CN115294771B - Monitoring method and device for road side equipment, electronic equipment and storage medium - Google Patents
Monitoring method and device for road side equipment, electronic equipment and storage medium Download PDFInfo
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Abstract
The application discloses a method and a device for monitoring road side equipment, electronic equipment and a storage medium, wherein the method comprises the following steps: obtaining quality evaluation data of road side equipment, wherein the quality evaluation data comprises communication data between the road side equipment and an automatic driving vehicle, road side perception data and vehicle perception data; processing the quality evaluation data according to a quality evaluation strategy corresponding to the quality evaluation data to obtain index values corresponding to the dimensionality of the roadside equipment in the multiple quality evaluation indexes; and determining the quality evaluation result of the road side equipment according to the index value corresponding to the dimensionality of each quality evaluation index of the road side equipment, so as to determine whether to trigger the alarm of the road side equipment. According to the method and the device, the perception data, the communication data and the like collected by the road side and the self vehicle are deeply mined, the service quality condition of road side equipment on the line can be evaluated and monitored in real time, the service quality of the road side is guaranteed, and compared with a mode of manual testing by operation and maintenance testers, the monitoring efficiency, the accuracy and the real-time performance are greatly improved.
Description
Technical Field
The application relates to the technical field of vehicle-road cooperation, in particular to a method and a device for monitoring road side equipment, electronic equipment and a storage medium.
Background
As the automatic driving of a single Vehicle gradually enters a bottleneck period, a Vehicle-to-Vehicle cooperation scheme based on a V2X (Vehicle to accelerating) technology is more and more considered as a necessary way for realizing unmanned automatic driving.
At present, the test flow of the V2X road side equipment is complex, the period is long, a large amount of manpower is needed for support, and for example, each set of equipment is provided with one test maintenance worker, and the problem feedback period of one set of equipment is 1 day. Therefore, the maintenance cost of the V2X road side equipment is calculated to be 1 person/day, and the maintenance cost is extremely high. Once the number of input personnel is reduced in order to save cost, the problem exposure period of the V2X road side equipment is multiplied, the potential safety hazard of automatic driving is further increased, the safety is the first element of automatic driving, and the commercialization of the automatic driving technology can be really realized only by ensuring the safety of automatic driving.
In addition, the service quality of the V2X roadside device may be degraded due to various problems such as abnormal weather, abnormal circuit, aging of the device, and the like after the delivery of the V2X roadside device, and currently, there is no effective means for monitoring the service quality in real time for the delivered V2X roadside device, and thus the requirement of an automatic driving scene cannot be effectively supported.
Disclosure of Invention
The embodiment of the application provides a method and a device for monitoring road side equipment, electronic equipment and a storage medium, so that the service quality of the road side equipment is effectively monitored.
The embodiment of the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides a method for monitoring roadside equipment, where the method includes:
acquiring quality evaluation data of the road side equipment, wherein the quality evaluation data comprises communication data between the road side equipment and the automatic driving vehicle, perception data of the road side equipment and perception data of the automatic driving vehicle;
determining a corresponding quality evaluation strategy according to the quality evaluation data, and processing the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensionality of the roadside equipment in multiple quality evaluation indexes;
determining a quality evaluation result of the road side equipment according to index values corresponding to the dimensionality of each quality evaluation index of the road side equipment;
and determining whether to trigger the alarm of the road side equipment according to the quality evaluation result of the road side equipment.
Optionally, the communication data between the roadside device and the autonomous vehicle includes communication delay data between the roadside device and the autonomous vehicle, the quality evaluation index includes a communication delay index, and the processing the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to a dimension of a plurality of quality evaluation indexes of the roadside device includes:
and calculating a communication time delay mean value of the road side equipment in a first preset time according to the communication time delay data between the road side equipment and the automatic driving vehicle, and taking the mean value as an index value of the communication time delay index.
Optionally, the communication data between the roadside device and the autonomous vehicle includes communication packet loss data between the roadside device and the autonomous vehicle, the quality evaluation index includes a communication packet loss rate index, and the processing the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to a dimension of the roadside device at a plurality of quality evaluation indexes includes:
determining the communication packet loss quantity and the total data packet quantity between the road side equipment and the automatic driving vehicle according to the communication packet loss data between the road side equipment and the automatic driving vehicle;
and calculating the communication packet loss rate of the road side equipment in a second preset time according to the communication packet loss quantity and the total data packet quantity between the road side equipment and the automatic driving vehicle, wherein the communication packet loss rate is used as an index value of the communication packet loss rate index.
Optionally, the quality evaluation index includes a perception deviation index, and the processing the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to the roadside device in a dimension of a plurality of quality evaluation indexes includes:
determining perception data of roadside equipment corresponding to the perception data of the autonomous vehicle;
time synchronization processing is carried out on the perception data of the road side equipment and the perception data of the automatic driving vehicle, and the perception data of the road side equipment and the perception data of the automatic driving vehicle at corresponding moments are obtained;
calculating sensing deviation data at the corresponding moment according to the sensing data of the road side equipment and the sensing data of the automatic driving vehicle at the corresponding moment;
and calculating the perception deviation mean value of the road side equipment in a third preset time and a plurality of first preset distance ranges according to the perception deviation data at the corresponding moment, and taking the perception deviation mean value as the index value of the perception deviation index.
