Traffic signal lamp issuing method, system and equipment based on vehicle-road cloud integration

Abstract

The invention provides a traffic signal lamp issuing method, system and device based on vehicle-road cloud integration, and the method comprises the steps: obtaining the path planning information or position information and course information of a vehicle end, and obtaining the path planning information or position information and course information according to the path planning information or position information and course information; matching information of traffic lights which are about to pass within a preset vehicle driving distance; when it is sensed that the vehicle enters the preset RSU coverage range of the intersection, dynamic data source parameters of the vehicle end are obtained, and corresponding weight parameter values are calculated according to the dynamic data source parameters; and matching a corresponding traffic signal lamp information data source according to the weight parameter value, and sending traffic signal lamp information corresponding to the intersection to the vehicle through the traffic signal lamp information data source. The optimal data source is dynamically selected, it is ensured that the vehicle can obtain accurate and timely traffic signal lamp information, and the efficiency and reliability of an intelligent traffic system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic systems, and in particular to a method, system and device for issuing traffic signals based on vehicle-road-cloud integration. Background Art

[0002] In existing intelligent transportation systems, vehicles usually rely on on-board devices to receive traffic light information, such as broadcasting the status of traffic lights through RSU (roadside units) or obtaining traffic light data through the network. However, due to the limited coverage of RSU and the existence of network delays, the timeliness and accuracy of vehicles' acquisition of traffic light information are affected. In a high-density traffic environment, a single data source may not meet the needs of all vehicles, resulting in poor traffic flow and affecting traffic efficiency.

[0003] Most existing map developers obtain traffic light data at each intersection through big data algorithm calculations, but the technical problems are as follows: High latency: Traditional map service providers such as Amap and Tencent Map obtain traffic light data through big data algorithm calculations, with a latency of about 2 seconds. The traffic light transmission latency based on V2X technology is only 20 milliseconds, which greatly improves the real-time nature of information transmission. This ultra-low latency capability is crucial for dynamic traffic management and autonomous driving vehicle intersection driving decision management, because it allows vehicles to respond to changes in traffic signals in a timely manner, thereby reducing traffic accidents and improving traffic efficiency. Low reliability: The vehicle-road-cloud integrated system can achieve direct communication between vehicles and roadside infrastructure through V2X technology, which is more stable and reliable than traditional methods that rely on cloud data processing. V2X technology supports vehicles to communicate even when there is no network coverage, which is crucial to ensuring the accurate transmission of traffic light information. Summary of the invention

[0004] The purpose of the present invention is to propose a method, system and device for issuing traffic light information based on vehicle-road-cloud integration, so as to solve the technical problems that vehicles have a single way of obtaining traffic light information, have a large delay and inaccurate information.

[0005] On the one hand, a method for issuing traffic lights based on vehicle-road-cloud integration is provided, comprising:

[0006] Obtaining the path planning information or location information and heading information of the vehicle, and matching the traffic light information within a preset driving distance and to be passed by the vehicle according to the path planning information or location information and heading information;

[0007] When it is sensed that a vehicle enters the preset RSU coverage range of the intersection, the dynamic data source parameters of the vehicle are obtained, and the corresponding weight parameter values ​​are calculated according to the dynamic data source parameters; and the corresponding traffic light information data source is matched according to the weight parameter value, and the traffic light information corresponding to the intersection is sent to the vehicle through the traffic light information data source; wherein, the traffic light information data source includes at least RSU broadcast or cloud control platform issuance.

[0008] Preferably, the dynamic data source parameters at least include:

[0009] Network delay parameters, including the delay time of RSU broadcast signals and the delay time of signals sent by the cloud control platform;

[0010] Signal strength parameter, which is the signal strength of the RSU;

[0011] Data accuracy parameters, including the accuracy score of RSU traffic light data and the accuracy score of cloud control platform traffic light data;

[0012] The distance parameter is the distance between the vehicle and the intersection.

[0013] Preferably, the calculating of the corresponding weight parameter value according to the dynamic data source parameter includes:

[0014] The data source weight of the corresponding RSU broadcast signal is calculated by the following formula:

[0015]

[0016] Among them, α is the delay weight coefficient; β is the signal strength weight coefficient; γ is the data accuracy weight coefficient; δ is the distance weight coefficient; W RSU is the data source weight of the RSU broadcast signal; T RSU is the delay time of the RSU broadcast signal; R RSU is the signal strength of RSU; A RSU Score the accuracy of the RSU signal light data; D Veh is the distance between the vehicle and the intersection.

