Traffic event detection capability test method, device and system and storage medium

Abstract

The invention discloses a traffic event detection capability testing method, which is used for saving human resource cost and improving the stability and consistency of an evaluation result, and comprises the following steps: obtaining historical detection data of a platform on a traffic event; judging whether the event detection capability of the platform is normal or not according to the historical detection data; when the event detection capability of the platform is normal, determining the score of at least one detection index according to the historical detection data of the traffic event; determining an overall detection capability score of the platform according to the score of the at least one detection index; and when the total detection capability score of the platform is smaller than a preset score, determining that the detection capability of the platform is unqualified. By adopting the scheme provided by the invention, the automatic evaluation of the detection capability is realized, the human resource cost is saved, and the stability and consistency of the evaluation result are also improved.

Description

Technical Field

[0001] The present application relates to the technical field of traffic incident detection, and in particular to a method, device, system and storage medium for testing traffic incident detection capability. Background Art

[0002] In the autonomous driving industry, testing of roadside traffic incident detection capabilities is a daily basic work. In the process of testing a large number of roadside traffic incidents, how to quickly evaluate the traffic incident detection capabilities and analyze the results is becoming increasingly important. In the prior art, the evaluation of the platform's traffic incident detection capabilities is usually performed manually, which not only consumes a lot of human resource costs, but is also affected by the subjectivity of the evaluators, and the stability and consistency of the evaluation results are poor.

[0003] Therefore, how to provide a traffic incident detection capability testing method to save human resource costs and improve the stability and consistency of evaluation results is a technical problem that needs to be solved urgently. Summary of the invention

[0004] This application provides a traffic incident detection capability testing method to save human resource costs and improve the stability and consistency of evaluation results, including:

[0005] Obtain the platform’s historical detection data on traffic incidents;

[0006] Determining whether the event detection capability of the platform is normal based on the historical detection data;

[0007] When the event detection capability of the platform is normal, determining a score of at least one detection indicator based on the historical detection data of the traffic event;

[0008] Determining an overall detection capability score of the platform based on the score of at least one detection metric;

[0009] When the overall detection capability score of the platform is less than the preset score, the platform detection capability is determined to be unqualified.

[0010] The beneficial effect of the present application is that it provides a system for scoring the platform detection capability based on historical detection data, thereby realizing automatic evaluation of the detection capability, saving human resource costs, and because a fixed evaluation method is formulated, the stability and consistency of the evaluation results can also be improved. In addition, compared with the manual evaluation method, this automatic evaluation method can also improve the efficiency of the evaluation.

[0011] In one embodiment, the acquisition of historical detection data of traffic events by the platform includes:

[0012] Obtain the platform's historical detection data for at least one of the following traffic events:

[0013] Speeding incidents, underspeed incidents, and congestion incidents.

[0014] In one embodiment, determining the score of at least one detection indicator based on the historical detection data of the traffic event includes:

[0015] Determine at least one of the following detection indicators based on the historical detection data of the traffic incident:

[0016] The average accuracy of traffic events, system recall, and average detection speed of traffic events;

[0017] The score of at least one detection indicator among the average accuracy rate of the traffic events, the system recall rate and the average detection speed of the traffic events is determined, wherein the indicator value of each detection indicator is positively correlated with the score of each detection indicator.

[0018] In one embodiment, the average accuracy of the traffic events is determined as follows:

[0019] Determine the detection accuracy of various types of traffic events;

[0020] Determine the weights of various traffic events;

[0021] The average accuracy of traffic events is determined according to the detection accuracy of each type of traffic events and the weights of the various types of traffic events.

[0022] In one embodiment, the system recall rate is determined as follows:

[0023] Determining the number of all traffic events successfully detected during a specific period, and the number of all traffic events occurring during the specific period;

[0024] The ratio of the number of all traffic events successfully detected in a specific period to the number of all traffic events occurring in the specific period is determined as the system recall rate.

[0025] In one embodiment, judging whether the event detection capability of the platform is normal according to the historical detection data includes:

[0026] Obtain the overall fluctuation range of the indicator values ​​of various detection indicators;

[0027] When the overall fluctuation range of the indicator values ​​of various detection indicators is less than the preset range, it is determined that the event detection capability of the platform is normal.

[0028] In one embodiment, determining the overall detection capability score of the platform according to the score of at least one detection indicator includes:

[0029] Obtain the weights of various detection indicators;

[0030] Perform weighted summation based on the weights of various test indicators and the scores of each test indicator;

[0031] The summed result is determined as the overall detection capability score of the platform.

