Design method of intelligent networked automobile vehicle-road cloud integrated information system

Abstract

The invention relates to the technical field of intelligent traffic, and discloses a design method of an intelligent network-connected automobile vehicle-road cloud integrated information system, which can realize integration and matching among vehicles, roads and cloud in the intelligent network-connected automobile vehicle-road cloud integrated information system, and comprises the following steps of: according to a time-space relationship of a road network level driving task, determining a road network level driving task according to the time-space relationship of the road network level driving task; designing a function scene of the intelligent networked automobile vehicle-road cloud integrated system; and according to the function scene design result and the realization logic of the global optimization of the road network level driving task, designing a logic scene of the intelligent network connection automobile vehicle-road cloud integrated system, and according to the logic scene design result and the realization logic of the global optimization of the road network level driving task, designing a physical scene of the intelligent network connection automobile vehicle-road cloud integrated system. According to the method, a staged, multi-scale, cross-domain and layered design method is adopted, and method support and architecture guidance can be provided for design, modeling, testing and verification of an automobile and road cloud integrated system.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, and in particular to a design method for a transportation information system. Background Art

[0002] Intelligent Connected Vehicle (ICV) refers to a new generation of automobile that is equipped with advanced on-board sensors, controllers, actuators and other devices, and integrates modern communication and network technologies to achieve intelligent information exchange and sharing. It has complex environmental perception, intelligent decision-making, collaborative control and execution functions, and can achieve safe, comfortable, energy-saving and efficient driving.

[0003] The vehicle-road-cloud integrated system integrates the physical space and information space of people, vehicles, roads, and clouds through the new generation of information and communication technology. Based on system collaborative perception, decision-making and control, it realizes an information-physical system that realizes safe, energy-saving, comfortable and efficient operation of the intelligent connected vehicle transportation system.

[0004] The vehicle-road-cloud integration of intelligent connected vehicles is an inevitable trend in technological evolution and a consensus in the industry. However, the overall construction of the vehicle-road-cloud integration of intelligent connected vehicles is currently in its early stages, and a complete system architecture has not yet been built. For example, the time span and spatial scale of existing scenario designs are small, and no attention is paid to issues such as integration and matching between vehicles, roads, and clouds, as well as functional interaction and collaborative integration. Summary of the invention

[0005] The present invention provides a design method for a vehicle-road-cloud integrated system for an intelligent networked vehicle, thereby realizing integration and matching among the vehicle, road, and cloud in the vehicle-road-cloud integrated system for an intelligent networked vehicle.

[0006] The present invention provides the following technical solutions:

[0007] A method for designing a vehicle-road-cloud integrated information system for an intelligent connected vehicle comprises the following steps:

[0008] S1. Functional scenario design: Based on the spatiotemporal relationship of the road network-level driving tasks, the functional scenarios of the vehicle-road-cloud integrated system of intelligent connected vehicles are designed, describing the vehicle-road-cloud-road network-level functions, the road section-level vehicle-road functions, the vehicle-body area-vehicle functions, and the relationships between the functions at each scale;

[0009] S2. Logical scenario design: Based on the functional scenario design results and the implementation logic of the global optimization of the road network-level driving task, the logical scenario of the intelligent connected vehicle vehicle-road-cloud integrated system is designed, describing the functions of the cloud, road and vehicle, as well as the logical relationship and interface between the above functions;

[0010] S3. Physical scenario design: Based on the results of logical scenario design and the implementation logic of global optimization of road network-level driving tasks, design the physical scenario of the intelligent connected vehicle's vehicle-road-cloud integrated system, and design the specific implementation strategies and input and output parameters of cloud-side, road-side, and vehicle-side functions.

[0011] The step S1 specifically includes the following steps:

[0012] S11. According to the spatiotemporal relationship of the road network-level driving tasks, a vehicle-road-cloud integrated scale model is constructed, wherein the vehicle-road-cloud integrated scale includes the following scales:

[0013] The vehicle-road-cloud scale is a spatiotemporal scope composed of the vehicle-road scale and the cloud, which enables vehicle-road-cloud interaction and collaboration within the road network.