[0017] Preferably, the calculating of the corresponding weight parameter value according to the dynamic data source parameter also includes:

[0018] The data source weight of the signal sent by the corresponding cloud control platform is calculated by the following formula:

[0019]

[0020] Among them, W Cloud The weight of the data source that sends the signal to the cloud control platform; T Cloud A is the delay time of sending signals from the cloud control platform; CloudScore the accuracy of traffic light data on the cloud control platform.

[0021] Preferably, the matching of the corresponding traffic light information data source according to the weight parameter value includes:

[0022] When the data source weight of the RSU broadcast signal is greater than the data source weight of the signal sent by the cloud control platform, the data source of the traffic light information is set to the RSU broadcast data.

[0023] When the data source weight of the RSU broadcast signal is less than the data source weight of the signal sent by the cloud control platform, the data source of the traffic light information is set to the data sent by the cloud control platform.

[0024] Preferably, the method further includes setting the traffic light information data source to RSU broadcast data if the distance between the vehicle and the intersection is less than a preset distance threshold.

[0025] Preferably, the method further includes setting the traffic light information data source to data sent by the cloud control platform if the RSU signal strength is lower than a preset signal threshold.

[0026] Preferably, it also includes:

[0027] When it is sensed that a vehicle has crossed the stop line of the intersection, the traffic light information corresponding to the intersection is stopped from being sent.

[0028] On the other hand, a traffic signal light issuing system based on vehicle-road-cloud integration is also provided, which is used to implement the traffic signal light issuing method based on vehicle-road-cloud integration, including:

[0029] The control end is used to obtain the path planning information or position information and heading information of the vehicle end, and match the traffic light information within a preset vehicle driving distance and to be passed according to the path planning information or position information and heading information;

[0030] When it is sensed that a vehicle enters the preset RSU coverage range of the intersection, the dynamic data source parameters of the vehicle are obtained, and the corresponding weight parameter values ​​are calculated according to the dynamic data source parameters; and the corresponding traffic light information data source is matched according to the weight parameter value, and the traffic light information corresponding to the intersection is sent to the vehicle through the traffic light information data source; wherein, the traffic light information data source includes at least RSU broadcast or cloud control platform issuance.

[0031] On the other hand, a device is also provided for sending traffic light information to vehicles through the traffic light sending method based on vehicle-road-cloud integration.

[0032] In summary, the implementation of the embodiments of the present invention has the following beneficial effects:

[0033] The method, system and device for issuing traffic lights based on vehicle-road-cloud integration provided by the present invention dynamically select the optimal data source by combining the distance between the vehicle and the intersection, network delay, RSU signal strength and the accuracy of traffic light data, thereby ensuring that the vehicle can obtain accurate and timely traffic light information, thereby improving the efficiency and reliability of the intelligent transportation system; the vehicle can select the best traffic light data source, thereby improving the accuracy of traffic light information; reducing the demand for new hardware, reducing deployment and maintenance costs, and improving the utilization efficiency of existing infrastructure. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, without paying creative labor, other drawings obtained based on these drawings still belong to the scope of the present invention.

[0035] Figure 1 This is a schematic diagram of the main process of a method for issuing traffic lights based on vehicle-road-cloud integration in an embodiment of the present invention.

[0036] Figure 2 This is a logical schematic diagram of a method for issuing traffic lights based on vehicle-road-cloud integration in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings.

[0038] like Figure 1 and Figure 2 FIG. 1 is a schematic diagram of an embodiment of a method for issuing traffic signal lights based on vehicle-road-cloud integration provided by the present invention. In this embodiment, the method includes the following steps:

[0039] Step S1, obtain the path planning information or location information and heading information of the vehicle, and match the traffic light information within the preset driving distance and that the vehicle will pass according to the path planning information or location information and heading information; understandably, the vehicle goes online to establish a long connection with the platform; the online vehicle sends the path planning information or location and heading information to the platform; the vehicle obtains the traffic light information matched by the platform according to the path planning information or location and heading information; there are two options for the data source of traffic light information, one is that the RSU directly collects it from the traffic signal machine; the other is to obtain it by docking with the traffic control platform. The latter can further improve the networking rate of traffic lights without the support of new hardware equipment. If the vehicle reports the path planning information to the platform, the platform will feedback the traffic light information within a certain driving distance and that the vehicle will pass.

