3 mechanical LiDARs and a 360TOPS computing platform. The price of the vehicle is as low as RMB130,000, equivalent to the annual salary of a courier working in a big city.

Previously, the prices of autonomous delivery vehicles ranged at RMB500,000-600,000 in 2020, and dropped to RMB200,000-300,000 in 2021 before falling to RMB130,000 in 2022. From 2023 to 2025, the cost of autonomous delivery vehicles will be lowered to less than RMB100,000.

Autonomous delivery vehicles vary in specification and functional purpose, and their prices thus differ greatly as a matter of course. In addition to prices, autonomous vehicles also come with hidden costs. Almost all ongoing autonomous delivery projects are equipped with autonomous driving engineers to participate in the whole process or remotely control at the backend, in a bid to intervene at any time in the case of emergencies.

From a cost perspective, autonomous delivery vehicles have yet to gain a big replacement edge over labor. The adoption of autonomous delivery vehicles at the earliest and acquisition of more long-tail scenario data is the only path for products and technology to mature.

The autonomous delivery vehicle market has boosted development of local components suppliers. Independent components companies participate in the autonomous delivery supply chain more deeply, and autonomous delivery vehicle manufacturers also cut down their costs with the help of local suppliers. Taking LiDAR as an example, Modai 20 carries Hesai long-range high-resolution Pandar Series LiDAR and mid-range XT Series LiDAR; GoFurther.AI's autonomous delivery vehicles bear the combined LiDAR solution (RS-LiDAR-16+RS-Bpearl) from RoboSense.

As companies promote and deploy their projects on large scale, especially signing city-level contracts (e.g., Unity Drive + Yancheng City, MOVE-X + Wuwei City, and JD + Changshu City), the hardware and O&M costs per autonomous delivery vehicle will be reduced with bulk purchase.

At present, both production capacity and output of autonomous delivery vehicles in China keeps growing. For example, MOVE-X's smart factory boasts planned annual capacity of 20,000 units; Haomo.AI already has annual capacity of 10,000 units.

The development of autonomous delivery vehicles is inseparable from capital support. In the past year, autonomous delivery companies like Pudu Technology and Neolix acquired hundreds of millions of yuan in investment.

3. The autonomous delivery market sustains rapid growth and will be worth RMB17 billion in 2025.

According to data from State Post Bureau of China, from January to July 2022, the courier service companies in China handled a total of 60.87 billion parcels (including 51.22 billion pieces delivered from January to June, a year-on-year increase of 3.7%, and 9.65 billion pieces in July, up 8.0%). By the end of 2021, express couriers in China have numbered 4.5 million, and food takeout delivery riders have exceeded 13 million, including 6 million Meituan riders.

Companies badly need to reduce costs and improve efficiency. Meituan plans to deploy 10,000 autonomous delivery vehicles nationwide within three years. On our estimate, China's outdoor autonomous delivery vehicle market will be valued at about RMB17 billion in 2025.

Some companies are also exploring new models for how to maximize efficiency of cooperative delivery between manpower and machines. For example, the autonomous delivery vehicle adoption program launched by JD is a typical case.

To reduce work intensity of couriers, JD Logistics has introduced "Autonomous Vehicle Adoption Program". In areas covered by autonomous delivery, the couriers of JD Logistics can apply for "adoption" of a certain number of autonomous delivery vehicles to help them work. Couriers thus become the "commander" of a robot delivery squad, handing the standard delivery work over to autonomous delivery vehicles, and themselves take on dynamic collection or other personalized services. This adoption program has favored an over 50% growth in JD's order delivery during peak seasons.

4. Autonomous delivery vehicles have a greater ability to connect scenarios.

Connecting to more public roads:

From fixed-area scenarios (e.g., campuses, scenic spots, communities, demonstration areas, hospitals and factories) to densely populated business districts, plazas and subway entrances, autonomous delivery is becoming more widespread, and plus continuous technological iterations and Corner Case scenario data accumulation, autonomous delivery vehicles offer higher safety and reliability and are applicable to more public road scenarios. Some companies have begun to enhance their road-level autonomous delivery business. One example is Whale Dynamic.