Optionally, the perception data of the autonomous vehicle includes a perception log generated by the autonomous vehicle passing by the roadside device during driving, and the determining the perception data of the roadside device corresponding to the perception data of the autonomous vehicle includes:
determining a running path of the automatic driving vehicle and the time when the automatic driving vehicle passes through a service range corresponding to the roadside device according to a perception log generated when the automatic driving vehicle passes through the roadside device during running;
and segmenting the perception data of the road side equipment according to the running path of the automatic driving vehicle and the time of the automatic driving vehicle passing through the service range corresponding to the road side equipment to obtain the perception data of the road side equipment corresponding to the perception data of the automatic driving vehicle.
Optionally, the sensing data of the autonomous vehicle includes vehicle positions of the autonomous vehicle at respective timestamps, the quality evaluation index includes a sensing tracking index, and the processing the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to a dimension of the roadside device at each of the plurality of quality evaluation indexes includes:
acquiring perception data of each timestamp corresponding to the road side equipment according to the vehicle position of the automatic driving vehicle at each timestamp;
determining vehicle identification information sensed by the road side equipment according to the sensing data of each timestamp corresponding to the road side equipment;
and calculating the hop rate of the perception data of the road side equipment in a fourth preset time and a plurality of second preset distance ranges according to the vehicle identification information perceived by the road side equipment, and taking the hop rate of the perception data as the index value of the perception tracking index.
Optionally, the quality evaluation result of the roadside device includes a fusion evaluation result corresponding to a plurality of quality evaluation indexes and an independent evaluation result corresponding to each quality evaluation index, and determining whether to trigger an alarm of the roadside device according to the quality evaluation result of the roadside device includes:
comparing the quality evaluation result of the road side equipment with a corresponding preset alarm threshold value;
if the quality evaluation result of the road side equipment triggers the preset alarm threshold, the road side equipment is alarmed;
otherwise, the road side equipment is not alarmed.
In a second aspect, an embodiment of the present application further provides a monitoring device for a roadside apparatus, where the device includes:
the system comprises an acquisition unit, a quality evaluation unit and a control unit, wherein the acquisition unit is used for acquiring quality evaluation data of the road side equipment, and the quality evaluation data comprises communication data between the road side equipment and the autonomous vehicle, perception data of the road side equipment and perception data of the autonomous vehicle;
the processing unit is used for determining a corresponding quality evaluation strategy according to the quality evaluation data and processing the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensionality of the multiple quality evaluation indexes of the road side equipment;
the first determining unit is used for determining the quality evaluation result of the road side equipment according to the index value corresponding to the dimensionality of each quality evaluation index of the road side equipment;
and the second determination unit is used for determining whether to trigger the alarm of the road side equipment according to the quality evaluation result of the road side equipment.
In a third aspect, an embodiment of the present application further provides a monitoring platform of a roadside device, where the monitoring platform of the roadside device includes a monitoring rear end of the roadside device and a monitoring front end of the roadside device, and the monitoring rear end of the roadside device includes the monitoring device of the roadside device.
In a fourth aspect, an embodiment of the present application further provides an electronic device, including:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform any of the methods described above.
In a fifth aspect, this application further provides a computer-readable storage medium storing one or more programs which, when executed by an electronic device including a plurality of application programs, cause the electronic device to perform any of the methods described above.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects: according to the monitoring method of the roadside device, quality evaluation data of the roadside device are obtained firstly, wherein the quality evaluation data comprise communication data between the roadside device and an automatic driving vehicle, perception data of the roadside device and perception data of the automatic driving vehicle; then, determining a corresponding quality evaluation strategy according to the quality evaluation data, and processing the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensionality of the roadside equipment in multiple quality evaluation indexes; then determining the quality evaluation result of the road side equipment according to the index value corresponding to the dimensionality of each quality evaluation index of the road side equipment; and finally, determining whether to trigger the alarm of the road side equipment according to the quality evaluation result of the road side equipment. According to the monitoring method of the road side equipment, the service quality of the road side equipment can be evaluated in real time by carrying out deep mining processing on the perception data, the communication data and the like acquired by the road side equipment and the automatic driving vehicle, so that real-time monitoring on the road side equipment can be completed, and compared with a manual testing mode of operation and maintenance testers, the monitoring efficiency, the accuracy and the real-time performance are greatly improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flowchart of a monitoring method for roadside equipment in an embodiment of the present application;
fig. 2 is a schematic structural diagram of a monitoring device of a roadside apparatus in an embodiment of the present application;
FIG. 3 is a schematic diagram of an architecture of a monitoring platform of a roadside device in an embodiment of the present application
Fig. 4 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only a few embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
An embodiment of the present application provides a method for monitoring a roadside device, and as shown in fig. 1, a flow diagram of the method for monitoring a roadside device in the embodiment of the present application is provided, where the method at least includes the following steps S110 to S140:
step S110, obtaining quality evaluation data of the road side equipment, wherein the quality evaluation data comprises communication data between the road side equipment and the automatic driving vehicle, perception data of the road side equipment and perception data of the automatic driving vehicle.
The monitoring method of the roadside device in the embodiment of the application can be executed by the rear end of a monitoring platform of the roadside device which is deployed independently, when the service quality of the roadside device is monitored, quality evaluation data of the roadside device needs to be obtained first, and the quality evaluation data specifically can include communication data between the roadside device (hereinafter referred to as "roadside") and an automatic driven vehicle (hereinafter referred to as "self vehicle"), perception data of the roadside, perception data of the self vehicle and the like.
Communication data between the road side and the vehicle is mainly used for evaluating the communication quality, the data processing efficiency and the like of the road side, sensing data of the road side and sensing data of the vehicle are mainly data related to the position, the posture and the like of the vehicle and are mainly used for evaluating the sensing capability of the road side, wherein the sensing data of the road side can be directly reported to a monitoring platform by the road side, and the sensing data of the vehicle can be directly reported to the monitoring platform by the vehicle.
