An information interaction method for vehicle-road cooperative driving tasks in a connected environment

Abstract

The present invention discloses an information interaction method for vehicle-road cooperative driving tasks in a networked environment, comprising: selecting a networked vehicle or roadside unit with the best interaction applicability as an information interaction center based on computing resource data and communication resource data of all networked vehicles and roadside units participating in the vehicle-road cooperative driving task; the information interaction center collects and aggregates current traffic status information and the position and status information of all networked vehicles, matches and generates an information interaction plan under the current scenario task, and sets timeliness and priority for information links of the information interaction plan based on cooperative driving interaction rules; the information interaction center adjusts interaction nodes for conflicting or inefficient information links to make all information links of the information interaction plan timely; and the information interaction center takes the lead in completing end-to-end information interaction between networked vehicles and roadside RSUs in the scenario based on the information links of the information interaction plan.

Description

Technical Field

[0001] The present invention relates to the technical field of cooperative driving of intelligent networked vehicles, and in particular to an information interaction method for vehicle-road cooperative driving tasks in a networked environment. Background Art

[0002] With the rapid advancement of intelligent and connected technologies, the vehicle-road cooperative control system based on cellular vehicle-to-everything (C-V2X) communication technology has become a hot research topic in the field of intelligent transportation. As a key element of the intelligent transportation system, intelligent vehicles play an important role in improving road traffic efficiency and safety. With the maturity of vehicle-by-wire technology and breakthroughs in vehicle networking related technologies, intelligent vehicles are gradually developing from single-vehicle intelligence to multi-vehicle coordination and vehicle-road coordination.

[0003] In order to complete the multi-vehicle cooperative driving task under vehicle-road cooperative control efficiently and safely, accurate information support is required. However, the information hierarchy in the networked cooperative driving environment is complex, and the information requirements change dynamically with the task scenario. There is a lack of information interaction methods oriented towards cooperative driving tasks in the networked environment. At present, information interaction methods are mostly used for specific driving tasks in simple scenarios, and the degree of flexibility is not high. Therefore, how to improve the existing cooperative driving information interaction methods so that they meet the information interaction requirements of most typical cooperative driving tasks has become an urgent problem to be solved. Summary of the invention

[0004] An embodiment of the present invention provides an information interaction method for vehicle-road cooperative driving tasks in a networked environment, so as to solve the problem that the information interaction method of the vehicle-road cooperative system in the prior art is not flexible enough to meet the information interaction requirements of most typical cooperative driving tasks.

[0005] An embodiment of the present invention provides an information interaction method for a vehicle-road cooperative driving task in a connected environment, comprising:

[0006] The roadside unit participating in the vehicle-road cooperative driving task obtains computing resource data and communication resource data of all connected vehicles and roadside units participating in the vehicle-road cooperative driving task; wherein the computing resource data and / or communication resource data include device hardware attributes and resource occupancy status;

[0007] According to the computing resource data and the communication resource data, the roadside unit calculates the cooperative driving scenario interaction suitability index of all connected vehicles and roadside units; based on the cooperative driving scenario interaction suitability index, the roadside unit selects the connected vehicle or roadside unit with the best interaction suitability as the information interaction center;

[0008] The information interaction center collects and summarizes the current traffic status information and the location and status information of all connected vehicles, matches and generates the information interaction plan under the current scenario task, and sets the timeliness and priority for the information link of the information interaction plan based on the collaborative driving interaction rules;

[0009] The information interaction center adjusts the interaction nodes of conflicting or inefficient information links to ensure that all information links of the information interaction plan are timely accessible. The information interaction center takes the lead in completing the end-to-end information interaction between the connected vehicles and the roadside RSUs in the scene based on the information links of the information interaction plan.

[0010] Optionally, it also includes:

[0011] The information interaction center will obtain the position and speed status of all connected vehicles, traffic event information of roadside units and traffic signal status in the current scene, and input them into the collaborative driving information database to generate an interaction plan for the vehicle-road collaborative driving task requirement information, and further use the collaborative driving interaction rules to set the interaction time and priority for the information interaction plan; among them, the collaborative driving information database is set in each connected vehicle and each roadside unit; the information in the collaborative driving information database is shared through the cellular vehicle network.

