A method, device, equipment and medium for evaluating vehicle field of view

Abstract

The present application relates to the field of vehicle assessment technology, and discloses a vehicle field of view assessment method, device, equipment and medium, the method comprising: obtaining the illumination distribution data of the vehicle's headlights on the ground; wherein the vehicle's field of view is divided into a plurality of field of view partitions, and any field of view partition corresponds to the field of view partition and blind area data; statistically analyzing the illumination distribution data on the field of view partition that meets the lighting conditions to obtain the illumination field of view data corresponding to any field of view partition; performing field of view assessment based on the illumination field of view data and blind area data corresponding to any field of view partition to obtain the field of view partition assessment data of any field of view partition; integrating the field of view assessment data according to the field of view partition to obtain the vehicle's field of view assessment data. Its beneficial effect is that the illumination distribution data and blind area data of the vehicle's headlights are combined to assess the vehicle's field of view from different angles, thereby improving the comprehensiveness and accuracy of the assessment data and providing effective guidance for the design of the vehicle.

Description

Technical Field

[0001] The present application relates to the field of vehicle assessment technology, and in particular to a vehicle field of view assessment method, device, equipment and medium. Background Art

[0002] During the driving process of the vehicle, the driver needs to observe the road conditions around the vehicle, and the driver's field of view determines the safety of the driving process. Therefore, in the process of designing and producing vehicles, it is necessary to evaluate the field of view of the vehicle while driving in a specific way to guide the design work of the vehicle and ensure the driving safety of the vehicle. However, the accuracy of evaluating the field of view of the vehicle in the relevant technology still needs to be improved. Summary of the invention

[0003] The present application provides a vehicle field of view assessment method, device, equipment and medium, which combine the illumination distribution data of the vehicle headlights and the blind spot area data to assess the vehicle field of view from different angles, thereby improving the comprehensiveness of the assessment data and further improving the accuracy of the assessment results, thereby providing effective guidance for vehicle design work.

[0004] In order to achieve the above objectives, the main technical solutions adopted in this application include:

[0005] In a first aspect, an embodiment of the present application provides a vehicle field of view assessment method, the method comprising:

[0006] Obtaining illumination distribution data of the vehicle's headlights on the ground; wherein the field of view of the vehicle is divided into a plurality of field of view partitions, and any field of view partition corresponds to the partition ground and blind spot area data;

[0007] Collecting statistics on the illumination distribution data on the ground of the partition that meets the lighting conditions, and obtaining the lighting field of view data corresponding to any field of view partition;

[0008] Performing a visual field evaluation on any visual field partition based on the illumination visual field data and the blind area data corresponding to any visual field partition to obtain partition evaluation data of any visual field partition;

[0009] The partition evaluation data of any of the field of view partitions are integrated to obtain the field of view evaluation data of the vehicle; wherein the field of view evaluation data is used to guide the design work of the vehicle.

[0010] The vehicle field of view range assessment method proposed in the embodiment of the present application obtains the illumination distribution data generated by the vehicle's headlights on the ground and the blind area data of the vehicle itself, performs field of view assessment on the vehicle in multiple field of view partitions respectively, and obtains the vehicle's field of view assessment data based on the partition assessment data of any field of view partition. Compared with the technical solutions in the related art, the present application combines the vehicle's blind area data on the basis of obtaining the vehicle's illumination distribution data, so that the assessment result not only considers the lighting effect of the headlights, but also considers the blind area data generated by the vehicle's body structure, thereby being able to comprehensively assess the vehicle's field of view, improving the comprehensiveness and accuracy of the assessment data, effectively providing data support for the vehicle's design work, and reducing the vehicle's design cost.

[0011] Optionally, performing a field of view evaluation on any field of view partition based on the illumination field of view data and the blind area data corresponding to any field of view partition to obtain the partition evaluation data of any field of view partition includes:

[0012] Using the blind area data to narrow the field of view of the lighting field of view data, to obtain adjusted field of view data;

[0013] A visual field evaluation is performed based on the adjusted visual field data and the area of ​​any visual field partition to obtain partition evaluation data of any visual field partition.

[0014] Optionally, the using the blind area data to narrow the field of view of the illumination field of view data to obtain the adjusted field of view data includes:

[0015] The difference between the illumination visual field data and the blind area data is calculated to obtain the adjustment visual field data.

[0016] Optionally, the integrating the partition evaluation data of any of the field of view partitions to obtain the field of view evaluation data of the vehicle includes:

[0017] Determining a partition weight of any field of view partition under a preset working condition;

[0018] Determining the field of view evaluation data of the vehicle under the preset working condition according to the partition weight and the partition evaluation data; wherein the number of the preset working conditions is multiple;

[0019] The field of vision evaluation data of the vehicle under each of the preset working conditions is integrated to obtain the field of vision evaluation data of the vehicle.

