CN113727064A - Method and device for determining field angle of camera - Google Patents
Method and device for determining field angle of camera Download PDFInfo
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Abstract
The embodiment of the disclosure discloses a method and a device for determining a camera field angle, and relates to the technical field of data processing. The main technical scheme of the embodiment of the disclosure comprises the following steps: under different angles of view to be selected, controlling a simulation test system to test an intelligent driving system of a test vehicle by using a plurality of simulation road scenes, wherein a fixed driving distance is reserved between a traffic vehicle and the test vehicle in each simulation road scene; and determining a target field angle from the field angles to be selected based on the fixed driving distance corresponding to each simulated road scene and the measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same field angle to be selected in the test result of the intelligent driving system, wherein the measured driving distance is determined based on a simulated road image which is shot by a camera of the simulated test system at the corresponding field angle to be selected and corresponds to the simulated road scene.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of data processing, in particular to a method and a device for determining a camera field angle.
Background
With the rapid development of automobile technology, intelligent driving systems such as ADAS (Advanced Driver assistance System) have been generally applied to automobiles, and the intelligent driving systems such as ADAS perform post-algorithm processing on road images in front of the automobile collected by a camera to realize functions such as lane departure and early warning of front collision, so as to assist the driving of a Driver. Because the intelligent driving system can ensure the driving safety to a certain extent, in the development process of the vehicle or the intelligent driving system, the simulation tests such as the hardware-in-loop simulation test and the like are carried out on the intelligent driving system, which is an indispensable link.
Simulation test systems such as hardware-in-the-loop simulation test systems are generally adopted to perform simulation test on the intelligent driving system. The existing simulation test system generally comprises a display device and a camera, wherein the display device is used for playing a simulation road image in a simulation road scene, and the camera on the camera simulation test vehicle is used for collecting the simulation road image played by the display device. And acquiring a simulation road image under a simulation road scene played by display equipment through a camera during testing, wherein the simulation road image comprises a traffic vehicle. And carrying out post algorithm processing according to the acquired images so as to test functions of lane departure, early warning of front vehicle collision and the like. At present, a camera in a simulation test system such as a hardware-in-loop simulation test system generally acquires an image according to a field angle of the camera on a real vehicle, but because a simulation road image in a simulation road scene played by a display device is different from a real road image in a real driving scene, the simulation road image acquired by the camera according to the field angle of the camera on the real vehicle is greatly different from the real road image, and the difference causes a large test error of an intelligent driving system test, so that the reliability of the intelligent driving system test is low.
Disclosure of Invention
In view of this, embodiments of the present disclosure provide a method and an apparatus for determining a field angle of a camera, and mainly aim to determine a field angle more suitable for a simulation test system to perform an intelligent driving system test, so as to improve sensing accuracy of the camera in the simulation test, thereby improving reliability of the simulation test. The main technical scheme comprises:
in a first aspect, an embodiment of the present disclosure provides a method for determining a field angle of a camera, where the method includes:
under different angles of view to be selected, controlling a simulation test system to test an intelligent driving system of a test vehicle by using a plurality of simulation road scenes, wherein a fixed driving distance is reserved between a traffic vehicle and the test vehicle in each simulation road scene;
and determining a target field angle from each to-be-selected field angle based on a fixed driving distance corresponding to each simulated road scene and a measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same to-be-selected field angle in an intelligent driving system test result, wherein the measured driving distance is determined based on a simulated road image corresponding to the simulated road scene, which is shot by a camera of the simulation test system at the corresponding to-be-selected field angle.
In a second aspect, an embodiment of the present disclosure provides an apparatus for determining a field angle of a camera, the apparatus including:
the test unit is used for controlling the simulation test system to test the intelligent driving system of the test vehicle by using a plurality of simulation road scenes under different angles of view to be selected, wherein a fixed driving distance exists between the traffic vehicle and the test vehicle in each simulation road scene;
the determining unit is used for determining a target field angle from each to-be-selected field angle based on a fixed driving distance corresponding to each simulated road scene and a measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same to-be-selected field angle in an intelligent driving system test result, wherein the measured driving distance is determined based on a simulated road image corresponding to the simulated road scene and shot by a camera of the simulated test system at the corresponding to-be-selected field angle.
In a third aspect, an embodiment of the present disclosure provides a simulation test system, where the system includes: the device comprises a camera, a display device, an intelligent driving system and the camera angle-of-view determining device in the second aspect;
the display equipment is used for playing a simulated road image corresponding to any simulated road scene under the control of the camera field angle determining device, wherein a fixed traffic distance is reserved between the traffic vehicle and the test vehicle in the simulated road scene, and the simulated road image comprises the traffic vehicle;
the camera simulates a camera on the test vehicle and is used for shooting a simulated road image played by the display equipment according to the angle of view to be selected set by the device for determining the angle of view of the camera;
the intelligent driving system is used for obtaining an intelligent driving system test result corresponding to the simulated road scene based on the collected simulated road image, and feeding the intelligent driving system test result back to the camera field angle determining device, so that the camera field angle determining device can determine a target field angle required by the camera during intelligent driving system test, wherein the intelligent driving system test result comprises a measured driving distance between the traffic vehicle and the test vehicle in the simulated road scene based on the simulated road image collected by the camera.
In a fourth aspect, an embodiment of the present disclosure provides a storage medium including a stored program, where when the program runs, a device in which the storage medium is located is controlled to execute the method for determining a camera angle of view according to the first aspect.
In a fifth aspect, embodiments of the present disclosure provide a human-computer interaction device, which includes a storage medium coupled with one or more processors configured to execute program instructions stored in the storage medium; the program instructions, when executed, implement the method for determining a camera angle of view according to the first aspect.