[0012] Optionally, it is characterized by further comprising:

[0013] Evaluate the acquired vehicle-road cooperative driving task requirement information:

[0014] If the task requirement information obtained by the connected vehicle or roadside unit is fully covered and has a high confidence level, the information acquisition is completed;

[0015] If the mission requirement information obtained by the connected vehicle or roadside unit is incomplete or has low confidence, a collaborative substitute and compensation estimation scheme for the missing information will be executed.

[0016] Optionally, it is characterized in that, based on the computing resource data and the communication resource data, the roadside unit calculates the cooperative driving scenario interaction applicability index of all connected vehicles and the roadside unit, including:

[0017] Quantitatively process the computing resource data and the communication resource data to obtain corresponding quantized values ​​of the computing resources and the communication resources;

[0018] According to the current vehicle-road cooperative driving task scenario, the computing resources and communication resources are calculated to obtain the interactive applicability index value of the cooperative driving scenario;

[0019] Among them, computing resource data includes: CPU frequency, computing power usage and computing power upper limit information; communication resource data includes: bandwidth, signal-to-noise ratio, channel properties and communication transmission rate.

[0020] Optionally, it is characterized in that the computing resource data and the communication resource data are quantized to obtain the corresponding quantized values ​​of the computing resources and the communication resources, including:

[0021] When the connected vehicle or roadside unit in the vehicle-road cooperative driving task scenario is used as a computing resource, the required resources of each computing unit node in the computing resource under the working upper limit state and the required resources to maintain the basic computing state are obtained;

[0022] All computing resources in the vehicle-road cooperative driving task scenario are calculated based on the CPU frequencies of all computing unit nodes:

[0023]

[0024] Among them, C k is the quantified value of computing resources of all task participants k, in Mcycles / s, which indicates the number of CPU clock cycles available per second; represents the node set of computing units in the task participant k device; f z is the CPU frequency of compute node z, in Hz; Indicates the upper limit utilization of computing node z; Indicates the basic computing occupancy rate of compute node z.

[0025] Optionally, it is characterized by further comprising:

[0026] When the connected vehicle or roadside unit in the vehicle-road cooperative driving task scenario is used as a communication resource, each task participant is a communication device, and the channel gain between the two communication devices is obtained; wherein the communication resource is calculated based on the bandwidth, transmission power and noise power of the communication device:

[0027]

[0028] Among them, R k is the communication resource quantification value of task participant k, in Mbit / s; B k is the bandwidth of task participant k, in MHz; K is the number of collaborative driving task participants; s kk is the channel gain of the communication device of task participant k, s ki is the channel gain between task participant k and task participant i; p k represents the transmission power of task participant k, p i represents the transmission power of task participant i; σ k represents the noise power of task participant k.

[0029] Optionally, it is characterized by further comprising:

[0030] The computing resources and communication resources of the task participants are evaluated and ranked by the scenario task applicability index; the scenario task applicability index calculation formula is:

[0031] Cd k =α t C k +β t R k

[0032] Among them, Cd k represents the scenario task applicability of participant k; α t and β t is the scenario task coefficient of collaborative driving task t.

[0033] Optionally, the information interaction center collects and aggregates the current traffic status information and the location and status information of all connected vehicles, and matches and generates an information interaction plan under the current scenario task, including:

[0034] The information exchange center aggregates the location, speed, acceleration and intention status information of connected vehicles participating in the vehicle-road cooperative driving task, the roadside unit scene map, traffic signals, traffic status and traffic event information;

[0035] The information interaction center combines the scene task type, task objectives, collaborative relationship between task participants and traffic flow characteristics of the vehicle-road cooperative driving task in the current scenario, matches the demand information of the task participants through the cooperative driving information database, and determines the ODC judgment information, scene perception information, vehicle status information and guidance and control information required by the task participants. It also defines the objects, time and areas of the guidance and control information in response to the information needs of different task participants in the four different stages of perception, decision-making, planning and guidance and control.

[0036] Optionally, it also includes:

[0037] The information interaction center uses the connected vehicles and roadside units participating in the vehicle-road cooperative driving task as interaction nodes to form an information interaction topology network; among them, the different information requirements of each interaction node form a variety of information interaction tasks;

[0038] The information interaction center sorts out the information interaction tasks of each interaction node; among them, according to the time and importance of each interaction node to obtain the required information, the information interaction task is set with timeliness requirements and priorities through the collaborative driving information interaction rule base, and the information interaction task is formed into a series of interaction links that change over time on the interaction topology;

[0039] The information interaction center dynamically adjusts the traffic modes of related links according to the temporal and spatial conflicts of the interactive links and the communication constraints of each interactive node, and forms a timely information interaction plan.

