WO2024021872A1 - 一种车路协同系统的测试系统及其测试方法 - Google Patents
一种车路协同系统的测试系统及其测试方法 Download PDFInfo
- Publication number
- WO2024021872A1 WO2024021872A1 PCT/CN2023/098463 CN2023098463W WO2024021872A1 WO 2024021872 A1 WO2024021872 A1 WO 2024021872A1 CN 2023098463 W CN2023098463 W CN 2023098463W WO 2024021872 A1 WO2024021872 A1 WO 2024021872A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- vehicle
- data
- test
- road
- sensing
- Prior art date
Links
- 238000012360 testing method Methods 0.000 title claims abstract description 78
- 238000010998 test method Methods 0.000 title claims abstract description 29
- 238000005516 engineering process Methods 0.000 claims abstract description 32
- 238000004891 communication Methods 0.000 claims abstract description 18
- 238000000034 method Methods 0.000 claims abstract description 14
- 230000008447 perception Effects 0.000 claims abstract description 11
- 238000004088 simulation Methods 0.000 claims abstract description 6
- 238000007405 data analysis Methods 0.000 claims description 9
- 238000001514 detection method Methods 0.000 claims description 9
- 230000008521 reorganization Effects 0.000 claims description 9
- 230000003993 interaction Effects 0.000 claims description 8
- 230000005540 biological transmission Effects 0.000 claims description 6
- 230000006870 function Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000005457 optimization Methods 0.000 claims description 5
- 230000010354 integration Effects 0.000 claims description 4
- 238000004140 cleaning Methods 0.000 claims description 3
- 238000013480 data collection Methods 0.000 claims description 3
- 238000011157 data evaluation Methods 0.000 claims description 3
- 238000013523 data management Methods 0.000 claims description 3
- 238000007667 floating Methods 0.000 claims description 3
- 238000011158 quantitative evaluation Methods 0.000 claims description 3
- 239000000523 sample Substances 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 2
- 238000011161 development Methods 0.000 abstract description 7
- 230000007613 environmental effect Effects 0.000 abstract 1
- 238000010276 construction Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012113 quantitative test Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Definitions
- the invention relates to the technical field of intelligent transportation vehicle-road collaboration, and specifically relates to a vehicle-road collaboration system testing system and a testing method thereof.
- the smart car industry not only includes the intelligent upgrade of the traditional automobile industry, but also involves a series of related industries such as communication systems and roadside facilities.
- Intelligence and connectivity are the general trend of the automotive industry.
- the collaborative development path of connectivity and vehicle-road collaboration between bicycle intelligence and vehicle-road collaboration has gradually become an industry consensus, which will surely bring about new products and ecological models, and has broad market prospects.
- the vehicle-road collaborative system for autonomous driving has two important characteristics. First, it is the intersection of multiple technologies and cross-industry integration, which requires the integrated perception of information from smart cars, transportation facilities, information communication infrastructure and resource platforms. A real-time digital mapping of the physical traffic system is formed on the cloud control platform, and hierarchical integration decisions are made to realize real-time adjustment of vehicle driving and traffic signals to optimize the safety, efficiency and other performance of vehicle and traffic operations; second, it has local attributes and is based on distribution With standardized deployment and personalized configuration, the vehicle-road collaboration system must meet the support and security management of local attributes such as communications, maps, and data platforms for specific regional scenarios.
- vehicle-road collaborative system testing technology still has many shortcomings and limitations, which are mainly reflected in the following aspects:
- Test methods Testing methods based on use cases cannot fully meet the needs of vehicle-road collaborative testing; testing methods and technologies based on scenarios need to be improved urgently, and scenario extraction, screening and construction of test scenarios are the main issues.
- the testing tool chain is seriously incomplete and lacks flexibility; for testing based on virtual simulation, the scene construction tool still has high technology and imperfect models. It cannot handle large-scale maps and traffic flows. The testing efficiency is low, the cost is high, and it is difficult to carry out. .
- the present invention provides a test system and a test method for a vehicle-road collaborative system.
- This method is aimed at the test requirements of the vehicle-road collaborative system such as environment perception, simulation and prediction, communication broadcast, and traffic guidance.
- the vehicle-road collaborative system testing technology and the latest engineering practices are systematically summarized, and the system architecture, characteristics and application scope of the vehicle-road collaborative system testing technology are deeply analyzed, which greatly promotes the development of intelligent Driving the rapid development of automotive technology and industry.
- a vehicle-road collaboration system including five layers: terminal layer, edge layer, access layer, platform layer and application layer;
- the terminal layer includes people, vehicles, and various types of equipment at the road end, such as smartphones, data receivers, hardware sensors, positioning equipment, etc., which are used to collect various types of data;
- Edge layer equipment deployed on the roadside for data collection, cleaning, perception computing, target tracking computing, and data management.