[0040] Step S2, when it is sensed that the vehicle enters the preset RSU coverage range of the intersection, the dynamic data source parameters of the vehicle are obtained, and the corresponding weight parameter values ​​are calculated according to the dynamic data source parameters; and the corresponding traffic light information data source is matched according to the weight parameter value, and the traffic light information corresponding to the intersection is sent to the vehicle through the traffic light information data source; wherein the traffic light information data source includes at least RSU broadcast or cloud control platform transmission. It can be understood that the vehicle continues to move; the vehicle enters the RSU coverage range of the intersection; the vehicle chooses to use the data broadcast by RSU or the cloud control platform according to the algorithm to dynamically calculate the weight; the vehicle crosses the stop line, leaves the intersection, and stops receiving the traffic light information of the intersection; according to the dynamic data source weight, the data source is dynamically selected based on parameters such as network delay, signal strength, data accuracy, and the distance between the vehicle and the intersection.

[0041] In one embodiment, the dynamic data source parameters include at least network delay parameters, including the delay time of the RSU broadcast signal and the delay time of the cloud control platform sending the signal; signal strength parameters, which are the signal strength of the RSU (RSSI-Received Signal Strength Indicator); data accuracy parameters, including the accuracy score of the RSU signal light data (evaluated based on historical data) and the accuracy score of the cloud control platform signal light data; distance parameters, which are the distance between the vehicle and the intersection. Veh: The distance between the vehicle and the intersection.

[0042] In one embodiment, the calculating of the corresponding weight parameter value according to the dynamic data source parameter includes:

[0043] The data source weight of the corresponding RSU broadcast signal is calculated by the following formula:

[0044]

[0045] Among them, α is the delay weight coefficient; β is the signal strength weight coefficient; γ is the data accuracy weight coefficient; δ is the distance weight coefficient; W RSU is the data source weight of the RSU broadcast signal; T RSU is the delay time of the RSU broadcast signal; R RSU is the signal strength of RSU; A RSU Score the accuracy of the RSU signal light data; D Veh is the distance between the vehicle and the intersection.

[0046] The data source weight of the signal sent by the corresponding cloud control platform is calculated by the following formula:

[0047]

[0048] Among them, W Cloud The weight of the data source that sends the signal to the cloud control platform; T Cloud A is the delay time of sending signals from the cloud control platform; Cloud Score the accuracy of traffic light data on the cloud control platform.

[0049] For the coefficient parameters, α: delay weight coefficient, usually a positive number, used to reflect the impact of network delay on decision-making. The lower the delay, the greater the weight. β: signal strength weight coefficient, reflecting the impact of RSU signal strength on decision-making. The stronger the signal strength, the greater the weight. γ: data accuracy weight coefficient, reflecting the impact of the historical accuracy of the data on the choice. The higher the accuracy, the greater the weight. δ: distance weight coefficient, indicating the impact of the distance between the vehicle and the intersection on the decision. The closer the distance, the greater the weight. According to the data accuracy weight coefficients involved above, it is necessary to determine the coefficient by combining multiple factors to calculate the data accuracy score of each data source, such as historical data of traffic light status, delay, signal strength, and real-time update frequency of data.

[0050] The main factor affecting accuracy: delay time T delay : The delay time for traffic light data to reach the vehicle from the data source (cloud control platform or RSU). The shorter the delay, the more timely the data and the higher the accuracy. Historical Accuracy A hist : The accuracy of the traffic light status in historical data, usually obtained through traffic control platform or RSU statistics. Signal update frequency F update : The update frequency of the signal light data (the frequency of data push). The higher the frequency, the more timely the data. RSU signal strength R RSSI : The strength of the RSU signal received by the vehicle. The stronger the signal, the smaller the probability of data packet loss and the higher the accuracy. The specific algorithm is as follows:

[0051]