[0040] Optionally, collaborative substitution and compensation estimation schemes for missing information include:

[0041] The information exchange center analyzes the categories, information sources, and interactive links of the missing information, and further determines whether the missing information can be supplemented based on the current scenario tasks;

[0042] If possible, the information interaction center obtains collaborative substitute information from similar complementary information sources within the scene;

[0043] If not, the information interaction center uses the information fusion algorithm based on DS evidence theory to perform compensation estimation.

[0044] Beneficial effects of the present invention:

[0045] 1. An embodiment of the present invention proposes an information interaction method for a vehicle-road cooperative driving task in a networked environment, adopts an evaluation method to select an interaction center, accurately matches information interaction needs through a cooperative driving information database and cooperative driving interaction rules, and forms a timely and achievable information interaction plan.

[0046] 2. The embodiment of the present invention sets an information confidence threshold to determine the validity of information, and combines the information collaborative replacement method and the information fusion complementary method to enhance the information demand coverage capability within the collaborative driving task scenario, further improving the various stages of the vehicle-road collaborative driving task information interaction process, and providing better information support for the collaborative driving of connected vehicles and roadside RSUs. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The features and advantages of the present invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the present invention in any way. In the accompanying drawings:

[0048] Figure 1 A flow chart of an information interaction method for a vehicle-road cooperative driving task in a networked environment according to an embodiment of the present invention is shown;

[0049] Figure 2 A flow chart of an information compensation estimation method according to an embodiment of the present invention is shown;

[0050] Figure 3 A flowchart of a collaborative driving task requirement information matching and information interaction scheme is shown in an embodiment of the present invention;

[0051] Figure 4 A relationship diagram of collaborative driving interaction information categories in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0053] The embodiment of the present invention provides an information interaction method for vehicle-road cooperative driving tasks in a networked environment, such as Figure 1 As shown, including:

[0054] Step S10, the roadside unit participating in the vehicle-road cooperative driving task obtains the computing resource data and communication resource data of all connected vehicles and roadside units participating in the vehicle-road cooperative driving task; wherein the computing resource data and / or communication resource data include device hardware attributes and resource occupancy status.

[0055] Step S20, based on the computing resource data and the communication resource data, the roadside unit calculates the collaborative driving scenario interaction suitability index of all connected vehicles and roadside units; based on the collaborative driving scenario interaction suitability index, the roadside unit selects the connected vehicle or roadside unit with the best interaction suitability as the information interaction center.

[0056] In step S30, the information interaction center collects and summarizes the current traffic status information and the location and status information of all connected vehicles, matches and generates an information interaction plan under the current scenario task, and sets the timeliness and priority for the information link of the information interaction plan based on the collaborative driving interaction rules.

[0057] In step S40, the information interaction center adjusts the interaction nodes of the conflicting or inefficient information links to make all information links of the information interaction plan timely accessible; the information interaction center takes the lead in completing the end-to-end information interaction between the networked vehicles and the roadside RSUs in the scene based on the information links of the information interaction plan.

[0058] As an optional implementation method, it also includes: the information interaction center will obtain the position and speed status of all connected vehicles in the current scene, traffic event information of the roadside unit and the traffic signal status, input them into the collaborative driving information database to generate an interaction plan for the vehicle-road collaborative driving task requirement information, and further use the collaborative driving interaction rules to set the interaction time and priority for the information interaction plan; wherein, the collaborative driving information database is set in each connected vehicle and each roadside unit; the information in the collaborative driving information database is shared through Cellular-Vehicle to Everything (C-V2X).

[0059] As an optional implementation, it also includes:

[0060] Evaluate the acquired vehicle-road cooperative driving task demand information:

[0061] If the task requirement information obtained by the connected vehicle or roadside unit is fully covered and has a high confidence level, the information acquisition is completed;

[0062] If the mission requirement information obtained by the connected vehicle or roadside unit is incomplete or has low confidence, a collaborative substitute and compensation estimation scheme for the missing information will be executed.

[0063] In this embodiment, it is determined whether the acquired information is comprehensive and reliable, and the information is supplemented through information collaborative substitution and fusion compensation estimation to meet the information comprehensive coverage collaborative driving requirements.