[0020] Optionally, determining the field of view evaluation data of the vehicle under the preset working condition according to the partition weight and the partition evaluation data includes:

[0021] Adjusting the partition evaluation data of any field of view partition based on the partition weight of any field of view partition under the preset working condition to obtain the adjusted evaluation data of any field of view partition under the preset working condition;

[0022] The adjustment evaluation data of any field of view partition under the preset working condition are summarized to obtain the field of view evaluation data of the vehicle under the preset working condition.

[0023] Optionally, the field of view partitions include a first field of view partition, a second field of view partition, a third field of view partition and a fourth field of view partition; the fourth field of view partition is the field of view of the right front of the vehicle with the driver's seat of the vehicle as the center; the first field of view partition, the second field of view partition and the third field of view partition are obtained by dividing the field of view of the left front of the vehicle with the line between the driver's seat of the vehicle and the front window pillar and the line between the driver's seat of the vehicle and the reflector as the dividing line; the blind spot area data corresponding to any field of view partition is determined by the following method:

[0024] Dividing the blind area according to the body structure of the vehicle to obtain the blind area range of the vehicle;

[0025] The blind area range of the visual field is compared with the visual field partitions, and the visual field blind area in any visual field partition is counted to obtain the blind area data corresponding to any visual field partition.

[0026] Optionally, a plurality of illumination sensors are arranged on the ground; and obtaining illumination distribution data of the headlights of the vehicle on the ground includes:

[0027] Using the multiple illumination sensors to collect illumination distribution generated by the vehicle on the ground, and obtaining illumination data of each of the multiple illumination sensors;

[0028] The illuminance distribution data is generated based on the illuminance data and positions of each of the plurality of illuminance sensors.

[0029] In a second aspect, an embodiment of the present application provides a vehicle field of view assessment device, the device comprising:

[0030] An illumination distribution acquisition module is used to acquire illumination distribution data of the vehicle's headlights on the ground; wherein the field of view of the vehicle is divided into a plurality of field of view partitions, and any field of view partition corresponds to the partition ground and blind spot area data;

[0031] An illumination field statistics module is used to collect statistics on the illumination distribution data on the ground of the partition that meets the illumination conditions, and obtain illumination field data corresponding to any field of view partition;

[0032] A visual field partition evaluation module, used to perform visual field evaluation on any visual field partition based on the illumination visual field data and blind area data corresponding to any visual field partition, to obtain partition evaluation data of any visual field partition;

[0033] An evaluation data integration module is used to integrate the partition evaluation data of any field of view partition to obtain the field of view evaluation data of the vehicle; wherein the field of view evaluation data is used to guide the design work of the vehicle.

[0034] In a third aspect, an embodiment of the present application provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method described in any one of the above embodiments by executing the computer instructions.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to enable a computer to execute any one of the methods in the above embodiments.

[0036] In a fifth aspect, an embodiment of the present application provides a computer program product, including computer instructions, and the computer instructions are used to enable a computer to execute any one of the methods in the above embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 A diagram of the steps for evaluating the vehicle's field of view provided in an embodiment of the present application;

[0039] Figure 2 A diagram showing the steps for obtaining partition evaluation data of any visual field partition in an embodiment of the present application;

[0040] Figure 3 A diagram showing the steps of obtaining the field of vision evaluation data of a vehicle in an embodiment of the present application;

[0041] Figure 4 A diagram showing the steps of obtaining the field of vision evaluation data of a vehicle under a preset working condition in an embodiment of the present application;

[0042] Figure 5 A schematic diagram of the field of view partitioning of a vehicle in an embodiment of the present application;

[0043] Figure 6 This is a schematic diagram of the relationship between the field of vision and field of vision partitions of the vehicle driver in the embodiment of the present application;

[0044] Figure 7a This is a schematic diagram of illumination distribution data of the first vehicle model in the embodiment of the present application;

[0045] Figure 7b This is a schematic diagram of illumination distribution data of the second vehicle model in the embodiment of the present application;

[0046] Figure 7c This is a schematic diagram of illumination distribution data of the third vehicle model in the embodiment of the present application;

[0047] Figure 8 A module diagram of a vehicle field of view assessment device provided in an embodiment of the present application;

[0048] Fig. 9 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0050] During the driving process, the driver needs to observe the road conditions around the vehicle, and the driver's field of vision determines the safety of the driving process. During nighttime driving, if the road lighting conditions are poor, the driver's field of vision is determined by the vehicle's headlight lighting range. Therefore, the relevant technology usually uses the headlight lighting range to evaluate the vehicle's field of vision. In actual situations, the vehicle's field of vision is also limited by the blind spot range caused by the vehicle's body structure. The accuracy of evaluating the vehicle's field of vision using only a single factor is low.

[0051] In order to ensure the safety of the vehicle, it is necessary to evaluate the field of vision of the vehicle when driving at night during the design and production of the vehicle, and guide the design of the vehicle based on the evaluation results to optimize the design of the vehicle. In the evaluation process, it is necessary to consider many factors that affect the field of vision of the vehicle. Compared with the solution in the related art that only evaluates the lighting range of the headlights, it is urgent to propose a method that can include multiple necessary data that affect the field of vision of the vehicle into the evaluation scope, thereby improving the comprehensiveness of the evaluation method, and then improving the accuracy of the evaluation results, so that the evaluation data can correctly reflect the field of vision of the vehicle.

