A wireless signal testing method and system for an unmanned vehicle

Abstract

The application discloses a wireless signal test method and system for an unmanned vehicle. The method obtains test basic data of the unmanned vehicle and performs test caliber normalization to obtain a wireless signal test input set. The method performs task fragmentation processing on the wireless signal test input set to obtain a task fragmented test data set. The method performs multi-link signal continuity evaluation on the task fragmented test data set to obtain a wireless signal continuity margin. The method extracts safety response constraints to obtain a segment safety response constraint result. The method performs test risk evaluation on the wireless signal continuity margin according to the segment safety response constraint result to obtain a segment wireless signal test evaluation result, and encapsulates and generates an unmanned vehicle wireless signal test result.

Description

Technical Field

[0001] This invention belongs to the field of wireless signal testing and vehicle operation data acquisition technology, specifically relating to a wireless signal testing method and system for unmanned vehicles. Background Technology

[0002] With the increasing number of autonomous vehicle testing scenarios in ports, mining areas, airport shuttle areas, logistics parks, and closed parks, testers need to collect vehicle-to-everything (V2X) communication data, roadside communication data, vehicle-to-cloud (V2X) communication data, and remote monitoring link data as the vehicles travel along fixed routes. This data is used to determine wireless signal coverage, link continuity, communication interruption locations, and signal recovery status within the test area. In these testing scenarios, autonomous vehicles typically travel along predetermined test routes. The testing system mainly collects data such as vehicle position, speed, operating status, communication link status, and test area location, and then correlates the collected wireless signal data with the vehicle's operating process.

[0003] Currently, wireless signal testing typically involves collecting data such as signal strength, signal-to-noise ratio, latency, jitter, packet loss rate, throughput, handover events, message reception rate, and communication distance using road test equipment, vehicle-mounted communication terminals, communication module logs, or network testing software. Based on the test route or area, it generates wireless coverage heatmaps, network quality reports, or link compliance conclusions. This type of solution can complete basic wireless signal data collection and quality statistics in scenarios such as general area coverage testing, single-link quality testing, and static point signal detection.

[0004] However, in test scenarios involving the collection of operational data for autonomous vehicles, existing solutions primarily collect wireless signal data based on route points, fixed time windows, or single communication indicators. This makes it difficult to correlate vehicle operation segments, vehicle motion states, multi-link wireless signal data, and the response constraints required for testing within the same data collection framework. Consequently, test results only reflect signal strength at a specific location or moment, failing to identify which vehicle operation segment the wireless signal changes occurred within, and struggling to distinguish between different data manifestations such as short-term signal fluctuations, continuous link degradation, and link recovery delays. Furthermore, existing test results typically focus on coverage strength, link compliance, or anomaly point marking, lacking a data processing method that can output wireless signal continuity margin, segment test evaluation results, and wireless signal test results based on vehicle operation segments. Summary of the Invention

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] This invention provides a wireless signal testing method and system for unmanned vehicles, aiming to at least partially solve the problem that existing wireless signal testing methods often rely on route points, fixed time windows, or single communication indicators, making it difficult to uniformly correlate vehicle operation segments, multi-link signal continuity, and safety response constraints, resulting in test results that fail to reflect the impact of wireless signal changes on specific unmanned driving operation segments.

[0007] To address the above problems, the present invention provides the following technical solution:

[0008] In a first aspect, the present invention provides a method for testing wireless signals of an unmanned vehicle, comprising:

[0009] Acquire basic test data for autonomous vehicles and normalize the test caliber to obtain the wireless signal test input set;

[0010] The wireless signal test input set is processed into task fragmentation to obtain a task fragmentation test dataset;

[0011] Multi-link signal continuity evaluation is performed on the fragmented test dataset of the task to obtain the wireless signal continuity margin;

[0012] Security response constraints are extracted from the fragmented test dataset of the task to obtain the fragment security response constraint results;

[0013] Based on the segment security response constraint results, the test risk assessment of the wireless signal continuity margin is performed to obtain the segment wireless signal test evaluation results.

[0014] The test results of the wireless signal segment test evaluation are packaged to obtain the wireless signal test results of the autonomous vehicle.

[0015] In a preferred embodiment, the step of performing task fragmentation processing on the wireless signal test input set to obtain a task fragmentation test dataset includes:

[0016] Time-slice alignment is performed on the wireless signal test input set to obtain a time-slice aligned record;

[0017] The test fields of the time-slice aligned records are reorganized to obtain the test process records;

[0018] The test process records are used to calculate segment boundaries to obtain task segment indexes;

[0019] The test process record is segmented according to the task segment index to obtain segment test records;

[0020] By attaching fragment attributes to the fragment test records, a task fragmented test dataset is obtained.

[0021] As a preferred embodiment, the step of calculating segment boundaries of the test process record to obtain the task segment index includes:

[0022] The task state transition detection is performed on the test process record to obtain the intensity of task state change;

[0023] The test process records are used to perform scene boundary detection to obtain the scene change intensity;

[0024] The test process records are used to detect communication link events and obtain the intensity of link changes.

[0025] Based on the intensity of task state change, scene change, and link change, the collaborative boundary response is calculated using the task-scene-link three-axis collaborative boundary response algorithm to obtain the collaborative boundary response result.

[0026] The collaborative boundary response results are subjected to boundary filtering to obtain valid task segment boundary points;

[0027] The boundary points of the valid task segments are numbered consecutively to obtain the task segment index.

[0028] As a preferred embodiment, the step of evaluating the multi-link signal continuity of the task-fragmented test dataset to obtain the wireless signal continuity margin includes:

[0029] The fragmented test dataset of the task is subjected to fragment link timing normalization to obtain basic data for fragment signal evaluation;

[0030] Multi-link continuous degradation window identification is performed on the basic data for evaluating the segment signal to obtain the segment link continuity characterization results;

[0031] Based on the task communication constraints in the basic data for evaluating the segment signals, the margin conversion of the segment link continuity characterization results is performed to obtain the wireless signal continuity margin.

[0032] As a preferred embodiment, the step of performing multi-link continuous degradation window identification on the basic data for evaluating the segment signal to obtain segment link continuity characterization results includes:

[0033] The basic data for evaluating the segment signal are divided into multi-link time windows to obtain a segment link window sequence;

[0034] The communication quality change statistics are performed on the fragment link window sequence to obtain the communication quality change parameters;

[0035] The communication interruption duration is statistically analyzed for the fragment link window sequence to obtain the communication interruption duration parameter;

[0036] The communication recovery time is statistically analyzed for the segment link window sequence to obtain the communication recovery time parameter;

[0037] The link weights of the communication quality change parameters, communication interruption duration parameters, and communication recovery time parameters are merged to obtain the segment link continuity characterization results.

[0038] As a preferred embodiment, the step of performing margin conversion on the segment link continuity characterization results based on the task communication constraints in the segment signal evaluation baseline data to obtain the wireless signal continuity margin includes:

[0039] Task attribute encoding is performed on the basic data for evaluating the segment signal to obtain the segment task attribute encoding result;

[0040] Based on the segment task attribute encoding results, task link dependency matching is performed to obtain the segment communication requirement benchmark;

[0041] Based on the segment communication requirement benchmark, the link quality direction is unified for the segment link continuity characterization results to obtain the direction-unified link quality results;

[0042] The continuous degradation ratio of the unified link quality results in the aforementioned direction is calculated to obtain the segment link degradation characterization results.

[0043] The degradation characterization results of the aforementioned link segments are converted into a margin using a degradation persistence attenuation margin algorithm to obtain the wireless signal continuity margin.

[0044] As a preferred embodiment, the step of extracting security response constraints from the task fragmentation test dataset to obtain fragment security response constraint results includes:

[0045] The vehicle motion state is converted into the fragmented test dataset of the task to obtain the fragmented motion response parameters;

[0046] Based on the segment motion response parameters, the link recovery response parameters are integrated to obtain segment response process data;

[0047] The response margin algorithm is used to calculate the safety response constraints of the fragment response process data to obtain the fragment safety response constraint results.

[0048] As a preferred embodiment, the step of conducting a test risk assessment of the wireless signal continuity margin based on the segment security response constraint results to obtain the segment wireless signal test evaluation results includes:

[0049] Based on the segment security response constraint results, the continuity margin of the wireless signal is reduced and compared to obtain the segment wireless signal risk assessment result;

[0050] The risk assessment results of the wireless signal segment are marked with task impact to obtain the test evaluation results of the wireless signal segment.

[0051] As a preferred embodiment, the step of performing a margin reduction comparison on the wireless signal continuity margin based on the segment security response constraint result to obtain the segment wireless signal risk assessment result includes:

[0052] Based on the segment security response constraint results, the wireless signal continuity margin is calculated by security response reduction to obtain the segment risk margin;

[0053] The risk margin of the segment is converted into a risk level to obtain the segment risk level;

[0054] The risk level of the segment is marked with task impact to obtain the task impact marking result;

[0055] The risk level of the segment is assigned a takeover risk label to obtain the takeover risk labeling result;

[0056] The risk levels, task impact marking results, and takeover risk marking results of the segments are merged under the same task segment to obtain the segment wireless signal risk determination result.

[0057] Secondly, the present invention provides a wireless signal testing system for unmanned vehicles, comprising:

[0058] The test data normalization module is used to acquire the basic test data of autonomous vehicles and normalize the test caliber to obtain the wireless signal test input set.

[0059] The task fragmentation module is used to perform task fragmentation processing on the wireless signal test input set to obtain a task fragmentation test dataset.

[0060] The signal continuity evaluation module is used to perform multi-link signal continuity evaluation on the task fragmentation test dataset to obtain the wireless signal continuity margin.

[0061] The security response constraint module is used to extract security response constraints from the task fragmentation test dataset to obtain fragment security response constraint results.

[0062] The test risk assessment module is used to assess the test risk of the wireless signal continuity margin based on the segment security response constraint results, and obtain the segment wireless signal test assessment results.

[0063] The test result encapsulation module is used to encapsulate the test results of the wireless signal segment test evaluation to obtain the wireless signal test results of the autonomous vehicle.

[0064] Thirdly, the present invention provides an electronic device including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the methods in the first and second aspects.

[0065] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the methods in the first and second aspects.

[0066] The wireless signal testing method and system for unmanned vehicles provided by this invention have the following advantages compared with the prior art:

[0067] 1. By standardizing the test data of autonomous vehicles and organizing the vehicle operation field, wireless communication field, test area field, and test task field into a unified wireless signal test input set, the wireless signal data can maintain the same data standard as the vehicle's operating location, operating status, and task configuration. This helps to reduce the problem of unclear segment attribution when wireless signals are statistically analyzed only by point or fixed time window.

[0068] 2. By fragmenting the wireless signal test input set into task segments and evaluating the continuity of multi-link signals within the task segments, the continuity margin of the wireless signal is obtained. This allows the test results to reflect not only the numerical value of signal quality but also segment-level communication performance such as continuous degradation, persistent interruption, and link recovery, which helps to improve the pertinence of wireless signal evaluation in autonomous vehicle operation test scenarios.

[0069] 3. By extracting the segment safety response constraint results and conducting a test risk assessment of the wireless signal continuity margin based on the segment safety response constraint results, the segment wireless signal test evaluation results are obtained. This allows the wireless signal test results to simultaneously mark the task impact type, takeover risk type, main impact link, and risk occurrence location, which is beneficial for generating test result outputs for unmanned vehicle operation segments. Attached Figure Description

[0070] Figure 1 This is an exemplary flowchart of a wireless signal testing method for unmanned vehicles provided in an embodiment of the present invention.