Step S120, determining a corresponding quality evaluation strategy according to the quality evaluation data, and processing the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensionalities of the roadside equipment in multiple quality evaluation indexes.
After the quality evaluation data of the road side equipment is obtained, a corresponding quality evaluation strategy needs to be further determined, in the embodiment of the application, a plurality of different quality evaluation indexes, such as a communication delay index, a communication packet loss rate index, a perception deviation index and the like of the road side equipment, can be defined based on the quality evaluation data of the road side equipment, and then the corresponding quality evaluation data is deeply mined and processed based on the evaluation requirements of each quality evaluation index, so that the index value of each quality evaluation index of the road side equipment is obtained.
Step S130, determining the quality evaluation result of the road side equipment according to the index value corresponding to the dimension of each quality evaluation index of the road side equipment.
Different quality evaluation indexes can reflect the service quality of the road side equipment in different dimensions, and certain internal relation exists among some quality evaluation indexes, for example, if the communication delay of the road side equipment is longer, the deviation of the perception data of the road side equipment caused by the communication delay is possibly larger. Therefore, when the final quality evaluation result is determined, different fusion strategies can be adopted according to the mutual connection among different types of indexes, for example, some indexes can be used as the evaluation result alone, and can be fused with the evaluation results of other indexes to obtain a comprehensive evaluation result. Of course, how to merge specifically, those skilled in the art can flexibly set according to actual requirements, and are not limited specifically herein.
And step S140, determining whether to trigger the alarm of the road side equipment according to the quality evaluation result of the road side equipment.
The quality evaluation result of the road side equipment obtained in the above steps reflects the service quality condition of the current road side equipment, and when the service quality of the road side equipment is poor, for example, the communication delay is too long, the packet loss rate is too high, and the like, certain influence may be caused on the safe driving of the autonomous vehicle, so that whether the quality evaluation result of the current road side equipment triggers an alarm condition or not can be further determined, the road side equipment with problems can be timely found, and the safe driving of the autonomous vehicle is ensured.
According to the method for monitoring the road side equipment, the service quality of the road side equipment can be evaluated in real time by deeply mining the sensing data, the communication data and the like acquired by the road side equipment and the automatic driving vehicle, so that the real-time monitoring on the road side equipment can be completed, and the monitoring efficiency, the accuracy and the real-time performance are greatly improved compared with a manual testing mode of operation and maintenance testers.
In some embodiments of the present application, the communication data between the roadside device and the autonomous vehicle includes communication delay data between the roadside device and the autonomous vehicle, the quality evaluation index includes a communication delay index, and the processing the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to a dimension of a plurality of quality evaluation indexes by the roadside device includes: and calculating a communication time delay mean value of the road side equipment in a first preset time according to the communication time delay data between the road side equipment and the automatic driving vehicle, and taking the mean value as an index value of the communication time delay index.
The communication data between the roadside and the vehicle in the embodiment of the application may specifically include communication delay data between the roadside and the vehicle, and the corresponding quality evaluation index may include a communication delay index. The role of the communication delay data may include two dimensions, one dimension is used to comprehensively evaluate the data processing efficiency and the communication efficiency of the roadside device, and the other dimension is used to separately evaluate the communication quality of the roadside device.
The communication delay data may be reported by the vehicle based on a communication manner between the roadside and the vehicle, for example, when the roadside broadcasts the sensing data to the vehicle entering its service range, the roadside may first add time of a real target corresponding to the sensing result in the sensing data, and since the roadside usually performs some processing on the sensing result and then sends the sensing result to the vehicle, the roadside may further add sending time of the sensing data. After receiving the road side sensing data, the vehicle can calculate the sensing communication time delay according to the time and the sending time of the real target corresponding to the sensing result carried in the road side sensing data and the receiving time of the vehicle. For example, the data processing efficiency and the communication efficiency of the roadside device may be comprehensively evaluated according to the time difference result between the reception time of the vehicle and the time of the real target corresponding to the sensing result, and the communication quality of the roadside device may be evaluated according to the time difference result between the reception time of the vehicle and the transmission time.
Because each roadside device has a corresponding service range, a plurality of autonomous vehicles may be capable of communicating with the roadside device within the corresponding service range within a period of time, and a plurality of communication delay data reported by the autonomous vehicles may be generated, therefore, according to the embodiment of the application, the communication delay data reported by all autonomous vehicles which pass through the service range of the roadside device and can communicate with the roadside device within the first preset time can be averaged according to actual monitoring requirements to obtain the communication delay average value, so that the communication delay condition of the roadside device within the first preset time is comprehensively reflected. Of course, the length of the first preset time may be flexibly adjusted according to actual requirements, and is not specifically limited herein.
In some embodiments of the present application, the communication data between the roadside device and the autonomous vehicle includes communication packet loss data between the roadside device and the autonomous vehicle, the quality evaluation index includes a communication packet loss rate index, and the processing the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to a dimension of a plurality of quality evaluation indexes by the roadside device includes: determining the communication packet loss quantity and the total data packet quantity between the road side equipment and the automatic driving vehicle according to the communication packet loss data between the road side equipment and the automatic driving vehicle; and calculating the communication packet loss rate of the road side equipment in a second preset time according to the communication packet loss quantity and the total data packet quantity between the road side equipment and the automatic driving vehicle, and taking the communication packet loss rate as an index value of the communication packet loss rate index.