By means of the technical scheme, the method and the device for determining the camera view angle provided by the embodiment of the disclosure control the simulation test system to test the intelligent driving system of the test vehicle by using a plurality of simulation road scenes under different view angles to be selected. And determining a target field angle from the field angles to be selected based on the fixed driving distance corresponding to each simulated road scene and the measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same field angle to be selected in the test result of the intelligent driving system. Therefore, the embodiment of the disclosure can determine the angle of view, which is more suitable for the intelligent driving system test of the simulation test system, from the different angles of view to be selected based on the test results of the simulation system under the different angles of view to be selected, so as to improve the sensing precision of the camera in the simulation test, and thus improve the reliability of the simulation test.
The foregoing description is only an overview of the embodiments of the present disclosure, and in order to make the technical means of the embodiments of the present disclosure more clearly understood, the embodiments of the present disclosure may be implemented in accordance with the content of the description, and in order to make the foregoing and other objects, features, and advantages of the embodiments of the present disclosure more clearly understood, the following detailed description of the embodiments of the present disclosure is given.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the embodiments of the present disclosure. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 shows a flowchart of a method for determining a field angle of a camera according to an embodiment of the present disclosure;
fig. 2 is a schematic view illustrating a field angle of a camera according to an embodiment of the disclosure;
fig. 3 is a schematic view illustrating another camera angle provided by an embodiment of the present disclosure;
fig. 4 shows a flowchart of another method for determining a field angle of a camera according to an embodiment of the present disclosure;
FIG. 5 shows a schematic diagram of a simulated road image provided by an embodiment of the disclosure;
FIG. 6 is a schematic diagram illustrating a bird's eye view of a simulated road image provided by an embodiment of the disclosure;
FIG. 7 illustrates a schematic diagram of another simulated road image provided by an embodiment of the present disclosure;
FIG. 8 is a schematic diagram illustrating a bird's eye view of another simulated road image provided by an embodiment of the present disclosure;
FIG. 9 illustrates a schematic diagram of yet another simulated road image provided by an embodiment of the present disclosure;
FIG. 10 is a schematic diagram illustrating a bird's eye view of yet another simulated road image provided by an embodiment of the present disclosure;
fig. 11 is a block diagram illustrating a camera angle determining apparatus according to an embodiment of the present disclosure;
fig. 12 is a block diagram illustrating another apparatus for determining a camera angle of view provided by an embodiment of the present disclosure;
FIG. 13 shows a block diagram of a simulation test system according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The simulation test system described in the embodiments of the present disclosure is used for testing an intelligent driving system deployed in a vehicle, and optionally, the simulation test system may be a hardware-in-loop simulation test system. The specific type of the intelligent driving system described herein may be determined based on business requirements, and the embodiment is not particularly limited. Alternatively, the smart driving system may be any one of the following: ADAS (Advanced Driver assistance System), partially automated System, highly automated System, and fully automated System. The ADAS is used for providing driving assistance for a driver so as to send out warning to remind the driver when the vehicle has safety risk, and exemplarily, lane departure warning, front vehicle collision warning and the like; the partial automation system is a system which can automatically intervene when a driver receives a warning but cannot take corresponding action in time, and exemplarily comprises an automatic emergency braking system, an emergency lane auxiliary system and the like; highly automated systems are used to replace systems in which the driver assumes responsibility for operating the vehicle for a certain period of time, but the driver is still required to monitor the driving activity. Fully automated systems are used to drive vehicles instead of drivers when unmanned vehicles or drivers engage in other activities unrelated to driving behavior, which are systems that do not require human supervision.
The simulation test system comprises a display device, a camera and an intelligent driving system. It should be noted that the simulation test System process may include, in addition to the above three components, a GPS (Global Positioning System), an IMU (Inertial Measurement Unit), a radar, a sensor, and the like, which are indispensable to the smart driving System. The display device is used for playing the simulated road image corresponding to the simulated road scene so as to simulate the driving environment where the test vehicle is located, wherein the driving environment can include but is not limited to traffic vehicles, pedestrians, roads, lane lines, road notice boards and the like. The camera simulates a camera on a test vehicle where the intelligent driving system is located, and the camera is used for shooting a simulation road image which is played by the display device and corresponds to a simulation road scene at a certain field angle. The intelligent driving system is used for obtaining an intelligent driving system test result corresponding to the simulated road scene based on the simulated road image collected by the camera, or the intelligent driving system is used for obtaining an intelligent driving system test result corresponding to the simulated road scene based on at least one or more of the simulated road image collected by the camera, the data collected by the GPS, the data collected by the IMU, the data collected by the radar or the data collected by the sensor.
In the prior art, when the simulation test system tests the intelligent driving system, the camera of the simulation system usually collects images at the field angle of the camera on the real vehicle, but because the simulated road image in the simulated road scene played by the display device is different from the real road image in the real driving scene, the simulated road image collected by the camera at the field angle of the camera on the real vehicle is greatly different from the real road image, and the difference causes a large test error of the intelligent driving system test, and the reliability of the intelligent driving system test is low. In order to determine the angle of view more conforming to the angle of view required by the simulation test system when the intelligent driving system is tested, the embodiment of the disclosure controls the simulation test system to respectively complete the test of the intelligent driving system under different angles of view to be selected, and selects the optimal angle of view from the angles of view to be selected based on the test result. The simulation test system tests the intelligent driving system with the optimal field angle so as to reduce the difference between the simulation road image acquired by the camera and the real road image in the real driving scene, thereby improving the sensing precision of the camera in the simulation test system and further improving the reliability of the simulation test.
In a first aspect, an embodiment of the present disclosure provides a method for determining a field angle of a camera, as shown in fig. 1, the method mainly includes:
101. and under different angles of view to be selected, controlling the simulation test system to test the intelligent driving system of the test vehicle by using a plurality of simulation road scenes, wherein a fixed driving distance exists between the traffic vehicle and the test vehicle in each simulation road scene.