[0064] In a specific embodiment, the information providers, i.e., connected vehicles, roadside RSUs, and other information sources, assign an initial confidence level to each type of information they provide based on the previous usage of the information, and update the confidence level with each completed information interaction. After the information interaction center completes the D2D information interaction, it compares the confidence level of the information interacted with by a threshold. If the information exceeds the threshold, it is deemed credible; if the information is below the threshold, it is deemed missing, and an information collaborative replacement or compensation estimation plan is executed.

[0065] The confidence threshold is:

[0066]

[0067] Among them, Cf th represents the confidence threshold of a certain type of information; ε is a calibrable and adjustable parameter obtained through actual vehicle testing, and the parameter value of different types of information is different; w is the number of historical cycles of the information; Cf l is the confidence level of the information in the lth historical period; ω l is the correction factor, obtained through actual vehicle testing, and meets the following requirements:

[0068]

[0069] The above formula increases the proportion of confidence in the recent historical period, making the recent confidence reference value higher.

[0070] The specific implementation process of the collaborative substitute and compensation estimation scheme includes: the information interaction center analyzes the specific conditions of the missing information, such as the category, information source, and interaction link, and further determines whether the missing information can be supplemented in combination with the current scene task. For situations that can be supplemented, collaborative substitute information is obtained from similar complementary information sources in the scene; for situations that cannot be supplemented, the information fusion algorithm based on DS evidence theory is used for compensation estimation.

[0071] In a specific embodiment, the implementation method of obtaining collaborative substitution information includes: the information interaction center matches highly relevant similar complementary information in the collaborative driving information library in the information interaction system according to the information attribute characteristics, uses the information collaborative substitution rules in the current scene to determine the substitution plan, and determines the complementary information source, analyzes the complementary information source in the scene, selects information sources with high relevance and confidence to obtain complementary information, and performs collaborative substitution according to the complementary information mapping and conversion method in the information interaction system.

[0072] like Figure 2 As shown in the figure, the specific implementation steps of the information fusion algorithm based on DS evidence theory are as follows:

[0073] According to the required fusion target information, obtain the relevant feature fact information of the information in the information exchange center, establish a fusion identification framework Θ applicable to the information, and construct a decision sample space containing multiple pairwise repulsive objects according to the possible fusion decision results of the information:

[0074] θ={θ 1 ,θ 2 , ..., θ n}

[0075] The power set of the identification frame Θ contains 2 n Elements:

[0076] P(θ)={φ,θ 1 ,θ 2 , {θ 1 ,θ 2}, ..., Θ}

[0077] The power set is the set of all subsets of Θ including the empty set; θ 1 θ 2 θ n θ i θ m

[0078] Aiming at the fusion decision orientation of target information, a fusion decision judgment rule under the identification framework is designed to judge whether each element in the power set in the fusion decision is a factual result. The basic probability distribution function under this rule is called the mass function: Θ →[0, 1], and satisfy the following formula:

[0079]

[0080] According to the actual verification test, different sets of judgment rules applicable to different information can be determined, and the basic probability distribution function under the rules can be obtained: m 1 , m 2 , ..., m n ;

[0081] According to the combined rule calculation method of DS evidence theory, the multi-probability distribution function under the combination of calculation rules is:

[0082]

[0083] Where M(A) is the multi-probability allocation function of element A in the identification framework power set, q is the normalization coefficient, and the expression is as follows:

[0084]

[0085] If q = 0, it means that the combination rules are contradictory and the combination cannot be performed;

[0086] The trust function Bel(A) and plausibility function Pl(A) of element A in the power set are calculated based on the multi-probability distribution function:

[0087]

[0088]

[0089] Where F is an element in the power set and it contains element A, [0, Bel(A)] is the support interval of A, [0, Pl(A)] is the unsuspected interval of A, and [Pl(A, 1] is the rejection interval of A;

[0090] The probability distribution of the recognition frame Θ is obtained by the PraPl method, and the final fusion result is determined based on it:

[0091]

[0092] Among them, PraPl(θ x ) is the element θ to be decided in Θ x The probability distribution of this fusion decision is θ under the combined rule judgment. x is the probability of the actual decision result, thus by comparing different θ in Θ x The probability distribution size is used to obtain the most likely decision result, and the target information is obtained based on the decision result.