Whale Dynamic uses L4 passenger car autonomous driving technology to build integrated solutions for small autonomous vehicles, targeting the road autonomous delivery market.

In September 2021, Alibaba announced that DAMO Academy is working to develop "Damanlu", a L4 autonomous light truck product for urban distribution scenarios, delivering goods from distribution stations to Cainiao Courier Stations in parks. In June 2022, Deqing County of Zhejiang became China's first city to issue public road test licenses for L4 autonomous trucks with "no people at the driver's seat", and Alibaba acquired one of the first two licenses. Damanlu carried out road tests in designated areas in Deqing, including some highway sections.

There are also companies trying to get through terminal distribution within 5 kilometers outdoors and enable free mobility in indoor and semi-enclosed environments. For example, Candela's split product, the Sunny new-generation autonomous logistics vehicle features automatic unloading and loading cabinet, real-time obstacle avoidance, cloud mapping, and multi-vehicle intelligent scheduling. The front large screen has the capabilities of human-computer interaction and advertising display. The vehicle has come into commercial operation. Candela realizes the seamless connection of indoor and outdoor logistics and distribution through the cooperative scheduling of outdoor Sunny autonomous vehicles and indoor Candlelight robots.

Unlike wheeled autonomous vehicles, quadruped robots are among the most complex and challenging types in robotics industry. On March 24, 2022, Pudu Technology unveiled D1, a quadruped delivery robot equipped with a dedicated pan-tilt delivery box. The active control via control algorithm allows pan-tilt delivery box to automatically adjust pitch attitude. When the robot walks and climbs slopes, the pan-tilt delivery box can always stay level. D1 can be used for the "last-three-kilometer" delivery in office buildings, parks, and residential quarters.

In January 2022, R3, the third-generation battery electric autonomous delivery vehicle jointly developed and designed by BYD and Nuro, made a debut. The biggest feature of this vehicle is the airbag installed outside to protect pedestrians on roads. The model is expected to be mass-produced in 2023.

At present, the logistics and food delivery giants, JD, Meituan and Cainiao are each phasing in their plans of introducing 10,000 autonomous delivery vehicles in the next three years. Other players have also increased the activities of daily autonomous delivery. White Rhino Zhida plans to realize daily delivery by 5,000 autonomous vehicles within five years.

Table of Contents

1. Autonomous Delivery Vehicle

  • 1.1 Definition and Classification
  • 1.2 Main Application Scenarios
  • 1.3 Outdoor Autonomous Delivery Application Scenarios
  • 1.4 Composition of Autonomous Delivery Vehicle system
  • 1.5 Main sensors and Characteristics of Autonomous Delivery Vehicle
  • 1.6 Chassis-by-Wire of Autonomous Delivery Vehicle
  • 1.7 Computing Platform of Autonomous Delivery Vehicle
  • 1.8 of Autonomous Delivery Industry Chain
  • 1.9 Parameter Information of Some Autonomous Delivery Vehicle
  • 1.10 New Autonomous Delivery Products in 2022H1
  • 1.11 Application of Autonomous Delivery During Epidemic in 2021-2022H1
  • 1.12 Autonomous Delivery Commercialization Stage
  • 1.13 Challenges Faced by Autonomous delivery Vehicle
  • 1.14 Development of Major Domestic Autonomous Delivery Enterprises
  • 1.15 Commercial Progress of Major Foreign Autonomous Delivery Vehicle

2. Autonomous Delivery Related Policies

  • 2.1 Policies Related to Domestic Autonomous Delivery
  • 2.2 Foreign Autonomous Delivery Policy: the United States
  • 2.3 Foreign Autonomous Delivery Policy: Europe
  • 2.4 Foreign Autonomous Delivery Policy: Japan