[0071] Figure 2 This is an exemplary structural framework diagram of a wireless signal testing system for unmanned vehicles provided in an embodiment of the present invention.

[0072] Figure 3 A comparison diagram showing the effect of the wireless signal testing method and system for unmanned vehicles provided in this embodiment of the invention with the prior art. Detailed Implementation

[0073] To make the technical means, creative features, and achieved objectives and effects of this invention easier to understand, the invention is further described below with reference to specific embodiments. However, the following embodiments are merely preferred embodiments of this invention and not all of them. Other embodiments obtained by those skilled in the art based on the embodiments described herein without creative effort are all within the protection scope of this invention. Unless otherwise specified, the experimental methods in the following embodiments are conventional methods, and the materials and reagents used in the following embodiments are commercially available unless otherwise specified.

[0074] Example 1 combined Figure 1 The exemplary flowchart of the wireless signal testing method for unmanned vehicles provided in the embodiment of the present invention is shown below, and the specific implementation steps are as follows:

[0075] Acquire basic test data for autonomous vehicles and normalize the test standards to obtain the wireless signal test input set.

[0076] The basic test data for autonomous vehicles refers to the collection and configuration of vehicle operation data, wireless communication data, test area data, and test task configuration data under the same test task. Vehicle operation data is collected by the onboard data acquisition terminal, recording at least the vehicle position, vehicle speed, vehicle heading angle, vehicle acceleration, vehicle operating status, and vehicle timestamp. Wireless communication data is collected by the onboard communication terminal, roadside communication test terminal, vehicle-to-cloud communication log interface, or remote monitoring link log interface, recording at least the link type, signal quality value, communication latency, packet loss status, communication interruption status, link recovery status, and communication timestamp. Test area data records at least the test route coordinates, area boundary coordinates, road segment number, and area affiliation. Test task configuration data records at least the test task number, test route number, sampling period, link type to be evaluated, task evaluation criteria, safety response constraint field, vehicle control architecture field, and response log access configuration. Among these, the vehicle control architecture field records the control path and execution entity for remote takeover / local safety degradation / safe parking. The response log access configuration indicates the time record access location for response events such as remote takeover request and confirmation, local degradation trigger and confirmation, and safe parking trigger and confirmation. The response log is written by the vehicle-side control terminal, remote monitoring platform, or safety response execution module according to the test task number. The basic test data serves as the input data for test caliber normalization.

[0077] The standardization of test criteria refers to the process of unifying the time, spatial, link, and task criteria in the basic test data. Specifically, vehicle timestamps, communication timestamps, and task configuration times are converted into relative test times; vehicle locations, test route coordinates, area boundary coordinates, and wireless coverage device locations are transformed to the same test area coordinate system; different communication sources are converted into a unified link type field; and test segment type, link evaluation object, task evaluation criterion, and safety response constraint fields are associated with the corresponding test time slots. Through the above processing, vehicle operation data, wireless communication data, test area data, and test task configuration data can be associated according to the same test task number and the same test time slot.

[0078] The wireless signal test input set refers to a unified data structure formed after test standardization. This data structure uses the test task number as the primary index and test relative time, vehicle number, route mileage, road segment, link type, and task association fields as sub-indexes. It records vehicle operation fields, wireless communication fields, test area fields, test task fields, and data quality marker fields. The wireless signal test input set serves as input for task fragmentation processing, enabling subsequent segmentation to simultaneously read vehicle operation status, operation scenario status, link status, and task configuration status.

[0079] Before starting the wireless signal test, establish the test task and assign a test task number to it. Write the vehicle number of the unmanned vehicle to be tested, the test route number, the test start time, the test end time, the sampling period, the communication equipment number participating in the test, and the link type to be evaluated into the test task so that the vehicle operation data, wireless communication data, area data, and task configuration data collected later can belong to the same test task.

[0080] After the test task is started, the vehicle-mounted data acquisition terminal records the vehicle position, vehicle speed, vehicle heading angle, vehicle acceleration, vehicle operating status, and vehicle timestamp according to the sampling period, and binds the above data with the test task number and vehicle number to form a vehicle operation acquisition record. At the same time, the vehicle-mounted communication terminal, roadside communication test terminal, vehicle-to-cloud communication log interface, and remote monitoring link log interface record the communication device number, link type, signal quality value, communication latency, packet loss status, communication interruption status, link recovery status, and communication timestamp under their respective links, and write the above data under the same test task number to form a wireless communication acquisition record.

[0081] While collecting vehicle operation and wireless communication data, the system also reads test area configuration data and test task configuration data. The test area configuration data records the test route coordinates, area boundary coordinates, road segment numbers, wireless coverage device locations, and area identifiers. The test task configuration data records the test segment type, link evaluation object, task evaluation criteria, and response constraint fields. The test area configuration data is bound to the test route number, and the test task configuration data is bound to the test task number, thus forming test area records and test task records that correspond to the vehicle operation and wireless communication data.

[0082] After completing the above data access, access verification is performed on vehicle operation collection records, wireless communication collection records, test area records, and test task records. During verification, the existence of the test task number, vehicle number, collection time, link type, and data source number is checked for each record. For records lacking these fields, the record is written to the exception temporary storage area, and the missing item type is written in the exception reason field. For records that pass the verification, they are written to the original test record set. Therefore, subsequent normalization processing is only performed on data with complete source and time identifiers, and exception records still retain traceability markers.

[0083] After the initial test record set is formed, the test start time is used as the zero point, and the vehicle timestamp, communication timestamp, and task configuration time are converted into relative test times. Then, continuous test time slices are generated according to the sampling period, and the vehicle operation data acquisition records and wireless communication data acquisition records are placed into their respective test time slices. If multiple records from the same data source exist within the same test time slice, the record with the earliest reception time is retained, and a duplicate record flag is written for the remaining records. If a record from a certain data source is missing within the same test time slice, a missing data acquisition flag is written for that test time slice, thus forming test records with a unified time caliber.

[0084] After standardizing the timeframe, the vehicle location, test route coordinates, area boundary coordinates, and wireless coverage device location are transformed to the same test area coordinate system. The vehicle location is then projected onto the test route, and the corresponding route mileage, road segment, and area affiliation are calculated. If the vehicle location cannot be projected onto the test route, a location out-of-bounds flag is written to the corresponding test time slice. If the vehicle location is successfully projected, the route mileage, road segment, and area affiliation are written to the corresponding test time slice, ensuring that each wireless communication data point corresponds to the vehicle's actual operating location within the test area.

[0085] Subsequently, the communication sources in the wireless communication acquisition records are uniformly converted into a link type field, and the signal quality value, communication delay, packet loss status, communication interruption status, and link recovery status of each link are written into the link status field of the same test time slice. For data sources that have not uploaded link status within the same test time slice, a missing link marker is written into the corresponding link status field; for data sources with complete link status fields, their link type, communication device number, and link status value are retained, so that wireless communication data from different sources can participate in subsequent fragmentation processing according to a unified link standard.

[0086] After unifying the time, space, and link standards, the test segment type, link evaluation object, task evaluation standard, and response constraint fields in the test task configuration data are attached to the corresponding test time slots. During attachment, the test task number is used as the primary matching field, and the test relative time, route mileage, and road segment are used as secondary matching fields. When task configuration data can be matched within the same test time slot, the corresponding task configuration field is written into the task association field. When task configuration data cannot be matched within the same test time slot, a task mismatch flag is written, and the vehicle operation data and wireless communication data for that test time slot are retained.

[0087] After the above processing, using the test task number as the primary index and the test relative time, vehicle number, route mileage, road segment, link type, and task association fields as sub-indexes, the vehicle operation field, wireless communication field, test area field, test task field, and data quality marker field are organized into a unified data structure to obtain the wireless signal test input set. This wireless signal test input set is used for subsequent task fragmentation processing.

[0088] The segment quality markers refer to a set of marker fields used to record data state anomalies that occur during data access, normalization processing, segmentation, and algorithm calculation. The set of segment quality marker values ​​includes at least: missing data acquisition marker, missing link marker, location out-of-bounds marker, task misconfiguration marker, duplicate record marker, duplicate link marker, missing link acquisition marker, missing motion state marker, default response position marker, missing braking parameter marker, stationary segment marker, missing response log marker, historical sample supplementation marker, missing link recovery sample marker, missing safety response constraint marker, missing boundary marker, and risk assessment misconfiguration marker. Segment quality markers are written to the corresponding test time slice or corresponding task segment number according to their generation location and are aggregated into data verification markers during the test result encapsulation stage.

[0089] The wireless signal test input set is processed into task fragmentation to obtain a task fragmentation test dataset.

[0090] The task fragmentation process refers to dividing a continuous test process in the wireless signal test input set into multiple task segments with task attributes and link state attributes. Specifically, the wireless signal test input set is first time-sliced ​​and test fields are reorganized to obtain test process records; then, segment boundaries are calculated on the test process records to obtain task segment indices; subsequently, the test process records are segmented and segment attributes are attached according to the task segment indices. This process is used to convert wireless signal test objects from continuous route records into segment-level test objects.

[0091] The task fragmentation test dataset refers to a collection of fragment-level data formed after task fragmentation processing. This dataset uses the test task number and task fragment number as a joint index, and records at least the fragment start time, fragment end time, fragment duration, fragment start position, fragment end position, fragment task type, fragment vehicle motion state, fragment link object, fragment link state sequence, fragment safety response field, and fragment quality marker. This dataset is used for multi-link signal continuity evaluation and safety response constraint extraction.

[0092] The wireless signal test input set is time-sliced ​​to obtain a time-slice aligned record. Specifically, the test task number, test relative time, vehicle number, route mileage, road segment, area affiliation, vehicle operation field, link status field, task association field, and data quality flag field are read from the wireless signal test input set, and the data under the same test task number are sorted according to the order of the test relative time. For records with the same test relative time and the same vehicle number, the vehicle operation field, link status field, test area field, and task association field are written into the same time-slice record. For time slices with missing sampling flags, missing link flags, location out-of-bounds flags, or task misconfiguration flags, the corresponding flags are retained in the data quality flag field to obtain the time-slice aligned record.

[0093] The time-slice aligned records are reorganized using test fields to obtain test process records. Specifically, using the test task number and test relative time as a joint index, the vehicle operation fields under each time slice are organized into vehicle status fields, route mileage, road segments, and area affiliation are organized into scene status fields, link type, signal quality value, communication latency, packet loss status, communication interruption status, and link recovery status are organized into link status fields, and test segment type, link evaluation object, task evaluation caliber, and security response constraint fields are organized into task configuration fields. Subsequently, the vehicle status fields, scene status fields, link status fields, task configuration fields, and data quality flag fields are written into the same test process record, so that each test process record corresponds to the vehicle operation status, operation scene status, and wireless link status within a test time slice.

[0094] The test process records are used to calculate segment boundaries to obtain task segment indices. Specifically, according to the relative time sequence of the tests, task state transition detection, runtime scenario boundary detection, and communication link event detection are performed on adjacent test process records to obtain the intensity of task state change, scenario change, and link change, respectively. Then, based on the intensity of task state change, scenario change, and link change, a collaborative boundary response is calculated using a task-scenario-link three-axis collaborative boundary response algorithm to obtain the collaborative boundary response result.