[0093] As an optional implementation, the interactive applicability of the cooperative driving scenario is evaluated for the connected vehicles and the roadside unit in the vehicle-road cooperative driving task scenario, including:

[0094] Obtain information such as the number, CPU frequency, computing power usage and computing power limit of the computing hardware of connected vehicles and roadside units, and obtain information such as bandwidth, noise, channel properties, power, etc. of communication hardware;

[0095] The computing hardware information and communication hardware information are quantified to obtain the corresponding quantified values ​​of computing resources and communication resources:

[0096] When the connected vehicle or roadside unit in the vehicle-road cooperative driving task scenario is used as a computing resource, the required resources of each computing unit node in the computing resource under the working upper limit state and the required resources to maintain the basic computing state are obtained;

[0097] All computing resources in the vehicle-road cooperative driving task scenario are calculated based on the CPU frequencies of all computing unit nodes:

[0098]

[0099] Among them, C k is the quantified value of computing resources of all task participants k, in Mcycles / s, which indicates the number of CPU clock cycles available per second; represents the node set of computing units in the task participant k device; f z is the CPU frequency of compute node z, in Hz; Indicates the upper limit utilization of computing node z; Indicates the basic computing occupancy rate of compute node z.

[0100] When the connected vehicle or roadside unit in the vehicle-road cooperative driving task scenario is used as a communication resource, each task participant is a communication device, and the channel gain between the two communication devices is obtained; wherein the communication resource is calculated based on the bandwidth, transmission power and noise power of the communication device:

[0101]

[0102] Among them, R k is the communication resource quantification value of task participant k, in Mbit / s; B k is the bandwidth of task participant k, in MHz; K is the number of collaborative driving task participants; s kk is the channel gain of the communication device of task participant k, s ki is the channel gain between task participant k and task participant i; p k represents the transmission power of task participant k, p i represents the transmission power of task participant i; σ k represents the noise power of task participant k.

[0103] A comprehensive comparison of computing resources and communication resources is made based on the current vehicle-road cooperative driving task scenarios.

[0104] In this embodiment, the computing resources and communication resources of the task participants are evaluated and ranked by the scenario task applicability index; wherein the scenario task applicability index calculation formula is:

[0105] Cdk =α t C k +β t R k ;

[0106] Among them, Cd k represents the scenario task applicability of participant k; α t and β t is the scenario task coefficient of collaborative driving task t.

[0107] As an optional implementation, Figure 3 As shown, the information interaction center generates an interactive solution for collaborative driving task requirement information through the collaborative driving information database, including:

[0108] The information exchange center aggregates the location, speed, acceleration and intention status information of connected vehicles participating in the vehicle-road cooperative driving task, the roadside unit scene map, traffic signals, traffic status and traffic event information;

[0109] The information interaction center combines the scene task type, task objectives, collaborative relationship between task participants and traffic flow characteristics of the vehicle-road cooperative driving task in the current scenario, matches the demand information of the task participants through the cooperative driving information database, and determines the ODC judgment information, scene perception information, vehicle status information and guidance and control information required by the task participants. It also defines the objects, time and areas of the guidance and control information in response to the information needs of different task participants in the four different stages of perception, decision-making, planning and guidance and control.

[0110] As an optional implementation, it also includes:

[0111] The information interaction center uses the connected vehicles and roadside units participating in the vehicle-road cooperative driving task as interaction nodes to form an information interaction topology network; the information interaction plan determines the different information requirements of each interaction node and forms a complex interaction task between task participants at the same location, at different times, and with multiple information categories;

[0112] The information interaction center prioritizes the complex interactive tasks under the information interaction scheme according to the time requirements for each interactive node to obtain a certain type of required information under the information interaction scheme and the importance of such information to the completion of the collaborative driving task. It sets timeliness requirements and priorities for the information interaction tasks through the collaborative driving information interaction rule base, sets priorities for the three categories of safety, efficiency, and service, and specifically subdivides the priorities according to the timeliness requirements. It also forms a series of interactive links that change over time on the interactive topology for the information interaction tasks.

[0113] The information interaction center dynamically adjusts the interaction nodes through which the interaction links pass in response to the time and space conflicts of the interaction links and the communication constraints of each interaction node, so that the interaction links are smooth and timely.