[0052] Based on the above problems, the present application provides a vehicle field of view range assessment method, device, equipment and medium, wherein the method includes: obtaining the illumination distribution data of the vehicle's headlights on the ground; wherein the vehicle's field of view is divided into multiple field of view partitions, and any field of view partition corresponds to the partition ground and blind spot area data; statistically analyzing the illumination distribution data on the partition ground that meets the lighting conditions to obtain the lighting field of view data corresponding to any field of view partition; performing field of view assessment based on the lighting field of view data and blind spot area data corresponding to any field of view partition to obtain the partition assessment data of any field of view partition; and integrating the partition assessment data to obtain the vehicle's field of view assessment data.

[0053] The vehicle field of view range assessment method proposed in the present application obtains the illumination distribution data generated by the vehicle's headlights on the ground and the blind area data of the vehicle itself, performs field of view assessment on the vehicle in multiple field of view partitions, and obtains the vehicle's field of view assessment data based on the partition assessment data of any field of view partition. Compared with the technical solutions in the related art, the present application combines the vehicle's blind area data on the basis of obtaining the vehicle's illumination distribution data, so that the assessment result not only considers the lighting effect of the headlights, but also considers the blind area data generated by the vehicle's body structure, thereby being able to comprehensively assess the vehicle's field of view, improving the comprehensiveness and accuracy of the assessment data, effectively providing data support for the vehicle's design work, and reducing the vehicle's design cost.

[0054] The vehicle field of view evaluation method provided in this specification can be applied to vehicles of different models to evaluate the field of view of the vehicle under multiple working conditions. It is understandable that this application is mainly aimed at the field of view in front of the vehicle, and after adaptive modification, this application can also be used to evaluate the field of view of the vehicle in any direction, where any direction includes but is not limited to: both sides of the vehicle and the rear of the vehicle, etc.

[0055] According to an embodiment of the present application, an embodiment of a vehicle field of view assessment method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0056] In this embodiment, a vehicle field of view range assessment method is provided, which can be used for the above-mentioned vehicles of different models. Figure 1 As shown, the method includes:

[0057] S100. Obtaining illumination distribution data of the vehicle's headlights on the ground; wherein the vehicle's field of view is divided into a plurality of field of view partitions, and any field of view partition corresponds to the partition ground and blind spot area data.

[0058] S200. Count the illumination distribution data on the partitioned ground that meets the lighting conditions to obtain the lighting field of view data corresponding to any field of view partition.

[0059] S300. Performing a visual field evaluation on any visual field partition based on the illumination visual field data and blind spot area data corresponding to any visual field partition to obtain partition evaluation data of any visual field partition.

[0060] S400. Integrate the partition evaluation data of any field of view partition to obtain the field of view evaluation data of the vehicle; wherein the field of view evaluation data is used to guide the design work of the vehicle.

[0061] The field of view of the vehicle may be the spatial range that the driver can observe during driving, and the field of view partition is a plurality of non-overlapping spatial ranges obtained by dividing the field of view of the vehicle, and the ground range included in the field of view partition is used as the partition ground. It can be understood that due to the limitation of the vehicle body structure, the vehicle has a certain blind area within the field of view, and any field of view partition has a corresponding blind area on the partition ground, which is used as the blind area data of any field of view partition.

[0062] Specifically, the illumination data of the headlights on the ground directly reflects the driver's visibility of the road surface, obstacles and other traffic participants, thereby limiting the driver's field of vision during nighttime driving. Obtain the illumination distribution data of the headlights on the ground. In the illumination distribution data, the illumination distribution data that meets the lighting conditions indicates that the illumination at the corresponding position is high enough so that the driver can clearly observe the object at the corresponding position. Therefore, the vehicle's illumination field of vision data can be obtained based on the illumination distribution data that meets the lighting conditions to indicate the vehicle's field of vision limited by the lighting range of the headlights.

[0063] To illustrate the lighting conditions by way of example, when evaluating the field of view, the vehicle can be parked in a place where the ambient brightness is less than 0.2 lx to reduce the impact of ambient lighting on the evaluation process. During the evaluation process, the vehicle's lights are turned on and the illumination distribution data of the lights on the ground is collected. The data that meets the lighting conditions in the illumination distribution data on the ground of each partition is counted to obtain the lighting field of view data corresponding to any field of view partition. Among them, the lighting condition can be that the illumination data in the illumination distribution data is greater than 0.4 lx.

[0064] Further, a field of view evaluation is performed on any field of view partition based on the illumination field of view data and the blind area data corresponding to any field of view partition. During the field of view evaluation, the visibility of any field of view partition is evaluated based on the illumination field of view data, and the invisibility of any field of view partition is evaluated based on the blind area data. The visibility evaluation result and the invisibility evaluation result of any field of view partition are combined to obtain the partition evaluation data of any field of view partition to represent the field of view range within the any field of view partition.