[0095] The aforementioned task scenario link three-axis collaborative boundary response algorithm refers to an algorithm used for segment boundary calculation. This algorithm takes test process records as input, detects changes in task state, runtime scenario, and communication link events in adjacent test time slices, and obtains the intensity of task state change, scenario change, and link change. Subsequently, it generates collaborative boundary response results through cross-item boundary response calculation, and performs boundary filtering and continuous interval numbering on the collaborative boundary response results to obtain the task segment index. This algorithm is used to generate valid task segment boundary points at time locations where task state, runtime scenario, and link events change simultaneously.

[0096] Task state transition detection is performed on the test process records to obtain the intensity of task state changes. Specifically, the test segment type, vehicle operating status, and task association fields within adjacent test time slices are read; a first task change flag is generated when the test segment type changes, a second task change flag is generated when the vehicle operating status changes, and a third task change flag is generated when the task association field changes from a task misconfiguration flag to a valid configuration field or vice versa; the sum of the values ​​of the first, second, and third task change flags is divided by three to obtain the task state change intensity, which ranges from 0 to 1.

[0097] The test process records are subjected to scenario boundary detection to obtain the scenario change intensity. Specifically, the route mileage, road segments, and region affiliation within adjacent test time slices are read; a first scenario change marker is generated when the change in route mileage exceeds twice the reference driving distance; the reference driving distance is the average of the changes in vehicle route mileage within the N consecutive test time slices preceding the current test time slice, where N is determined by the length of the sliding statistical window in the test task configuration data, and is taken as 10 if not recorded. A second scenario change marker is generated when a road segment changes, and a third scenario change marker is generated when a region affiliation changes; the sum of the values ​​of the first, second, and third scenario change markers is divided by three to obtain the scenario change intensity, which ranges from 0 to 1.

[0098] Communication link event detection is performed on the test process records to obtain the link change intensity. Specifically, the link status field and data quality flag field of each adjacent test time slice are read; according to the link evaluation object and task evaluation caliber in the test task configuration data, the signal quality value is divided into three link quality states: satisfied, critical, and unsatisfied; a first link change flag is generated when the link quality state of adjacent test time slices switches, a second link change flag is generated when the communication interruption state changes, a third link change flag is generated when the link recovery state changes, and a fourth link change flag is generated when the data quality flag corresponding to the link type changes; the values ​​of the first, second, third, and fourth link change flags are summed and divided by four to obtain the link change intensity, which ranges from 0 to 1.

[0099] The collaborative boundary response is calculated using the task scenario link three-axis collaborative boundary response algorithm, and the result is obtained using the following formula: ,

[0100] in, This represents the collaborative boundary response value corresponding to the test relative time t; This indicates the intensity of the task state change corresponding to the relative time t during the test; This indicates the intensity of scene change corresponding to the relative time t during the test; This indicates the intensity of link change corresponding to the test relative time t; This represents the triaxial cooperative gain coefficient, ranging from 0.5 to 1.0, with an initial value of 0.7. When manually annotated valid segment boundary samples exist during the trial operation phase of the test site, the objective is to maximize the hit rate of the cooperative boundary response value at the manually annotated boundary points. A grid search is performed within the range of values ​​with a step size of 0.05, and the value with the highest hit rate is used as the corrected value. When there are no manually labeled samples, Set the initial value to 0.7.

[0101] The collaborative boundary response results are subjected to boundary filtering to obtain valid task segment boundary points. Specifically, the collaborative boundary response value is compared with a boundary response threshold; when... When the test relative time t is reached, it is marked as the boundary point of the valid task segment; when At that time, no valid task segment boundary points are generated.

[0102] The boundary response threshold The determination method is as follows: when there are valid manually labeled fragment boundary samples, the lower quartile of the collaborative boundary response value corresponding to the manually labeled boundary point is taken as... When no manually labeled samples are available, the distribution of all cooperative boundary response values ​​under the same test route is statistically analyzed, and the cooperative boundary response value corresponding to the 80th percentile is taken as... .

[0103] The boundary points of the valid task segments are numbered consecutively to obtain a task segment index. Specifically, according to the relative time sequence of the tests, the test process records between two adjacent valid task segment boundary points are divided into a continuous interval, and a task segment number is written for this continuous interval; when the duration of the continuous interval is less than twice a sampling period, the continuous interval is merged into the previous task segment; when the continuous interval is located at the start of the test and its duration is less than twice a sampling period, the continuous interval is merged into the next task segment; when a valid task segment boundary point is missing, all test process records from the test start time to the test end time are divided into a task segment, and a boundary missing marker is written into the task segment index.

[0104] The test process records are segmented according to the task segment index to obtain segment test records. Specifically, the task segment number is used as the main segment index, and test process records belonging to the same continuous interval are grouped into the same segment test record. Each segment test record contains the segment start time, segment end time, segment duration, starting route mileage, ending route mileage, road segment set, area affiliation set, vehicle status sequence, link status sequence, task configuration field, and data quality flag field. For time slices with missing data collection flags, missing link flags, location out-of-bounds flags, or task configuration missing flags, the corresponding flags are summarized into segment quality flags and written into the segment test record.

[0105] The fragment test records are appended with fragment attributes to obtain a task fragmentation test dataset. Specifically, the task configuration field in each fragment test record is used to determine the fragment task attribute, the duration of each test fragment type within the task fragment is calculated, and the test fragment type with the longest duration is written into the fragment task type; when two test fragment types have the same duration, the test fragment type with the higher safety response constraint level is selected as the fragment task type according to the task evaluation criteria in the test task configuration data.

[0106] The motion states of the vehicle state sequences in the segment test records are merged. Based on the vehicle speed, acceleration, and heading angle change, the speed state, acceleration / deceleration state, and steering state of the task segment are generated and written into the segment's vehicle motion state. The link state sequences in the segment test records are merged into link objects. Based on the link type field, the link types with valid link state fields within the task segment are counted, and the corresponding link types are written into the segment's link objects. For link types that only have missing link markers, the link type is written into the segment's quality marker.

[0107] Constraint fields are appended to the safety response constraint fields in the segment test records. Safety response constraint fields matching the segment task type are written to the segment safety response field. When no safety response constraint field matches the segment task type, a missing safety response constraint flag is written to the segment quality flag. Subsequently, the segment task type, segment vehicle motion state, segment link object, segment safety response field, and segment quality flag are bound to the corresponding task segment number to obtain the task fragmentation test dataset.

[0108] The task fragmentation test dataset uses the test task number and task fragment number as a joint index, and records at least the fragment start time, fragment end time, fragment duration, fragment start position, fragment end position, fragment task type, fragment vehicle motion state, fragment link object, fragment link state sequence, fragment safety response field, and fragment quality marker.

[0109] In one embodiment, the task scenario link three-axis collaborative boundary response algorithm further includes:

[0110] In a wireless signal test scenario for unmanned vehicles in a port container yard, the unmanned vehicle follows a test route from an open straight section into a gantry-obstructed area. Within the gantry-obstructed area, it performs tasks such as low-speed passage, avoiding yard work vehicles, and maintaining the remote monitoring link. The test system continuously records the vehicle's operating status, area affiliation status, and link status fields according to the relative test time. The vehicle operating status records states such as straight-line cruising, low-speed passage, deceleration for avoidance, and resumption of cruising. The area affiliation status records areas such as open sections, gantry-obstructed areas, and internal yard passages. The link status fields record the signal quality, communication interruption status, and link recovery status of the vehicle-to-cloud link, the remote monitoring link, and the vehicle-to-infrastructure (V2I) link.

[0111] When an autonomous vehicle enters a gantry-obstructed area from an open, straight road section, the task scenario link three-axis collaborative boundary response algorithm first performs task state transition detection on the vehicle's operating state in adjacent test time slices. If the vehicle's operating state changes from straight-line cruising to low-speed passage, the algorithm generates the task state change intensity. Subsequently, the algorithm performs operational scenario boundary detection on the area affiliation in adjacent test time slices. If the area affiliation changes from an open road section to a gantry-obstructed area, the algorithm generates the scenario change intensity. Simultaneously, the algorithm performs communication link event detection on the link status field in adjacent test time slices. If the vehicle-to-cloud link or remote monitoring link experiences a cross-level change in signal quality, a change in communication interruption status, or a change in link recovery status, the algorithm generates the link change intensity.

[0112] When task state change intensity, scene change intensity, and link change intensity occur simultaneously around the same relative test time, the task-scene-link three-axis collaborative boundary response algorithm calculates the collaborative boundary response for the three types of change intensity and compares the collaborative boundary response value with the boundary response threshold. When the collaborative boundary response value reaches the boundary response threshold, the relative test time is marked as a valid task segment boundary point. Subsequently, the system uses this valid task segment boundary point as the starting boundary to divide the corresponding test process record within the gantry occlusion area into independent task segments and writes a task segment number for each task segment.

[0113] Within this independent task segment, the system continues to write the segment task type as a gantry obstruction passage segment, group the vehicle speed, vehicle acceleration, and heading angle changes into segment vehicle motion state, group the vehicle-cloud link, remote monitoring link, and vehicle-road cooperative link into segment link object, and attach the corresponding segment safety response field to the task segment number, thereby obtaining task segmented test data containing segment task type, segment vehicle motion state, segment link state sequence, and segment safety response field.

[0114] During the same test, if the vehicle only experiences short-term speed fluctuations, but the area affiliation remains in an open road section and the link status field does not show communication interruption, link recovery, or signal quality changes across levels, the algorithm will not generate valid task segment boundary points. If the wireless link only experiences signal quality fluctuations at a single sampling point, but the vehicle's operating status and area affiliation do not change synchronously, the algorithm will also not generate new task segment indexes. Therefore, the system divides the time periods related to changes in the autonomous vehicle's operating task, operating scenario, and link status into independent task segments, and distinguishes ordinary cruise segments, gantry obstruction passage segments, and link recovery segments in terms of data structure, enabling subsequent multi-link signal continuity evaluations to calculate wireless signal continuity margins for different task segments.

[0115] Multi-link signal continuity is evaluated on the fragmented test dataset of the task to obtain the wireless signal continuity margin.

[0116] The multi-link signal continuity evaluation refers to the process of characterizing and calculating the continuity of multiple link types within the same task segment. Specifically, the task-fragmented test dataset is subjected to segment link timing normalization to obtain basic data for segment signal evaluation; multi-link continuity degradation window identification is performed on the basic data for segment signal evaluation to obtain segment link continuity characterization results; and then, the segment link continuity characterization results are converted into margins based on task communication constraints. This evaluation is used to generate a wireless signal continuity margin that reflects the continuity margin of wireless links within the task segment.

[0117] The wireless signal continuity margin refers to the segment-level margin result calculated under mission communication constraints, assessing the continuity status of multiple links within the same mission segment. This result is generated based on the segment link continuity characterization results, segment communication requirement baseline, persistent degradation ratio, and joint degradation penalty term for critical links. It at least records the mission segment number, margin value, continuity flag, link types involved in the calculation, set of critical links, segment link degradation characterization results, and segment quality flag. This margin is used for subsequent test risk assessment in conjunction with the segment security response constraint results.

[0118] The fragmented test dataset is subjected to fragment link timing normalization to obtain basic data for fragment signal evaluation. Specifically, the test task number, task fragment number, fragment start time, fragment end time, fragment duration, fragment task type, fragment vehicle motion state, fragment link object, fragment link state sequence, fragment safety response field, and fragment quality flag are read from the fragmented test dataset. Using the task fragment number as the fragment-level index, the link state sequence within each task fragment is sorted in ascending order according to the relative test time.