[0052] The meaning of the parameters in the formula: A score : Traffic light accuracy score, ranging from [0,1]. The closer to 1, the more accurate the traffic light data. delay : Delay time of signal light data. T max : The maximum delay time threshold is set. Data exceeding this threshold is considered invalid. Usually set to the maximum delay that the system can accept, such as 500ms. hist : The accuracy of the historical data of the traffic light, ranging from [0,1], is determined by the historical statistical data of the traffic light. update : The update frequency of the traffic light data, indicating the number of times the traffic light status is updated per second. max : The maximum update frequency threshold is used to normalize the update frequency. For example, the maximum update frequency can be set to 10 times / second. RSSI : RSU signal strength, measured using RSSI. max : Maximum signal strength threshold, usually set to -30dBm (very strong signal). α, β, γ, δ: These are weight coefficients that reflect the impact of different factors on accuracy. Their values ​​can be adjusted according to system requirements. α: Weight of delay, usually set to a higher value because delay directly affects the timeliness of data, with a recommended value of 0.4. β: Weight of historical accuracy, with a recommended value of 0.3; γ: Weight of update frequency, with a recommended value of 0.2; δ: Weight of signal strength, with a recommended value of 0.1. In summary, this accuracy scoring algorithm combines factors such as signal delay, historical data, signal update frequency, and signal strength to dynamically calculate the credibility of traffic light data. In this way, vehicles can select the optimal data source based on the score to ensure the accuracy and security of traffic light information.

[0053] One embodiment further includes, if the distance between the vehicle and the intersection is less than a preset distance threshold, setting the traffic light information data source to the RSU broadcast data. That is, when the distance between the vehicle and the intersection meets a special condition, that is, if D veh Less than a certain threshold D threshold (i.e., when the vehicle approaches the intersection very closely), the RSU broadcast information is given priority, even if the data delay of the cloud control platform is lower.

[0054] One embodiment further includes, if the RSU signal strength is lower than a preset signal threshold, setting the traffic light information data source to the data sent by the cloud control platform. That is, when the RSU signal strength meets a special condition, that is, if the RSU signal strength R RSU If it is lower than a certain value (e.g., the RSU signal is very weak), the RSU broadcast information is ignored and the data of the cloud control platform is directly selected.

[0055] In this embodiment, data sources are dynamically selected through multiple channels: it is proposed that the vehicle dynamically selects a method for obtaining traffic light information according to real-time conditions, including push from the cloud control platform and RSU broadcast. Weight scoring algorithm and accuracy scoring algorithm: a traffic light data accuracy scoring algorithm is designed, which combines factors such as delay, historical accuracy, update frequency, signal strength and distance to provide a basis for data source selection. Real-time communication mechanism: a long connection is established between the vehicle and the cloud control platform to ensure real-time acquisition of traffic light information. Intelligent decision-making logic: when the vehicle approaches an intersection, the data source used is automatically adjusted according to factors such as network delay and signal strength to improve the accuracy and timeliness of the information. Improved coverage: by connecting to the traffic management platform, the networking rate of traffic lights is increased, reducing the need for new hardware. Adapt to complex traffic scenarios: in high-density traffic environments, it can flexibly respond to the needs for obtaining traffic light information in different situations and improve traffic efficiency.

[0056] The embodiment of the present invention further provides a traffic signal light issuing system based on vehicle-road-cloud integration, which is used to implement the traffic signal light issuing method based on vehicle-road-cloud integration, including:

[0057] The control end is used to obtain the path planning information or position information and heading information of the vehicle end, and match the traffic light information within a preset vehicle driving distance and to be passed according to the path planning information or position information and heading information;

[0058] When it is sensed that a vehicle enters the preset RSU coverage range of the intersection, the dynamic data source parameters of the vehicle are obtained, and the corresponding weight parameter values ​​are calculated according to the dynamic data source parameters; and the corresponding traffic light information data source is matched according to the weight parameter value, and the traffic light information corresponding to the intersection is sent to the vehicle through the traffic light information data source; wherein, the traffic light information data source includes at least RSU broadcast or cloud control platform issuance.

[0059] An embodiment of the present invention further provides a device for sending traffic light information to vehicles through the traffic light sending method based on vehicle-road-cloud integration.

[0060] It should be noted that the system described in the above embodiment corresponds to the method described in the above embodiment. Therefore, the undetailed parts of the system described in the above embodiment can be obtained by referring to the contents of the method described in the above embodiment, and will not be repeated here.

[0061] In summary, the implementation of the embodiments of the present invention has the following beneficial effects:

[0062] The method, system and device for issuing traffic lights based on vehicle-road-cloud integration provided by the present invention dynamically select the optimal data source by combining the distance between the vehicle and the intersection, network delay, RSU signal strength and the accuracy of traffic light data, thereby ensuring that the vehicle can obtain accurate and timely traffic light information, thereby improving the efficiency and reliability of the intelligent transportation system; the vehicle can select the best traffic light data source, thereby improving the accuracy of traffic light information; reducing the demand for new hardware, reducing deployment and maintenance costs, and improving the utilization efficiency of existing infrastructure.