- MEC perception computing
- RSU RSU
- the access layer uses channels such as positioning networks, proprietary networks, operator networks, and emergency rescue communications to ensure secure information communications between people, vehicles, and the cloud;
- the platform layer realizes the collection of digital resources of roads, infrastructure, vehicles, individuals and other information
- the application layer provides personalized platform access capabilities and application services for governments, car companies, individuals, etc.
- the vehicle-road collaborative system is based on single-vehicle intelligent autonomous driving, and uses advanced vehicle and road sensing and positioning equipment to perform real-time high-precision sensing and positioning of the road traffic environment, and follows a preset protocol to realize vehicle-to-vehicle communication. , different levels of information interaction and sharing between vehicles and roads, and vehicles and people, and covers varying degrees of vehicle automated driving, as well as collaborative optimization between vehicles and roads.
- the vehicle-road collaboration system also includes a roadside sensing system, which is composed of a roadside sensing unit, external facilities, a data transmission unit, a roadside computing unit, ancillary supporting facilities, etc.;
- Roadside sensing unit is used to extract various elements of road traffic status, such as kinematic information of traffic participants, information to determine traffic event triggers, support information for calculating traffic flow-related indicators, etc., including cameras, millimeter-wave radar, laser Traffic detectors such as radar;
- External facilities are used to provide sensing information sources for specific scenarios such as red light warning, floating vehicle information collection, and sensing data sharing, including signals, RSUs, cloud platforms, traffic control systems, etc.;
- Data transmission unit used for communication between system components and between the system and external devices
- the roadside computing unit is used to store and process the original data or result data of the roadside sensing unit, and generate high-precision sensing result information;
- Ancillary supporting facilities are related equipment used to provide support services such as deployment, power supply, time synchronization, and information security for the system.
- a test system for vehicle-road collaboration system including a vehicle-side data recording module, a data analysis and reorganization module, a data evaluation software, a system parameter configuration module and a vehicle-side true value system;
- the vehicle-side data recording module records the information released by the vehicle-road collaboration system, including the category, positioning, speed, heading angle and other data of multi-target traffic participants;
- the data analysis and reorganization module will split the information of multi-target traffic participants and align the data structure and dimensions with the data of the vehicle-side true value system;
- Data evaluation software the core of the test system, is based on single-objective and multi-objective structured data
- the system parameter configuration module is used to set the test equipment acquisition parameters and accuracy requirements. Its main function is to set the baseline difference between different true value data and the time reference and spatial reference of the vehicle-road cooperative sensing system;
- the vehicle-side true value system collects the true values of kinematic indicators such as positioning, speed, heading angle, etc. of a single traffic participant.
- the test system is based on intelligent autonomous driving of single-vehicles, and uses advanced vehicle and road sensing and positioning equipment to perform real-time high-precision sensing and positioning of the road traffic environment. It follows the preset protocol to realize vehicle-to-vehicle and vehicle-to-vehicle interactions. Different levels of information interaction and sharing between roads, vehicles and people, and covering different levels of vehicle automated driving, as well as collaborative optimization between vehicles and roads, and through vehicle automation, network interconnection and system integration, ultimately build a safe and efficient vehicle-road collaborative system.
- the implementation of the test system requires the synergy of multiple technologies, including multi-sensor fusion sensing technology, high-precision map and mobile positioning technology, collaborative decision-making and collaborative control technology, and high-reliability and low-latency network communication.
- Information technology cloud computing technology, functional safety and expected functional safety, Internet of Things technology, network security technology, etc.
- a test method for a vehicle-road collaborative system test system includes the following steps:
- S2 Record the information released by the vehicle-road collaboration system through the vehicle-side data recording module, including the category, positioning, speed, heading angle and other data of multi-target traffic participants, and stamp the time stamp of the reception moment;
- test method can be divided into use case-based test method, scenario-based test method, probe-based quantitative test method and simulation test method according to the different requirements of the test method on test input and test process.
- Four kinds of tests The comparison of methods is shown in Table 1 below:
- the invention provides a test system and a test method for a vehicle-road collaborative system. It has the following beneficial effects:
- the present invention provides a test system and test method for a vehicle-road collaborative system.
- This method is aimed at the test requirements of the vehicle-road collaborative system such as environment perception, simulation and prediction, communication broadcast, and traffic guidance. From the test system and the test method , testing tools, etc., it systematically summarizes the vehicle-road collaborative system testing technology and the latest engineering practices, and deeply analyzes the system architecture, characteristics and application scope of the vehicle-road collaborative system testing technology, which greatly promotes the intelligent driving vehicle technology and industry of rapid development.
- the present invention provides a vehicle-road collaborative system test system and its test method.
- This method adopts the comprehensive construction method of development scenarios and the theoretical method of scene complexity evaluation, and establishes scene definition standards, which greatly speeds up the application of scene test methods.
- By establishing flexible and customizable testing tools we can effectively improve the authenticity of the virtual environment and effectively study the electrical and virtual aspects of sensors. Interaction models of traffic environments.
- Figure 1 is a schematic structural diagram of the test system of the vehicle-road collaborative system of the present invention.