[0119] When segment link timing is regularized, the evaluation time range of the current task segment is limited by the segment start time and segment end time, and a segment evaluation time axis is generated according to the sampling period of the wireless signal test input set. The signal quality value, communication delay, packet loss status, communication interruption status, and link recovery status in the segment link state sequence are written into the corresponding sampling points of the segment evaluation time axis. If multiple link state records of the same link type exist at the same sampling point, the link state record with the smallest time difference from the center of that sampling point is retained, and the remaining link state records are written into the duplicate link mark. If no link state record of the same link type exists at a certain sampling point, a link missing sampling mark is written into that sampling point. After the above processing, the basic data for segment signal evaluation is obtained with the task segment number, test relative time, and link type as joint indices.

[0120] The basic data for evaluating the segment signal includes at least the task segment number, segment task type, segment vehicle motion state, link type, sampling point time, signal quality value, communication delay, packet loss status, communication interruption status, link recovery status, link missing sampling flag, duplicate link flag, task communication constraints, and segment quality flag. The task communication constraints are generated from the link evaluation object and task evaluation caliber in the task configuration field and are bound to the segment task type and link type. The task communication constraints must record at least the following fields: minimum link quality threshold bound to the segment task type and link type, allowable fluctuation range, link recovery time requirement, tolerable continuous degradation duration ratio, link dependency coefficient, link evaluation object priority, evaluation time window length, continuous degradation sensitivity level, continuous degradation tolerance level, mandatory dependency link identifier, margin satisfaction threshold, and margin critical threshold. For link types within the same task segment that do not match task communication constraints, this link type is written into the segment quality flag, and no valid margin value is generated in the corresponding link margin conversion.

[0121] The task communication constraints are generated differently according to link type: For vehicle-to-cloud links, the minimum link quality threshold is jointly determined by signal quality value, communication latency, and packet loss rate, and the link recovery time requirement is mapped according to the remote command timeliness requirement in the test task configuration data; for remote monitoring links, the minimum link quality threshold further reads the link recovery time requirement and message reception rate requirement in addition to the signal quality value; for vehicle-road cooperative links, the minimum link quality threshold prioritizes message reception rate and communication latency, and is generated in combination with the coverage of roadside communication equipment; for vehicle-side local communication links, the minimum link quality threshold is determined by signal quality value and packet loss rate. The link dependency coefficient of each link type is generated according to the difference in its supporting role under the segment task type, and the main link, backup link, and auxiliary link are respectively valued according to the aforementioned link evaluation object priority mapping rules. When the task communication constraints do not record the above fields for a certain link type, the default link evaluation template under the task evaluation caliber for that link type is used.

[0122] After the basic data for segment signal evaluation is formed, the state data of different link types within each task segment have been organized onto the same segment evaluation time axis. The processing object of the continuity evaluation is transformed from discrete sampling points to continuous windows on the segment evaluation time axis. Based on this data state, multi-link continuous degradation window identification is performed on the basic data for segment signal evaluation to obtain the segment link continuity characterization results. Specifically, the basic data for segment signal evaluation within each task segment is divided into multi-link time windows to obtain a sequence of segment link windows. During the division, multiple continuous windows are generated by sliding along the segment evaluation time axis according to the evaluation time window length, using the task segment number and link type as indices. The evaluation time window length is determined by the task evaluation caliber in the task communication constraints. When the task communication constraints do not record the evaluation time window length, it is determined according to one-fifth of the duration of the task segment, and the evaluation time window length is not less than three sampling periods and not greater than one-half of the duration of the task segment.

[0123] Communication quality change statistics are performed on the segment link window sequence to obtain communication quality change parameters. Specifically, within each segment link window, signal quality value, communication delay, packet loss status, and link missing sampling marker are read; the minimum, average, and fluctuation range of the signal quality value within the window are calculated; the maximum, average, and fluctuation range of the communication delay within the window are calculated; the number of packet loss sampling points within the window is calculated; and the number of missing sampling points within the window is calculated. The above statistical results are then bound to the corresponding task segment number, link type, and window number to obtain the communication quality change parameters.

[0124] The communication interruption duration is statistically analyzed for the segment link window sequence to obtain the communication interruption duration parameter. Specifically, within each segment link window, packet loss status, communication interruption status, and link missing sampling marker are read. Sampling points with consecutive packet loss status, communication interruption status, or link missing sampling marker are merged into a continuous interruption segment, and the start time, end time, and duration of each continuous interruption segment are calculated. When there are multiple continuous interruption segments within the same segment link window, the continuous interruption segment with the longest duration is taken as the maximum communication interruption duration of that window. At the same time, the cumulative interruption time of all continuous interruption segments within that window is calculated to obtain the communication interruption duration parameter.

[0125] The communication recovery time is statistically analyzed for the segment link window sequence to obtain communication recovery time parameters. Specifically, within each task segment, the communication interruption status, link recovery status, and link missing sampling marker are read. The sampling point where the communication interruption status changes from interruption to non-interruption and the link recovery status is recorded as recovery completion is marked as the recovery completion point. The starting sampling points that were continuously in the communication interruption status or link missing sampling status before the recovery completion point are marked as degradation start points. The duration between the degradation start point and the recovery completion point is calculated to obtain the link recovery time. When there are multiple link recovery times within a task segment, the maximum link recovery time, the average link recovery time, and the standard deviation of the link recovery time are recorded to obtain the communication recovery time parameters.

[0126] At this point, communication quality variation parameters, communication interruption duration parameters, and communication recovery time parameters have been generated for each link type within the same task segment. These parameters correspond to link quality fluctuations, interruption duration states, and recovery time states, and are still distributed within different segment link windows. To organize the window-level statistical results into segment-level continuity evaluation objects, the communication quality variation parameters, communication interruption duration parameters, and communication recovery time parameters are weighted and merged to obtain segment link continuity characterization results. Specifically, according to the task segment number and link type, the communication quality variation parameters, communication interruption duration parameters, and communication recovery time parameters corresponding to each segment link window belonging to the same link type are merged. During merging, the window duration is used as the window weight, and the communication quality variation parameters, communication interruption duration parameters, and communication recovery time parameters within each window are converted into segment-level parameters. These segment-level parameters are then bound to the link type to obtain the segment link continuity characterization results.

[0127] The segment link continuity characterization results are indexed by task segment number and link type, and at least record the minimum signal quality value, average signal quality value, signal quality fluctuation amplitude, maximum communication delay value, average communication delay value, communication delay fluctuation amplitude, number of packet loss sampling points, number of missing sampling points, maximum communication interruption duration, cumulative interruption time, maximum link recovery time, average link recovery time, standard deviation of link recovery time, link missing sampling mark, and duplicate link mark.

[0128] After the segment link continuity characterization results are completed, the continuity status of each link type has been converted from the segment link window statistics into segment-level parameters. However, different task segments have different communication requirements for different link types, and the evaluation criteria for the degradation of the same link differ in different task segments. Therefore, based on the task communication constraints in the segment signal evaluation baseline data, the segment link continuity characterization results are converted into a margin to obtain the wireless signal continuity margin. Specifically, the segment signal evaluation baseline data is encoded with task attributes to obtain segment task attribute encoding results. During task attribute encoding, the segment task type, segment vehicle motion state, and segment link object are written into the same task attribute encoding field; wherein, the segment task type is used to determine the communication evaluation target of the current task segment, the segment vehicle motion state is used to determine the motion state constraints of the current task segment, and the segment link object is used to determine the link type participating in the evaluation of the current task segment.

[0129] Based on the segment task attribute encoding results, task link dependency matching is performed to obtain the segment communication requirement baseline. Specifically, the segment task attribute encoding results are matched with task communication constraints to determine the minimum link quality threshold, reference fluctuation range, tolerable continuous degradation duration ratio, and link dependency coefficient for each link type under each task segment. When a link type within the same task segment does not match the minimum link quality threshold, that link type is marked as a non-evaluation link. When a link type matches the minimum link quality threshold, that link type is written into the segment communication requirement baseline.

[0130] The minimum link quality threshold is determined by the link quality constraint value recorded in the task communication constraints for that link type; the reference fluctuation range is determined by the allowable fluctuation range recorded in the task communication constraints for that link type, or, if not recorded, the standard deviation of the link quality index for that link type before directional unification within the task segment is taken as the reference fluctuation range; the tolerable continuous degradation duration ratio is as described above. The determination method is generated; the link dependency coefficient is determined by the dependency field jointly recorded in the task communication constraint for the segment task type and the link type. If not recorded, it is mapped according to the priority of the link evaluation object under the segment task type: the main link takes 0.8 to 1.0, the backup link takes 0.4 to 0.7, and the auxiliary link takes 0.1 to 0.3. The default values ​​are 0.9, 0.55, and 0.2 respectively.

[0131] Once the segment communication requirements baseline is determined, each link type has obtained its corresponding minimum link quality threshold, reference fluctuation range, tolerable continuous degradation duration ratio, and link dependency coefficient. The critical link set... , refers to the set of link types that play a decisive role in the communication support for the execution of the task in the j-th task segment. The critical link set is generated from the fragment communication requirement baseline: link types with a link dependency coefficient greater than or equal to the critical link threshold in the fragment communication requirement baseline are included in the critical link set; when a link type does not reach the critical link threshold but is marked as a mandatory dependency link by task communication constraints under the fragment task type, that link type is also included in the critical link set. The critical link threshold is determined by the task evaluation caliber in the test task configuration data, and is taken as 0.7 if not recorded. Link types not included in the critical link set participate in the calculation of wireless signal continuity margin as auxiliary links, but do not participate in the calculation of the critical link joint degradation penalty term.

[0132] Because the segment link continuity characterization results contain both indicators where larger values ​​represent better performance and indicators where smaller values ​​represent better performance, it is necessary to unify the link quality direction of the segment link continuity characterization results based on the segment communication requirement benchmark to obtain a unified link quality result. Specifically, the communication quality change parameter, communication interruption duration parameter, and communication recovery time parameter are read from the segment link continuity characterization results; for signal quality value, message success rate, and link availability rate, these are retained as positive quality indicators where larger values ​​represent better link continuity; for communication latency, communication interruption duration, cumulative interruption time, and link recovery time, they are converted inversely according to the corresponding thresholds in the segment communication requirement benchmark to obtain positive quality indicators where larger values ​​represent better link continuity; for link types that cannot match the corresponding thresholds, the link type is written into the segment quality tag and is not included in the wireless signal continuity margin calculation.

[0133] After the unified link quality results are generated, the quality indicators of each link type have been converted to the same evaluation direction. Under this unified result, the link quality indicators of each link type are compared with the minimum link quality threshold on a sample-by-sample basis to identify the continuous degradation range of the link within the task segment. Specifically, the continuous degradation ratio is calculated on the unified link quality results to obtain the segment link degradation characterization results. The unified link quality indicators are read according to the task segment number and link type, and the link quality indicators are compared with the minimum link quality threshold in the segment communication requirement benchmark. When the link quality indicator is lower than the minimum link quality threshold, the corresponding sampling point is marked as a degradation sampling point. The consecutive degradation sampling points within the same task segment are merged into a continuous degradation segment. The cumulative duration of continuous degradation for this link type within the task segment is calculated, and the cumulative duration of continuous degradation is divided by the duration of the task segment to obtain the continuous degradation ratio. The continuous degradation ratio, the minimum link quality threshold, the reference fluctuation amplitude, and the link dependency coefficient are written into the same task segment and the same link type to obtain the segment link degradation characterization results.