[0014] The vehicle-road scale is the spatiotemporal range composed of the vehicle scale and the road end, realizing the interaction and coordination between the vehicle and the road within the road section;

[0015] The vehicle scale is the space-time range consisting of the vehicle body and the adjacent vehicles around the vehicle body, realizing the interaction and coordination between vehicles;

[0016] S12. Based on the vehicle-road-cloud integration scale model, describe the following functions:

[0017] Cloud-road-network-level functions describe the vehicle-road-cloud integrated functions of intelligent connected vehicles at the vehicle-road-cloud scale, and describe the top-level functions of cloud, road-cloud collaboration, and vehicle-cloud collaboration at the vehicle-road-cloud scale;

[0018] The road section level vehicle-road function describes the road end and vehicle-road coordination functions at the vehicle-road scale;

[0019] From the vehicle body area vehicle function, the vehicle-side function is described at the vehicle scale;

[0020] The relationship between functions of various scales, describing the interaction and coordination between vehicle-road-cloud scale functions, vehicle-road scale functions and vehicle-vehicle scale functions; describing the interaction and coordination between vehicle-road scale functions and vehicle-vehicle scale functions under cloud-side coordinated decision-making; describing the interaction and coordination between vehicle-vehicle scale functions under road-side coordinated decision-making.

[0021] Step S2 specifically includes the following steps:

[0022] S21. According to the implementation logic of global optimization of road network-level driving tasks, a vehicle-road-cloud integrated cross-domain model is constructed, including the following logical domains:

[0023] The cloud is responsible for the realization of road network-level cloud functions at the vehicle-road-cloud scale, and for the information exchange between the vehicle-road-cloud integrated system and external systems;

[0024] Road-side: responsible for realizing the road-cloud collaborative functions at the road network level at the vehicle-road-cloud scale, and for realizing the road-side functions at the vehicle-road scale;

[0025] On the vehicle side, it is responsible for realizing the road network-level vehicle-cloud collaborative functions at the vehicle-road-cloud scale, the vehicle-road collaborative functions at the vehicle-road scale, and the vehicle functions at the vehicle-vehicle scale;

[0026] S22. Based on the vehicle-road-cloud integrated cross-domain model, design the logical functions of the cloud, road, and vehicle, as well as the logical relationships and interfaces between the above functions, including:

[0027] The cloud communicates with the road side and the vehicle side, receives data uploaded by the road side and the vehicle side, and the data uploaded by the road side and the vehicle side include location information, real-time traffic perception data, real-time vehicle operation status, real-time vehicle perception data and / or alarm events; performs vehicle-road-cloud fusion perception according to the association relationship of the road network to form vehicle-road-cloud fusion information, and the vehicle-road-cloud fusion information includes traffic situation information, traffic decision information, traffic control information, warning events and / or vehicle driving decision information; the cloud also exchanges information with external systems, and the external systems include meteorological systems, traffic control systems, emergency systems, map systems and / or positioning systems, and makes collaborative decisions based on the tasks of the road network and the information obtained, obtains the road network traffic situation, traffic decision information and / or vehicle driving decision information, and sends them to the road side and the vehicle side;

[0028] The road end communicates with the cloud, other road ends and vehicle ends, sends real-time dynamic traffic perception data of the road section to the cloud, sends road section traffic situation information and / or road section traffic decision information to the surrounding road ends, and sends road section-level dynamic traffic perception data to the vehicle end; receives road network road traffic situation and / or traffic decision information from the cloud, receives road section traffic situation information and / or road section traffic decision information from the surrounding road ends, receives real-time operation status and perception data of the vehicle end in the road section, realizes vehicle-road-cloud fusion perception according to the association relationship of the road section, forms traffic situation information, traffic decision information, traffic control information, warning events and / or vehicle driving decision information of the road section and sends them to the vehicle end;

[0029] The vehicle side communicates with the cloud side, the road side and other vehicle sides, sends the vehicle side's real-time operating status and / or perception data to the cloud side, sends the vehicle side's real-time operating status and / or perception data to the road side, and sends the vehicle side's real-time operating status and / or perception data to the vehicle side; receives road network traffic situation and / or vehicle driving decision information from the cloud side, receives vehicle driving decision information from the road side, traffic perception information of the road section, traffic situation information of the road section, etc., receives real-time operating status and perception data of the vehicle side around the vehicle body, realizes vehicle-road-cloud fusion perception according to the position of the vehicle side, and forms vehicle driving decision information.