[0065] Compared with the technical solutions in the related art that only use the vehicle's headlight illumination range or blind spot range to evaluate the field of view, the present application combines the vehicle's headlight illumination range and blind spot range, reflects the vehicle's field of view during nighttime driving through the vehicle's headlight illumination range, and limits the field of view through the vehicle's blind spot range, so that the obtained evaluation results can reflect the vehicle's actual field of view, thereby improving the comprehensiveness and accuracy of the evaluation results, enhancing the guiding effect of the evaluation results on vehicle design work, and thereby reducing the vehicle's design costs.

[0066] Furthermore, the partition evaluation data of any field of view partition in different field of view partitions are integrated to obtain the field of view evaluation data of the vehicle. It should be noted that the importance of each field of view partition to the driving safety of the vehicle is different. In the integration process, it is necessary to integrate according to the importance of each field of view partition, so as to obtain the field of view evaluation data of the vehicle according to the partition evaluation data of each field of view partition, thereby reflecting the field of view quality and safety of the vehicle during driving.

[0067] The vehicle field of view range assessment method provided in this embodiment obtains the illumination distribution data generated by the vehicle's headlights on the ground and the blind area data of the vehicle itself, performs field of view assessment on the vehicle in multiple field of view partitions, and obtains the vehicle's field of view assessment data based on the partition assessment data of any field of view partition. Compared with the technical solutions in the related art, the present application combines the vehicle's blind area data on the basis of obtaining the vehicle's illumination distribution data, so that the assessment result not only considers the lighting effect of the headlights, but also considers the blind area data generated by the vehicle's body structure, thereby being able to comprehensively assess the vehicle's field of view, improving the comprehensiveness and accuracy of the assessment data, effectively providing data support for the vehicle's design work, and reducing the vehicle's design cost.

[0068] Reference Figure 2 As shown, as an embodiment of the present application, a field of view evaluation is performed on any field of view partition based on the illumination field of view data and blind area data corresponding to any field of view partition, and the partition evaluation data of any field of view partition is obtained, including:

[0069] S310. Use the blind spot area data to narrow the field of view of the lighting field of view data to obtain adjusted field of view data.

[0070] S320. Perform a visual field evaluation based on the adjusted visual field data and the area of ​​any visual field partition to obtain partition evaluation data of any visual field partition.

[0071] Specifically, when evaluating the field of view of any field of view partition, the illumination field of view data reflects the visibility of any field of view partition, and the blind area data reflects the invisibility of any field of view partition. Therefore, the blind area data can be used as a penalty item for any field of view partition during field of view evaluation to limit the illumination field of view data, thereby narrowing the field of view range of any field of view partition and obtaining adjusted field of view data.

[0072] Furthermore, the adjusted field of view data reflects the actual field of view range in any field of view partition, and the partition evaluation data obtained by proportional calculation based on the adjusted field of view data and the area of ​​any field of view partition reflects the field of view coverage of any field of view partition. It can be understood that the higher the partition evaluation data, the higher the field of view coverage of any field of view partition, and the driver can observe the road conditions in any field of view partition more clearly and comprehensively during driving, thereby improving the safety of the driving process.

[0073] As an embodiment of the present application, the blind area data is used to narrow the field of view of the lighting field of view data to obtain the adjusted field of view data, including:

[0074] S312. Calculate the difference between the illumination field of view data and the blind spot area data to obtain adjustment field of view data.

[0075] Specifically, the lighting visual field data reflects the visual field of the vehicle, while the blind spot area data limits the visual field of the vehicle. Therefore, when evaluating the visual field, the difference between the lighting visual field data and the blind spot area data is calculated, so that the blind spot area data is used to narrow the visual field of the lighting visual field data, so as to adjust the visual field of the vehicle and obtain the adjusted visual field data.

[0076] It should be noted that the illumination field of view data and the blind spot area data are independent of each other. In the process of reducing the field of view, the blind spot area data is used as a penalty item for any field of view partition during field of view evaluation. If the blind spot area data is greater than the illumination field of view data, the adjusted field of view data of any field of view partition is negative, indicating that the visibility of any field of view partition is poor and cannot meet the design requirements.

[0077] Reference Figure 3 As shown, as an embodiment of the present application, the field of view evaluation data of the vehicle is obtained by integrating the partition evaluation data of any field of view partition, including:

[0078] S410. Determine the partition weight of any field of view partition under a preset working condition.

[0079] S420. Determine the field of view evaluation data of the vehicle under a preset working condition according to the partition weight and the partition evaluation data; wherein the number of the preset working conditions is multiple.

[0080] S430. Integrate the field of vision evaluation data of the vehicle under each preset working condition to obtain the field of vision evaluation data of the vehicle.