The communication data of the embodiment of the present application may further include communication packet loss data, and the corresponding quality evaluation index may include a communication packet loss rate index. When sensing data is transmitted to the vehicle by the road side, data packets may be lost due to self reasons and the like, and the more the data packets are lost, the worse the communication service quality of the road side device is, the greater the influence on the automatic driving function is. Therefore, the communication service quality of the road side equipment can be evaluated by deeply mining and processing the communication packet loss data.
The communication packet loss data may also be reported by the vehicle, and specifically, when the roadside broadcasts the sensing data to the vehicle, the roadside may add a sequence number identifier to the sensing data, and add 1 to the sequence number identifier corresponding to the sensing data every time the sensing data is sent. After receiving the sensing data of the roadside, the self-vehicle can compare whether the serial number identification carried in the sensing data received each time is continuous, namely whether the difference between the serial number identification and the serial number identification of the sensing data received last time is 1, and if not, the data transmission of the roadside is subject to the packet loss condition. The self-vehicle can upload all packet loss conditions of the self-vehicle in the corresponding service range passing through the road side to the monitoring platform.
The monitoring platform may perform statistical analysis on all communication packet loss data corresponding to the roadside device within the second preset time, for example, the communication packet loss rate may be calculated according to a ratio of the communication packet loss number to the total data packet number, and the higher the communication packet loss rate is, the worse the communication service quality is, so that the communication service quality of the roadside device may be evaluated according to the level of the communication packet loss rate. Of course, the length of the second preset time may also be flexibly adjusted according to actual requirements, and is not specifically limited herein.
In some embodiments of the present application, the quality evaluation index includes a perception deviation index, and the processing the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to a dimension of a plurality of quality evaluation indexes by the roadside device includes: determining perception data of roadside equipment corresponding to the perception data of the autonomous vehicle; time synchronization processing is carried out on the perception data of the road side equipment and the perception data of the automatic driving vehicle, and perception data of the road side equipment and perception data of the automatic driving vehicle at corresponding moments are obtained; calculating perception deviation data at the corresponding moment according to the perception data of the roadside equipment and the perception data of the automatic driving vehicle at the corresponding moment; and calculating the perception deviation mean value of the road side equipment in a third preset time and a plurality of first preset distance ranges according to the perception deviation data at the corresponding moment, and taking the perception deviation mean value as the index value of the perception deviation index.
The perception data of the roadside and the self-vehicle in the embodiment of the application can comprise data such as vehicle position, speed, course angle and acceleration, and the corresponding quality evaluation indexes specifically comprise a plurality of perception deviation indexes such as position deviation indexes, speed deviation indexes, course angle deviation indexes and acceleration deviation.
Since the roadside senses a plurality of self-vehicles passing through the service range of the roadside in the service process, when index values of perception deviation indexes of different dimensions are calculated, the method and the device for calculating the perception deviation indexes of the roadside can align the perception data of the roadside in the third preset time with the perception data reported by the self-vehicles, specifically can align the vehicle dimensions and align the time dimensions, and accordingly obtains the perception data of the roadside and each self-vehicle at corresponding time. And then, respectively subtracting the position, the speed, the course angle, the acceleration and other perception data of the road side and each self vehicle at the corresponding time to obtain the perception deviation data such as position deviation, speed deviation, course angle deviation, acceleration deviation and the like. And finally, respectively averaging different types of perception deviation data in the dimension of the road side to obtain perception deviation means such as a position deviation mean, a speed deviation mean, a course angle deviation mean, an acceleration deviation mean and the like, and taking the perception deviation means as the index value of the corresponding perception deviation index.
Under an actual automatic driving scene, the deviation of the roadside sensing data may become larger gradually as the sensing distance becomes larger, so that the accuracy requirements of different sensing distances on the roadside sensing data are different in the service range of the whole roadside device. Based on this, when the embodiment of the application performs statistics on the sensing deviation data, the whole service range of the roadside device may be divided into a plurality of sub-ranges, and if the whole service range is 200 meters, the sensing deviation data in different ranges of 0-50 meters, 50-100 meters, 100-150 meters, and 150-200 meters may be respectively performed statistics, and the sensing deviation mean values in the ranges may be respectively obtained.
In some embodiments of the subject application, the perception data of the autonomous vehicle comprises a perception log generated by the autonomous vehicle passing by the roadside device during driving, and the determining perception data of the roadside device corresponding to the perception data of the autonomous vehicle comprises: determining a running path of the automatic driving vehicle and the time when the automatic driving vehicle passes through a service range corresponding to the roadside device according to a perception log generated when the automatic driving vehicle passes through the roadside device during running; and segmenting the perception data of the road side equipment according to the running path of the automatic driving vehicle and the time of the automatic driving vehicle passing through the service range corresponding to the road side equipment to obtain the perception data of the road side equipment corresponding to the perception data of the automatic driving vehicle.
When the perception data of the roadside device corresponding to the perception data of the autonomous vehicle is determined, the perception data of the autonomous vehicle such as time-coordinate-speed-course-acceleration and the like can be obtained from a vehicle end log of the autonomous vehicle according to time sequence, then corresponding latest timestamp data is searched in all perception data of the roadside according to timestamps and vehicle position information obtained from the vehicle end log, the latest vehicle is further searched in the latest timestamp data and serves as the autonomous vehicle perceived by the roadside, and finally the perception data of the autonomous vehicle such as the position, the speed, the course and the like perceived by the roadside are segmented from all perception data of the roadside, so that the perception data of the vehicle dimension are aligned.