[0032] The present application also provides a traffic incident detection capability testing device, comprising:

[0033] The acquisition module is used to obtain the historical detection data of traffic events on the platform;

[0034] A judgment module, used to judge whether the event detection capability of the platform is normal according to the historical detection data;

[0035] A first determination module, configured to determine a score of at least one detection indicator based on historical detection data of the traffic event when the event detection capability of the platform is normal;

[0036] A second determination module, configured to determine an overall detection capability score of the platform based on a score of at least one detection indicator;

[0037] The third determination module is used to determine that the platform detection capability is unqualified when the overall detection capability score of the platform is less than a preset score.

[0038] In one embodiment, the acquisition module includes:

[0039] The first acquisition submodule is used to obtain the historical detection data of the platform for at least one of the following traffic events:

[0040] Speeding incidents, underspeed incidents, and congestion incidents.

[0041] In one embodiment, the first determining module includes:

[0042] The first determination submodule is used to determine at least one of the following detection indicators based on the historical detection data of the traffic event:

[0043] The average accuracy of traffic incidents,systems and the average detection speed of traffic incidents;

[0044] The second determination submodule is used to determine the score of at least one detection indicator among the average accuracy of the traffic event, the system and the average detection speed of the traffic event, wherein the indicator value of each detection indicator is positively correlated with the score of each detection indicator.

[0045] In one embodiment, the average accuracy of the traffic events is determined as follows:

[0046] Determine the detection accuracy of various types of traffic events;

[0047] Determine the weights of various traffic events;

[0048] The average accuracy of traffic events is determined according to the detection accuracy of each type of traffic events and the weights of the various types of traffic events.

[0049] In one embodiment, the system recall rate is determined as follows:

[0050] Determining the number of all traffic events successfully detected during a specific period, and the number of all traffic events occurring during the specific period;

[0051] The ratio of the number of all traffic events successfully detected in a specific period to the number of all traffic events occurring in the specific period is determined as the system recall rate.

[0052] In one embodiment, the judgment module includes:

[0053] The second acquisition submodule is used to obtain the overall fluctuation range of the index values ​​of various detection indicators;

[0054] The third determination submodule is used to determine that the event detection capability of the platform is normal when the overall fluctuation range of the indicator values ​​of various detection indicators is less than a preset range.

[0055] In one embodiment, the second determining module includes:

[0056] The third acquisition submodule is used to obtain the weights of various detection indicators;

[0057] A summation submodule is used to perform weighted summation according to the weights of various detection indicators and the scores of each detection indicator;

[0058] The fourth determination submodule is used to determine the summation result as the overall detection capability score of the platform.

[0059] The present application also provides a traffic incident detection capability testing system, comprising:

[0060] at least one processor; and,

[0061] a memory communicatively connected to the at least one processor; wherein,

[0062] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the traffic event detection capability testing method recorded in any one of the above embodiments.

[0063] The present application also provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor corresponding to the traffic event detection capability test system, the traffic event detection capability test system can implement the traffic event detection capability test method recorded in any of the above embodiments.

[0064] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings.

[0065] The technical solution of the present application is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The accompanying drawings are used to provide a further understanding of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings:

[0067] Figure 1 This is a flow chart of a method for testing traffic incident detection capability in one embodiment of the present application;

[0068] Figure 2 This is a block diagram of a traffic incident detection capability testing device in one embodiment of the present application;

[0069] Figure 3 This is a schematic diagram of the hardware structure of a traffic incident detection capability testing system in one embodiment of the present application. DETAILED DESCRIPTION

[0070] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application.

[0071] Figure 1 Flow chart of a method for testing traffic incident detection capability in one embodiment of the present application. Figure 1 As shown, the method can be implemented as the following steps S101-S105:

[0072] In step S101, the historical detection data of the platform on traffic events is obtained;

[0073] In step S102, judging whether the event detection capability of the platform is normal according to the historical detection data;

[0074] In step S103, when the event detection capability of the platform is normal, a score of at least one detection indicator is determined based on the historical detection data of the traffic event;

[0075] In step S104, the overall detection capability score of the platform is determined according to the score of at least one detection indicator;

[0076] In step S105, when the overall detection capability score of the platform is less than a preset score, it is determined that the platform detection capability is unqualified.