The number of views to be selected in this embodiment may be based on service requirements, and the number is not specifically limited in this embodiment. Optionally, the setting method of the field angle to be selected at least includes at least one of the following:
the method comprises the steps of firstly, obtaining a first sample field angle; a plurality of different angles of view to be selected are set at the set first step-length change rate based on the first sample angle of view.
The first sample field angle in this method is set by two ways: firstly, the first sample view angle is set manually by the user according to the service requirement of the user, the setting mode is flexible, and the user can flexibly set the first sample view angle according to the requirement of the user. Secondly, the first sample view angle is the view angle of the camera on the real vehicle corresponding to the test vehicle, and in the setting mode, the first sample view angle is the view angle of the camera on the real vehicle, so that the view angle to be selected close to the view angle of the camera on the real vehicle can be determined.
In the method, after the first sample field angle is acquired, a plurality of different field angles to be selected are set according to the set first step length change rate. When a plurality of different angles of view to be selected are set at the set first step length change rate, the angles of view to be selected can be set in three ways: first, a plurality of different angles of view to be selected are set at a first step-length change rate with a growing trend based on a first sample angle of view, for example, the first sample angle of view is 30 °, the first step-length change rate is 1 °, and then 5 angles of view to be selected are set to be "30 °, 31 °, 32 °, 33 °, 34 °. Secondly, on the basis of the first sample angle of view, a plurality of different angles of view to be selected are set according to the decreasing trend and the first step length change rate, for example, the first sample angle of view is 30 °, the first step length change rate is 1 °, and then the set 5 angles of view to be selected are 30 °, 29 °, 28 °, 27 ° and 26 °. Thirdly, with the first sample angle of view as a reference, setting a plurality of different angles of view to be selected at a first step length change rate with a trend of increasing and a trend of decreasing, illustratively, the first sample angle of view is 30 °, the first step length change rate is 1 °, and then the set 5 angles of view to be selected are "30 °, 29 °, 28 °, 31 °, 32 °.
And secondly, acquiring a plurality of different first sample field angles, and determining the acquired first sample field angles as the field angles to be selected.
The plurality of first sample viewing angles in the method are determined by a user, and can be read from a user terminal or a storage position designated by the user through a specific interface.
It should be noted that no matter which method of the first method and the second method is adopted for the angle of view to be selected, the determined angle of view to be selected should ensure that the image shot by the camera only includes the simulated road image, and should not include other things. In addition, it should be noted that the first sample field angle may be: a horizontal angle of view, a vertical angle of view, and a total angle of view (the total angle of view is an angle of view in a diagonal direction). When the first sample field angle is not the integrated sample field angle but the horizontal field angle and/or the vertical field angle, the horizontal field angle and/or the vertical field angle needs to be converted into the integrated field angle, and then the field angle to be selected is determined. Illustratively, as shown in fig. 2, 11 is a simulated road image displayed by the display device, 12 is a camera, the angle aoc is a horizontal angle of view, and the angle doc is a vertical angle of view. As shown in fig. 3, 11 is a simulated road image displayed by the display device, 12 is a camera, and the angle boa is an integrated angle of view.
The number of the simulated road scenes in this embodiment may be determined based on the service requirement, and the number is not specifically limited in this embodiment. The simulated road scene at least comprises the following parts: firstly, be the road of horizontal straight line road or straight line area bend in the emulation road scene, there is a traffic car in this emulation road scene, and this traffic car is in same lane or different lanes with the test car, and traffic car and test car are at the uniform velocity and are gone, have fixed traffic interval between traffic car and the test car, that is to say traffic car and test car keep relative still. The second is that the simulated road scene is a horizontal straight line road or a road with a straight line and a curve, a traffic vehicle exists in the simulated road scene, the traffic vehicle and the test vehicle are positioned in the same lane or different lanes, the traffic vehicle and the test vehicle have speed change conditions, and no matter the traffic vehicle and the test vehicle run at constant speed or at variable speed in the simulated road scene, the traffic vehicle and the test vehicle have fixed inter-vehicle distance, namely the traffic vehicle and the test vehicle keep relatively static.
Under different angles of view to be selected, the simulation road scenes used for controlling the simulation test system to test the intelligent driving system can be different or the same. Illustratively, the to-be-selected field angles include a to-be-selected field angle 1 and a to-be-selected field angle 2, wherein the simulated road scenes used for controlling the simulation testing system to test the intelligent driving system under the to-be-selected field angle 1 are a simulated road scene 1 and a simulated road scene 2, and the simulated road scenes used for controlling the simulation testing system to test the intelligent driving system under the to-be-selected field angle 1 are a simulated road scene 3 and a simulated road scene 4. Illustratively, the to-be-selected field angles include a to-be-selected field angle 1 and a to-be-selected field angle 2, wherein under the to-be-selected field angles 1 and 2, simulation road scenes used for controlling the simulation testing system to test the intelligent driving system are simulation road scenes 1 and 2. In order to increase the comparability between the test results corresponding to the angles of view to be selected, the simulation road scenes used by the simulation test system for testing the intelligent driving system under different angles of view to be selected are the same.