- Figure 2 is a schematic structural diagram of the roadside sensing system of the present invention.
- embodiments of the present invention provide a vehicle-road collaboration system, including five layers: terminal layer, edge layer, access layer, platform layer and application layer;
- the terminal layer includes people, vehicles, and various types of equipment at the road end, such as smartphones, data receivers, hardware sensors, positioning equipment, etc., which are used to collect various types of data;
- the edge layer is the data collection, cleaning, perception computing, target tracking calculation, and data management equipment deployed on the roadside, such as MEC, RSU, etc., to realize the perception collection and basic computing functions of vehicle and road environment data;
- the access layer uses channels such as positioning networks, proprietary networks, operator networks, and emergency rescue communications to ensure secure information communications between people, vehicles, and the cloud;
- the platform layer realizes the collection of digital resources of roads, infrastructure, vehicles, individuals and other information
- the application layer provides personalized platform access capabilities and application services for governments, car companies, individuals, etc.
- the vehicle-road collaborative system is based on single-vehicle intelligent autonomous driving and uses advanced vehicle and road sensing and positioning equipment to perform real-time high-precision sensing and positioning of the road traffic environment. It follows the preset protocol to realize vehicle-to-vehicle and vehicle-to-vehicle interactions. Different levels of information interaction and sharing between roads, vehicles and people, and covering different levels of vehicle automated driving, as well as collaborative optimization between vehicles and roads.
- the vehicle-road collaboration system also includes a roadside sensing system, which is composed of a roadside sensing unit, external facilities, a data transmission unit, a roadside computing unit, ancillary supporting facilities, etc.;
- Roadside sensing unit is used to extract various elements of road traffic status, such as kinematic information of traffic participants, information to determine traffic event triggers, support information for calculating traffic flow-related indicators, etc., including cameras, millimeter-wave radar, laser Traffic detectors such as radar;
- External facilities are used to provide sensing information sources for specific scenarios such as red light warning, floating vehicle information collection, and sensing data sharing, including signals, RSUs, cloud platforms, traffic control systems, etc.;
- Data transmission unit used for communication between system components and between the system and external devices