[0081] Specifically, the preset working conditions may include any of the working conditions such as the vehicle going straight, the vehicle turning left at a right angle, the vehicle turning right at a right angle, the vehicle turning left at a U-turn, and the vehicle turning right at a U-turn. Under each preset working condition, the field of view partition has different partition weights, and the partition weights under different preset working conditions are exemplified: under the straight working condition, the driver needs to observe the road conditions directly in front of the vehicle, so the field of view partition in front of the vehicle will have a higher partition weight, and the field of view partition on the side of the vehicle will have a lower partition weight. Under working conditions such as the vehicle turning left at a right angle, the vehicle turning right at a right angle, the vehicle turning left at a U-turn, or the vehicle turning right at a U-turn, the driver needs to observe the road conditions in the direction of the vehicle's turn, so the field of view partition in the direction of the vehicle's turn will have a higher partition weight, and the field of view partitions in other directions will have lower partition weights.

[0082] Furthermore, for each preset working condition, the field of view evaluation data of the vehicle under the preset working condition is determined according to the partition weight under the preset working condition and the partition evaluation data corresponding to each field of view partition. It can be understood that the field of view evaluation data reflects the driving safety of the vehicle under the preset working condition. The higher the field of view evaluation data, the higher the driving safety of the vehicle under the preset working condition, and vice versa.

[0083] Furthermore, the field of vision evaluation data of the vehicle under each preset working condition is integrated to obtain the field of vision evaluation data of the vehicle. The field of vision evaluation data represents the overall evaluation result of the field of vision of the vehicle under all preset working conditions, and reflects the design rationality of the vehicle's lights, body structure and other structures. The higher the field of vision evaluation data, the more reasonable the design of the vehicle is, and it can meet the safety requirements of vehicle driving; the lower the field of vision evaluation data, the less the design of the vehicle meets the requirements. At this time, the vehicle design can be modified according to the field of vision evaluation data of the vehicle and the field of vision evaluation data under each preset working condition, so as to improve the rationality of the vehicle design and improve the safety of vehicle driving.

[0084] Reference Figure 4 As shown, as an embodiment of the present application, the field of view evaluation data of the vehicle under the preset working condition is determined according to the partition weight and the partition evaluation data, including:

[0085] S422. Adjust the partition evaluation data of any field of view partition based on the partition weight of any field of view partition under the preset working condition to obtain the adjusted evaluation data of any field of view partition under the preset working condition.

[0086] S424. Summarize the adjustment evaluation data of any field of view partition under the preset working condition to obtain the field of view evaluation data of the vehicle under the preset working condition.

[0087] Specifically, the process of integrating the field of view evaluation data of the vehicle under each preset working condition may be to adjust the partition evaluation data of any field of view partition according to the partition weight of any field of view partition under the preset working condition to obtain adjusted evaluation data. It should be noted that the adjusted evaluation data reflects the contribution of the actual field of view range of any field of view partition to the overall field of view range of the vehicle.

[0088] Furthermore, the adjustment evaluation data is summarized, that is, the field of view evaluation data of all field of view partitions when the vehicle is in the preset working condition are added together to obtain the field of view evaluation data of the vehicle in the preset working condition, which reflects the driving safety of the vehicle and the field of view performance under different preset working conditions. It is understandable that the field of view evaluation data can help designers discover design defects of the vehicle and provide designers with a data basis to help designers modify the above-mentioned design defects, thereby improving the driving safety of the vehicle and the driving experience of the driver.

[0089] The field of view assessment data is exemplarily illustrated with reference to Tables 1 to 3, wherein Table 1 shows the data results of the vehicle in each field of view partition, Table 2 shows the partition weight of each field of view partition under different preset working conditions, and Table 3 shows the field of view assessment data obtained according to Tables 1 and 2.

[0090] Table 1 Data results of vehicles in each field of view

[0091]

[0092] Table 2 Partition weights of each field of view partition under different preset conditions

[0093] Field of view partition Straight driving condition Turn left at a right angle Turn right at a right angle Turn left U-turn Turn right U-turn First Division 0 0.6 0 0.1 0 Second Division 0 0.3 0 0.3 0 Third Division 0.5 0.1 0.1 0.6 0.1 Fourth District 0.5 0 0.9 0 0.9

[0094] Table 3 Vehicle vision evaluation data

[0095] Preset conditions Vision assessment data for preset conditions Straight driving condition 0.15 Turn left at a right angle 0.19 Turn right at a right angle 0.19 Turn left U-turn 0.14 Turn right U-turn 0.19

[0096] According to Table 3, in this embodiment, the field of vision evaluation data of the vehicle under various preset working conditions are summed, and the field of vision evaluation data of the vehicle is obtained to be 0.86.