[0077] In this application, the platform's historical detection data on traffic events is obtained; specifically, traffic events may be speeding events, low-speed events, and congestion events.

[0078] The event detection capability of the platform is judged based on the historical detection data. The specific judgment process is as follows:

[0079] The overall fluctuation range of the indicator values ​​of various detection indicators is obtained; when the overall fluctuation range of the indicator values ​​of various detection indicators is less than the preset range, it is determined that the event detection capability of the platform is normal.

[0080] When the event detection capability of the platform is normal, the score of at least one detection indicator is determined based on the historical detection data of the traffic event, specifically:

[0081] The detection index may be an average accuracy rate of traffic events, an average detection speed of the system and traffic events. The score of at least one of the average accuracy rate of traffic events, the average detection speed of the system and traffic events is determined, wherein the index value of each detection index is positively correlated with the score of each detection index.

[0082] The average accuracy of traffic events is determined by: determining the detection accuracy of each type of traffic events; determining the weights of each type of traffic events; and determining the average accuracy of traffic events based on the detection accuracy of each type of traffic events and the weights of the various types of traffic events.

[0083] The system determines the recall rate by: determining the number of all traffic events successfully detected within a specific period, and the number of all traffic events that occurred within the specific period; and determining the ratio of the number of all traffic events successfully detected within a specific period to the number of all traffic events that occurred within the specific period as the system recall rate.

[0084] The overall detection capability score of the platform is determined according to the score of at least one detection indicator. Specifically: the weights of various detection indicators are obtained; a weighted sum is taken according to the weights of various detection indicators and the scores of each detection indicator; and the sum result is determined to be the overall detection capability score of the platform.

[0085] For example, 15 events actually occurred, including 5 speeding events, 5 underspeed events, and 5 congestion events. The system successfully identified 14 events, of which 12 were correctly identified and 2 were incorrectly identified. The 12 correct identifications were: 1. 5 speeding events were correctly identified, 4 underspeed events were correctly identified, and 3 congestion events were correctly identified. Then, the average event detection time was 350 milliseconds, and the following conclusions can be drawn:

[0086] 1. Average accuracy of traffic incidents:

[0087] First, the index values ​​of the accuracy of specific events are as follows: 1. Accuracy of speeding events: 5 / 5=100%; 2. Accuracy of low-speed events: 4 / 5=80%; 3. Accuracy of congestion events: 3 / 5=60%.

[0088] After calculating the index values ​​of these three indicators, the average accuracy score of the traffic event is calculated. Specifically, the accuracy score of a specific traffic event can be calculated first, and then the average accuracy score of the traffic event can be determined according to the weights of various traffic events. For example, according to the above example, the system speeding recognition ability score is 100, the low-speed recognition ability score is 80, and the congestion recognition ability score is 60. Generally, speeding is a more serious traffic violation. That is to say, for the system, the most important ability is the recognition ability of speeding events. Therefore, the recognition ability of speeding events is given a higher weight, and the recognition ability of congestion events is second. For example, the weight of the speeding event recognition ability is 0.5, the weight of the low-speed event recognition ability is 0.2, and the weight of the congestion event recognition ability is 0.3. The system's recognition ability scores for specific events are weighted and summed, and the final score of the average accuracy of the traffic event is 100×0.5+80×0.2+60×0.3=84.

[0089] In addition, when calculating the average accuracy score of a traffic event, the average accuracy of the traffic event can be calculated first, and then the average accuracy score of the traffic event can be calculated. For example, the average accuracy of the traffic event is 100%×0.5+80%×0.2+60%×0.3=84%. Then the final score of the average accuracy of the traffic event is determined to be 84.

[0090] 2. System recall rate

[0091] The system recall rate is the ratio of the number of events successfully identified to the total number of events, i.e. 14 / 15 = 93%. This indicator is used to test the system's ability to detect events. Therefore, the system recall rate score can be 93.

[0092] 3. Average detection speed of traffic incidents

[0093] The indicator value of the average detection speed of traffic incidents is calculated as follows:

[0094] When the average detection speed of traffic events is greater than or equal to 200 milliseconds per event, that is, the average detection time of each event is less than or equal to 200 milliseconds, the score is 95;

[0095] When the average detection speed of traffic incidents is less than 200 milliseconds per incident, but greater than or equal to 300 milliseconds per incident, that is, the average incident detection time is 200-300 milliseconds, the score is 90;

[0096] When the average detection speed of traffic incidents is less than 300 milliseconds per incident, but greater than or equal to 500 milliseconds per incident, that is, the average incident detection time is 300-500 milliseconds, the score is 80;

[0097] When the average detection speed of traffic events is less than 500 milliseconds per event, but greater than or equal to 1000 milliseconds per event, that is, the average event detection time is 500-1000 milliseconds, the score is 60.