[0134] The segment link degradation characterization results have consolidated the link quality indicators, persistent degradation ratio, minimum link quality threshold, reference fluctuation amplitude, and link dependency coefficient for each link within the task segment into a single link evaluation caliber. Before calculating the radio signal continuity margin, a joint degradation check is performed on the set of critical links to determine whether any critical links simultaneously fall below their corresponding minimum link quality threshold, and a joint degradation penalty term for critical links is calculated. This joint degradation penalty term for critical links represents the reduction in radio signal continuity margin when critical links within the same task segment simultaneously degrade, and its calculation formula is as follows: ,

[0135] in, This represents the critical link joint degradation penalty term corresponding to the j-th task segment; This represents the set of critical links corresponding to the j-th task segment; k represents the link type number. This represents the percentage of continuous degradation of the k-th link within the j-th task segment; Indicates the percentage of continuous degradation that can be tolerated; This represents the link quality index after the direction of the k-th link within the j-th task segment is unified; This represents the minimum link quality threshold required by the j-th task segment for the k-th link; This indicates an indicator function, which takes the value 1 when the condition is true and 0 when the condition is false; j represents the task segment number.

[0136] in, If all links in the critical link set are below the corresponding minimum link quality threshold, then a joint degradation penalty is calculated based on the portion of each critical link whose continuous degradation rate exceeds the tolerable continuous degradation duration. If at least one link in the critical link set is not below the corresponding minimum link quality threshold, then the joint degradation penalty term is zero.

[0137] After obtaining the joint degradation penalty term for critical links, the degradation characterization results of the aforementioned link segments are converted into a margin using a degradation persistence attenuation margin algorithm to obtain the wireless signal continuity margin. This degradation persistence attenuation margin algorithm incorporates the link quality margin, persistence degradation ratio, and joint degradation penalty term for critical links into the same calculation caliber, specifically using the following formula: ,

[0138] in, This represents the wireless signal continuity margin corresponding to the j-th task segment; This represents the link dependency coefficient of the j-th task segment to the k-th link; This represents the reference fluctuation range of the k-th link; Indicates the sensitivity coefficient to the persistence of degradation; Indicates the joint degradation penalty coefficient for critical links; An exponential function with the natural constant e as its base, where e represents the natural constant.

[0139] The degradation persistence sensitivity coefficient The determination method is as follows: when the task evaluation criteria record the continuous degradation sensitivity level, the continuous degradation high sensitivity level is taken as... Sensitivity level is taken in continuous degradation Continuous degradation of low sensitivity level When no continuous degradation sensitivity level is recorded. The default value is 2.0. This refers to the joint degradation penalty coefficient for critical links. The method for determining the critical link set is as follows: when the number of links in the critical link set is 1, then... When there are 2, take If there are 3 or more, take The percentage of tolerable continuous degradation duration. The determination method is as follows: when the continuous degradation tolerance level is recorded as low / medium / high in the task evaluation criteria, take the following values ​​respectively. When not recorded The default value is 0.15. When manually labeled link degradation samples exist during the trial operation phase of the test site, a grid search is performed on the above parameters within their respective value ranges with a step size of 0.05. The value that maximizes the hit rate of the wireless signal continuity margin on the manually labeled link degradation samples is used as the correction result.

[0140] When wireless signal continuity margin When the margin requirement is greater than or equal to the threshold in the segment communication requirement baseline, the task segment is marked as a continuity-satisfied segment; when the wireless signal continuity margin... When the margin in the segment communication requirement baseline meets the threshold and is greater than or equal to the margin critical threshold, the task segment is marked as a continuity critical segment; when the wireless signal continuity margin If the value is less than the margin threshold, the task segment is marked as a segment with unsatisfactory continuity. The continuity marker, the link type involved in the calculation, the set of critical links, the segment link degradation characterization results, and the segment quality marker are written under the same task segment number to obtain the wireless signal continuity margin.

[0141] The margin satisfaction threshold and margin critical threshold are generated by the fragment communication requirement benchmark based on the task evaluation criteria in the test task configuration data. When the task evaluation criteria do not record the above thresholds, they are mapped according to the security level corresponding to the fragment task type: the margin satisfaction threshold for high security level fragment task types is 0.7 and the margin critical threshold is 0.4; the medium security level corresponds to 0.5 / 0.25; and the low security level corresponds to 0.3 / 0.1.

[0142] The degradation persistence attenuation margin algorithm refers to an algorithm used for margin conversion. This algorithm takes the segment link degradation characterization results as input, reads the directional unified link quality index, minimum link quality threshold, reference fluctuation amplitude, persistence degradation ratio, and link dependency coefficient for each link type under the same task segment; first, it performs joint degradation determination based on the critical link set to obtain the critical link joint degradation penalty term; then, it calculates the wireless signal continuity margin based on the link quality margin, persistence degradation ratio, and critical link joint degradation penalty term. This algorithm is used to incorporate short-term fluctuations, persistence degradation, and critical link joint degradation into the same wireless signal continuity evaluation caliber.

[0143] In one embodiment, the degradation persistence decay margin algorithm further includes:

[0144] In the wireless signal testing scenario of unmanned vehicles in a port container yard, task fragmentation processing divides the test process of the vehicle passing through the gantry obstruction area into an independent task segment. Under each task segment, the segment task type, segment vehicle motion state, segment link object, and segment link state sequence are bound. The signal continuity evaluation module reads the link state data of the vehicle-to-cloud link, remote monitoring link, and vehicle-to-infrastructure (V2I) link within this task segment, and performs segment link timing regularization on the signal quality, communication latency, communication interruption status, and link recovery status of each link.

[0145] In this task segment, if the vehicle-to-cloud link experiences signal quality degradation only at one sampling point, but subsequently recovers to above the minimum link quality threshold corresponding to the task communication constraint, then this link only forms a short-term degradation record. When calculating the persistent degradation ratio, the degradation persistence margin algorithm writes this short-term degradation record into a smaller persistent degradation ratio, ensuring that its reduction in wireless signal continuity margin remains within the corresponding short-term fluctuation range. If the remote monitoring link has multiple consecutive sampling points below the minimum link quality threshold within the gantry obstruction area, and the link recovery time spans the main traffic period in this task segment, then the algorithm merges the consecutive sampling points below the threshold into a persistent degradation segment, calculates the persistent degradation ratio of the link within this task segment, and applies persistent attenuation to the link quality margin during margin conversion.

[0146] Within the same task segment, if both the vehicle-to-cloud link and the remote monitoring link belong to the critical link set in the segment's communication requirement baseline, and both are simultaneously below their corresponding minimum link quality thresholds, the degradation persistence attenuation margin algorithm performs a joint degradation determination on the critical link set and generates a critical link joint degradation penalty term. If only the auxiliary link degrades, and the critical links are not simultaneously below the minimum link quality thresholds, the critical link joint degradation penalty term is not triggered. Therefore, when calculating the wireless signal continuity margin, the system distinguishes between short-term signal fluctuations, single-link continuous degradation, and critical link joint degradation, and writes the obtained wireless signal continuity margin under the corresponding task segment number for subsequent safety response constraint extraction and test risk assessment.

[0147] Security response constraints are extracted from the fragmented test dataset of the task to obtain the fragment security response constraint results.

[0148] The safety response constraint extraction refers to the process of extracting and calculating segment-level constraint data related to safety response time from the task-fragmented test dataset. Specifically, the vehicle motion state is converted into segment motion response parameters on the task-fragmented test dataset; link recovery response parameters are integrated based on the segment motion response parameters to obtain segment response process data; and then, safety response constraints are calculated using a response margin algorithm that is coupled in parallel to the link recovery response process. This process is used to obtain the segment safety response constraint results corresponding to each task segment.

[0149] The segment safety response constraint result refers to the safety response constraint data calculated based on the vehicle motion state, link recovery state, and response closed-loop state within the same task segment. This result includes at least the segment's available response time, equivalent response consumption time, segment safety response margin, safety response flag, segment response type, parallel overlap coefficient, expected link recovery time, standard deviation of link recovery time, expected response time, standard deviation of response time, and segment quality flag. This result is used for risk assessment of wireless signal continuity margin testing.

[0150] The vehicle motion state is converted on the task fragmentation test dataset to obtain the segment motion response parameters. Specifically, the test task number, task segment number, segment start time, segment end time, segment duration, segment start position, segment end position, segment task type, segment vehicle motion state, segment safety response field, and segment quality flag are read from the task fragmentation test dataset. Using the task segment number as an index, the vehicle speed, vehicle acceleration, vehicle heading angle change, and route mileage change within the same task segment are merged to obtain the segment speed representative value, segment acceleration representative value, segment heading change, and remaining available distance for that task segment.

[0151] The segment velocity representative value is determined by the maximum value of the vehicle velocity sequence within the task segment; the segment acceleration representative value is determined by the absolute value of the braking directional acceleration within the task segment; the segment heading change is determined by the difference in heading angle between the starting and ending sampling points of the task segment; the remaining usable distance of the segment is determined by the difference in route mileage between the segment's starting position and the response constraint position recorded in the segment's safety response field. If the segment's safety response field does not record the response constraint position, the segment's ending position is used as the response constraint position, and a default response position marker is written into the segment quality marker; if the segment velocity representative value, segment acceleration representative value, or route mileage is missing, a motion state missing marker is written under the corresponding task segment, and no valid segment motion response parameters are generated for that task segment.

[0152] After the vehicle motion state is converted, the available response time of the segment is calculated based on the segment speed representative value, the remaining available distance of the segment, and the segment safety response field. Specifically, when the segment speed representative value is greater than zero, the remaining available distance of the segment is divided by the segment speed representative value to obtain the basic available time of the segment; when the segment safety response field records braking capability parameters, the segment speed representative value is divided by the braking capability parameters to obtain braking time, and the basic available time of the segment is subtracted from the braking time to obtain the available response time of the segment; when the segment safety response field does not record braking capability parameters, the basic available time of the segment is written into the available response time of the segment, and a braking parameter missing mark is written into the segment quality mark; when the segment speed representative value is zero, the available response time of the segment is written as the response waiting time, which is taken as the segment duration, and a stationary segment mark is written into the segment quality mark. Subsequently, the segment speed representative value, segment acceleration representative value, segment heading change, remaining available distance of the segment, and available response time of the segment are written under the same task segment number to obtain the segment motion response parameters.

[0153] The segment motion response parameters determine the available time and distance for safe response within the same task segment. Under this time and distance caliber, link recovery response parameters are integrated based on the segment motion response parameters to obtain segment response process data. Specifically, using the task segment number, available response time, and remaining available distance in the segment motion response parameters as integration indexes, the segment link objects, segment link state sequences, link recovery states, communication interruption states, segment safe response fields, and segment quality markers under the same task segment number in the task fragmentation test dataset are read. Link recovery time parameters, response time parameters, and parallel overlap coefficients are then generated based on the communication interruption state, link recovery state, and segment safe response fields.

[0154] For each link type within the same task segment, the communication interruption state and link recovery state are scanned according to the relative test time order. When the communication interruption state changes from interruption to non-interruption state, and the link recovery state is marked as recovery completion, the sampling point is taken as the link recovery completion point. The starting sampling point that is continuously in the communication interruption state or the link missing sampling state is searched backward, and this starting sampling point is taken as the link degradation start point. The time difference between the link recovery completion point and the link degradation start point is written into the link recovery time sample. If there are multiple link recovery time samples within the same task segment, the expected value of the link recovery time and the standard deviation of the link recovery time are calculated. If there are insufficient link recovery time samples, the link recovery time samples are read from the historical test records under the same test route, the same link type, and the same task segment type, and a historical sample supplement mark is written into the segment quality mark. If there are still no usable samples in the historical test records, the link recovery time requirement recorded for this link type in the task communication constraints is taken as the expected value of the link recovery time, and the standard deviation of the link recovery time is taken as one-tenth of the expected value of the link recovery time, and a link recovery sample missing mark is written into the segment quality mark.