[0030] In step S3, the physical scenario of the intelligent connected vehicle vehicle-road-cloud integrated system method is a hierarchical model, in which:

[0031] The cloud includes an integrated base layer, a domain standard component layer, and a standardized hierarchical shared interface layer;

[0032] The road side includes the road side data processing layer, the road side fusion perception and collaborative decision-making layer, and the road side control layer;

[0033] The vehicle side includes the vehicle side data processing layer, the vehicle side fusion perception and collaborative decision-making layer, and the vehicle side control layer.

[0034] The beneficial effects of the present invention are as follows: The design method of the intelligent networked vehicle vehicle-road-cloud integrated system of the present invention adopts a phased design method. In the functional scene design, the functions are gradually decomposed according to the scales of the road network level, the road section level, and the surrounding of the vehicle body, highlighting the idea of ​​network empowerment, describing the functions of each scale from large scale to small scale, as well as the interaction and synergy between the functions of each scale, ensuring the accurate decomposition between large-scale and small-scale functions, and the physical scene design embodies the two major technical features of layered decoupling and cross-domain sharing, breaking through the data barriers between different fields and regions, realizing the integration of basic data, and cross-domain sharing and sharing of infrastructure, services and platforms. It can provide method support and architectural guidance for the design, modeling, testing, verification, etc. of the vehicle-road-cloud integrated system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0036] Figure 1 A schematic diagram of a design method of a vehicle-road-cloud integrated information system for an intelligent networked vehicle according to the present invention;

[0037] Figure 2 It is a schematic diagram for describing the functional scenarios in the present invention;

[0038] Figure 3 A schematic diagram for describing a logical scenario in the present invention;

[0039] Figure 4 is a schematic diagram of a cloud physical model in the present invention;

[0040] Figure 5 is a schematic diagram of the physical model of the road end of the present invention;

[0041] Figure 6 It is a schematic diagram of the vehicle-side physical model in the present invention. DETAILED DESCRIPTION

[0042] The specific implementation of the present invention will be described below in conjunction with the accompanying drawings.

[0043] This embodiment uses a model-based systems engineering (MBSE) method to model the intelligent connected vehicle vehicle-road-cloud integrated information system, including the following steps:

[0044] S1. Functional scenario design. Figure 2 , the vehicle-road-cloud integration system needs to be able to describe the collaborative perception and collaborative decision-making of the vehicle-road-cloud at the road network level, and can achieve global optimization operation at the road network level; the road network includes many road sections, and the road sections contain many vehicles with different performance and different driving tasks, that is, the road network and the road sections serve the vehicles, and by achieving the optimized operation of the vehicles, the optimization of the road network traffic status and the optimization of the driving tasks can be achieved. The characteristics of vehicle-road-cloud integration are to highlight the value of networking and intelligence at a large scale, and to achieve fusion perception and collaborative decision-making among multiple subjects at a large scale. To this end, this embodiment designs the functional scenarios of the vehicle-road-cloud integration system method for intelligent connected vehicles based on the spatiotemporal relationship of road network-level driving tasks, and describes the relationship between the vehicle-road-cloud road network-level functions, the road section-level vehicle-road functions, and the vehicle-vehicle functions in the vehicle body area, as well as the functions of each scale; specifically includes the following steps:

[0045] S11. According to the spatiotemporal relationship of the road network-level driving tasks, a vehicle-road-cloud integrated scale model is constructed, wherein the vehicle-road-cloud integrated scale includes the following scales:

[0046] The vehicle-road-cloud scale is a spatiotemporal scope composed of the vehicle-road scale and the cloud, which realizes vehicle-to-vehicle interaction and coordination, vehicle-road interaction and coordination, and vehicle-road-cloud interaction and coordination within the road network;

[0047] The vehicle-road scale is the space-time range composed of the vehicle scale and the road end, which realizes the interaction and coordination between the vehicle and the road within the road section. According to the actual situation, the length covered by each road end facility is about 500 meters;

[0048] The vehicle scale is the space-time range of the vehicle body and the adjacent vehicles around it, which realizes the interaction and coordination between vehicles. According to the actual situation, the space-time range can be limited to within 20 meters of the vehicle body, within 1 second, and the number of adjacent vehicles can be limited to 4-8;

[0049] S12. Based on the vehicle-road-cloud integration scale model, describe the following functions:

[0050] Cloud-road-network-level functions describe the vehicle-road-cloud integrated functions of intelligent connected vehicles at the vehicle-road-cloud scale, and describe the top-level functions of cloud, road-cloud collaboration, and vehicle-cloud collaboration at the vehicle-road-cloud scale;

[0051] The road section level vehicle-road function describes the road end and vehicle-road coordination functions at the vehicle-road scale;

[0052] From the vehicle body area vehicle function, the vehicle-side function is described at the vehicle scale;

[0053] The relationship between functions of various scales, describing the interaction and coordination between vehicle-road-cloud scale functions and vehicle-road scale functions and vehicle-vehicle scale functions; describing the interaction and coordination between vehicle-road scale functions and vehicle-vehicle scale functions under cloud-coordinated decision-making.