In this embodiment, the plurality of simulated road scenes used for testing the intelligent driving system may be the same kind of scenes or different kinds of scenes. Illustratively, the plurality of simulated road scenes used for testing the intelligent driving system comprise a simulated road scene 5 and a simulated road scene 6, wherein a horizontal straight road is arranged in the simulated road scene 5, a traffic vehicle is arranged in the simulated road scene, the traffic vehicle and the test vehicle are in the same lane, the traffic vehicle and the test vehicle run at a constant speed, and a fixed inter-vehicle distance is formed between the traffic vehicle and the test vehicle. The simulated road scene 6 is a horizontal straight road, a traffic vehicle exists in the simulated road scene, the traffic vehicle and the test vehicle are located in the same lane, the traffic vehicle and the test vehicle have speed change conditions, the traffic vehicle and the test vehicle run at constant speed in the simulated road scene, and the traffic vehicle and the test vehicle have fixed inter-vehicle distance no matter the traffic vehicle and the test vehicle run at constant speed or at variable speed. Illustratively, the plurality of simulated road scenes used for testing the intelligent driving system comprise a simulated road scene 7 and a simulated road scene 8, wherein the simulated road scene 7 is a horizontal straight road, a traffic vehicle exists in the simulated road scene, the traffic vehicle and the test vehicle are in the same lane, the traffic vehicle and the test vehicle run at a constant speed, and a fixed inter-vehicle distance is formed between the traffic vehicle and the test vehicle. The simulated road scene 8 is a horizontal straight line road, a traffic vehicle exists in the simulated road scene, the traffic vehicle and the test vehicle are located in the same lane or different lanes, the traffic vehicle and the test vehicle run at a constant speed, and a fixed inter-vehicle distance is reserved between the traffic vehicle and the test vehicle. The simulated road scene 7 differs from the simulated road scene 8 only in that the fixed inter-vehicle distance between the traffic vehicle and the test vehicle differs.
In this embodiment, if the plurality of simulated road scenes used for testing the intelligent driving system are the same type of simulated road scenes, only the fixed inter-vehicle distances between the traffic vehicle and the test vehicle in the simulated road scenes are different. Optionally, the change rate of the fixed inter-vehicle distance in different simulated road scenes is a set step length. If the plurality of simulated road scenes used for testing the intelligent driving system are different types of simulated road scenes, the fixed inter-vehicle distances between the traffic vehicle and the test vehicle in the simulated road scenes can be the same or different. In order to increase the comparability of the test results corresponding to the angles of view to be selected, the plurality of simulated road scenes are the same type of simulated road scenes, and the fixed inter-vehicle distances between the traffic vehicles and the test vehicles are different in the simulated road scenes.
In this embodiment, after a plurality of different angles of view to be selected and a plurality of simulated road scenes are determined, the simulation testing system is controlled to test the intelligent driving system of the test vehicle by using the plurality of simulated road scenes under the different angles of view to be selected. Illustratively, the candidate field angles include a candidate field angle 1 and a candidate field angle 2, and the simulated road scene includes a simulated road scene 1 and a simulated road scene 2. The simulation test system is controlled to respectively use the simulation road scene 1 and the simulation road scene 2 to test the intelligent driving system under the field angle 1 to be selected, and the simulation test system is controlled to respectively use the simulation road scene 1 and the simulation road scene 2 to test the intelligent driving system under the field angle 2 to be selected.
102. And determining a target field angle from each to-be-selected field angle based on a fixed driving distance corresponding to each simulated road scene and a measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same to-be-selected field angle in an intelligent driving system test result, wherein the measured driving distance is determined based on a simulated road image corresponding to the simulated road scene, which is shot by a camera of the simulated test system at the corresponding to-be-selected field angle.
In this embodiment, the process of determining the target field angle from each of the angles to be selected based on the fixed inter-vehicle distance corresponding to each of the simulated road scenes and the measured inter-vehicle distance between the traffic vehicle and the test vehicle in each of the simulated road scenes corresponding to the same angle to be selected in the test result of the intelligent driving system specifically includes the following steps:
step one, determining the error between the measured vehicle distance between the traffic vehicle and the test vehicle and the corresponding fixed vehicle distance in each simulated road scene corresponding to the same field angle to be selected.
Specifically, the specific form of the error between the measured inter-vehicle distance and the corresponding fixed inter-vehicle distance between the transportation vehicle and the test vehicle is not specifically limited in this embodiment, and may be an absolute error or a relative error. The absolute error is calculated as follows:
d=|LTrue-LTest|
d, representing the absolute error between the measured vehicle distance between the traffic vehicle and the test vehicle in any simulated road scene b and the corresponding fixed vehicle distance; l isTestRepresenting the measured inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene b; l isTrueAnd representing the fixed inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene b.
The calculation formula of the relative error is as follows:
c representing the measured inter-vehicle distance between the traffic vehicle and the test vehicle in any simulated road scene b and corresponding fixedDetermining an absolute error between the distances between the vehicles; l isTestRepresenting the measured inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene b; l isTrueAnd representing the fixed inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene b.
Illustratively, the fixed inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene 1 is 10, and the fixed inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene 2 is 8. The simulation test system is controlled to test the intelligent driving system by using the simulation road scene 1 under the field angle 1 to be selected, the measured inter-vehicle distance between the traffic vehicle and the test vehicle in the obtained simulation road scene 1 is 9, and the relative error between the measured inter-vehicle distance 9 between the traffic vehicle and the test vehicle and the corresponding fixed inter-vehicle distance 10 in the simulation road scene 1 corresponding to the field angle 1 to be selected is 10. And controlling the simulation test system to test the intelligent driving system by using the simulation road scene 2 under the field angle 1 to be selected, wherein the measured inter-vehicle distance between the traffic vehicle and the test vehicle in the simulation road scene 2 is 7, and the relative error between the measured inter-vehicle distance 7 between the traffic vehicle and the test vehicle and the corresponding fixed inter-vehicle distance 8 in the simulation road scene 2 corresponding to the field angle 1 to be selected is 12.5%.
Specifically, the error corresponding to each simulated road scene under different field angles can be obtained through the step.
And step two, determining a target field angle from the field angles to be selected based on the errors corresponding to the field angles to be selected.
The concrete implementation method of the second step at least comprises the following steps:
firstly, summing all errors corresponding to the same field angle to be selected to respectively obtain the error sum value of each field angle to be selected; and determining the target field angle based on the magnitude of the error sum value of each field angle to be selected.