- the roadside computing unit is used to store and process the original data or result data of the roadside sensing unit, and generate high-precision sensing result information;
- Ancillary supporting facilities are related equipment used to provide support services such as deployment, power supply, time synchronization, and information security for the system.
- a test system for vehicle-road collaboration system including a vehicle-side data recording module, a data analysis and reorganization module, a data evaluation software, a system parameter configuration module and a vehicle-side true value system;
- the vehicle-side data recording module records the information released by the vehicle-road collaboration system, including the categories of multi-target traffic participants. identification, positioning, speed, heading angle and other data;
- the data analysis and reorganization module will split the information of multi-target traffic participants and align the data structure and dimensions with the data of the vehicle-side true value system;
- Data evaluation software the core of the test system, is based on single-objective and multi-objective structured data
- the system parameter configuration module is used to set the test equipment acquisition parameters and accuracy requirements. Its main function is to set the baseline difference between different true value data and the time reference and spatial reference of the vehicle-road cooperative sensing system;
- the vehicle-side true value system collects the true values of kinematic indicators such as positioning, speed, heading angle, etc. of a single traffic participant.
- a test method for a vehicle-road collaborative system test system including the following steps:
- S2 Record the information released by the vehicle-road collaboration system through the vehicle-side data recording module, including the category, positioning, speed, heading angle and other data of multi-target traffic participants, and stamp the time stamp of the reception moment;
- this testing method can be divided into use case-based testing method, scenario-based testing method, probe-based quantitative testing method and simulation testing method. Comparison of the four testing methods, As shown in Table 1 below:
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Traffic Control Systems (AREA)
Abstract
本发明提供一种车路协同系统的测试系统及其测试方法，涉及智能交通车路协同技术领域。该车路协同系统的测试系统及其测试方法，包括终端层、边缘层、接入层、平台层和应用层五个层级；终端层，包括人、车、路端的各类设备，如智能手机、数据接收器、硬件传感器、定位设备等，用于各类数据的采集。该方法针对车路协同系统的环境感知、仿真与预测、通信播报、交通引导等测试需求，从测试体系、测试方法、测试工具等方面，系统地总结了车路协同系统测试技术和最新工程实践，深入地分析了车路协同系统测试技术的体系架构、特点和适用范围，极大地促进了智能驾驶汽车技术及产业的快速发展。
Description
本发明涉及智能交通车路协同技术领域，具体为一种车路协同系统的测试系统及其测试方法。
智能汽车产业不仅包含传统汽车产业的智能化升级，还涉及通信系统、路侧设施等一系列关联产业。智能化与网联化是汽车产业大势所趋，单车智能和车路协同的网联协同发展路径逐渐成为行业共识，必将带来新的产品与生态模式，具备广阔的市场前景。