[0054] Based on the above functions, the implementation logic of the global optimization function of road network-level driving tasks at the vehicle-road-cloud scale can be described.

[0055] S2. Logical scenario design, see Figure 3 According to the results of functional scenario design and the implementation logic of global optimization of road network-level driving tasks, the cloud receives real-time operation status data and perception data from the road side and vehicle side, integrates the perceived road network traffic situation and traffic decision information, and vehicle driving decision information, and makes collaborative decisions on operation suggestions for the road side and vehicle side in the road network; the road side and vehicle side make collaborative decisions on specific operation given values ​​for the road side and vehicle side and implement control based on their own perception data, combined with the real-time dynamic traffic perception data and operation suggestions issued by the cloud side; the logical scenario of the vehicle-road-cloud integrated system method for intelligent connected vehicles is designed, and the functions of the cloud side, road side and vehicle side, as well as the logical relationship and interface between the above functions are described; the specific steps include the following:

[0056] S21. According to the implementation logic of global optimization of road network-level driving tasks, a vehicle-road-cloud integrated cross-domain model is constructed, including the following logical domains:

[0057] The cloud is responsible for the realization of road network-level cloud functions at the vehicle-road-cloud scale, and for the information exchange between the vehicle-road-cloud integrated system and external systems;

[0058] Road-side: responsible for realizing road-side functions at the road network level at the vehicle-road-cloud scale, and responsible for realizing road-side functions at the vehicle-road scale;

[0059] The vehicle side is responsible for realizing the road network-level vehicle-side functions at the vehicle-road-cloud scale, the vehicle-side functions at the vehicle-road scale, and the vehicle functions at the vehicle-vehicle scale;

[0060] S22. Based on the vehicle-road-cloud integrated cross-domain model, design the logical functions of the cloud, road, and vehicle, as well as the logical relationships and interfaces between the above functions, including:

[0061] The cloud communicates with the road side and the vehicle side, receives data uploaded by the road side and the vehicle side, and the data uploaded by the road side and the vehicle side include location information, real-time traffic perception data, real-time vehicle operation status, real-time vehicle perception data and / or alarm events; performs vehicle-road-cloud fusion perception according to the association relationship of the road network to form vehicle-road-cloud fusion information, and the vehicle-road-cloud fusion information includes traffic situation information, traffic decision information, traffic control information, warning events and / or vehicle driving decision information; the cloud also exchanges information with external systems, and the external systems include meteorological systems, traffic control systems, emergency systems, map systems and / or positioning systems, and makes collaborative decisions based on the tasks of the road network and the information obtained, obtains the road network traffic situation, traffic decision information and / or vehicle driving decision information, and sends them to the road side and the vehicle side;

[0062] The road end communicates with the cloud, other road ends and vehicle ends, sends real-time dynamic traffic perception data of the road section to the cloud, sends road section traffic situation information and / or road section traffic decision information to the surrounding road ends, and sends road section-level dynamic traffic perception data to the vehicle end; receives road network road traffic situation and / or traffic decision information from the cloud, receives road section traffic situation information and / or road section traffic decision information from the surrounding road ends, receives real-time operation status and perception data of the vehicle end in the road section, realizes vehicle-road-cloud fusion perception according to the association relationship of the road section, forms traffic situation information, traffic decision information, traffic control information, warning events and / or vehicle driving decision information of the road section and sends them to the vehicle end;

[0063] The vehicle side communicates with the cloud side, the road side and other vehicle sides, sends the vehicle side's real-time operating status and / or perception data to the cloud side, sends the vehicle side's real-time operating status and / or perception data to the road side, and sends the vehicle side's real-time operating status and / or perception data to the vehicle side; receives road network traffic situation and / or vehicle driving decision information from the cloud side, receives vehicle driving decision information from the road side, traffic perception information of the road section, traffic situation information of the road section, etc., receives real-time operating status and perception data of the vehicle side around the vehicle body, realizes vehicle-road-cloud fusion perception according to the position of the vehicle side, and forms vehicle driving decision information.