Specifically, the error sum corresponding to the same field angle to be selected is calculated by the following formula:
the p1 guarantees the error sum value of any angle b to be selected, and n represents the total number of simulated road scenes used by the simulation test system under the angle b to be selected when the simulation test system tests the intelligent driving system; i represents the ith simulation road scene in the used simulation road scenes; m isiAnd after the ith simulation road scene used by the simulation test system in the test of the intelligent driving system is represented, obtaining the error between the measured inter-vehicle distance between the traffic vehicle and the test vehicle and the corresponding fixed inter-vehicle distance in the ith simulation road scene, wherein the error is an absolute error or a relative error.
The error summation value of all the field angles to be selected can be obtained through the formula.
Specifically, after the error sum value of the field angle to be selected is obtained, the target field angle can be determined according to the error sum value of each field angle to be selected, the target field angle is the field angle required by the camera when the intelligent driving system is tested by the simulation test system, the simulated road image which can be acquired by the camera under the target field angle is close to the real road scene, and the test accuracy of the simulation test system can be improved.
Specifically, the candidate field angle with the smallest error sum value is determined from the candidate field angles as the target candidate field angle, and the smallest error sum value enables the camera to acquire the simulated road image closest to the real road scene based on the candidate field angle, that is, the error between the acquired simulated road image and the real road image is the smallest.
Secondly, multiplying all errors corresponding to the same field angle to be selected to respectively obtain error product values of all the field angles to be selected; and determining the target field angle based on the magnitude of the error product value of each field angle to be selected.
Specifically, the error product value corresponding to the same field angle to be selected is calculated by the following formula:
the p2 guarantees the error product value of any angle b to be selected, and n represents the total number of simulated road scenes used by the simulation test system of the angle b to be selected when the simulation test system tests the intelligent driving system; i represents the ith simulation road scene in the used simulation road scenes; m isiAnd after the ith simulation road scene used by the simulation test system in the test of the intelligent driving system is represented, obtaining the error between the measured inter-vehicle distance between the traffic vehicle and the test vehicle and the corresponding fixed inter-vehicle distance in the ith simulation road scene, wherein the error is an absolute error or a relative error.
The error product values of all the field angles to be selected can be obtained through the formula.
Specifically, after the error product value of the field angle to be selected is obtained, the target field angle can be determined according to the error product value of each field angle to be selected, the target field angle is the field angle required by the camera when the intelligent driving system is tested by the simulation test system, the simulated road image which can be acquired by the camera under the target field angle is close to the real road scene, and the test accuracy of the simulation test system can be improved.
Specifically, the candidate field angle with the smallest error product value is determined from the candidate field angles as the target candidate field angle, and because the error product value is the smallest, the simulated road image which is closest to the real road scene and can be collected by the camera based on the candidate field angle is the smallest, that is, the error between the collected simulated road image and the real road image is the smallest.
Thirdly, distributing corresponding weights for all errors corresponding to the same field angle to be selected, and summing products of all the errors and the respective weights to respectively obtain product sum values of all the field angles to be selected; and determining the target field angle based on the magnitude of the product sum value of the field angles to be selected.
Specifically, the corresponding weight may be assigned to each error corresponding to the same field angle to be selected based on at least the following principles:
in principle one, corresponding to each error of the same field angle to be selected, weights are distributed to the errors according to the fixed inter-vehicle distance corresponding to each error.
Specifically, in the driving process of the vehicle, the closer the following distance between the vehicle and the vehicle ahead of the vehicle is, the higher the probability of the vehicle in an accident such as rear-end collision is, that is, the closer the following distance between the vehicles is, the higher the shooting accuracy of the camera is, and the smaller the fixed following distance corresponding to the error is, the larger the weight is assigned to the fixed following distance.
Of course, if there is a requirement for service, the larger the distance between vehicles under some driving conditions, the higher the probability of danger, the larger the fixed following distance corresponding to the error, the larger the weight assigned to it.
And in principle two, corresponding to each error of the same view angle to be selected, distributing weights to the errors according to the fixed inter-vehicle distance corresponding to each error and the requirement of a test working condition, wherein the test working condition is related to the driving risk degree.
Specifically, when weights are assigned to the errors, the fixed inter-vehicle distance and the driving risk degree corresponding to the errors need to be considered comprehensively, wherein the driving risk degree is related to the function of the tested intelligent driving system.
For example, if the tested smart driving system functions as an automatic emergency brake, the smaller the fixed following distance corresponding to the error, the greater the weight assigned to the error.
No matter which of the above principles is adopted to assign the weight to the error, the sum of products corresponding to the same field angle to be selected can be calculated by the following formula:
the p3 guarantees the product sum value of any angle b to be selected, and n represents the total number of simulated road scenes used by the simulation test system of the angle b to be selected when the simulation test system tests the intelligent driving system; i represents the ith simulation road scene in the used simulation road scenes; m isiAfter an ith simulation road scene used by a simulation test system in testing an intelligent driving system is represented, obtaining an error between a measured inter-vehicle distance between a traffic vehicle and a test vehicle and a corresponding fixed inter-vehicle distance in the ith simulation road scene, wherein the error is an absolute error or a relative error; h isiAnd after representing the ith simulation road scene used by the simulation test system when the intelligent driving system is tested, obtaining the weight corresponding to the error between the measured inter-vehicle distance between the traffic vehicle and the test vehicle and the corresponding fixed inter-vehicle distance in the ith simulation road scene.
The product sum value of all the field angles to be selected can be obtained through the formula.
Specifically, after the product sum value of the to-be-selected field angles is obtained, the target field angle can be determined according to the product sum value of each to-be-selected field angle, the target field angle is the field angle required by the camera when the intelligent driving system is tested by the simulation testing system, the simulated road image which can be acquired by the camera under the target field angle is close to the real road scene, and the testing accuracy of the simulation testing system can be improved.
Specifically, the candidate field angle with the smallest product sum value is determined from the candidate field angles as the target candidate field angle, and because the product sum value is the smallest, the simulated road image which is closest to the real road scene and can be collected by the camera based on the candidate field angle is the smallest, that is, the error between the collected simulated road image and the real road image is the smallest.