与常规汽车相比，面向自动驾驶的车路协同系统具备两大重要特征，一是多技术交叉、跨产业融合，需要智能汽车、交通设施、信息通信基础设施与资源平台信息的融合感知，在云控平台上形成物理交通系统的实时数字映射，进行分层融合决策，实现车辆行驶与交通信号的实时调节，以优化车辆与交通运行的安全、效率等性能；二是具有本地属性，基于分布式部署和个性化配置，车路协同系统要满足特定区域场景在通信、地图、数据平台等本地属性的支撑和安全管理。
从自动驾驶汽车到智能汽车，再到智能网联汽车，智能驾驶汽车技术及产业的快速发展，车路协同系统测试技术起到了重要的支撑作用。
现阶段，车路协同系统测试技术仍存在许多不足和局限性，主要体现在以下方面：
(1)测试方法方面。基于用例的测试方法不能完全满足车路协同测试需求；基于场景的测试方法和技术亟待完善，场景提取、筛选以及测试场景的构建是主要问题。
(2)测试工具方面。测试工具链严重不完整，缺少灵活性；基于虚拟仿真的测试，场景构建工具还存在技术高、模型不完善的局面，不能处理大尺度地图和交通流，测试效率低、成本高，开展比较困难。
发明内容
(一)解决的技术问题
针对现有技术的不足，本发明提供了一种车路协同系统的测试系统及其测试方法，该方法针对车路协同系统的环境感知、仿真与预测、通信播报、交通引导等测试需求，从测试体系、测试方法、测试工具等方面，系统地总结了车路协同系统测试技术和最新工程实践，深入地分析了车路协同系统测试技术的体系架构、特点和适用范围，极大地促进了智能驾驶汽车技术及产业的快速发展。
(二)技术方案
为实现以上目的，本发明通过以下技术方案予以实现：一种车路协同系统，包括终端层、边缘层、接入层、平台层和应用层五个层级；
终端层，包括人、车、路端的各类设备，如智能手机、数据接收器、硬件传感器、定位设备等，用于各类数据的采集；
边缘层，路侧部署的数据采集、清洗、感知计算、目标跟踪计算、数据管理的设备，
如MEC、RSU等，实现对车辆、道路环境数据的感知收集和基础计算功能；
接入层，利用定位网络、专有网络、运营商网络和应急救援通信等渠道，保障人一车一路一云的信息安全通信；
平台层，实现道路、基础设施、车辆、个人等信息的数字化资源汇集；
应用层，为政府、车企、个人等提供个性化的平台接入能力和应用服务。
优选的，所述车路协同系统是在单车智能自动驾驶的基础上，通过先进的车、道路感知和定位设备，对道路交通环境进行实时高精度感知定位，遵循预设协议，实现车与车、车与路、车与人之间不同程度的信息交互共享，并涵盖不同程度的车辆自动化驾驶，以及车辆与道路间的协同优化。
优选的，所述车路协同系统还包括路侧感知系统，所述路侧感知系统由路侧感知单元、外部设施、数据传输单元、路侧计算单元、附属配套设施等组成；
路侧感知单元，用于提取道路交通状态的各类要素，如交通参与者的运动学信息、判定交通事件触发的信息、计算交通流相关指标的支撑信息等，包括摄像机、毫米波雷达、激光雷达等交通检测器；
外部设施，用于为闯红灯预警、浮动车信息采集、感知数据共享等特定场景提供感知信源，包括信号机、RSU、云平台、交通管控系统等；
数据传输单元，用于系统组成设备之间以及系统与外部设备进行通信；
路侧计算单元，用于对路侧感知单元的原始数据或结果数据进行存储、处理，生成高精度的感知结果信息；
附属配套设施，用于为系统提供部署、供电、时间同步、信息安全等支撑服务的相关设备。
优选的，一种车路协同系统的测试系统，包括车端数据记录模块、数据分析与重组织模块、数据评测软件、系统参数配置模块和车端真值系统；
车端数据记录模块，记录车路协同系统发布的信息，包括多目标交通参与者的类别、定位、速度、航向角等数据；
数据分析与重组织模块，将分拆多目标交通参与者的信息，并与车端真值系统的数据，进行数据结构和维度的对齐；
数据评测软件，测试系统的核心，基于单目标和多目标的结构化数据；
系统参数配置模块，用于设置测试设备采集参数和精度要求，更主要的作用是设置不同真值数据和车路协同感知系统的时间参考和空间参考的基准差异；
车端真值系统，采集单一交通参与者目标的定位、速度、航向角等运动学指标真值。
优选的，该测试系统是在单车智能自动驾驶的基础上，通过先进的车、道路感知和定位设备，对道路交通环境进行实时高精度感知定位，遵循预设协议，实现车与车、车与路、车与人之间不同程度的信息交互共享，并涵盖不同程度的车辆自动化驾驶，以及车辆与道路间的协同优化，并通过车辆自动化、网络互联化和系统集成化，最终构建安全、高效的车路协同系统。
优选的，该测试系统的实现需要多种技术的协同作用实现，具体包括多传感器融合感知技术、高精度地图与移动定位技术、协同决策与协同控制技术、高可靠低时延网络通
信技术、云计算技术、功能安全与预期功能安全、物联网技术、网络安全技术等。
优选的，一种车路协同系统的测试系统的测试方法，包括以下步骤：
S1.通过车端真值系统采集单一交通参与者目标的定位、速度、航向角等运动学指标真值；
S2.通过车端数据记录模块记录车路协同系统发布的信息，包括多目标交通参与者的类别、定位、速度、航向角等数据，并打上接收时刻的时间戳；
S3.通过数据分析与重组织模块将分拆多目标交通参与者的信息，并与车端真值系统的数据，进行数据结构和维度的对齐，辅助下一步的数据评测计算；
S4.通过数据评测软件对单目标和多目标的结构化数据在感知距离、系统感知时延、定位精度、尺寸检测精度、速度检测精度、航向角检测精度、车道感知覆盖率、感知范围、系统频率、准确率与召回率、轨迹跟踪成功率、轨迹跟踪中位距离等指标上进行量化评测；
S5.通过系统参数配置模块设置测试设备采集参数和精度要求，并且设置不同真值数据和车路协同感知系统的时间参考和空间参考的基准差异。
优选的，所述测试方法按照测试方法对测试输入和测试过程要求的不同，可以分为基于用例的测试方法、基于场景的测试方法、基于探针的量化测试方法和仿真测试方法，四种测试方法的对比，如下表1所示：
表1四种测试方法对比
本发明提供了一种车路协同系统的测试系统及其测试方法。具备以下有益效果：
1、本发明提供了一种车路协同系统的测试系统及其测试方法，该方法针对车路协同系统的环境感知、仿真与预测、通信播报、交通引导等测试需求，从测试体系、测试方法、测试工具等方面，系统地总结了车路协同系统测试技术和最新工程实践，深入地分析了车路协同系统测试技术的体系架构、特点和适用范围，极大地促进了智能驾驶汽车技术及产业的快速发展。
2、本发明提供了一种车路协同系统的测试系统及其测试方法，该方法采用发展场景综合构建方法和场景复杂度评估理论方法，并建立场景定义标准，大大加快场景测试方法的应用，并且着力发展模块化的测试工具，适配多种测试方法，尤其是基于场景的测试方法，通过建立柔性化、可定制的测试工具，有效提高虚拟环境的真实性，有效研究传感器的电气与虚拟交通环境的交互模型。
图1为本发明的车路协同系统的测试系统结构示意图；