[0097] As an embodiment of the present application, the visual field partition includes a first visual field partition, a second visual field partition, a third visual field partition and a fourth visual field partition; the fourth visual field partition is the visual field of the right front of the vehicle with the driver's seat of the vehicle as the center; the first visual field partition, the second visual field partition and the third visual field partition are obtained by dividing the visual field of the left front of the vehicle with the line between the driver's seat of the vehicle and the front window pillar and the line between the driver's seat of the vehicle and the reflector as the dividing line; the blind spot area data corresponding to any visual field partition is determined by the following method:

[0098] S510. Divide the blind area according to the body structure of the vehicle to obtain the blind area range of the vehicle.

[0099] S520. Compare the blind area range of the visual field with the visual field partition, and count the blind area of ​​any visual field partition to obtain the blind area data corresponding to any visual field partition.

[0100] Specifically, under different preset working conditions, each field of view partition has different importance to vehicle driving safety. Field of view partition is used to divide the field of view of the vehicle, so as to reflect the actual needs of the driver for the field of view of the vehicle under each preset working condition, so that the field of view evaluation data is more in line with the actual use scenario and the accuracy of the field of view evaluation data is improved.

[0101] Reference Figure 5 As shown, with the driver's seat of the vehicle as the center, the field of vision in front of the vehicle is divided into the left front field of vision and the right front field of vision, and the field of vision in front of the right side of the vehicle is divided into the fourth partition. For the field of vision in front of the left side of the vehicle, firstly, the connection line between the driver's seat of the vehicle and the front window pillar is determined as the first connection line, and the third partition is obtained according to the center line passing through the driver's seat and the first connection line. Secondly, the connection line between the driver's seat of the vehicle and the reflector is determined as the second connection line, and the second partition is obtained according to the first connection line and the second connection line, and the first partition is obtained according to the boundary line perpendicular to the center line and the second connection line.

[0102] It should be noted that the reference Figure 6 As shown, when observing from the driver's seat of the vehicle to the left front field of view of the vehicle, the first connecting line distinguishes the front field of view and the side field of view in the left front field of view of the vehicle, and the second connecting line distinguishes the side field of view and the rear field of view in the left front field of view of the vehicle.

[0103] Furthermore, the body structure of the vehicle will cause a certain blind spot in the driver's field of vision. By dividing the blind spot of the vehicle according to the body structure, the range of the blind spot of the vehicle can be obtained. After the field of vision is divided, the blind spot range and the field of vision partition are compared with each other to determine the overlapping area of ​​the blind spot range and the field of vision partition, so as to count the blind spot in any field of vision partition and obtain the corresponding blind spot area data.

[0104] As an embodiment of the present application, a plurality of illuminance sensors are arranged on the ground; obtaining illuminance distribution data of vehicle lights on the ground includes:

[0105] S110. Using a plurality of illumination sensors to collect illumination distribution generated by the vehicle on the ground, obtain illumination data of each of the plurality of illumination sensors.

[0106] S120. Generate illumination distribution data based on the illumination data and positions of each of the plurality of illumination sensors.

[0107] Specifically, the illumination sensors arranged on the ground are in a matrix form, that is, the distances between adjacent illumination sensors are equal, and the illumination sensors are neatly arranged. During the evaluation process, the vehicle lights are turned on so that the lights illuminate the positions where the illumination sensors are arranged on the ground, thereby collecting the illumination distribution generated by the vehicle lights on the ground and obtaining the illumination data of each of the multiple illumination sensors. It can be understood that in the illumination sensor matrix, the position of each illumination sensor is known, so according to the illumination data and position of each illumination sensor, the illumination distribution data generated by the vehicle lights on the ground can be determined.

[0108] For example, refer to Figures 7a to 7c , Figure 7a , Figure 7b and Figure 7c The illumination distribution data of different vehicle models are shown respectively, where the data in each matrix point represents the illumination data of the illumination sensor at that position, and the red line represents the dividing line of the field of view partition. Figure 7a As shown, for a vehicle of the first model, the lighting field of view data in the first partition is 15, the lighting field of view data in the second partition is 52, and the lighting field of view data in the third partition is 43.

[0109] Similarly, if Figure 7b As shown, for the second vehicle type, the lighting field of view data in the first partition is 15, the lighting field of view data in the second partition is 33, and the lighting field of view data in the third partition is 43. Figure 7c As shown, for the third vehicle model, the lighting field of view data in the first partition is 13, the lighting field of view data in the second partition is 30, and the lighting field of view data in the third partition is 43. According to the lighting field of view data in the above field of view partitions, the field of view ranges of the first, second and third vehicles can be evaluated.

[0110] Furthermore, the illumination field of the vehicle headlights can be preliminarily evaluated based on the above data. Taking a left turn as an example, when the preset working condition is a left U-turn, the illumination field of view data of the first working condition is the sum of the illumination field of view data of the first partition and the second partition. Referring to Table 4, the illumination field of view data of the first working condition corresponding to the first model, the second model and the third model are shown.

[0111] Table 4 Preliminary evaluation results of different vehicle models when the preset working condition is a left U-turn

[0112]

[0113] When the preset working condition is to turn left at a right angle, the second working condition lighting field of view data is the sum of the lighting field of view data of the second partition and the third partition. Refer to Table 5 for the second working condition lighting field of view data of the vehicles corresponding to the first model, the second model and the third model.