[0064] S3. Physical scenario design: Based on the results of the logical scenario design and the implementation logic of the global optimization of the road network-level driving task, the physical scenario of the intelligent connected vehicle vehicle-road-cloud integrated system method is designed, and the specific implementation strategies and input and output parameter values ​​of the cloud, road, and vehicle functions are designed. Finally, the global optimization decision of the driving tasks of each subject at the road network level can be realized. The physical scenario of the intelligent connected vehicle vehicle-road-cloud integrated system method is a layered model, in which:

[0065] See also Figure 4The cloud physical model includes a cloud-based integrated base layer, a cloud-based domain standard component layer, and a cloud-based standardized hierarchical shared interface layer; the standardized hierarchical shared interface layer is used to connect external systems related to traffic services, including meteorological systems, traffic control systems, emergency systems, map systems, and positioning systems; the cloud-based domain standard component layer is mainly used to obtain basic road network traffic information and multi-source data spatiotemporal synchronization from the cloud-based integrated base layer, to realize the cloud-based fusion perception function, collaborative decision-making function, etc., and to transmit road network traffic dynamic change information to the cloud-based standardized hierarchical shared interface layer, and to transmit collaborative decision-making information to the cloud-based integrated base layer. The fusion perception function and collaborative decision-making function mainly include road network traffic dynamic situation perception, road network vehicle dynamic situation perception, road network traffic status perception, obtain road network vehicle operation status, road network traffic warning events, traffic light timing parameter recommendations for sections within the road network, speed limit recommendations for sections within the road network, vehicle speed recommendations within the road network, etc., and provide event warning reminder service information, including forward congestion reminder, beyond-visual-range and blind spot perception, red light running warning, forward collision Collision warning and collision warning for vulnerable traffic participants; the cloud-integrated base layer is mainly used to store data from the road side and the vehicle side, cloud-perception result data, and collaborative decision-making data. The road-side data includes basic road network information obtained from the road network road layer, road network traffic facility layer, road network temporary operation layer, road network target layer, road network environment layer and road network data communication layer. The road network basic information is part of the road network traffic basic information. The road network traffic basic information vehicle perception data, vehicle status data, vehicle positioning data, road-side perception data and traffic light real-time phase information are subjected to data spatiotemporal fusion processing, and perceive road network-level road hazard information, road network-level safety warning information, road network-level emergency events, road network-level traffic event information, road network-level vehicle failure information, etc., and synchronize multi-source data of road sections in spatiotemporal with the cloud-domain standard parts layer, and obtain road section collaborative decision-making information from the cloud-domain standard parts layer to provide road network-level safety event reminder services, collision warning reminder services, traffic dynamic situation, traffic control information, vehicle-road collaborative information and beyond-visual-range and blind spot perception, etc.

[0066] See also Figure 5The road-end physical model includes a road-end data processing layer, a road-end fusion perception and collaborative decision-making layer, and a road-end control layer; the road-end data processing layer is mainly used to store data on the road and vehicle ends. The road-end data includes basic information on the road section obtained from the road section layer, the road section traffic facilities layer, the road section temporary operation layer, the road section target layer, the road section environment layer, and the road section data communication layer. The basic information on the road section is part of the basic information on the road section traffic. The basic information on the road section traffic is processed by data spatiotemporal fusion with the dynamic change data of the previous section of the road section vehicle, the road section vehicle status data and perception data, the vehicle positioning data, the road-end perception data, the real-time phase information of the traffic lights, and the cloud-based decision-making information, and perceives the road section road hazard information, the road section safety warning information, the road section emergency events, the road section traffic event information, the road section vehicle failure information, etc., and synchronizes the multi-source data of the road section in spatiotemporal with the road-end fusion perception and collaborative decision-making layer, and obtains the collaborative decision-making information on the road section from the road-end fusion perception and collaborative decision-making layer. To provide road section safety event reminder service, road section collision warning reminder service, road section traffic dynamic situation, road section traffic control information, road section vehicle-road cooperative information and road section beyond visual range and blind spot perception, etc.; the road-side fusion perception and collaborative decision-making layer is mainly used to realize the road-side fusion perception function, collaborative decision-making function, etc., mainly including road section traffic dynamic situation perception, road section traffic state perception, road section vehicle dynamic situation perception, obtain road section vehicle operation status, road section traffic safety warning events, road section traffic light timing and vehicle speed recommendations, road section speed limit control, road section event perception, etc., provide event warning reminder service information, and exchange road section vehicle-road collaborative decision-making information with the road section control layer. The event warning reminder service information includes forward congestion reminder, beyond visual range and blind spot perception, red light running warning, forward collision warning and collision warning for vulnerable traffic participants; the road-side control layer mainly realizes the control of road section traffic facilities, and the road section traffic facilities include C-V2X (cellular Vehicle-to-everything) RSU (Road Side Unit) cellular vehicle network road side unit, traffic signal, traffic sign and variable information board, etc.