According to the method for determining the camera view angle, the simulation test system is controlled to test the intelligent driving system of the test vehicle by using a plurality of simulation road scenes under different view angles to be selected. And determining a target field angle from the field angles to be selected based on the fixed driving distance corresponding to each simulated road scene and the measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same field angle to be selected in the test result of the intelligent driving system. Therefore, the embodiment of the disclosure can determine the angle of view, which is more suitable for the intelligent driving system test of the simulation test system, from the different angles of view to be selected based on the test results of the simulation test system under the different angles of view to be selected, so as to improve the sensing precision of the camera in the simulation test, and thus improve the reliability of the simulation test.
In a second aspect, the method for determining the camera angle of view according to the embodiment of the disclosure may be applied to an independent upper computer, where the upper computer is connected to the simulation test system, and the upper computer determines the target angle of view for the simulation test system by applying the method for determining the camera angle of view according to the embodiment of the disclosure. The method for determining the camera angle of view according to the embodiments of the present disclosure may also be directly applied to any one of the components in the simulation test system, where the component determines the target angle of view for the simulation test system by applying the method for determining the camera angle of view according to the embodiments of the present disclosure. According to the method of the first aspect, another embodiment of the present disclosure further provides a method for determining a field angle of a camera, as shown in fig. 4, the method mainly includes:
201. and setting a plurality of different angles of view to be selected and a plurality of simulated road scenes, wherein a fixed traffic distance is reserved between the traffic vehicle and the test vehicle in each simulated road scene.
Specifically, the angle of view to be selected and the setting method of the simulated road scene in this step are substantially the same as those described in the first aspect, and therefore, the details will not be repeated here.
Illustratively, the determined candidate angles of view include 30 ° and 31 °. 3 simulated road scenes are determined, wherein the fixed inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene 1 is 10 meters, the fixed inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene 2 is 20 meters, and the fixed inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene 3 is 30 meters.
202. Executing the following steps for each field angle to be selected: adjusting the field angle of the camera to the field angle to be selected, and controlling a display device of the simulation test system to sequentially play simulation road images corresponding to a plurality of simulation road scenes; when the display equipment plays a simulation road image corresponding to any simulation road scene, controlling a camera of the simulation test system to acquire the simulation road image; and obtaining an intelligent driving system test result corresponding to the simulated road scene based on the acquired simulated road image.
Specifically, a to-be-selected field angle is selected, the driving device is controlled to adjust the field angle of the camera to the to-be-selected field angle, and then the display device is controlled to sequentially play the simulation road images corresponding to the plurality of simulation road scenes. When the display device plays the simulated road image corresponding to any simulated road scene, in order to ensure that the simulated road image acquired by the camera is accurate, the camera acquires the simulated road image after the display device plays the simulated road image for a certain time. Illustratively, the camera collects the simulated road image only after the display device plays the traffic vehicle and the test vehicle simultaneously run at a constant speed of 50km/h for 30 seconds.
For example, the following describes, by taking an angle of view to be selected as an example, a control simulation test system that controls a simulation test system to test an intelligent driving system of a test vehicle by using a plurality of simulation road scenes respectively at the angle of view to be selected:
the simulation test system comprises a camera, a display device and an intelligent driving system, and in addition, a convex lens can be further arranged between the display device and the camera in order to adjust the focal length of the camera. The test process with the selected field angle of 30 degrees comprises the following steps: adjusting the field angle of a camera to 30 degrees, firstly playing a simulated road image corresponding to a simulated road scene 1 on a display device, wherein the simulated road image is as shown in fig. 5 (a vehicle A in fig. 5 is a traffic vehicle), controlling the camera to collect the simulated road image ' fig. 5 ', and obtaining an intelligent driving system test result corresponding to the simulated road scene based on the collected simulated road image ' fig. 5 ', wherein the test result comprises a measured driving distance between the traffic vehicle A and a test vehicle B, and the test driving distance is determined by converting the simulated road image shot by the camera at the corresponding to-be-selected field angle of 30 degrees into a bird's-eye view as shown in fig. 6 by the simulation test system. After the test for the simulated road scene 1 is completed, playing a simulated road image corresponding to the simulated road scene on the display device, wherein the simulated road image is as shown in fig. 7 (the vehicle a in fig. 7 is a traffic vehicle), controlling the camera to collect the simulated road image "fig. 7", and obtaining an intelligent driving system test result corresponding to the simulated road scene based on the collected simulated road image "fig. 7", wherein the test result comprises a measured inter-vehicle distance between the traffic vehicle a and the test vehicle B, and the test inter-vehicle distance is determined by converting the simulated road image shot by the camera at a corresponding to-be-selected field angle into a bird's-eye view as shown in fig. 8 by the simulation test system. After the test for the simulated road scene 2 is completed, playing a simulated road image corresponding to the simulated road scene 3 on the display device, wherein the simulated road image is as shown in fig. 9 (the vehicle a in fig. 9 is a traffic vehicle), controlling the camera to collect the simulated road image "fig. 9", and obtaining an intelligent driving system test result corresponding to the simulated road scene based on the collected simulated road image "fig. 9", wherein the test result comprises a measured inter-vehicle distance between the traffic vehicle a and the test vehicle B, and the test inter-vehicle distance is determined by converting the simulated road image shot by the camera at a corresponding to-be-selected field angle into a bird's-eye view as shown in fig. 10 by the simulation test system.
203. And determining the error between the measured traffic space and the corresponding fixed traffic space between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same field angle to be selected.
For example, the following describes the error determination process with an example of an alternative field angle: corresponding to the field angle to be selected of 30 degrees, the measured vehicle-to-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene 1 is 9 meters, the measured vehicle-to-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene 1 is 19 meters, and the measured vehicle-to-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene 1 is 28 meters.