In some embodiments of the present application, the perception data of the autonomous vehicle includes vehicle positions of the autonomous vehicle at respective time stamps, the quality evaluation index includes a perception tracking index, and the processing the quality evaluation data by using the quality evaluation policy to obtain index values corresponding to dimensions of the roadside device at a plurality of quality evaluation indexes includes: acquiring perception data of each timestamp corresponding to road side equipment according to the vehicle position of the automatic driving vehicle at each timestamp; determining vehicle identification information sensed by the road side equipment according to the sensing data of each timestamp corresponding to the road side equipment; and calculating the hop rate of the perception data of the road side equipment in a fourth preset time and a plurality of second preset distance ranges according to the vehicle identification information perceived by the road side equipment, and taking the hop rate of the perception data as the index value of the perception tracking index.
The sensing data of the self-vehicle can comprise the vehicle position of the self-vehicle at each timestamp, and the corresponding quality evaluation indexes specifically comprise sensing tracking indexes and are used for evaluating the time and space tracking continuity of the road side for the same self-vehicle target.
When the index value of the perception tracking index is determined, the index value can be calculated based on a vehicle unique identifier (UUID), specifically, vehicle position information of each timestamp perceived by the vehicle when the vehicle passes through a service range of roadside equipment can be firstly obtained, then, the perception data of the roadside corresponding to each timestamp is obtained from all perception data of the roadside, information such as the vehicle unique identifier perceived by the roadside and the like is further obtained from the perception data of the roadside according to the vehicle position of the vehicle, and finally, the hop rate of the perception data of the roadside is calculated by judging whether the vehicle unique identifier perceived by the roadside is continuous in time and space. For example, if two adjacent times of sensing that the timestamps of the same UUID are not consecutive, the case of time discontinuity can be regarded as a case of one jump, or if the vehicle displacement corresponding to the timestamps of the same UUID sensed two adjacent times of sensing exceeds the vehicle displacement threshold value between the adjacent timestamps, the case of space discontinuity can be regarded as a case of one jump, and the two manners can respectively count the jumping cases of the sensed data of the roadside in time and space.
It should be noted that, because the calculation of the index value of the perception tracking index also depends on the perception data, and the tracking accuracy requirements for the roadside devices in different ranges are also different, similar to the perception deviation index, the service range of the whole roadside device may also be divided into a plurality of sub-ranges, and the index value of the perception tracking index corresponding to each sub-range may be respectively counted.
In some embodiments of the present application, the quality evaluation index includes a perceived obstacle index, and the processing the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to a dimension of the roadside device in a plurality of quality evaluation indexes includes: determining obstacle data sensed by the road side equipment according to the sensed data of the road side equipment, wherein the obstacle data comprises the size of an obstacle; comparing the size of the obstacle sensed by the roadside device with the size of an actual obstacle; and calculating the accuracy of the obstacle data of the roadside equipment in a fifth preset time and a plurality of third preset distance ranges according to the comparison result, and using the accuracy as an index value of the perceived obstacle index.
The quality evaluation index of the embodiment of the application can also comprise a perceived obstacle index, and is mainly used for evaluating the accuracy of the roadside device for sensing the size of the obstacle. Specifically, the size data of the obstacle can be determined from the sensing data of the road side equipment, and then the data are compared with the real size of the obstacle, so that whether the deviation between the data and the obstacle is smaller than a preset deviation threshold value or not is determined, if the deviation is smaller than the preset deviation threshold value, the road side equipment can be considered to be accurate in sensing the size of the obstacle, otherwise, the road side equipment is considered to be inaccurate, and therefore the obstacle sensing accuracy rate of the road side equipment in a period of time can be counted.
Similarly, since the calculation of the index value of the perceived obstacle index also depends on the perception data, and the perception accuracy requirements of the road side equipment in different ranges are different, similar to the perception deviation index, the service range of the whole road side equipment can be divided into a plurality of sub-ranges, and the index values of the perceived obstacle index corresponding to each sub-range can be respectively counted.
In some embodiments of the present application, the quality evaluation result of the roadside device includes a fusion evaluation result corresponding to a plurality of quality evaluation indexes and an independent evaluation result corresponding to each quality evaluation index, and determining whether to trigger an alarm of the roadside device according to the quality evaluation result of the roadside device includes: comparing the quality evaluation result of the road side equipment with a corresponding preset alarm threshold value; if the quality evaluation result of the road side equipment triggers the preset alarm threshold, the road side equipment is alarmed; otherwise, the road side equipment is not alarmed.
The quality evaluation results of the roadside device may include independent evaluation results obtained based on index values of the quality evaluation indexes, and the alarm requirements corresponding to different quality evaluation indexes are different, so that the index values of different quality evaluation indexes may be compared with corresponding independent alarm thresholds, respectively, to determine whether to trigger an alarm of the roadside device in a certain quality evaluation index dimension.
The quality evaluation result of the roadside device may further include a fusion evaluation result obtained by fusing index values of the multiple quality evaluation indexes, and the specific fusion strategy may be, for example, performing weighted fusion after different weights are assigned to different quality evaluation indexes, and then comparing the weighted fusion index value with a corresponding comprehensive alarm threshold value, thereby determining whether to trigger the alarm of the roadside device. When the roadside device does not trigger the corresponding alarm threshold value in each independent quality evaluation index dimension, the integration mode can comprehensively evaluate and monitor the service quality of the roadside device on the whole, and the roadside device can be guaranteed to provide services such as more efficient communication and perception as far as possible.
Of course, regarding the size of the above alarm threshold, those skilled in the art can flexibly set the alarm threshold according to actual requirements, and is not limited specifically herein.