图2为本发明的路侧感知系统结构示意图。
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
实施例：
如图1-2所示，本发明实施例提供一种车路协同系统，包括终端层、边缘层、接入层、平台层和应用层五个层级；
终端层，包括人、车、路端的各类设备，如智能手机、数据接收器、硬件传感器、定位设备等，用于各类数据的采集；
边缘层，路侧部署的数据采集、清洗、感知计算、目标跟踪计算、数据管理的设备，如MEC、RSU等，实现对车辆、道路环境数据的感知收集和基础计算功能；
接入层，利用定位网络、专有网络、运营商网络和应急救援通信等渠道，保障人一车一路一云的信息安全通信；
平台层，实现道路、基础设施、车辆、个人等信息的数字化资源汇集；
应用层，为政府、车企、个人等提供个性化的平台接入能力和应用服务。
所述车路协同系统是在单车智能自动驾驶的基础上，通过先进的车、道路感知和定位设备，对道路交通环境进行实时高精度感知定位，遵循预设协议，实现车与车、车与路、车与人之间不同程度的信息交互共享，并涵盖不同程度的车辆自动化驾驶，以及车辆与道路间的协同优化。
所述车路协同系统还包括路侧感知系统，所述路侧感知系统由路侧感知单元、外部设施、数据传输单元、路侧计算单元、附属配套设施等组成；
路侧感知单元，用于提取道路交通状态的各类要素，如交通参与者的运动学信息、判定交通事件触发的信息、计算交通流相关指标的支撑信息等，包括摄像机、毫米波雷达、激光雷达等交通检测器；
外部设施，用于为闯红灯预警、浮动车信息采集、感知数据共享等特定场景提供感知信源，包括信号机、RSU、云平台、交通管控系统等；
数据传输单元，用于系统组成设备之间以及系统与外部设备进行通信；
路侧计算单元，用于对路侧感知单元的原始数据或结果数据进行存储、处理，生成高精度的感知结果信息；
附属配套设施，用于为系统提供部署、供电、时间同步、信息安全等支撑服务的相关设备。
一种车路协同系统的测试系统，包括车端数据记录模块、数据分析与重组织模块、数据评测软件、系统参数配置模块和车端真值系统；
车端数据记录模块，记录车路协同系统发布的信息，包括多目标交通参与者的类
别、定位、速度、航向角等数据；
数据分析与重组织模块，将分拆多目标交通参与者的信息，并与车端真值系统的数据，进行数据结构和维度的对齐；
数据评测软件，测试系统的核心，基于单目标和多目标的结构化数据；
系统参数配置模块，用于设置测试设备采集参数和精度要求，更主要的作用是设置不同真值数据和车路协同感知系统的时间参考和空间参考的基准差异；
车端真值系统，采集单一交通参与者目标的定位、速度、航向角等运动学指标真值。
一种车路协同系统的测试系统的测试方法，包括以下步骤：
S1.通过车端真值系统采集单一交通参与者目标的定位、速度、航向角等运动学指标真值；
S2.通过车端数据记录模块记录车路协同系统发布的信息，包括多目标交通参与者的类别、定位、速度、航向角等数据，并打上接收时刻的时间戳；
S3.通过数据分析与重组织模块将分拆多目标交通参与者的信息，并与车端真值系统的数据，进行数据结构和维度的对齐，辅助下一步的数据评测计算；
S4.通过数据评测软件对单目标和多目标的结构化数据在感知距离、系统感知时延、定位精度、尺寸检测精度、速度检测精度、航向角检测精度、车道感知覆盖率、感知范围、系统频率、准确率与召回率、轨迹跟踪成功率、轨迹跟踪中位距离等指标上进行量化评测；
S5.通过系统参数配置模块设置测试设备采集参数和精度要求，并且设置不同真值数据和车路协同感知系统的时间参考和空间参考的基准差异。
该测试方法按照测试方法对测试输入和测试过程要求的不同，可以分为基于用例的测试方法、基于场景的测试方法、基于探针的量化测试方法和仿真测试方法，四种测试方法的对比，如下表1所示：
表1四种测试方法对比
尽管已经示出和描述了本发明的实施例，对于本领域的普通技术人员而言，可以理解在不脱离本发明的原理和精神的情况下可以对这些实施例进行多种变化、修改、替换和变型，本发明的范围由所附权利要求及其等同物限定。
Claims (8)
- 一种车路协同系统，其特征在于，包括终端层、边缘层、接入层、平台层和应用层五个层级；终端层，包括人、车、路端的各类设备，如智能手机、数据接收器、硬件传感器、定位设备等，用于各类数据的采集；边缘层，路侧部署的数据采集、清洗、感知计算、目标跟踪计算、数据管理的设备，如MEC、RSU等，实现对车辆、道路环境数据的感知收集和基础计算功能；接入层，利用定位网络、专有网络、运营商网络和应急救援通信等渠道，保障人一车一路一云的信息安全通信；平台层，实现道路、基础设施、车辆、个人等信息的数字化资源汇集；应用层，为政府、车企、个人等提供个性化的平台接入能力和应用服务。
- 根据权利要求1所述的一种车路协同系统，其特征在于，所述车路协同系统是在单车智能自动驾驶的基础上，通过先进的车、道路感知和定位设备，对道路交通环境进行实时高精度感知定位，遵循预设协议，实现车与车、车与路、车与人之间不同程度的信息交互共享，并涵盖不同程度的车辆自动化驾驶，以及车辆与道路间的协同优化。
- 根据权利要求1所述的一种车路协同系统，其特征在于，所述车路协同系统还包括路侧感知系统，所述路侧感知系统由路侧感知单元、外部设施、数据传输单元、路侧计算单元、附属配套设施等组成；路侧感知单元，用于提取道路交通状态的各类要素，如交通参与者的运动学信息、判定交通事件触发的信息、计算交通流相关指标的支撑信息等，包括摄像机、毫米波雷达、激光雷达等交通检测器；外部设施，用于为闯红灯预警、浮动车信息采集、感知数据共享等特定场景提供感知信源，包括信号机、RSU、云平台、交通管控系统等；数据传输单元，用于系统组成设备之间以及系统与外部设备进行通信；路侧计算单元，用于对路侧感知单元的原始数据或结果数据进行存储、处理，生成高精度的感知结果信息；附属配套设施，用于为系统提供部署、供电、时间同步、信息安全等支撑服务的相关设备。
- 根据权利要求1-3所述的一种车路协同系统的测试系统，其特征在于，包括车端数据记录模块、数据分析与重组织模块、数据评测软件、系统参数配置模块和车端真值系统；车端数据记录模块，记录车路协同系统发布的信息，包括多目标交通参与者的类别、定位、速度、航向角等数据；数据分析与重组织模块，将分拆多目标交通参与者的信息，并与车端真值系统的数据，进行数据结构和维度的对齐；数据评测软件，测试系统的核心，基于单目标和多目标的结构化数据；系统参数配置模块，用于设置测试设备采集参数和精度要求，更主要的作用是设置不同真值数据和车路协同感知系统的时间参考和空间参考的基准差异；车端真值系统，采集单一交通参与者目标的定位、速度、航向角等运动学指标真值。