[0098] Therefore, since the average event detection time of this application is 350 milliseconds, the average detection speed score of traffic events is 80.

[0099] Based on the above three levels, the overall system score = (84a + 93b + 80c), where abc are preset weights. Assuming that the weight ratio of the system recall rate, average precision rate, and average detection speed of traffic events is set to 0.4:0.4:0.2, the overall detection capability score of the platform = (84×0.4+93×0.4+80×0.2) = 33.6+37.2+16 = 86.8.

[0100] When the overall detection capability score of the platform is less than the preset score, the platform detection capability is determined to be unqualified.

[0101] Assuming the preset score is 85 points, when the platform's overall detection capability score is less than 85, it is determined that the platform's detection capability is unqualified. In the above example, the platform's overall detection capability score is 86.8, which is greater than 85. Therefore, the test result is that the platform's detection capability is qualified.

[0102] In addition, in the present application, after calculating the overall detection capability score of the platform, the overall detection capability score of the platform can be saved.

[0103] The beneficial effect of the present application is that it provides a system for scoring the platform detection capability based on historical detection data, thereby realizing automatic evaluation of the detection capability, saving human resource costs, and because a fixed evaluation method is formulated, the stability and consistency of the evaluation results can also be improved. In addition, compared with the manual evaluation method, this automatic evaluation method can also improve the efficiency of the evaluation.

[0104] In one embodiment, step S101 may be implemented as the following steps:

[0105] Obtain the platform's historical detection data for at least one of the following traffic events:

[0106] Speeding incidents, underspeed incidents, and congestion incidents.

[0107] In one embodiment, the above step S103 can be implemented as the following steps A1-A2:

[0108] In step A1, at least one of the following detection indicators is determined based on the historical detection data of the traffic event:

[0109] The average accuracy of traffic incidents,systems and the average detection speed of traffic incidents;

[0110] In step A2, the score of at least one detection indicator among the average accuracy of the traffic event, the system and the average detection speed of the traffic event is determined, wherein the indicator value of each detection indicator is positively correlated with the score of each detection indicator.

[0111] In one embodiment, the average accuracy of the traffic events is determined as follows:

[0112] Determine the detection accuracy of various types of traffic events;

[0113] Determine the weights of various traffic events;

[0114] The average accuracy of traffic events is determined according to the detection accuracy of each type of traffic events and the weights of the various types of traffic events.

[0115] In one embodiment, the system recall rate is determined as follows:

[0116] Determining the number of all traffic events successfully detected during a specific period, and the number of all traffic events occurring during the specific period;

[0117] The ratio of the number of all traffic events successfully detected in a specific period to the number of all traffic events occurring in the specific period is determined as the system recall rate.

[0118] In one embodiment, the above step S102 may be implemented as the following steps B1-B2:

[0119] In step B1, the overall fluctuation range of the index values ​​of various detection indexes is obtained;

[0120] In step B2, when the overall fluctuation range of the indicator values ​​of various detection indicators is smaller than the preset range, it is determined that the event detection capability of the platform is normal.

[0121] In one embodiment, the step S104 may be implemented as the following steps C1-C3:

[0122] In step C1, the weights of various detection indicators are obtained;

[0123] In step C2, a weighted sum is performed according to the weights of various detection indicators and the scores of each detection indicator;

[0124] In step C3, the summation result is determined as the overall detection capability score of the platform.

[0125] Figure 2 FIG. 1 is a block diagram of a traffic incident detection capability testing device in one embodiment of the present application. Figure 2 As shown, the device includes the following modules:

[0126] An acquisition module 201 is used to acquire historical detection data of traffic events by the platform;

[0127] A judgment module 202 is used to judge whether the event detection capability of the platform is normal according to the historical detection data;

[0128] A first determination module 203 is used to determine a score of at least one detection indicator based on the historical detection data of the traffic event when the event detection capability of the platform is normal;

[0129] A second determination module 204, configured to determine an overall detection capability score of the platform according to a score of at least one detection indicator;

[0130] The third determination module 205 is used to determine that the platform detection capability is unqualified when the overall detection capability score of the platform is less than a preset score.