[0114] In a specific embodiment, the information interaction scheme involves four types of interactive information: ODC discrimination information, scene perception information, vehicle status information, and guidance control information. The relationship between these four types of information and the specific types of information in the collaborative driving scene is as follows: Figure 4 As shown, the information categories existing in the collaborative driving scenario are: basic vehicle safety information, roadside safety information, map information, traffic light information, traffic event / sign information, RTCM differential enhancement information, information on roadside unit vehicle collaboration or guidance, traffic participants, road obstacles and traffic events perception sharing information, vehicle intention and request information, parking area information, basic safety information of vulnerable traffic participants (pedestrians, non-motor vehicles), connectionless fleet management information, vehicle payment information, vehicle intention sharing information, business capability announcement information. These categories of information alone or in combination form the above four categories of interactive information.

[0115] In a specific embodiment, when the information interaction task under the information interaction scheme involves a specific interaction information category, the security, efficiency, and service priority levels are set according to Table 1:

[0116] Table 1 Different priority categories of interactive information in cooperative driving scenarios

[0117]

[0118] In the process of information interaction led by the interaction center, the priority of the interaction link is security first, efficiency second, and service last. The priority interaction links of the same category are sorted according to the timeliness requirements. The sorting method is set according to Table 2. The smaller the level, the higher the priority.

[0119] Table 2 Information link time priority level

[0120]

[0121] This embodiment proposes an information interaction method for vehicle-road cooperative driving tasks in a networked environment, adopts an evaluation method to select an information interaction center, accurately matches information interaction needs through means such as a cooperative driving information database and cooperative driving interaction rules, and forms a timely information interaction plan, sets an information confidence threshold to determine the validity of the information, and combines an information cooperative replacement method and an information fusion complementary method to enhance the information demand coverage capability within the cooperative driving task scenario, further improve the flexibility of information interaction for vehicle-road cooperative driving tasks, and provide better information support for the cooperative driving of networked vehicles and roadside RSUs.

[0122] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. An information interaction method for vehicle-road cooperative driving tasks in a connected environment, characterized in that: include: The roadside unit participating in the vehicle-road cooperative driving task obtains computing resource data and communication resource data of all connected vehicles participating in the vehicle-road cooperative driving task and the roadside unit; wherein the computing resource data and / or the communication resource data include device hardware attributes and resource occupancy status; The roadside unit calculates the cooperative driving scenario interaction suitability index of all the connected vehicles and the roadside unit according to the computing resource data and the communication resource data; based on the cooperative driving scenario interaction suitability index, the roadside unit selects the connected vehicle or the roadside unit with the best interaction suitability as the information interaction center; The information interaction center collects and aggregates the current traffic status information and the location and status information of all the connected vehicles, matches and generates an information interaction plan under the current scenario task, and sets the timeliness and priority for the information link of the information interaction plan based on the collaborative driving interaction rules; The information interaction center adjusts the interaction nodes of conflicting or inefficient information links to make all information links of the information interaction scheme reachable in time; the information interaction center takes the lead in completing the end-to-end information interaction between the networked vehicles and the roadside RSU in the scene based on the information links of the information interaction scheme; According to the computing resource data and the communication resource data, the roadside unit calculates the cooperative driving scenario interaction applicability index of all the connected vehicles and the roadside unit, including: Quantizing the computing resource data and the communication resource data to obtain corresponding quantized values ​​of computing resources and communication resources; The computing resources and the communication resources are calculated according to the current vehicle-road cooperative driving task scenario to obtain a cooperative driving scenario interaction applicability index value; The computing resource data includes: CPU frequency, computing power usage and computing power upper limit information; the communication resource data includes: bandwidth, signal-to-noise ratio, channel attributes and communication transmission rate; The computing resource data and the communication resource data are quantized to obtain corresponding quantized values ​​of computing resources and communication resources, including: When the networked vehicle or the roadside unit in the vehicle-road cooperative driving task scenario is used as a computing resource, the required resources of each computing unit node in the computing resource under the working upper limit state and the required resources under the basic computing state are obtained; All computing resources in the vehicle-road cooperative driving task scenario are obtained by summarizing and calculating the CPU frequencies of all the computing unit nodes: Among them, C k is the quantified value of computing resources of all task participants k, in Mcycles / s, which indicates the number of CPU clock cycles available per second; represents the node set of computing units in the task participant k device; z is the CPU frequency of compute node z, in Hz; represents the upper limit utilization rate of the computing node z; Indicates the basic computing occupancy rate of the computing node z; When the networked vehicle or the roadside unit in the vehicle-road cooperative driving task scenario is used as a communication resource, each of the task participants is a communication device, and the channel gain between the two communication devices is obtained; wherein the communication resource is calculated according to the bandwidth, transmission power and noise power of the communication device: Among them, R k is the communication resource quantification value of task participant k, in Mbit / s; B k is the bandwidth of task participant k, in MHz; K is the number of collaborative driving task participants; sk k is the channel gain of the communication device of task participant k, sk i is the channel gain between task participant k and task participant i; p k represents the transmission power of task participant k, p i represents the transmission power of task participant i; σk represents the noise power of task participant k; The computing resources and communication resources of the task participants are evaluated and ranked by the scenario task applicability index; wherein the scenario task applicability index calculation formula is: CD k =a t C k +b t R k Among them, Cd k represents the scenario task applicability of participant k; α t and β t is the scenario task coefficient of collaborative driving task t.