To sum up, the method for monitoring the road side equipment at least achieves the following technical effects: according to the method, the quality evaluation data such as the driving data of the automatic driving vehicle in the service range of the road side equipment and the perception data of the road side equipment are deeply mined and analyzed, the feedback capability of the road side service quality at the minute level can be realized, the problem discovery efficiency is greatly improved, and the equipment maintenance cost is reduced. In practical application, the service quality test of each set of equipment only needs 5 minutes/server, the quality monitoring of 24 hours all day can be realized, and the excavation capacity of the road side problem is improved greatly compared with the existing mode.
The embodiment of the present application further provides a monitoring device 200 of a roadside apparatus, as shown in fig. 2, provides a schematic structural diagram of the monitoring device of the roadside apparatus in the embodiment of the present application, where the device 200 includes: an obtaining unit 210, a processing unit 220, a first determining unit 230, and a second determining unit 240, wherein:
an obtaining unit 210, configured to obtain quality evaluation data of a roadside device, where the quality evaluation data includes communication data between the roadside device and an autonomous vehicle, perception data of the roadside device, and perception data of the autonomous vehicle;
a processing unit 220, configured to determine a corresponding quality evaluation policy according to the quality evaluation data, and process the quality evaluation data by using the quality evaluation policy to obtain an index value corresponding to a dimension of the roadside device at the multiple quality evaluation indexes;
a first determining unit 230, configured to determine a quality evaluation result of the roadside device according to index values corresponding to the dimensionalities of the roadside devices at each quality evaluation index;
and a second determining unit 240, configured to determine whether to trigger an alarm of the roadside device according to the quality evaluation result of the roadside device.
In some embodiments of the present application, the communication data between the roadside device and the autonomous vehicle includes communication delay data between the roadside device and the autonomous vehicle, the quality evaluation index includes a communication delay index, and the processing unit 220 is specifically configured to: and calculating a communication time delay mean value of the road side equipment in a first preset time according to the communication time delay data between the road side equipment and the automatic driving vehicle, and taking the mean value as an index value of the communication time delay index.
In some embodiments of the present application, the communication data between the roadside device and the autonomous vehicle includes communication packet loss data between the roadside device and the autonomous vehicle, the quality evaluation indicator includes a communication packet loss rate indicator, and the processing unit 220 is specifically configured to: determining the communication packet loss quantity and the total data packet quantity between the road side equipment and the automatic driving vehicle according to the communication packet loss data between the road side equipment and the automatic driving vehicle; and calculating the communication packet loss rate of the road side equipment in a second preset time according to the communication packet loss quantity and the total data packet quantity between the road side equipment and the automatic driving vehicle, wherein the communication packet loss rate is used as an index value of the communication packet loss rate index.
In some embodiments of the present application, the quality evaluation indicator includes a perception deviation indicator, and the processing unit 220 is specifically configured to: determining perception data of roadside equipment corresponding to the perception data of the automatic driving vehicle; time synchronization processing is carried out on the perception data of the road side equipment and the perception data of the automatic driving vehicle, and perception data of the road side equipment and perception data of the automatic driving vehicle at corresponding moments are obtained; calculating perception deviation data at the corresponding moment according to the perception data of the roadside equipment and the perception data of the automatic driving vehicle at the corresponding moment; and calculating the perception deviation mean value of the road side equipment in a third preset time and a plurality of first preset distance ranges according to the perception deviation data at the corresponding moment, and taking the perception deviation mean value as the index value of the perception deviation index.
In some embodiments of the present application, the perception data of the autonomous vehicle includes a perception log generated when the autonomous vehicle passes through the roadside apparatus during driving, and the processing unit 220 is specifically configured to: determining a running path of the automatic driving vehicle and the time when the automatic driving vehicle passes through a service range corresponding to the roadside device according to a perception log generated when the automatic driving vehicle passes through the roadside device during running; and segmenting the perception data of the road side equipment according to the running path of the automatic driving vehicle and the time of the automatic driving vehicle passing through the service range corresponding to the road side equipment to obtain the perception data of the road side equipment corresponding to the perception data of the automatic driving vehicle.
In some embodiments of the present application, the perception data of the autonomous vehicle includes vehicle positions of the autonomous vehicle at respective time stamps, the quality evaluation indicator includes a perception tracking indicator, and the processing unit 220 is specifically configured to: acquiring perception data of each timestamp corresponding to the road side equipment according to the vehicle position of the automatic driving vehicle at each timestamp; determining vehicle identification information sensed by the road side equipment according to the sensing data of each timestamp corresponding to the road side equipment; and calculating the hop rate of the perception data of the road side equipment in a fourth preset time and a plurality of second preset distance ranges according to the vehicle identification information perceived by the road side equipment, and taking the hop rate of the perception data as the index value of the perception tracking index.
In some embodiments of the present application, the quality evaluation indicator includes a perceived obstacle indicator, and the processing unit 220 is specifically configured to: determining obstacle data perceived by the road side equipment according to the perception data of the road side equipment, wherein the obstacle data comprises the size of an obstacle; comparing the size of the obstacle sensed by the roadside device with the size of an actual obstacle; and calculating the accuracy of the obstacle data of the road side equipment in a fifth preset time and a plurality of third preset distance ranges according to the comparison result, and taking the accuracy as an index value of the perceived obstacle index.
In some embodiments of the present application, the quality evaluation result of the roadside apparatus includes a fusion evaluation result corresponding to a plurality of quality evaluation indexes and an independent evaluation result corresponding to each quality evaluation index, and the second determining unit 240 is specifically configured to: comparing the quality evaluation result of the road side equipment with a corresponding preset alarm threshold value; if the quality evaluation result of the road side equipment triggers the preset alarm threshold, the road side equipment is alarmed; otherwise, the road side equipment is not alarmed.