[0155] The response type of a task segment is identified by analyzing its safety response field. Specifically, if the safety response field contains a remote takeover requirement, the segment is marked as a remote takeover response type; if it contains a local degradation requirement, it is marked as a safety degradation response type; and if it contains a parking distance or parking time requirement, it is marked as a safe parking response type. If the same task segment matches multiple response types, the response type with the highest safety response constraint level is selected as the segment response type according to the task evaluation criteria in the test task configuration data.

[0156] The response closure time requirement is read from the segment security response field based on the segment response type, and the response time parameter is generated by combining it with the response log in the test record. When calculating the response time parameter in the response log, the trigger event time and confirmation event time within the same task segment are read according to the task segment number. When both the trigger event time and confirmation event time exist, the trigger event time is subtracted from the confirmation event time to obtain the response time sample. When the trigger event time exists but the confirmation event time does not exist, the sample is written to the unclosed-loop response flag. When the trigger event time is missing, the task segment is written to the missing flag in the response log. For the remote takeover response type, the trigger event time is the time when the remote takeover request is issued, and the confirmation event time is the time when the takeover command is confirmed. For the security degradation response type, the trigger event time is the degradation trigger time, and the confirmation event time is the degradation status confirmation time. For the security stop response type, the trigger event time is the stop trigger time, and the confirmation event time is the stop status confirmation time. If multiple response time samples exist within the same task segment, the expected response time and standard deviation of the response time are calculated. If a response time sample is missing, the expected response time is generated based on the response closed-loop time requirement in the test task configuration data, and the standard deviation of the response time is set to one-twentieth of the expected response time. A missing response log flag is then written into the segment quality flag. When a missing response log flag exists in the segment quality flag, the segment security response constraint result corresponding to that task segment is not deleted. Instead, the task segment is added to the segment to be reviewed and marked according to the impact of data review during the subsequent test risk assessment phase.

[0157] After the link recovery time and response time parameters are determined, the parallel overlap coefficient is determined based on the segment response type. The parallel overlap coefficient represents the proportion of time overlap allowed between the link recovery process and the response process; the parallel overlap coefficient for the remote takeover response type is 0 to 0.2, for the safety degradation response type it is 0.5 to 0.8, and for the safety stop response type it is 0.3 to 0.6. The specific values ​​are determined by the vehicle control architecture field and task evaluation criteria in the test task configuration data; when the test task configuration data does not record the parallel overlap coefficient, the value is 0.1 for the remote takeover response type, 0.7 for the safety degradation response type, and 0.5 for the safety stop response type. Subsequently, the available response time of the segment, the expected value of the link recovery time, the standard deviation of the link recovery time, the expected value of the response time, the standard deviation of the response time, the parallel overlap coefficient, and the segment quality label are written under the same task segment number to obtain the segment response process data.

[0158] The segment response process data has organized the vehicle motion state, link recovery state, and response closed-loop state under the same task segment number; under this data caliber, the segment response process data is used to calculate the safety response constraint through the response margin algorithm to obtain the segment safety response constraint result.

[0159] The aforementioned response margin algorithm refers to an algorithm used for calculating security response constraints. This algorithm takes fragment response process data as input, reading the fragment's available response time, expected link recovery time, standard deviation of link recovery time, expected response time, standard deviation of response time, and parallel overlap coefficient. It first calculates the equivalent response consumption time after the link recovery process and response process are coupled in parallel, and then combines the standard deviation of link recovery time, standard deviation of response time, and security confidence coefficient to calculate the fragment's security response margin. This algorithm is used to generate fragment security response constraint results, enabling test risk assessment to be calculated according to the link recovery status and response time constraints within the task fragment.

[0160] First, calculate the equivalent response time after the link recovery process and the response process are coupled in parallel. The specific formula is as follows: ,

[0161] in, This represents the equivalent response time for the j-th task segment; This represents the expected link recovery time for the j-th task segment; This represents the expected response time for the j-th task segment; This represents the parallel overlap coefficient corresponding to the j-th task segment; This means taking the smaller of the two values ​​within the parentheses.

[0162] After obtaining the equivalent response time, the available response time of the segment, the equivalent response time, the standard deviation of the link recovery time, and the standard deviation of the response time are written into the same margin calculation caliber to calculate the segment security response margin. The specific formula is as follows: ,

[0163] in, This represents the segment security response margin corresponding to the j-th task segment; This represents the available response time for the segment corresponding to the j-th task segment; This represents the safety confidence coefficient, the value of which is determined based on the confidence requirement in the test task configuration data. For example, when the confidence requirement is 95%,... Take 1.96; This represents the standard deviation of the link recovery time corresponding to the j-th task segment; This represents the standard deviation of the response time corresponding to the j-th task segment.

[0164] Among them, when the fragment safety response margin When the safety response margin is greater than or equal to the threshold, the task segment is marked as a safety response satisfied segment; when the segment's safety response margin is greater than or equal to the threshold, the task segment is marked as a safety response satisfied segment. If the safety response margin is less than the safety response satisfaction threshold and greater than or equal to the safety response critical threshold, the task segment is marked as a safety response critical segment; when the segment's safety response margin... If the threshold for a safe response is less than the required threshold, the task segment is marked as a segment where the safe response is not met.

[0165] The security response satisfaction threshold and the security response critical threshold are determined by the security response constraint field in the test task configuration data. When the security response constraint field does not record the above thresholds, the security response satisfaction threshold is 0, and the security response critical threshold is the time value corresponding to a negative sampling period, denoted as... ,in The sampling period.

[0166] The fragment available response time, equivalent response consumption time, fragment safety response margin, safety response flag, fragment response type, parallel overlap coefficient, expected link recovery time, standard deviation of link recovery time, expected response time, standard deviation of response time, and fragment quality flag are written under the same task fragment number to obtain the fragment safety response constraint results.

[0167] In one embodiment, the response margin algorithm further includes:

[0168] In a wireless signal test scenario for unmanned vehicles in a port container yard, the vehicle-to-cloud link experienced continuous interruptions after the unmanned vehicle entered the gantry obstruction area, resulting in a delay in the recovery of the remote monitoring link, while the vehicle remained in a low-speed passage state. The system has divided this process into gantry obstruction passage segments through task fragmentation processing, and bound the segment vehicle motion state, segment link state sequence, and segment safety response fields to each task segment.

[0169] The safety response constraint module first calculates the available response time for the vehicle to complete the response before reaching the response constraint position from the current segment's starting position, based on the vehicle speed, route mileage, and response constraint position within the task segment. Then, the module identifies the link interruption start point and link recovery completion point from the segment link state sequence to obtain the link recovery time; it then reads the remote takeover request issuance time and takeover command confirmation time from the response log to obtain the response time. Thus, the link recovery time, response time, and available response time for the segment are written under the same task segment number.

[0170] When the task segment is a remote takeover response, the parallel overlap coefficient between the link recovery process and the takeover response process takes a lower value, indicating that remote takeover requires link recovery to form an effective closed loop. When the task segment is a local safety degradation response, the parallel overlap coefficient takes a higher value, indicating that the vehicle's local degradation response can still be synchronously entered into the execution record during the link recovery process. The response margin algorithm calculates the equivalent response consumption time accordingly and generates the segment safety response margin by combining the standard deviation of the link recovery time and the standard deviation of the response time.

[0171] For example, in the same gantry obstruction passage segment, if the link recovery time is long and the parallel overlap coefficient corresponding to the remote takeover response type is low, the equivalent response consumption time is close to the sum of the link recovery time and the response time, and the segment's safety response margin decreases accordingly. If the segment corresponds to the local safety degradation response type, and the response log shows that the local degradation response can be completed synchronously during link recovery, then the parallel overlap portion is included in the response margin calculation, and the equivalent response consumption time is reduced accordingly. Through this processing, the segment safety response constraint results can distinguish the different constraint calibers in response time for remote takeover segments, local safety degradation segments, and safe parking segments, and write the segment safety response margin, safety response flag, and segment response type under the same task segment number for subsequent test risk assessment.

[0172] In a wireless signal test scenario for unmanned mining trucks in a mining area, the trucks travel from the loading area to the unloading area via a climbing channel, following a test route. At the curve of the climbing channel, a drop in vehicle-to-cloud link signal and a delay in remote monitoring link recovery occur. The system divides the process of navigating the climbing channel and curve into independent task segments through task fragmentation processing, and binds the segment's vehicle motion state, link state sequence, and safety response field to each task segment. When the task segment corresponds to a safe stopping response type, the response margin algorithm writes the time difference between the stopping trigger time and the stopping state confirmation time into the response time sample, and the time difference between the link interruption start point and the link recovery completion point into the link recovery time sample. It then calculates the equivalent response consumption time according to the parallel overlap coefficient corresponding to the safe stopping response type, obtaining the segment's safety response margin for the climbing channel and curve navigating segment.

[0173] In a wireless signal test scenario for an unmanned shuttle bus in an airport shuttle area, the unmanned shuttle bus performs remote monitoring and vehicle-to-cloud scheduling tasks on the connecting corridor between the remote gate and the terminal building. When the shuttle bus enters an obstructed section of the corridor, the vehicle-to-cloud link experiences a brief interruption, while the roadside vehicle-to-infrastructure (V2I) link remains normal. The system divides the process of passing through the obstructed corridor into independent task segments. When a task segment corresponds to a local security degradation response type, the response margin algorithm writes the time difference between the local degradation trigger time and the degradation status confirmation time into the response time sample, and calculates the equivalent response consumption time according to the parallel overlap coefficient corresponding to the local security degradation response type, so that the task segment can form an effective segment security response margin while the link is still in the recovery process.

[0174] Based on the segment security response constraint results, a test risk assessment is performed on the continuity margin of the wireless signal to obtain the segment wireless signal test evaluation results.

[0175] The test result encapsulation refers to the process of collecting, classifying, and summarizing the test evaluation results of the wireless signals of each task segment under the same test task. Specifically, the test evaluation results of the wireless signals of each task segment are read according to the test task number, and a list of test-passed segments, a list of test-critical segments, and a list of test-high-risk segments are formed according to the test evaluation level. At the same time, the main influencing links, the location of the risk, the type of task impact, the type of takeover risk, and the data verification mark are sorted out to obtain the wireless signal test results of the autonomous vehicle.

[0176] The wireless signal test results for autonomous vehicles refer to the final test output records corresponding to the same test task. These results use the test task number as the primary index and include at least the overall test level, a list of passed wireless signal test segments, a list of critical wireless signal test segments, a list of high-risk wireless signal test segments, the main influencing links, the location of the risk, the task impact type, the takeover risk type, and data verification markers. These results characterize the wireless signal test evaluation of autonomous vehicles across different task segments within the test route.

[0177] The aforementioned test risk assessment refers to the process of reducing the continuity margin of wireless signals, converting risk levels, marking task impacts, and marking takeover risks based on the segment security response constraint results. Specifically, the continuity margin of wireless signals under the same task segment is first correlated with the segment security response constraint results. Then, the continuity margin of wireless signals is reduced based on the insufficient security response, resulting in a segment risk margin. Subsequently, a segment risk level is generated based on the segment risk margin, along with task impact marking and takeover risk marking results. This assessment is used to obtain the segment wireless signal test evaluation results.