- 根据权利要求4所述的一种车路协同系统的测试系统，其特征在于，该测试系统是在单车智能自动驾驶的基础上，通过先进的车、道路感知和定位设备，对道路交通环境进行实 时高精度感知定位，遵循预设协议，实现车与车、车与路、车与人之间不同程度的信息交互共享，并涵盖不同程度的车辆自动化驾驶，以及车辆与道路间的协同优化，并通过车辆自动化、网络互联化和系统集成化，最终构建安全、高效的车路协同系统。
- 根据权利要求4所述的一种车路协同系统的测试系统，其特征在于，该测试系统的实现需要多种技术的协同作用实现，具体包括多传感器融合感知技术、高精度地图与移动定位技术、协同决策与协同控制技术、高可靠低时延网络通信技术、云计算技术、功能安全与预期功能安全、物联网技术、网络安全技术等。
- 一种车路协同系统的测试系统的测试方法，其特征在于，包括以下步骤：S1.通过车端真值系统采集单一交通参与者目标的定位、速度、航向角等运动学指标真值；S2.通过车端数据记录模块记录车路协同系统发布的信息，包括多目标交通参与者的类别、定位、速度、航向角等数据，并打上接收时刻的时间戳；S3.通过数据分析与重组织模块将分拆多目标交通参与者的信息，并与车端真值系统的数据，进行数据结构和维度的对齐，辅助下一步的数据评测计算；S4.通过数据评测软件对单目标和多目标的结构化数据在感知距离、系统感知时延、定位精度、尺寸检测精度、速度检测精度、航向角检测精度、车道感知覆盖率、感知范围、系统频率、准确率与召回率、轨迹跟踪成功率、轨迹跟踪中位距离等指标上进行量化评测；S5.通过系统参数配置模块设置测试设备采集参数和精度要求，并且设置不同真值数据和车路协同感知系统的时间参考和空间参考的基准差异。
- 根据权利要求6所述的一种车路协同系统的测试系统的测试方法，其特征在于，所述测试方法按照测试方法对测试输入和测试过程要求的不同，可以分为基于用例的测试方法、基于场景的测试方法、基于探针的量化测试方法和仿真测试方法，四种测试方法的对比，如下表1所示：表1四种测试方法对比
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210880842.5 | 2022-07-26 | ||
| CN202210880842.5A CN115346367A (zh) | 2022-07-26 | 2022-07-26 | 一种车路协同系统的测试系统及其测试方法 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2024021872A1 true WO2024021872A1 (zh) | 2024-02-01 |
Family
ID=83950665
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2023/098463 WO2024021872A1 (zh) | 2022-07-26 | 2023-06-06 | 一种车路协同系统的测试系统及其测试方法 |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN115346367A (zh) |
| WO (1) | WO2024021872A1 (zh) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117852316A (zh) * | 2024-03-07 | 2024-04-09 | 中国人民解放军军事科学院国防科技创新研究院 | 通讯约束下集群协同导航仿真测试系统及方法 |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115346367A (zh) * | 2022-07-26 | 2022-11-15 | 上海交通大学 | 一种车路协同系统的测试系统及其测试方法 |
| CN115597889B (zh) * | 2022-11-22 | 2023-03-14 | 北京理工大学深圳汽车研究院(电动车辆国家工程实验室深圳研究院) | 基于软件定义测试车辆的方法、系统及软件定义测试系统 |
| CN115775457B (zh) * | 2023-01-31 | 2023-05-05 | 江苏天一航空工业股份有限公司 | 一种用于民航机场车路协同路径测试方法及系统 |
| CN116449806B (zh) * | 2023-06-14 | 2023-09-01 | 中汽智联技术有限公司 | 基于安全层信息的车辆信息融合控制功能测试方法和系统 |
| CN116824869B (zh) * | 2023-08-31 | 2023-11-24 | 国汽(北京)智能网联汽车研究院有限公司 | 车路云一体化交通融合感知测试方法、装置、系统及介质 |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111554088A (zh) * | 2020-04-13 | 2020-08-18 | 重庆邮电大学 | 一种多功能v2x智能路侧基站系统 |
| CN112769929A (zh) * | 2020-12-31 | 2021-05-07 | 重庆车辆检测研究院有限公司 | 面向车路协同技术的场地在环测试系统及测试方法 |
| CN112816954A (zh) * | 2021-02-09 | 2021-05-18 | 中国信息通信研究院 | 一种基于真值的路侧感知系统评测方法和系统 |
| CN113347254A (zh) * | 2021-06-02 | 2021-09-03 | 安徽工程大学 | 基于v2x的智能交通控制车联网系统及其控制方法 |
| CN216357337U (zh) * | 2021-10-20 | 2022-04-19 | 深圳市未来智能网联交通系统产业创新中心 | 一种智能网联研究测试装置 |
| WO2022121248A1 (zh) * | 2020-12-11 | 2022-06-16 | 国汽(北京)智能网联汽车研究院有限公司 | 测试评价信息确定方法、装置、设备及计算机存储介质 |
| CN115346367A (zh) * | 2022-07-26 | 2022-11-15 | 上海交通大学 | 一种车路协同系统的测试系统及其测试方法 |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113190921B (zh) * | 2021-05-14 | 2021-11-19 | 上海交通大学 | 用于智能汽车驾乘性能测试的自动评价方法及系统 |