[0067] See also Figure 6The vehicle-side physical model includes a vehicle-side data processing layer, a vehicle-side fusion perception and collaborative decision-making layer, and a vehicle-side control layer; the vehicle-side data processing layer is mainly used to store vehicle-side data, including the vehicle's digital identity and multi-source data of the vehicle, the multi-source data of the vehicle includes dynamic change data of vehicles around the vehicle body, vehicle status data and perception data around the vehicle body, road-side traffic basic information, vehicle positioning data, road-side collaborative decision-making information and 9 cloud-based collaborative decision-making information; the multi-source data of the vehicle is processed through data spatiotemporal fusion to obtain road hazard information of the road section and safety warning information around the vehicle, and synchronize the multi-source data of the vehicle with the vehicle-side fusion perception and collaborative decision-making layer; the vehicle-side data processing layer also receives the collaborative decision-making information of the multi-source data of the vehicle and the vehicle-side fusion perception and collaborative decision-making layer to provide road section safety event reminder services. , road section collision warning reminder service, road section traffic dynamic situation, road section traffic control information, road section vehicle-road collaborative information and road section beyond-visual-range and blind spot perception; the vehicle-side fusion perception and collaborative decision-making layer is mainly used to realize the vehicle-side fusion perception function, collaborative decision-making function, etc., mainly including the perception of the dynamic traffic situation around the vehicle, the perception of the traffic status around the vehicle, the perception of traffic safety warning events around the vehicle, vehicle-to-vehicle collaborative decision-making, vehicle trajectory planning, road hazard warning events, etc. The road hazard warning events include forward congestion reminder, red light running warning, forward collision warning and collision warning for vulnerable traffic participants, etc.; the vehicle-side control layer mainly includes vehicle-side control facilities to realize vehicle control, including lateral speed control, lateral acceleration control, longitudinal speed control, longitudinal acceleration control, warning event response, etc.

[0068] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0069] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A design method for an intelligent connected vehicle vehicle-road-cloud integrated information system, characterized in that: The steps include: S1. Functional scenario design: Based on the spatiotemporal relationship of the road network-level driving tasks, the functional scenarios of the vehicle-road-cloud integrated system of intelligent connected vehicles are designed, describing the vehicle-road-cloud-road network-level functions, the road section-level vehicle-road functions, the vehicle-body area-vehicle functions, and the relationships between the functions at each scale; S2. Logical scenario design: Based on the functional scenario design results and the implementation logic of the global optimization of the road network-level driving task, the logical scenario of the intelligent connected vehicle vehicle-road-cloud integrated system is designed, describing the functions of the cloud, road and vehicle, as well as the logical relationship and interface between the above functions; S3. Physical scenario design: Based on the results of logical scenario design and the implementation logic of global optimization of road network-level driving tasks, design the physical scenario of the intelligent connected vehicle's vehicle-road-cloud integrated system, and design the specific implementation strategies and input and output parameters of cloud-side, road-side, and vehicle-side functions.

2. The method according to claim 1, characterized in that The step S1 specifically includes the following steps: S11. According to the spatiotemporal relationship of the road network-level driving tasks, a vehicle-road-cloud integrated scale model is constructed, wherein the vehicle-road-cloud integrated scale includes the following scales: The vehicle-road-cloud scale is a spatiotemporal scope composed of the vehicle-road scale and the cloud, which enables vehicle-road-cloud interaction and collaboration within the road network. The vehicle-road scale is the spatiotemporal range composed of the vehicle scale and the road end, realizing the interaction and coordination between the vehicle and the road within the road section; The vehicle scale is the space-time range consisting of the vehicle body and the adjacent vehicles around the vehicle body, realizing the interaction and coordination between vehicles; S12. Based on the vehicle-road-cloud integration scale model, describe the following functions: Cloud-road-network-level functions describe the vehicle-road-cloud integrated functions of intelligent connected vehicles at the vehicle-road-cloud scale, and describe the top-level functions of cloud, road-cloud collaboration, and vehicle-cloud collaboration at the vehicle-road-cloud scale; The road section level vehicle-road function describes the road end and vehicle-road coordination functions at the vehicle-road scale; From the vehicle body area vehicle function, the vehicle-side function is described at the vehicle scale; The relationship between functions of various scales, describing the interaction and coordination between vehicle-road-cloud scale functions, vehicle-road scale functions and vehicle-vehicle scale functions; describing the interaction and coordination between vehicle-road scale functions and vehicle-vehicle scale functions under cloud-side coordinated decision-making; describing the interaction and coordination between vehicle-vehicle scale functions under road-side coordinated decision-making.