It can be understood that the monitoring device for roadside equipment described above can implement each step of the monitoring method for roadside equipment provided in the foregoing embodiment, and the relevant explanations regarding the monitoring method for roadside equipment are applicable to the monitoring device for roadside equipment, and are not described herein again.
The embodiment of the application further provides a monitoring platform of the road side equipment, wherein the monitoring platform of the road side equipment comprises a monitoring rear end of the road side equipment and a monitoring front end of the road side equipment, and the monitoring rear end of the road side equipment comprises a monitoring device of the road side equipment.
As shown in fig. 3, a schematic architecture diagram of a monitoring platform of a roadside device in the embodiment of the present application is provided, where the monitoring platform of the roadside device in the embodiment of the present application mainly includes a monitoring back end and a monitoring front end of the roadside device, the monitoring back end is mainly used to define some specific monitoring logics and index thresholds, and perform operations such as data acquisition, mining processing, and storage, and the monitoring front end is mainly used to display processing results of the back end, for example, the monitoring front end may include index value display and graphical display of quality evaluation indexes of each dimension, so that relevant people can more intuitively know quality of service conditions of each roadside device and find problems in time.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 4, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but this does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program, and the monitoring device of the road side equipment is formed on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
acquiring quality evaluation data of the road side equipment, wherein the quality evaluation data comprises communication data between the road side equipment and the automatic driving vehicle, perception data of the road side equipment and perception data of the automatic driving vehicle;
determining a corresponding quality evaluation strategy according to the quality evaluation data, and processing the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensionality of the roadside equipment in multiple quality evaluation indexes;
determining a quality evaluation result of the road side equipment according to index values corresponding to the dimensionality of each quality evaluation index of the road side equipment;
and determining whether to trigger the alarm of the road side equipment according to the quality evaluation result of the road side equipment.
The method executed by the monitoring device of the roadside apparatus according to the embodiment shown in fig. 1 of the present application may be applied to a processor, or may be implemented by the processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute the method executed by the monitoring device of the roadside device in fig. 1, and implement the functions of the monitoring device of the roadside device in the embodiment shown in fig. 1, which are not described herein again in this embodiment of the present application.
An embodiment of the present application further provides a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which, when executed by an electronic device including multiple application programs, enable the electronic device to perform the method performed by the monitoring apparatus for a roadside device in the embodiment shown in fig. 1, and are specifically configured to perform:
acquiring quality evaluation data of the road side equipment, wherein the quality evaluation data comprises communication data between the road side equipment and the automatic driving vehicle, perception data of the road side equipment and perception data of the automatic driving vehicle;
determining a corresponding quality evaluation strategy according to the quality evaluation data, and processing the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensionality of the roadside equipment in multiple quality evaluation indexes;
determining a quality evaluation result of the road side equipment according to index values corresponding to the dimensionality of each quality evaluation index of the road side equipment;
and determining whether to trigger the alarm of the road side equipment according to the quality evaluation result of the road side equipment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus comprising the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method of monitoring roadside equipment, wherein the method comprises:
acquiring quality evaluation data of the road side equipment, wherein the quality evaluation data comprises communication data between the road side equipment and the automatic driving vehicle, perception data of the road side equipment and perception data of the automatic driving vehicle;
determining a corresponding quality evaluation strategy according to the quality evaluation data, and processing the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensionalities of the road side equipment in multiple quality evaluation indexes;
determining a quality evaluation result of the road side equipment according to index values corresponding to the dimensionality of each quality evaluation index of the road side equipment;
determining whether to trigger the alarm of the road side equipment according to the quality evaluation result of the road side equipment;
the quality evaluation indexes comprise perception deviation indexes, and the processing of the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensions of the roadside equipment in the multiple quality evaluation indexes comprises the following steps:
determining perception data of roadside equipment corresponding to the perception data of the autonomous vehicle;
time synchronization processing is carried out on the perception data of the road side equipment and the perception data of the automatic driving vehicle, and the perception data of the road side equipment and the perception data of the automatic driving vehicle at corresponding moments are obtained;
calculating perception deviation data at the corresponding moment according to the perception data of the roadside equipment and the perception data of the automatic driving vehicle at the corresponding moment;
calculating a perception deviation mean value of the road side equipment in a third preset time and a plurality of first preset distance ranges according to perception deviation data at corresponding moments, and taking the perception deviation mean value as an index value of the perception deviation index;
the first preset distance ranges are different sub-ranges obtained after the whole service range of the road side equipment is divided, and the different sub-ranges respectively correspond to different perception accuracy requirements.
2. The method of claim 1, wherein the communication data between the roadside device and the autonomous vehicle comprises communication delay data between the roadside device and the autonomous vehicle, the quality evaluation index comprises a communication delay index, and the processing the quality evaluation data by using the quality evaluation strategy to obtain the index value corresponding to the roadside device in the dimension of the plurality of quality evaluation indexes comprises:
and calculating a communication time delay mean value of the road side equipment in a first preset time according to the communication time delay data between the road side equipment and the automatic driving vehicle, and taking the mean value as an index value of the communication time delay index.