[0178] The aforementioned segment wireless signal test evaluation result refers to the wireless signal test evaluation record formed for a single task segment. This result must at least record the test task number, task segment number, test evaluation level, task impact type, takeover risk type, primary affected link, secondary link type, risk occurrence time range, risk occurrence location range, and data verification mark. This result is used for test result encapsulation.

[0179] Based on the segment security response constraint results, the wireless signal continuity margin is reduced and compared to obtain the segment wireless signal risk assessment result. Specifically, the test task number, task segment number, wireless signal continuity margin, continuity flag, critical link set, link type involved in the calculation, and segment quality flag are read from the wireless signal continuity margin; simultaneously, the test task number, task segment number, segment security response margin, security response flag, segment response type, available response time, equivalent response consumption time, and segment quality flag are read from the segment security response constraint results.

[0180] Using the test task number and task segment number as joint matching fields, the wireless signal continuity margin and segment security response constraint results are correlated within the same task segment. When the correlation is successful, the wireless signal continuity margin and segment security response constraint results are written into the same segment risk assessment record; when the correlation fails, a risk assessment mismatch mark is written under the corresponding task segment, and the task segment is marked as a segment to be reviewed, without generating a valid segment risk margin.

[0181] The wireless signal continuity margin reflects the continuity slack of the wireless link within a task segment, while the segment security response constraint result reflects the time slack available for security response within that task segment. After both are associated with the same task segment, a security response reduction calculation is performed on the wireless signal continuity margin to obtain the segment risk margin. Specifically, the segment security response margin, the segment available response time, and the security response satisfaction threshold are read. When the segment security response margin is lower than the security response satisfaction threshold, a security response deficiency is calculated; when the segment security response margin is greater than or equal to the security response satisfaction threshold, the security response deficiency is set to zero. Subsequently, the security response deficiency is normalized according to the segment available response time, and the wireless signal continuity margin is reduced according to the security response reduction coefficient corresponding to the segment response type to obtain the segment risk margin. The security response reduction calculation uses the following formula: ,

[0182] in, This represents the segment risk margin corresponding to the j-th task segment; This represents the wireless signal continuity margin corresponding to the j-th task segment; This represents the security response reduction factor corresponding to the j-th task segment; This indicates that the security response corresponding to the j-th task segment meets the threshold; This represents the segment security response margin corresponding to the j-th task segment; This represents the available response time for the segment corresponding to the j-th task segment; This represents the zero-prevention constant, whose value is the time value corresponding to the sampling period.

[0183] The security response reduction factor The value is determined based on the segment response type: Remote takeover response type: value range 0.8 to 1.2, default value 1.0; Safety degradation response type: value range 0.6 to 1.0, default value 0.8; Safety shutdown response type: value range 0.5 to 0.9, default value 0.7. When the task evaluation caliber specifies a safety response reduction level, the upper limit, default value, and lower limit of the corresponding range are used for high, medium, and low, respectively; otherwise, the default value is used.

[0184] After the segment risk margin is determined, the risk assessment object is transformed from a single continuity margin into a segment-level risk quantity that simultaneously includes wireless link continuity and security response constraints. Based on this segment-level risk quantity, the segment risk margin is converted into a risk level to obtain the segment risk level. Specifically, the risk level conversion threshold in the test task configuration data is read, and the segment risk margin is compared with the risk level conversion threshold. When the segment risk margin is greater than or equal to the risk satisfaction threshold, the corresponding task segment is marked as a low-risk segment; when the segment risk margin is less than the risk satisfaction threshold but greater than or equal to the risk critical threshold, the corresponding task segment is marked as a critical risk segment; when the segment risk margin is less than the risk critical threshold, the corresponding task segment is marked as a high-risk segment. The risk satisfaction threshold and the risk critical threshold are determined by the task evaluation caliber in the test task configuration data. When the test task configuration data does not record the above thresholds, the risk satisfaction threshold is 0, and the risk critical threshold is the time value corresponding to twice the negative sampling period, denoted as . .

[0185] The risk level of the segments is marked with task impact to obtain task impact marking results. Specifically, the task type, vehicle motion status, critical link set, link types involved in the calculation, continuity marker, and safety response marker are read. When the segment risk level is low-risk, the task impact marking result is written as "task impact not triggered". When the segment risk level is critical-risk and the link types involved in the calculation belong to the critical link set, the task impact marking result is written as "critical impact of critical link". When the segment risk level is critical-risk and the link types involved in the calculation do not belong to the critical link set, the task impact marking result is written as "critical impact of auxiliary link". When the segment risk level is high-risk, the task impact marking result is written as "high-risk impact of task segment". For task segments with risk assessment missing markers, link missing markers, or safety response log missing markers, the task impact marking result is written as "data review impact".

[0186] The segment risk level is assigned a takeover risk label to obtain the takeover risk labeling result. Specifically, the segment response type, segment safety response margin, safety response label, and segment risk level are read. When the segment response type is a remote takeover response type and the segment risk level is a high-risk segment, the takeover risk labeling result is written as "remote takeover high risk." When the segment response type is a remote takeover response type and the segment risk level is a critical risk segment, the takeover risk labeling result is written as "remote takeover critical risk." When the segment response type is a safety degradation response type or a safety shutdown response type and the segment risk level is a high-risk segment, the takeover risk labeling result is written as "safety response high risk." When the segment risk level is a low-risk segment, the takeover risk labeling result is written as "takeover risk not triggered." For task segments whose safety response label is "safety response does not meet the requirements," the takeover risk labeling result is written as at least a critical risk level or higher.

[0187] After the segment risk level, task impact marking result, and takeover risk marking result are formed, the above results are merged under the same task segment to obtain the segment radio signal risk assessment result. Specifically, using the test task number and task segment number as a joint index, the segment risk margin, segment risk level, task impact marking result, takeover risk marking result, radio signal continuity margin, segment security response margin, continuity mark, security response mark, and segment quality mark are written into the same risk assessment record. When there are multiple link types participating in the calculation within the same task segment, the main influencing link is determined based on the critical link set, the link types participating in the calculation, the continuity mark, and the segment quality mark, and the remaining link types participating in the calculation are written into the auxiliary link field to obtain the segment radio signal risk assessment result.

[0188] The segment wireless signal risk assessment results are marked with task impact information to obtain segment wireless signal test evaluation results. Specifically, the segment risk level, task impact marking results, takeover risk marking results, main impact links, secondary link fields, and segment quality markings are read from the segment wireless signal risk assessment results. The segment task type, segment vehicle motion state, segment link object, segment start time, segment end time, segment start position, and segment end position are read from the task fragmented test dataset to generate segment test evaluation fields. These segment test evaluation fields include test evaluation level, task impact type, takeover risk type, main impact links, secondary link types, risk occurrence time range, risk occurrence location range, and data verification markings.

[0189] When a segment's risk level is low, the test evaluation level is written as "Wireless signal test passed"; when the segment's risk level is critical, the test evaluation level is written as "Wireless signal test critical"; when the segment's risk level is high, the test evaluation level is written as "Wireless signal test high risk". The task impact marking result is written to the task impact type, the takeover risk marking result is written to the takeover risk type, the main affected link is written to the main affected link field, the segment start time and end time are written to the risk occurrence time range, and the segment start position and end position are written to the risk occurrence position range. When there are missing risk assessment markers, missing link sampling markers, or missing security response log markers in the segment quality marking, the data verification marker is written to the segment test evaluation field. Subsequently, the segment test evaluation field is bound to the corresponding test task number and task segment number to obtain the segment wireless signal test evaluation result.

[0190] The test results of the wireless signal segment test evaluation are packaged to obtain the wireless signal test results of the autonomous vehicle.

[0191] When encapsulating the test results of the wireless signal segment test evaluation results, the test evaluation level, task impact type, takeover risk type, main affected link, risk occurrence time range, risk occurrence location range, and data verification mark corresponding to each task segment under the same test task number are read and organized according to the time order of the task segment number to form a segment evaluation result set.

[0192] After forming the fragment evaluation result set, each task fragment is classified according to the test evaluation level. The task fragments that pass the wireless signal test, the task fragments that are critical to the wireless signal test, and the task fragments that are high risk of the wireless signal test are written into the corresponding fragment list respectively. For task fragments with data verification marks, the data verification marks are retained in the corresponding fragment list and written into the verification prompt field.

[0193] Subsequently, by combining the main influencing links, risk location ranges, and task impact types from the segment evaluation result set, summary fields at the test task level are generated. Specifically, the link types that appear more than or equal to the summary condition threshold in high-risk or critical segments are written into the main influencing link field; the summary condition threshold is determined by the task evaluation criteria in the test task configuration data, and if not recorded, it is taken as one-third of the total number of high-risk and critical segments under that test task, rounded up; the corresponding road segments, regional affiliation, or route mileage range are written into the risk location field; and the corresponding task impact type and takeover risk type are written into the task impact field and takeover risk field.

[0194] After completing the above sorting, the test task number, test route number, test start time, test end time, list of various segments, main influencing links, risk occurrence location, task impact type, takeover risk type, and data verification mark are written into the same test result record to obtain the wireless signal test results of the autonomous vehicle.

[0195] The wireless signal test results for autonomous vehicles use the test task number as the primary index to characterize the wireless signal test evaluation of each task segment under that test task. It includes at least the overall test level, a list of passed wireless signal test segments, a list of critical wireless signal test segments, a list of high-risk wireless signal test segments, the main influencing links, the location of the risk, the task impact type, the takeover risk type, and a data verification mark. The overall level is determined according to the highest risk level among all task segments; when there are high-risk wireless signal test segments, the overall level is written as "high-risk test"; when there are no high-risk wireless signal test segments but there are critical wireless signal test segments, the overall level is written as "critical test"; when all task segments pass the wireless signal test and there is no data verification mark, the overall level is written as "passed test"; when there is a data verification mark, the verification mark is written after the corresponding overall level.

[0196] Combination Figure 3 The figure shows a comparison of the wireless signal testing method and system for autonomous vehicles with existing technologies. The black bars represent the technical effects of the present invention, while the gray bars represent existing technologies. Figure 3 It can be seen that the present invention is superior to the prior art to a certain extent.

[0197] Example 2, a wireless signal testing system for an unmanned vehicle based on Example 1, is described below:

[0198] The test data normalization module is used to acquire the basic test data of autonomous vehicles and normalize the test caliber to obtain the wireless signal test input set.

[0199] Specifically, the test data normalization module accesses vehicle operation data collection records, wireless communication data collection records, test area records, and test task records, and performs access verification according to the test task number, vehicle number, collection time, link type, and data source number. For records with complete fields, the record is written to the original test record set; for records with missing fields, the record is written to the exception temporary storage area along with the exception reason field. Subsequently, the test data normalization module uses the test start time as the zero point, converts the vehicle timestamp, communication timestamp, and task configuration time into relative test times, and generates continuous test time slices according to the sampling period. Then, it converts the vehicle location, test route coordinates, area boundary coordinates, and wireless coverage device location to the same test area coordinate system, converts the communication source in the wireless communication data collection records into a link type field, and attaches the test segment type, link evaluation object, task evaluation caliber, and safety response constraint fields to the corresponding test time slices, thereby obtaining the wireless signal test input set.

[0200] The task fragmentation module is used to perform task fragmentation processing on the wireless signal test input set to obtain a task fragmentation test dataset.