3. The method according to claim 1, characterized in that Step S2 specifically includes the following steps: S21. According to the implementation logic of global optimization of road network-level driving tasks, a vehicle-road-cloud integrated cross-domain model is constructed, including the following logical domains: The cloud is responsible for the realization of road network-level cloud functions at the vehicle-road-cloud scale, and for the information exchange between the vehicle-road-cloud integrated system and external systems; Road-side: responsible for realizing road-cloud coordination functions at the road network level at the vehicle-road-cloud scale, and for realizing road-side functions at the vehicle-road scale; On the vehicle side, it is responsible for realizing the road network-level vehicle-cloud collaborative functions at the vehicle-road-cloud scale, realizing the vehicle-road collaborative functions at the vehicle-road scale, and realizing the vehicle functions at the vehicle-vehicle scale; S22. Based on the vehicle-road-cloud integrated cross-domain model, design the logical functions of the cloud, road, and vehicle, as well as the logical relationships and interfaces between the above functions, including: The cloud communicates with the road side and the vehicle side, receives data uploaded by the road side and the vehicle side, and the data uploaded by the road side and the vehicle side include location information, real-time traffic perception data, real-time vehicle operation status, real-time vehicle perception data and / or alarm events; performs vehicle-road-cloud fusion perception according to the association relationship of the road network to form vehicle-road-cloud fusion information, and the vehicle-road-cloud fusion information includes traffic situation information, traffic decision information, traffic control information, warning events and / or vehicle driving decision information; the cloud also exchanges information with external systems, and the external systems include meteorological systems, traffic control systems, emergency systems, map systems and / or positioning systems, and makes collaborative decisions based on the tasks of the road network and the information obtained, obtains the road network traffic situation, traffic decision information and / or vehicle driving decision information, and sends them to the road side and the vehicle side; The road end communicates with the cloud, other road ends and vehicle ends, sends real-time dynamic traffic perception data of the road section to the cloud, sends road section traffic situation information and / or road section traffic decision information to the surrounding road ends, and sends road section-level dynamic traffic perception data to the vehicle end; receives road network road traffic situation and / or traffic decision information from the cloud, receives road section traffic situation information and / or road section traffic decision information from the surrounding road ends, receives real-time operation status and perception data of the vehicle end in the road section, realizes vehicle-road-cloud fusion perception according to the association relationship of the road section, forms traffic situation information, traffic decision information, traffic control information, warning events and / or vehicle driving decision information of the road section and sends them to the vehicle end; The vehicle side communicates with the cloud side, the road side and other vehicle sides, sends the vehicle side's real-time operating status and / or perception data to the cloud side, sends the vehicle side's real-time operating status and / or perception data to the road side, and sends the vehicle side's real-time operating status and / or perception data to the vehicle side; receives road network traffic situation and / or vehicle driving decision information from the cloud side, receives vehicle driving decision information from the road side, traffic perception information of the road section, traffic situation information of the road section, etc., receives real-time operating status and perception data of the vehicle side around the vehicle body, realizes vehicle-road-cloud fusion perception according to the position of the vehicle side, and forms vehicle driving decision information.

4. The method according to claim 1, characterized in that In step S3, the physical scenario of the intelligent connected vehicle vehicle-road-cloud integrated system method is a hierarchical model, in which: The cloud includes an integrated base layer, a domain standard component layer, and a standardized hierarchical shared interface layer; The road side includes the road side data processing layer, the road side fusion perception and collaborative decision-making layer, and the road side control layer; The vehicle side includes the vehicle side data processing layer, the vehicle side fusion perception and collaborative decision-making layer, and the vehicle side control layer.

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