[0131] In one embodiment, the acquisition module includes:

[0132] The first acquisition submodule is used to obtain the historical detection data of the platform for at least one of the following traffic events:

[0133] Speeding incidents, underspeed incidents, and congestion incidents.

[0134] In one embodiment, the first determining module includes:

[0135] The first determination submodule is used to determine at least one of the following detection indicators based on the historical detection data of the traffic event:

[0136] The average accuracy of traffic incidents,systems and the average detection speed of traffic incidents;

[0137] The second determination submodule is used to determine the score of at least one detection indicator among the average accuracy of the traffic event, the system and the average detection speed of the traffic event, wherein the indicator value of each detection indicator is positively correlated with the score of each detection indicator.

[0138] In one embodiment, the average accuracy of the traffic events is determined as follows:

[0139] Determine the detection accuracy of various types of traffic events;

[0140] Determine the weights of various traffic events;

[0141] The average accuracy of traffic events is determined according to the detection accuracy of each type of traffic events and the weights of the various types of traffic events.

[0142] In one embodiment, the system recall rate is determined as follows:

[0143] Determining the number of all traffic events successfully detected during a specific period, and the number of all traffic events occurring during the specific period;

[0144] The ratio of the number of all traffic events successfully detected in a specific period to the number of all traffic events occurring in the specific period is determined as the system recall rate.

[0145] In one embodiment, the judgment module includes:

[0146] The second acquisition submodule is used to obtain the overall fluctuation range of the index values ​​of various detection indicators;

[0147] The third determination submodule is used to determine that the event detection capability of the platform is normal when the overall fluctuation range of the indicator values ​​of various detection indicators is less than a preset range.

[0148] In one embodiment, the second determining module includes:

[0149] The third acquisition submodule is used to obtain the weights of various detection indicators;

[0150] A summation submodule is used to perform weighted summation according to the weights of various detection indicators and the scores of each detection indicator;

[0151] The fourth determination submodule is used to determine the summation result as the overall detection capability score of the platform.

[0152] The present application also provides a traffic incident detection capability testing system, comprising:

[0153] at least one processor; and,

[0154] a memory communicatively connected to the at least one processor; wherein,

[0155] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the traffic event detection capability testing method recorded in any one of the above embodiments.

[0156] Figure 3 FIG. 1 is a schematic diagram of the hardware structure of a traffic incident detection capability test system in one embodiment of the present application. Figure 3 As shown, the traffic incident detection capability test system includes:

[0157] at least one processor 320; and,

[0158] A memory 304 in communication with the at least one processor 320; wherein,

[0159] The memory 304 stores instructions that can be executed by the at least one processor 320, and the instructions are executed by the at least one processor 320 to implement the traffic event detection capability testing method recorded in any of the above embodiments.

[0160] Reference Figure 3 The traffic event detection capability testing system 300 may include one or more of the following components: a processing component 302 , a memory 304 , a power component 306 , a multimedia component 308 , an audio component 310 , an input / output (I / O) interface 312 , a sensor component 314 , and a communication component 316 .

[0161] The processing component 302 generally controls the overall operation of the traffic incident detection capability testing system 300. The processing component 302 may include one or more processors 320 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 302 may include one or more modules to facilitate the interaction between the processing component 302 and other components. For example, the processing component 302 may include a multimedia module to facilitate the interaction between the multimedia component 308 and the processing component 302.

[0162] The memory 304 is configured to store various types of data to support the operation of the traffic incident detection capability test system 300. Examples of such data include instructions for any application or method operating on the traffic incident detection capability test system 300, such as text, pictures, videos, etc. The memory 304 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0163] The power supply component 306 provides power to various components of the traffic incident detection capability test system 300. The power supply component 306 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the traffic incident detection capability test system 300.

[0164] The multimedia component 308 includes a screen that provides an output interface between the traffic incident detection capability test system 300 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 308 may also include a front camera and / or a rear camera. When the traffic incident detection capability test system 300 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0165] The audio component 310 is configured to output and / or input audio signals. For example, the audio component 310 includes a microphone (MIC), and when the traffic event detection capability test system 300 is in an operation mode, such as an alarm mode, a recording mode, a speech recognition mode, and a speech output mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 304 or sent via the communication component 316. In some embodiments, the audio component 310 also includes a speaker for outputting audio signals.