Determining the error between the measured inter-vehicle distance between the traffic vehicle and the test vehicle and the corresponding fixed inter-vehicle distance in the simulated road scene 1 as follows:
determining the error between the measured inter-vehicle distance between the traffic vehicle and the test vehicle and the corresponding fixed inter-vehicle distance in the simulated road scene 2 as follows:
determining the error between the measured inter-vehicle distance between the traffic vehicle and the test vehicle and the corresponding fixed inter-vehicle distance in the simulated road scene 3 as follows:
204. and determining the target field angle from the field angles to be selected based on the errors corresponding to the field angles to be selected.
Specifically, corresponding weights are distributed to all errors corresponding to the same to-be-selected field angle, products of all the errors and the respective weights of all the errors are added, and product added values of all to-be-selected field angles are obtained respectively. And determining the target field angle based on the magnitude of the product sum value of the field angles to be selected.
Illustratively, the following description is made with a candidate field angle of 30 °:
corresponding to the field angle to be selected of 30 degrees, the corresponding product sum value is:
p3=10%×0.5+5%×0.3+6%×0.2=0.077
similarly, illustratively, the sum of the products corresponding to the field angle 31 ° to be selected is determined to be 0.11.
Since 0.11 of the product sum value of the field angles to be selected of 31 degrees is greater than 0.077 of the product sum value of the field angles to be selected of 30 degrees, the field angle to be selected of 30 degrees is determined as the target field angle to be selected.
205. Determining whether the target view angle meets the requirement, and if so, executing 208; otherwise, 206 is performed.
Specifically, in order to ensure that the target angle of view is the most accurate angle of view, it is necessary to determine whether the target angle of view satisfies the requirement, and 208 is executed only when the target angle of view satisfies the requirement. When the target field angle does not meet the requirements, 206 is executed.
Specifically, the method for determining whether the target field angle meets the requirement may be: and determining the accumulative determination times of the target field angle, determining whether the accumulative determination times reach a time threshold, if so, indicating that the target field angle meets the test requirement on the intelligent driving system, and executing 208. If the number of times threshold is not reached, it indicates that the target field of view does not meet the test requirements for the intelligent driving system, and execution 206 is performed.
206. The target field angle is determined as the second sample field angle.
207. Based on the second sample field angle, a plurality of different angles of view to be selected are re-set at the set second step size change rate, and 202 is performed.
Specifically, in order to improve the accuracy of the determination of the target field angle, the second step-size change rate for resetting the candidate field angle should be smaller than the step-size change rate between the candidate field angles involved in the target field angle.
Illustratively, the target field of view involves candidate field angles of 30 ° and 31 °, with a step-size rate of change of 1 ° therebetween. In order to improve the determination accuracy of the target angle of view, the second step-length change rate for resetting the angle of view to be selected may be set to 05 °.
It should be noted that the process of resetting a plurality of different angles of view to be selected at the set second step length change rate based on the second sample angle of view is substantially the same as the above-mentioned process of setting a plurality of angles of view to be selected based on the first sample angle of view, and therefore, the description thereof will not be repeated.
208. And determining the target field angle as the field angle required by the camera when the simulation test system performs the test.
Specifically, the target view angle is a view angle required by the camera when the intelligent driving system is formally tested by the simulation test system. The target field angle is selected based on the test results of the simulation test system under different field angles, so that the test requirement of the simulation test system on testing the intelligent driving system is better met.
In a third aspect, according to the method shown in fig. 1 or fig. 4, another embodiment of the present disclosure further provides an apparatus for determining a camera angle of view, as shown in fig. 11, the apparatus mainly includes:
the testing unit 31 is configured to control the simulation testing system to test the intelligent driving system of the test vehicle by using a plurality of simulation road scenes under different angles of view to be selected, where a fixed inter-vehicle distance exists between the traffic vehicle and the test vehicle in each simulation road scene;
the determining unit 32 is configured to determine a target field angle from each of the candidate field angles based on a fixed inter-vehicle distance corresponding to each of the simulated road scenes and a measured inter-vehicle distance between the traffic vehicle and the test vehicle in each of the simulated road scenes corresponding to the same candidate field angle in the test result of the intelligent driving system, where the measured inter-vehicle distance is determined based on a simulated road image corresponding to the simulated road scene, which is captured by a camera of the simulation test system at the corresponding candidate field angle.
According to the device for determining the camera view angle, the simulation test system is controlled to use a plurality of simulation road scenes to test the intelligent driving system of the test vehicle under different view angles to be selected. And determining a target field angle from the field angles to be selected based on the fixed driving distance corresponding to each simulated road scene and the measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same field angle to be selected in the test result of the intelligent driving system. Therefore, the embodiment of the disclosure can determine the angle of view, which is more suitable for the intelligent driving system test of the simulation test system, from the different angles of view to be selected based on the test results of the simulation test system under the different angles of view to be selected, so as to improve the sensing precision of the camera in the simulation test, and thus improve the reliability of the simulation test.
In some embodiments, as shown in fig. 12, the determining unit 32 includes:
a first determining module 321, configured to determine an error between a measured inter-vehicle distance between the traffic vehicle and the test vehicle and a corresponding fixed inter-vehicle distance in each simulated road scene corresponding to the same to-be-selected field angle;
the second determining module 322 is configured to determine the target field of view from each of the to-be-selected field of view based on each error corresponding to each of the to-be-selected field of view.
In some embodiments, as shown in fig. 12, the second determining module 322 is configured to sum the errors corresponding to the same to-be-selected field angle to obtain an error sum value of each to-be-selected field angle; and determining the target field angle based on the magnitude of the error sum value of each field angle to be selected.
In some embodiments, as shown in fig. 12, the second determining module 322 is configured to multiply the errors corresponding to the same to-be-selected field of view to obtain error product values of the to-be-selected field of view respectively; and determining the target field angle based on the magnitude of the error product value of each field angle to be selected.