2. The information interaction method for vehicle-road cooperative driving tasks in a connected environment according to claim 1, characterized in that: Also includes: The information interaction center obtains the position and speed status of all the connected vehicles in the current scene, the traffic event information of the roadside unit and the traffic signal status, and inputs them into the collaborative driving information library to generate the information interaction plan under the current scene task, and further uses the collaborative driving interaction rules to set the interaction time and priority for the information link of the information interaction plan; wherein the collaborative driving information library is set in each of the connected vehicles and each of the roadside units; the information in the collaborative driving information library is shared through the cellular vehicle network.

3. The information interaction method for vehicle-road cooperative driving tasks in a connected environment according to claim 2, characterized in that: Also includes: Evaluate the acquired vehicle-road cooperative driving task requirement information: If the task requirement information acquired by the connected vehicle or the roadside unit is fully covered and has a high confidence level, the information acquisition is completed; If the mission requirement information acquired by the connected vehicle or the roadside unit is incomplete or has low confidence, a collaborative replacement and compensation estimation scheme for the missing information is executed.

4. The information interaction method for vehicle-road cooperative driving tasks in a connected environment according to claim 2, characterized in that: The information interaction center collects and aggregates the current traffic status information and the location and status information of all the connected vehicles, and matches and generates an information interaction plan under the current scenario task, including: The information exchange center aggregates the location, speed, acceleration and intention status information of the networked vehicles participating in the vehicle-road cooperative driving task, the roadside unit scene map, traffic signals, traffic status and traffic event information; The information interaction center combines the scene task type, task objectives, collaborative relationship of the task participants and traffic flow characteristics of the vehicle-road collaborative driving task in the current scene, matches the demand information of the task participants through the collaborative driving information database, determines the ODC judgment information, scene perception information, vehicle status information and guidance and control information required by the task participants, and defines the objects, time and areas of the guidance and control information in response to the information needs of different task participants in the four different stages of perception, decision-making, planning and guidance and control.

5. The information interaction method for vehicle-road cooperative driving tasks in a connected environment according to claim 1, characterized in that: Also includes: The information interaction center uses the networked vehicles and the roadside units participating in the vehicle-road cooperative driving task as interaction nodes to form an information interaction topology network; wherein the different information requirements of each interaction node form multiple types of information interaction tasks; The information interaction center sorts out the information interaction tasks of each interaction node; wherein, according to the time and importance of each interaction node obtaining the required information, the information link of the information interaction task is set with timeliness requirements and priorities through the collaborative driving information interaction rules, and the information interaction task is formed into a series of interaction links that change over time on the interaction topology; The information interaction center dynamically adjusts the traffic mode of the relevant links according to the time and space conflicts of the interactive links and the communication limitations of each of the interactive nodes, so as to form a timely information interaction plan.

6. The information interaction method for vehicle-road cooperative driving tasks in a connected environment according to claim 3, characterized in that: The collaborative substitution and compensation estimation schemes for missing information include: The information interaction center analyzes the category, information source and interaction link of the missing information, and further determines whether the missing information can be supplemented in combination with the current scenario task; If so, the information exchange center obtains collaborative substitute information from similar complementary information sources in the scene; If not, the information interaction center uses an information fusion algorithm based on DS evidence theory to perform compensation estimation.

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