3. The method of claim 1, wherein the communication data between the roadside device and the autonomous vehicle comprises communication packet loss data between the roadside device and the autonomous vehicle, the quality evaluation index comprises a communication packet loss rate index, and the processing the quality evaluation data by using the quality evaluation strategy to obtain the index value corresponding to the roadside device in the dimension of the plurality of quality evaluation indexes comprises:
determining the communication packet loss quantity and the total data packet quantity between the road side equipment and the automatic driving vehicle according to the communication packet loss data between the road side equipment and the automatic driving vehicle;
and calculating the communication packet loss rate of the road side equipment in a second preset time according to the communication packet loss quantity and the total data packet quantity between the road side equipment and the automatic driving vehicle, wherein the communication packet loss rate is used as an index value of the communication packet loss rate index.
4. The method of claim 1, wherein the perception data of the autonomous vehicle comprises a perception log generated by the autonomous vehicle passing by the roadside device during travel, and the determining perception data of the roadside device corresponding to the perception data of the autonomous vehicle comprises:
determining a running path of the automatic driving vehicle and the time when the automatic driving vehicle passes through a service range corresponding to the roadside device according to a perception log generated when the automatic driving vehicle passes through the roadside device during running;
and segmenting the perception data of the road side equipment according to the running path of the automatic driving vehicle and the time of the automatic driving vehicle passing through the service range corresponding to the road side equipment to obtain the perception data of the road side equipment corresponding to the perception data of the automatic driving vehicle.
5. The method of claim 1, wherein the perception data of the autonomous vehicle comprises vehicle positions of the autonomous vehicle at respective time stamps, the quality assessment indicators comprise perception tracking indicators, and the processing the quality assessment data using the quality assessment strategy to obtain the indicator values corresponding to the roadside device in the dimensions of the plurality of quality assessment indicators comprises:
acquiring perception data of each timestamp corresponding to road side equipment according to the vehicle position of the automatic driving vehicle at each timestamp;
determining vehicle identification information sensed by the road side equipment according to the sensing data of each timestamp corresponding to the road side equipment;
and calculating the hop rate of the perception data of the road side equipment in a fourth preset time and a plurality of second preset distance ranges according to the vehicle identification information perceived by the road side equipment, and taking the hop rate of the perception data as the index value of the perception tracking index.
6. The method of claim 1, wherein the quality evaluation result of the road side device comprises a fusion evaluation result corresponding to a plurality of quality evaluation indexes and an independent evaluation result corresponding to each quality evaluation index, and the determining whether to trigger the alarm of the road side device according to the quality evaluation result of the road side device comprises:
comparing the quality evaluation result of the road side equipment with a corresponding preset alarm threshold value;
if the quality evaluation result of the road side equipment triggers the preset alarm threshold, the road side equipment is alarmed;
otherwise, the road side equipment is not alarmed.
7. A monitoring device of a roadside apparatus, wherein the device comprises:
the system comprises an acquisition unit, a quality evaluation unit and a quality evaluation unit, wherein the acquisition unit is used for acquiring quality evaluation data of road side equipment, and the quality evaluation data comprises communication data between the road side equipment and an automatic driving vehicle, perception data of the road side equipment and perception data of the automatic driving vehicle;
the processing unit is used for determining a corresponding quality evaluation strategy according to the quality evaluation data and processing the quality evaluation data by using the quality evaluation strategy to obtain index values corresponding to the dimensionality of the multiple quality evaluation indexes of the road side equipment;
the first determining unit is used for determining the quality evaluation result of the road side equipment according to the index value corresponding to the dimensionality of each quality evaluation index of the road side equipment;
the second determination unit is used for determining whether to trigger the alarm of the road side equipment according to the quality evaluation result of the road side equipment;
the quality evaluation index includes a perception deviation index, and the processing unit is specifically configured to:
determining perception data of roadside equipment corresponding to the perception data of the automatic driving vehicle;
time synchronization processing is carried out on the perception data of the road side equipment and the perception data of the automatic driving vehicle, and the perception data of the road side equipment and the perception data of the automatic driving vehicle at corresponding moments are obtained;
calculating perception deviation data at the corresponding moment according to the perception data of the roadside equipment and the perception data of the automatic driving vehicle at the corresponding moment;
calculating a perception deviation mean value of the road side equipment in a third preset time and a plurality of first preset distance ranges according to perception deviation data at corresponding moments, and taking the perception deviation mean value as an index value of the perception deviation index;
the first preset distance ranges are different sub-ranges obtained after the whole service range of the road side equipment is divided, and the different sub-ranges respectively correspond to different perception accuracy requirements.
8. A monitoring platform of road side equipment, wherein the monitoring platform of the road side equipment comprises a monitoring back end of the road side equipment and a monitoring front end of the road side equipment, and the monitoring back end of the road side equipment comprises the monitoring device of the road side equipment according to claim 7.
9. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the method of any of claims 1 to 6.
10. A computer readable storage medium storing one or more programs which, when executed by an electronic device comprising a plurality of applications, cause the electronic device to perform the method of any of claims 1-6.
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CN113741485A (en) * | 2021-06-23 | 2021-12-03 | 阿波罗智联(北京)科技有限公司 | Control method and device for cooperative automatic driving of vehicle and road, electronic equipment and vehicle |
CN114485658A (en) * | 2021-12-08 | 2022-05-13 | 上海智能网联汽车技术中心有限公司 | Device and method for precision evaluation of roadside sensing system |
CN114173307A (en) * | 2021-12-17 | 2022-03-11 | 浙江海康智联科技有限公司 | Roadside perception fusion system based on vehicle-road cooperation and optimization method |
CN114648231A (en) * | 2022-03-29 | 2022-06-21 | 北京清研宏达信息科技有限公司 | Quality evaluation method for road-side data of vehicle-road cooperation |
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