3. Low-speed Autonomous Delivery Market

  • 3.1 Global Market
    • 3.1.1 Market Size
    • 3.1.2 Major Autonomous Delivery Companies and Their Development
  • 3.2 Chinese market
    • 3.2.1 Market Size
    • 3.2.2 Operation of Major low-speed Autonomous Delivery Vehicle Companies in China
    • 3.2.3 Market Demand
    • 3.2.4 Development of Express Delivery and Instant Delivery Accelerates Landing of Autonomous Delivery Vehicle
  • 3.3 Development Trend
    • 3.3.1 Autonomous Delivery Vehicle Replace Manual Acceleration
    • 3.3.2 Cost of Autonomous Delivery Vehicle is Reducing Quickly
    • 3.3.3 Autonomous Delivery Vehicle Industry will Enter a Period of Rapid Development in 2023
    • 3.3.4 Active Financing: Financing of Low-speed Autonomous Delivery Enterprises
    • 3.3.5 Scenario Continues to Expand, and Technology Accelerates Iteration
    • 3.3.6 More Automakers join Autonomous Delivery Industry

4 Layout of Autonomous Delivery Vehicle of Major Application Providers

  • 4.1 JD.com Logistics Technology
    • 4.1.1 Development History
    • 4.1.2 Autonomous Delivery Vehicle Layout
    • 4.1.3 Autonomous Delivery Vehicle 5.0
    • 4.1.4 Autonomous Delivery Vehicle Landing Case
    • 4.1.5 Robot Application Planning
    • 4.1.6 Autonomous Driving Architecture
  • 4.2 Meituan
    • 4.2.1 Previous Strategic Adjustments
    • 4.2.2 Development History of Meituan Autonomous Delivery
    • 4.2.3 Autonomous Delivery Vehicle: Magic Bag 20
    • 4.2.4 Hao.ai and HeSai Help Magic Bag 20
    • 4.2.5 Autonomous Delivery Vehicle Landing Case
    • 4.2.6 Core Technology Architecture of Autonomous Delivery
    • 4.2.7 Advantages of Autonomous Delivery
  • 4.3 Alibaba Autonomous Delivery
    • 4.3.1 Development History of Alibaba Autonomous Delivery
    • 4.3.2 Autonomous Delivery Vehicle: Xiaomanlu and its Core Competitiveness
    • 4.3.3 Operation Data of Xiaomanlu
    • 4.3.4 Landing Case of Xiaomanlu
    • 4.3.5 Damanlu
  • 4.4 Overall Comparison of Autonomous Delivery of JD.com, Meituan, Ali Xiaomanlu