[0114] Table 5 Preliminary evaluation results of different vehicle models when the preset working condition is turning left at a right angle

[0115]

[0116] According to the lighting field of view data of the vehicle in each field of view partition, the total lighting field of view data of the vehicle of the corresponding model can be obtained. Refer to Table 6 for the total lighting field of view data of the vehicles corresponding to the first model, the second model and the third model.

[0117] Table 6 Preliminary evaluation results of the field of view of different vehicle models

[0118]

[0119] When there are more vehicle models, the lighting field of view data of vehicles of different models can be evaluated and sorted in a form similar to Tables 1 to 3, so as to obtain a preliminary evaluation result of the vehicle field of view.

[0120] Accordingly, please refer to Figure 8 , an embodiment of the present application provides a vehicle field of view assessment device, the device comprising:

[0121] The illumination distribution acquisition module 100 is used to acquire illumination distribution data of the vehicle's headlights on the ground; wherein the vehicle's field of view is divided into a plurality of field of view partitions, and any field of view partition corresponds to the partition ground and blind spot area data.

[0122] The lighting field of view statistics module 200 is used to collect statistics on the illumination distribution data that meets the lighting conditions on the partitioned ground to obtain the lighting field of view data corresponding to any field of view partition.

[0123] The visual field partition evaluation module 300 is used to perform visual field evaluation on any visual field partition based on the illumination visual field data and blind area data corresponding to any visual field partition, so as to obtain partition evaluation data of any visual field partition.

[0124] The evaluation data integration module 400 is used to integrate the partition evaluation data of any field of view partition to obtain the field of view evaluation data of the vehicle; wherein the field of view evaluation data is used to guide the design work of the vehicle.

[0125] In some optional embodiments, the visual field partition assessment module 300 includes:

[0126] The field of view reduction unit is used to reduce the field of view of the lighting field of view data by using the blind area data to obtain adjusted field of view data.

[0127] The partition evaluation unit is used to perform a visual field evaluation based on the adjusted visual field data and the area of ​​any visual field partition to obtain the partition evaluation data of any visual field partition.

[0128] In some optional embodiments, the field of view reduction unit includes:

[0129] The field of view difference subunit is used to find the difference between the illumination field of view data and the blind area data to obtain the adjusted field of view data.

[0130] In some optional implementations, the assessment data integration module 400 includes:

[0131] The weight determination unit is used to determine the partition weight of any field of view partition under preset working conditions.

[0132] The field of view evaluation unit is used to determine the field of view evaluation data of the vehicle under preset working conditions according to the partition weights and the partition evaluation data; wherein the number of preset working conditions is multiple.

[0133] The data integration unit is used to integrate the field of vision evaluation data of the vehicle under each preset working condition to obtain the field of vision evaluation data of the vehicle.

[0134] In some optional embodiments, the visual field assessment unit comprises:

[0135] The weight adjustment subunit is used to adjust the partition evaluation data of any field of view partition based on the partition weight of any field of view partition under the preset working condition, so as to obtain the adjusted evaluation data of any field of view partition under the preset working condition.

[0136] The evaluation summary subunit is used to summarize the adjustment evaluation data of any field of view partition under the preset working conditions to obtain the field of view evaluation data of the vehicle under the preset working conditions.

[0137] In some optional embodiments, the visual field partition includes a first visual field partition, a second visual field partition, a third visual field partition and a fourth visual field partition; the fourth visual field partition is the visual field of the right front of the vehicle with the driver's seat of the vehicle as the center; the first visual field partition, the second visual field partition and the third visual field partition are obtained by dividing the visual field of the left front of the vehicle with the connection line between the driver's seat of the vehicle and the front window pillar and the connection line between the driver's seat of the vehicle and the reflector as the dividing line; the device also includes a blind spot area statistics module, including:

[0138] The blind spot division unit is used to divide the blind spot according to the body structure of the vehicle to obtain the blind spot range of the vehicle.

[0139] The blind area statistics unit is used to compare the visual field blind area range with the visual field partition, and to count the visual field blind area in any visual field partition to obtain the blind area data corresponding to any visual field partition.

[0140] In some optional implementations, a plurality of illuminance sensors are provided on the ground; the illuminance distribution acquisition module 100 includes:

[0141] The illumination data acquisition unit is used to collect the illumination distribution generated by the vehicle on the ground using multiple illumination sensors to obtain illumination data of each of the multiple illumination sensors.

[0142] The illumination distribution generating unit is used to generate illumination distribution data based on the illumination data and positions of each of the plurality of illumination sensors.

[0143] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0144] The vehicle field of view assessment device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0145] See also Fig. 9 , Fig. 9It is a structural diagram of a computer device provided by an embodiment of the present application. As shown in the figure, the computer device includes: one or more processors 10, a memory 20, and an interface for connecting various components, including a high-speed interface and a low-speed interface. Each component uses different buses to communicate with each other, and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig. 9 A processor 10 is taken as an example.