[0063] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for issuing traffic signal lights based on vehicle-road-cloud integration, characterized in that: include: Obtaining the path planning information or location information and heading information of the vehicle, and matching the traffic light information within a preset driving distance and to be passed by the vehicle according to the path planning information or location information and heading information; When a vehicle is sensed to enter the preset RSU coverage area of ​​the intersection, the dynamic data source parameters of the vehicle are obtained, and the corresponding weight parameter values ​​are calculated according to the dynamic data source parameters; And according to the weight parameter value, the corresponding traffic light information data source is matched, and the traffic light information corresponding to the intersection is sent to the vehicle through the traffic light information data source; wherein, the traffic light information data source at least includes RSU broadcast or cloud control platform issuance.

2. The method according to claim 1, characterized in that The dynamic data source parameters at least include: Network delay parameters, including the delay time of RSU broadcast signals and the delay time of signals sent by the cloud control platform; Signal strength parameter, which is the signal strength of the RSU; Data accuracy parameters, including the accuracy score of RSU traffic light data and the accuracy score of cloud control platform traffic light data; The distance parameter is the distance between the vehicle and the intersection.

3. The method according to claim 2, characterized in that The calculation of the corresponding weight parameter value according to the dynamic data source parameter includes: The data source weight of the corresponding RSU broadcast signal is calculated by the following formula: Among them, α is the delay weight coefficient; β is the signal strength weight coefficient; γ is the data accuracy weight coefficient; δ is the distance weight coefficient; W RSU is the data source weight of the RSU broadcast signal; T RSU is the delay time of the RSU broadcast signal; R RSU is the signal strength of RSU; A RSU Score the accuracy of the RSU signal light data; D Veh is the distance between the vehicle and the intersection.

4. The method according to claim 3, characterized in that The calculating of the corresponding weight parameter value according to the dynamic data source parameter also includes: The data source weight of the signal sent by the corresponding cloud control platform is calculated by the following formula: Among them, W Cloud The weight of the data source that sends the signal to the cloud control platform; T Cloud A is the delay time of sending signals from the cloud control platform; Cloud Score the accuracy of traffic light data on the cloud control platform.

5. The method according to claim 4, characterized in that The method of matching the corresponding traffic light information data source according to the weight parameter value includes: When the data source weight of the RSU broadcast signal is greater than the data source weight of the signal sent by the cloud control platform, the data source of the traffic light information is set to the RSU broadcast data. When the data source weight of the RSU broadcast signal is less than the data source weight of the signal sent by the cloud control platform, the data source of the traffic light information is set to the data sent by the cloud control platform.

6. The method according to claim 2, characterized in that The method also includes setting the traffic light information data source to RSU broadcast data if the distance between the vehicle and the intersection is less than a preset distance threshold.

7. The method according to claim 2, characterized in that It also includes setting the traffic light information data source to the data sent by the cloud control platform if the RSU signal strength is lower than a preset signal threshold.

8. The method according to claim 1, characterized in that Also includes, When it is sensed that a vehicle has crossed the stop line of the intersection, the traffic light information corresponding to the intersection is stopped from being sent.

9. A traffic signal light issuing system based on vehicle-road-cloud integration, used to implement the traffic signal light issuing method based on vehicle-road-cloud integration as described in any one of claims 1 to 8, characterized in that: include, The control end is used to obtain the path planning information or position information and heading information of the vehicle end, and match the traffic light information within a preset vehicle driving distance and to be passed according to the path planning information or position information and heading information; When a vehicle is sensed to enter the preset RSU coverage area of ​​the intersection, the dynamic data source parameters of the vehicle are obtained, and the corresponding weight parameter values ​​are calculated according to the dynamic data source parameters; And according to the weight parameter value, the corresponding traffic light information data source is matched, and the traffic light information corresponding to the intersection is sent to the vehicle through the traffic light information data source; wherein, the traffic light information data source at least includes RSU broadcast or cloud control platform issuance.

10. A device, characterized in that: Traffic light information is sent to the vehicle through the traffic light sending method based on vehicle-road-cloud integration as described in any one of claims 1-8.

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