5 Major Low-Speed Autonomous Delivery Vehicle Vendors in China

  • 5.1 Unity Drive
    • 5.1.1 Profile
    • 5.1.2 Development History
    • 5.1.2 Main Products
    • 5.1.2 Remote Cockpit
    • 5.1.2 TaaS System
    • 5.1.3 Technical Advantages
    • 5.1.4 Operation Cases
    • 5.1.5 Partners
  • 5.2 Go Further.AI
    • 5.2.1 Profile
    • 5.2.2 Development History
    • 5.2.3 Terminal Logistics Autonomous Delivery Vehicle "Juedi"
    • 5.2.3 Autonomous Logistics Vehicle "Fanyu"
    • 5.2.3 Factory Materials Autonomous Vehicle
    • 5.2.3 Micro Service Robots
    • 5.2.4 Unmanned Core Kit of Autonomous Driving
    • 5.2.4 Operation Platform Architecture of Autonomous Vehicle
    • 5.2.5 Application Scenarios of Autonomous Vehicle
    • 5.2.6 Operation case: Autonomous Delivery of Terminal Logistics
    • 5.2.6 Operation Case: Community Business Scenario
    • 5.2.6 Operation Case: Industry 4.0 Scenario
    • 5.2.7 Production Situation
  • 5.3 White Rhino Zhida
    • 5.3.1 Profile
    • 5.3.2 Configuration of Autonomous Delivery Vehicle
    • 5.3.3 Core Technology
    • 5.3.4 Typical cases of Autonomous Delivery Vehicle Landing
  • 5.4 Neolix
    • 5.4.1 Profile
    • 5.4.2 Technical Advantages of Autonomous Delivery Vehicle
    • 5.4.3 Autonomous Delivery Vehicle Scenario Landing - Overall
    • 5.4.3 Autonomous Delivery Vehicle Scenario Landing
    • 5.4.4 Autonomous Delivery Vehicle Scenario Landing Case
    • 5.4.5 Operation Configuration Conditions of Autonomous Delivery Vehicle
    • 5.4.6 Operation and Sales Process of Autonomous Delivery Vehicle
    • 5.4.7 Partners
  • 5.5 Uisee Technology
    • 5.5.1 Profile
    • 5.5.2 Development History
    • 5.5.3 Product System
    • 5.5.4 Autonomous Airport Baggage Logistics Vehicle
    • 5.5.5 Factory Autonomous Logistics Vehicle
    • 5.5.6 L4 Autonomous Driving Solution UiBox
    • 5.5.7 Autonomous Delivery Vehicle Landing Case
    • 5.5.8 Core Technology
    • 5.5.9 Shadow Mode
    • 5.5.10 Development Planning and Strategy
  • 5.6 Haomo.ai
    • 5.6.1 Profile
    • 5.6.2 Development History
    • 5.6.3 Low-speed Autonomous Delivery Vehicle
    • 5.6.4 Landing of Xiaomotuo
    • 5.6.5 L4 low-speed Autonomous Delivery Vehicle Manufacturing Base
    • 5.6.6 Xiaomotuo End Logistics Distribution Transcript
    • 5.6.7 Other Operational Achievements
  • 5.7 MOVE-X
    • 5.7.1 Profile
    • 5.7.2 Development History
    • 5.7.3 Autonomous Delivery Vehicle
    • 5.7.4 Parameters of RC ONE
    • 5.7.5 Application of Autonomous Delivery Vehicle
    • 5.7.6 Mass Production L4 Autonomous Delivery Vehicle Manufacturing and Testing Base
  • 5.8 Idriverplus
    • 5.8.1 Profile
    • 5.8.2 Development History
    • 5.8.3 Main Low-speed Intelligent Vehicle Products
    • 5.8.4 Application Case of Autonomous Delivery Logistics Vehicle
    • 5.8.5 Data-driven Autonomous Driving Mass Production Solutions
  • 5.9 CYBER-AI
    • 5.9.1 Profile
    • 5.9.2 Core Team Members
    • 5.9.3 CYBER-EXP-01 Autonomous Vehicle
    • 5.9.4 CYBER-EXP-01 Autonomous Vehicle Hardware Configuration
    • 5.9.5 CYBER-VCU
    • 5.9.6 Partners
  • 5.10 Candela (Shenzhen) Technology
    • 5.10.1 Profile
    • 5.10.2 Indoor/Outdoor Products
    • 5.10.3 Terminal Delivery Autonomous Logistics Vehicle
    • 5.10.4 Sunshine Outdoor Autonomous Logistics Vehicle Application Case
    • 5.10.5 Scenario Operation Process
    • 5.10.6 Production Situation
  • 5.11 Ant Ranger Technology
    • 5.11.1 Profile
    • 5.11.2 Autonomous Logistics Vehicle
  • 5.12 Whale Dynamic
    • 5.12.1 Profile
    • 5.12.2 Passenger Car Technology Translates to Highway-level Autonomous Vehicle
    • 5.12.3 Autonomous Delivery Vehicle
    • 5.12.4 L4 Solution Partner
  • 5.13 Hunan Apollo Intelligent Transportation
    • 5.13.1 Profile
    • 5.13.2 Autonomous Driving R & D Center
    • 5.13.3 Autonomous Delivery Vehicle BOBO * GO
    • 5.13.4 Autonomous Delivery Vehicle Landing Case
  • 5.14 Jushi Technology
    • 5.14.1 Profile
    • 5.14.2 Development History
    • 5.14.3 Core Technology
    • 5.14.4 QBOX Autonomous vehicle
    • 5.14.5 Application Cases of Autonomous Vehicles
  • 5.15 Excelland AI
    • 5.15.1 Profile
    • 5.15.2 Development History
    • 5.15.3 Product Matrix
    • 5.15.4 Outdoor Autonomous Delivery Vehicle
    • 5.15.5 Application Cases
  • 5.16 Pudu Technology
    • 5.16.1 Profile
    • 5.16.2 Product Matrix
    • 5.16.3 Quadruped Delivery Robot
  • 5.17 Nuro
    • 5.17.1 Profile
    • 5.17.2 Development History
    • 5.17.3 Evolution of Autonomous Delivery Vehicle
    • 5.17.4 Autonomous Delivery Vehicle R2
    • 5.17.5 Cooperation with BYD R3