[0146] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0147] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0148] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0149] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0150] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0151] The embodiment of the present application also provides a computer-readable storage medium. The above method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0152] The embodiment of the present application provides a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method of any embodiment of the present application.

[0153] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

[0154] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0155] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0156] 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 in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0157] 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.

[0158] 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.

[0159] 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. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0160] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0161] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0162] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

[0163] Although the embodiments of the present application have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A vehicle field of view assessment method, characterized in that: The method comprises: Obtaining illumination distribution data of the vehicle's headlights on the ground; wherein the field of view of the vehicle is divided into a plurality of field of view partitions, and any field of view partition corresponds to the partition ground and blind spot area data; Collecting statistics on the illumination distribution data on the ground of the partition that meets the lighting conditions, and obtaining the lighting field of view data corresponding to any field of view partition; Performing a visual field evaluation on any visual field partition based on the illumination visual field data and the blind area data corresponding to any visual field partition to obtain partition evaluation data of any visual field partition; The partition evaluation data of any of the field of view partitions are integrated to obtain the field of view evaluation data of the vehicle; wherein the field of view evaluation data is used to guide the design work of the vehicle.

2. The method according to claim 1, characterized in that The performing a field of view evaluation on any field of view partition based on the illumination field of view data and the blind area data corresponding to any field of view partition to obtain the partition evaluation data of any field of view partition includes: Using the blind area data to narrow the field of view of the lighting field of view data, to obtain adjusted field of view data; A visual field evaluation is performed based on the adjusted visual field data and the area of ​​any visual field partition to obtain partition evaluation data of any visual field partition.

3. The method according to claim 2, characterized in that The step of using the blind area data to narrow the field of view of the illumination field of view data to obtain the adjusted field of view data includes: The difference between the illumination visual field data and the blind area data is calculated to obtain the adjustment visual field data.

4. The method according to claim 1, characterized in that: The integrating the partition evaluation data of any of the field of view partitions to obtain the field of view evaluation data of the vehicle includes: Determining a partition weight of any field of view partition under a preset working condition; Determining the field of view evaluation data of the vehicle under the preset working condition according to the partition weight and the partition evaluation data; wherein the number of the preset working conditions is multiple; The field of vision evaluation data of the vehicle under each of the preset working conditions is integrated to obtain the field of vision evaluation data of the vehicle.

5. The method according to claim 4, characterized in that The determining, according to the partition weight and the partition evaluation data, the field of view evaluation data of the vehicle under the preset working condition comprises: Adjusting the partition evaluation data of any field of view partition based on the partition weight of any field of view partition under the preset working condition to obtain the adjusted evaluation data of any field of view partition under the preset working condition; The adjustment evaluation data of any field of view partition under the preset working condition are summarized to obtain the field of view evaluation data of the vehicle under the preset working condition.

6. The method according to any one of claims 1 to 5, characterized in that The visual field partitions include a first visual field partition, a second visual field partition, a third visual field partition and a fourth visual field partition; the fourth visual field partition is a visual field of the right front of the vehicle centered on the driver's seat of the vehicle; The first field of view partition, the second field of view partition and the third field of view partition are obtained by dividing the field of view of the left front of the vehicle with the line between the driver's seat and the front window pillar and the line between the driver's seat and the reflector as the dividing lines; The blind area data corresponding to any field of view partition is determined by: Dividing the blind area according to the body structure of the vehicle to obtain the blind area range of the vehicle; The blind area range of the visual field is compared with the visual field partitions, and the visual field blind area in any visual field partition is counted to obtain the blind area data corresponding to any visual field partition.

7. The method according to any one of claims 1 to 5, characterized in that A plurality of illumination sensors are arranged on the ground; and the step of obtaining illumination distribution data of the headlights of the vehicle on the ground includes: Using the multiple illumination sensors to collect illumination distribution generated by the vehicle on the ground, and obtaining illumination data of each of the multiple illumination sensors; The illuminance distribution data is generated based on the illuminance data and positions of each of the plurality of illuminance sensors.

8. A vehicle field of view assessment device, characterized in that: The device comprises: An illumination distribution acquisition module is used to acquire illumination distribution data of the vehicle's headlights on the ground; wherein the field of view of the vehicle is divided into a plurality of field of view partitions, and any field of view partition corresponds to the partition ground and blind spot area data; An illumination field statistics module is used to collect statistics on the illumination distribution data on the ground of the partition that meets the illumination conditions, and obtain illumination field data corresponding to any field of view partition; A visual field partition evaluation module, used to perform visual field evaluation on any visual field partition based on the illumination visual field data and blind area data corresponding to any visual field partition, to obtain partition evaluation data of any visual field partition; An evaluation data integration module is used to integrate the partition evaluation data of any field of view partition to obtain the field of view evaluation data of the vehicle; wherein the field of view evaluation data is used to guide the design work of the vehicle.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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