| CN114550450A (zh) * | 2022-02-15 | 2022-05-27 | 云控智行科技有限公司 | 一种验证路侧感知设备感知精度的方法、装置及电子设备 |
| CN114580575A (zh) * | 2022-04-29 | 2022-06-03 | 中智行(苏州)科技有限公司 | 一种自动驾驶视觉感知的可持续闭环链路的构建方法 |
-
2022
- 2022-07-26 CN CN202210880842.5A patent/CN115346367A/zh active Pending
-
2023
- 2023-06-06 WO PCT/CN2023/098463 patent/WO2024021872A1/zh unknown
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111554088A (zh) * | 2020-04-13 | 2020-08-18 | 重庆邮电大学 | 一种多功能v2x智能路侧基站系统 |
| WO2022121248A1 (zh) * | 2020-12-11 | 2022-06-16 | 国汽(北京)智能网联汽车研究院有限公司 | 测试评价信息确定方法、装置、设备及计算机存储介质 |
| CN112769929A (zh) * | 2020-12-31 | 2021-05-07 | 重庆车辆检测研究院有限公司 | 面向车路协同技术的场地在环测试系统及测试方法 |
| CN112816954A (zh) * | 2021-02-09 | 2021-05-18 | 中国信息通信研究院 | 一种基于真值的路侧感知系统评测方法和系统 |
| CN113347254A (zh) * | 2021-06-02 | 2021-09-03 | 安徽工程大学 | 基于v2x的智能交通控制车联网系统及其控制方法 |
| CN216357337U (zh) * | 2021-10-20 | 2022-04-19 | 深圳市未来智能网联交通系统产业创新中心 | 一种智能网联研究测试装置 |
| CN115346367A (zh) * | 2022-07-26 | 2022-11-15 | 上海交通大学 | 一种车路协同系统的测试系统及其测试方法 |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117852316A (zh) * | 2024-03-07 | 2024-04-09 | 中国人民解放军军事科学院国防科技创新研究院 | 通讯约束下集群协同导航仿真测试系统及方法 |
| CN117852316B (zh) * | 2024-03-07 | 2024-05-28 | 中国人民解放军军事科学院国防科技创新研究院 | 通讯约束下集群协同导航仿真测试系统及方法 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115346367A (zh) | 2022-11-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2024021872A1 (zh) | 一种车路协同系统的测试系统及其测试方法 | |
| CN109816811B (zh) | 一种自然驾驶数据采集装置 | |
| WO2022141910A1 (zh) | 一种基于行车安全风险场的车路激光雷达点云动态分割及融合方法 | |
| CN113870553B (zh) | 一种面向混合交通流的路网运行状态检测系统及方法 | |
| CN105976629A (zh) | 一种行车信息共享的方法、车载平台及智能交通系统 | |
| CN111458721B (zh) | 一种暴露垃圾的识别定位方法、装置及系统 | |
| US11375041B2 (en) | Autonomous vehicle ad-hoc networking and data processing | |
| CN113112805B (zh) | 一种基于基站通讯与路口摄像头定位的路口监测预警方法 | |
| CN112306051A (zh) | 一种高速公路无人驾驶交警车辆机器人系统 | |
| CN107037281A (zh) | 自动驾驶车辆通过信号干扰区的能力的测试方法及测试场 | |
| CN112530156A (zh) | 基于边缘计算的智能网联汽车开放道路系统和建设方法 | |
| CN112258850A (zh) | 一种车路协同系统边缘侧多传感器数据融合系统 | |
| CN216357337U (zh) | 一种智能网联研究测试装置 | |
| CN102768797A (zh) | 一种城市路况信息评价方法及装置 | |
| Kloeker et al. | Traffic detection using modular infrastructure sensors as a data basis for highly automated and connected driving | |
| CN113433548B (zh) | 一种数据监控方法、装置、设备及存储介质 | |
| Shangguan et al. | Interactive perception-based multiple object tracking via CVIS and AV | |
| CN112702385B (zh) | 一种面向智能网联的边缘计算处理系统 | |
| CN113724499A (zh) | 一种道路交通事件三维可视化分析方法及系统 | |
| Li et al. | How does c-v2x perform in urban environments? results from real-world experiments on urban arterials | |
| CN105761538A (zh) | 基于视频识别的辅助报站方法、系统及车载终端 | |
| CN107525525A (zh) | 一种新能源汽车的路径校准系统及方法 | |
| CN116935652A (zh) | 一种智慧交通用信息系统集成平台数据管理系统 | |
| CN116863652A (zh) | 一种基于互联网加技术的地质灾害预警方法 | |
| CN116129631A (zh) | 一种车路协同数据处理方法及相关设备 |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 23845085 Country of ref document: EP Kind code of ref document: A1 |