[0201] Specifically, the task fragmentation module performs time-slice alignment and test field reorganization on the wireless signal test input set to form a test process record. Subsequently, it calculates the segment boundaries of the test process record using a task scenario link three-axis cooperative boundary response algorithm to obtain the task segment index. In the segment boundary calculation, this module performs task state transition detection, runtime scenario boundary detection, and communication link event detection on the test process record to obtain the intensity of task state changes, scenario changes, and link changes. Based on these three intensity levels, it calculates the cooperative boundary response to generate the results. The cooperative boundary response results are then filtered for boundaries and numbered as continuous intervals to obtain the task segment index. The task fragmentation module then segments the test process record according to the task segment index and attaches segment attributes, binding the segment task type, segment vehicle motion state, segment link object, segment safety response field, and segment quality marker to the task segment number to obtain the task fragmentation test dataset.

[0202] The signal continuity evaluation module is used to perform multi-link signal continuity evaluation on the task fragmentation test dataset to obtain the wireless signal continuity margin.

[0203] Specifically, the signal continuity evaluation module performs segment link timing normalization on the task fragmented test dataset, generating basic segment signal evaluation data according to task segment number, test relative time, and link type. Subsequently, the module identifies multi-link continuous degradation windows within the basic segment signal evaluation data, dividing the segment link window sequence according to the segment evaluation time axis, and statistically analyzing communication quality change parameters, communication interruption duration parameters, and communication recovery time parameters within each segment link window. The window-level statistical results are then weighted and merged according to task segment number and link type to obtain the segment link continuity characterization results. Based on the task communication constraints in the basic segment signal evaluation data, the module performs margin conversion on the segment link continuity characterization results using a degradation persistence attenuation margin algorithm to obtain the wireless signal continuity margin. This margin conversion includes task attribute encoding, task link dependency matching, link quality direction unification, continuous degradation ratio calculation, and critical link joint degradation penalty calculation.

[0204] The security response constraint module is used to extract security response constraints from the task fragmentation test dataset to obtain fragment security response constraint results.

[0205] Specifically, the safety response constraint module performs vehicle motion state conversion on the task fragmentation test dataset, merging vehicle speed, vehicle acceleration, vehicle heading angle change, and route mileage change according to the task fragment number to obtain fragment motion response parameters. This module then integrates link recovery response parameters based on these fragment motion response parameters, using the task fragment number, fragment available response time, and remaining available distance as integration indices. It reads the link recovery status, communication interruption status, and fragment safety response fields for the same task fragment, generating link recovery time parameters, response time parameters, and parallel overlap coefficients to obtain fragment response process data. Subsequently, the safety response constraint module performs safety response constraint calculations on the fragment response process data using a response margin algorithm that is parallelly coupled to the link recovery response process, obtaining the fragment safety response constraint results.

[0206] The test risk assessment module is used to assess the test risk of the wireless signal continuity margin based on the segment security response constraint results, and obtain the segment wireless signal test assessment results.

[0207] Specifically, the test risk assessment module uses the test task number and task segment number as joint matching fields to associate the wireless signal continuity margin and segment security response constraint results within the same task segment. After successful association, the module performs security response reduction calculations on the wireless signal continuity margin based on the segment security response constraint results to obtain the segment risk margin. The test risk assessment module then performs risk level conversion on the segment risk margin to obtain the segment risk level. Next, it applies task impact marking and takeover risk marking to the segment risk level, obtaining task impact marking results and takeover risk marking results. Subsequently, the segment risk level, task impact marking results, and takeover risk marking results are merged within the same task segment to obtain the segment wireless signal risk determination result. The test risk assessment module applies task impact marking at the test assessment layer to the segment wireless signal risk determination result, writing the test assessment level, task impact type, takeover risk type, main affected link, risk occurrence time range, risk occurrence location range, and data verification mark into the segment test assessment field to obtain the segment wireless signal test assessment result.

[0208] The test result encapsulation module is used to encapsulate the test results of the wireless signal segment test evaluation to obtain the wireless signal test results of the autonomous vehicle.

[0209] Specifically, the test result encapsulation module reads the wireless signal test evaluation results corresponding to each task segment under the same test task number, and organizes them into a segment evaluation result set according to the time order of the task segment number. Then, it categorizes each task segment according to the test evaluation level, forming a list of wireless signal test-passing segments, a list of wireless signal test-critical segments, and a list of wireless signal test-high-risk segments. The test result encapsulation module combines the main influencing links, risk location range, task impact type, and takeover risk type from the segment evaluation result set to generate the main influencing links, risk location, task impact type, and takeover risk type at the test task level. These fields, along with the test task number, test route number, test start time, test end time, and data verification mark, are written into the same test result record to obtain the wireless signal test results for the autonomous vehicle.

[0210] In this embodiment, each module can be executed by the same processor, or it can be deployed in an on-board test terminal, a roadside test terminal, or a test server to execute collaboratively. The modules maintain data association through test task number, task segment number, test relative time, and link type, so that the test results of the autonomous vehicle wireless signal output by the system can be mapped to specific task segments, specific link types, and specific risk locations.

[0211] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for testing wireless signals of an unmanned vehicle, characterized in that, include: Acquire basic test data for autonomous vehicles and normalize the test caliber to obtain the wireless signal test input set; The wireless signal test input set is processed into task fragmentation to obtain a task fragmentation test dataset; Multi-link signal continuity evaluation is performed on the fragmented test dataset of the task to obtain the wireless signal continuity margin; Security response constraints are extracted from the fragmented test dataset of the task to obtain the fragment security response constraint results; Based on the segment security response constraint results, the test risk assessment of the wireless signal continuity margin is performed to obtain the segment wireless signal test evaluation results. The test results of the wireless signal segment test evaluation are packaged to obtain the wireless signal test results of the autonomous vehicle.

2. The wireless signal testing method for unmanned vehicles according to claim 1, characterized in that, The wireless signal test input set is processed into task fragmentation to obtain a task fragmentation test dataset, including: Time-slice alignment is performed on the wireless signal test input set to obtain a time-slice aligned record; The test fields of the time-slice aligned records are reorganized to obtain the test process records; The test process records are used to calculate segment boundaries to obtain task segment indexes; The test process record is segmented according to the task segment index to obtain segment test records; By attaching fragment attributes to the fragment test records, a task fragmented test dataset is obtained.

3. The wireless signal testing method for unmanned vehicles according to claim 2, characterized in that, The test process records are used to calculate segment boundaries to obtain task segment indexes, including: The task state transition detection is performed on the test process record to obtain the intensity of task state change; The test process records are used to perform scene boundary detection to obtain the scene change intensity; The test process records are used to detect communication link events and obtain the intensity of link changes. Based on the intensity of task state change, scene change, and link change, the collaborative boundary response is calculated using the task-scene-link three-axis collaborative boundary response algorithm to obtain the collaborative boundary response result. The collaborative boundary response results are subjected to boundary filtering to obtain valid task segment boundary points; The boundary points of the valid task segments are numbered consecutively to obtain the task segment index.

4. The wireless signal testing method for unmanned vehicles according to claim 1, characterized in that, The multi-link signal continuity is evaluated on the fragmented test dataset of the task to obtain the wireless signal continuity margin, including: The fragmented test dataset of the task is subjected to fragment link timing normalization to obtain basic data for fragment signal evaluation; Multi-link continuous degradation window identification is performed on the basic data for evaluating the segment signal to obtain the segment link continuity characterization results; Based on the task communication constraints in the basic data for evaluating the segment signals, the margin conversion of the segment link continuity characterization results is performed to obtain the wireless signal continuity margin.

5. The wireless signal testing method for unmanned vehicles according to claim 4, characterized in that, Multi-link continuous degradation window identification is performed on the basic data for evaluating the segment signal to obtain segment link continuity characterization results, including: The basic data for evaluating the segment signal are divided into multi-link time windows to obtain a segment link window sequence; The communication quality change statistics are performed on the fragment link window sequence to obtain the communication quality change parameters; The communication interruption duration is statistically analyzed for the fragment link window sequence to obtain the communication interruption duration parameter; The communication recovery time is statistically analyzed for the segment link window sequence to obtain the communication recovery time parameter; The link weights of the communication quality change parameters, communication interruption duration parameters, and communication recovery time parameters are merged to obtain the segment link continuity characterization results.

6. The wireless signal testing method for unmanned vehicles according to claim 4, characterized in that, Based on the task communication constraints in the basic data for evaluating the segment signals, the margin conversion of the segment link continuity characterization results is performed to obtain the wireless signal continuity margin, including: Task attribute encoding is performed on the basic data for evaluating the segment signal to obtain the segment task attribute encoding result; Based on the segment task attribute encoding results, task link dependency matching is performed to obtain the segment communication requirement benchmark; Based on the segment communication requirement benchmark, the link quality direction is unified for the segment link continuity characterization results to obtain the direction-unified link quality results; The continuous degradation ratio of the unified link quality results in the aforementioned direction is calculated to obtain the segment link degradation characterization results. The degradation characterization results of the aforementioned link segments are converted into a margin using a degradation persistence attenuation margin algorithm to obtain the wireless signal continuity margin.

7. The wireless signal testing method for unmanned vehicles according to claim 1, characterized in that, The security response constraints of the fragmented test dataset are extracted to obtain the fragment security response constraint results, including: The vehicle motion state is converted into the fragmented test dataset of the task to obtain the fragmented motion response parameters; Based on the segment motion response parameters, the link recovery response parameters are integrated to obtain segment response process data; The response margin algorithm is used to calculate the safety response constraints of the fragment response process data to obtain the fragment safety response constraint results.

8. The wireless signal testing method for unmanned vehicles according to claim 1, characterized in that, Based on the segment security response constraint results, a test risk assessment is performed on the continuity margin of the wireless signal to obtain the segment wireless signal test evaluation results, including: Based on the segment security response constraint results, the continuity margin of the wireless signal is reduced and compared to obtain the segment wireless signal risk assessment result; The risk assessment results of the wireless signal segment are marked with task impact to obtain the test evaluation results of the wireless signal segment.

9. The wireless signal testing method for unmanned vehicles according to claim 8, characterized in that, Based on the segment security response constraint results, the continuity margin of the wireless signal is reduced and compared to obtain the segment wireless signal risk assessment result, including: Based on the segment security response constraint results, the wireless signal continuity margin is calculated by security response reduction to obtain the segment risk margin; The risk margin of the segment is converted into a risk level to obtain the segment risk level; The risk level of the segment is marked with task impact to obtain the task impact marking result; The risk level of the segment is assigned a takeover risk label to obtain the takeover risk labeling result; The risk levels, task impact marking results, and takeover risk marking results of the segments are merged under the same task segment to obtain the segment wireless signal risk determination result.

10. A wireless signal testing system for an unmanned vehicle, characterized in that, include: The test data normalization module is used to acquire the basic test data of autonomous vehicles and normalize the test caliber to obtain the wireless signal test input set. The task fragmentation module is used to perform task fragmentation processing on the wireless signal test input set to obtain a task fragmentation test dataset. The signal continuity evaluation module is used to perform multi-link signal continuity evaluation on the task fragmentation test dataset to obtain the wireless signal continuity margin. The security response constraint module is used to extract security response constraints from the task fragmentation test dataset to obtain fragment security response constraint results. The test risk assessment module is used to assess the test risk of the wireless signal continuity margin based on the segment security response constraint results, and obtain the segment wireless signal test assessment results. The test result encapsulation module is used to encapsulate the test results of the wireless signal segment test evaluation to obtain the wireless signal test results of the autonomous vehicle.

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