[0166] I / O interface 312 provides an interface between processing component 302 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0167] The sensor assembly 314 includes one or more sensors for providing various aspects of status evaluation for the traffic event detection capability test system 300. For example, the sensor assembly 314 may include a sound sensor. In addition, the sensor assembly 314 may detect the open / closed state of the traffic event detection capability test system 300, the relative positioning of the components, such as the display and keypad of the traffic event detection capability test system 300, and the sensor assembly 314 may also detect the operating state of the traffic event detection capability test system 300 or a component of the traffic event detection capability test system 300, such as the operating state of the wind distribution plate, the structural state, the operating state of the discharge scraper, etc., the orientation or acceleration / deceleration of the traffic event detection capability test system 300 and the temperature change of the traffic event detection capability test system 300. The sensor assembly 314 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 314 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 314 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, a material stack thickness sensor, or a temperature sensor.

[0168] The communication component 316 is configured to enable the traffic incident detection capability test system 300 to provide the ability to communicate with other devices and cloud platforms in a wired or wireless manner. The traffic incident detection capability test system 300 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 316 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 316 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0169] In an exemplary embodiment, the traffic event detection capability test system 300 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to execute the traffic event detection capability test method described in any of the above embodiments.

[0170] The present application also provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor corresponding to the traffic event detection capability test system, the traffic event detection capability test system can implement the traffic event detection capability test method recorded in any of the above embodiments.

[0171] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0172] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0173] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0174] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0175] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for testing traffic incident detection capability, characterized in that: include: Obtain the platform’s historical detection data on traffic incidents; Determining whether the event detection capability of the platform is normal based on the historical detection data; When the event detection capability of the platform is normal, determining a score of at least one detection indicator based on the historical detection data of the traffic event; Determining an overall detection capability score of the platform based on the score of at least one detection metric; When the overall detection capability score of the platform is less than the preset score, the platform detection capability is determined to be unqualified.

2. The method according to claim 1, characterized in that The acquisition platform's historical detection data of traffic events includes: Obtain the platform's historical detection data for at least one of the following traffic events: Speeding incidents, underspeed incidents, and congestion incidents.

3. The method according to claim 1, characterized in that The step of determining the score of at least one detection indicator based on the historical detection data of the traffic event includes: Determine at least one of the following detection indicators based on the historical detection data of the traffic incident: The average accuracy of traffic events, system recall, and average detection speed of traffic events; Determine the score of at least one detection indicator of the average accuracy rate of the traffic events, the system recall rate, and the average detection speed of the traffic events, wherein the indicator value of each detection indicator is positively correlated with the score of each detection indicator.

4. The method according to claim 3, characterized in that The average accuracy of the traffic events is determined as follows: Determine the detection accuracy of various types of traffic events; Determine the weights of various traffic events; The average accuracy of traffic events is determined according to the detection accuracy of each type of traffic events and the weights of the various types of traffic events.

5. The method according to claim 3, characterized in that The recall rate of the system is determined as follows: Determining the number of all traffic events successfully detected during a specific period, and the number of all traffic events occurring during the specific period; The ratio of the number of all traffic events successfully detected in a specific period to the number of all traffic events occurring in the specific period is determined as the system recall rate.

6. The method according to claim 1, characterized in that The determining whether the event detection capability of the platform is normal according to the historical detection data includes: Obtain the overall fluctuation range of the indicator values ​​of various detection indicators; When the overall fluctuation range of the indicator values ​​of various detection indicators is less than the preset range, it is determined that the event detection capability of the platform is normal.

7. The method according to claim 1, characterized in that Determining the overall detection capability score of the platform according to the score of at least one detection indicator includes: Obtain the weights of various detection indicators; Perform weighted summation based on the weights of various test indicators and the scores of each test indicator; The summed result is determined as the overall detection capability score of the platform.

8. A traffic incident detection capability testing device, characterized in that: include: The acquisition module is used to obtain the historical detection data of traffic events on the platform; A judgment module, used to judge whether the event detection capability of the platform is normal according to the historical detection data; A first determination module, configured to determine a score of at least one detection indicator based on historical detection data of the traffic event when the event detection capability of the platform is normal; A second determination module, configured to determine an overall detection capability score of the platform based on a score of at least one detection indicator; The third determination module is used to determine that the platform detection capability is unqualified when the overall detection capability score of the platform is less than a preset score.

9. A traffic incident detection capability testing system, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the traffic event detection capability testing method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor corresponding to the traffic event detection capability test system, the traffic event detection capability test system can implement the traffic event detection capability test method as described in any one of claims 1 to 7.

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