In some embodiments, as shown in fig. 12, the second determining module 322 is configured to assign corresponding weights to errors corresponding to the same to-be-selected field angles, and sum products of the errors and their respective weights to obtain sum values of the products of the to-be-selected field angles, respectively; and determining the target field angle based on the magnitude of the product sum value of the field angles to be selected.
Further, corresponding to each error of the same view angle to be selected, distributing weight to each error according to the fixed inter-vehicle distance corresponding to each error;
or corresponding to each error of the same view angle to be selected, distributing weight to each error according to the fixed inter-vehicle distance corresponding to each error and the requirement of the test working condition, wherein the test working condition is related to the driving risk degree.
In some embodiments, the error between the measured inter-vehicle distance and the corresponding fixed inter-vehicle distance between the transit vehicle and the test vehicle is: relative error or absolute error.
In some embodiments, as shown in fig. 12, the testing unit 31 is configured to perform, for each of the candidate angles of view: adjusting the field angle of a camera of the simulation test system to the field angle to be selected, and controlling a display device of the simulation test system to sequentially play simulation road images corresponding to a plurality of simulation road scenes; when the display equipment plays the simulation road image corresponding to any simulation road scene, controlling the camera to acquire the simulation road image; and obtaining an intelligent driving system test result corresponding to the simulated road scene based on the acquired simulated road image.
In some embodiments, as shown in fig. 12, the apparatus for determining the angle of field of the camera further includes:
an acquisition unit 33 configured to acquire a first sample angle of view;
a first setting unit 34 configured to set a plurality of different angles of view to be selected at the set first step-size change rate based on the first sample angle of view.
In some embodiments, as shown in fig. 12, the apparatus for determining the angle of field of the camera further includes:
a second setting unit 35 for determining the target angle of view determined by the determining unit 32 as a second sample angle of view; and resetting a plurality of different angles of view to be selected according to the set second step length change rate based on the second sample angle of view, and controlling the simulation test system to use a plurality of simulation road scenes to test the intelligent driving system of the test vehicle under the different angles of view to be selected.
The camera angle determining device provided by the embodiment of the third aspect may be configured to execute the camera angle determining method provided by the embodiment of the first aspect or the second aspect, and the related meanings and specific embodiments may refer to the related descriptions in the embodiment of the first aspect or the second aspect, and are not described in detail here.
In a fourth aspect, another embodiment of the present disclosure further provides a simulation test system, as shown in fig. 13, the system mainly includes: a camera 41, a display device 42, an intelligent driving system 43, and a camera angle-of-view determination device 44 according to claim 11;
the display device 42 is configured to play a simulated road image corresponding to any simulated road scene under the control of the determination device for the field angle of the camera 41, where a fixed inter-vehicle distance exists between a traffic vehicle and a test vehicle in the simulated road scene, and the simulated road image includes the traffic vehicle;
the camera 41 simulates a camera on the test vehicle, and is used for shooting a simulated road image played by the display device 42 at the view angle to be selected set by the camera view angle determining device 44;
the intelligent driving system 43 is configured to obtain an intelligent driving system test result corresponding to the simulated road scene based on the collected simulated road image, and feed the intelligent driving system test result back to the camera angle of view determining device 44, so that the camera angle of view determining device 44 determines a target angle of view required by the camera during the intelligent driving system test, where the intelligent driving system test result includes a measured inter-vehicle distance between the traffic vehicle and the test vehicle in the simulated road scene based on the simulated road image collected by the camera 41.
According to the simulation test system provided by the embodiment of the disclosure, under different angles of view to be selected, the simulation test system is controlled to respectively use a plurality of simulation road scenes to test the intelligent driving system of the test vehicle. And determining a target field angle from the field angles to be selected based on the fixed driving distance corresponding to each simulated road scene and the measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same field angle to be selected in the test result of the intelligent driving system. Therefore, the embodiment of the disclosure can determine the angle of view, which is more suitable for the intelligent driving system test of the simulation test system, from the different angles of view to be selected based on the test results of the simulation test system under the different angles of view to be selected, so as to improve the sensing precision of the camera in the simulation test, and thus improve the reliability of the simulation test.
In some embodiments, the intelligent driving system 43 is an advanced driving assistance system.
The simulation test system provided by the embodiment of the fourth aspect may be configured to execute the method for determining the camera angle provided by the embodiment of the first aspect or the second aspect, and the related meanings and specific embodiments may be referred to in the description of the embodiment of the first aspect or the second aspect, and will not be described in detail here.
In a fifth aspect, an embodiment of the present disclosure provides a storage medium, where the storage medium includes a stored program, and when the program runs, a device in which the storage medium is located is controlled to execute the method for determining the camera angle according to the first aspect or the second aspect.
The storage medium may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
In a sixth aspect, embodiments of the present disclosure provide a human-computer interaction device, the device comprising a storage medium coupled to one or more processors configured to execute program instructions stored in the storage medium; the program instructions, when executed, implement the method for determining a camera angle of view according to any one of the first aspect or the second aspect.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, embodiments of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, embodiments of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (15)
1. A method for determining the field angle of a camera, which is characterized by comprising the following steps:
under different angles of view to be selected, controlling a simulation test system to test an intelligent driving system of a test vehicle by using a plurality of simulation road scenes, wherein a fixed driving distance is reserved between a traffic vehicle and the test vehicle in each simulation road scene;
and determining a target field angle from each to-be-selected field angle based on a fixed driving distance corresponding to each simulated road scene and a measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same to-be-selected field angle in an intelligent driving system test result, wherein the measured driving distance is determined based on a simulated road image corresponding to the simulated road scene, which is shot by a camera of the simulation test system at the corresponding to-be-selected field angle.
2. The method of claim 1, wherein determining a target field of view from each of the candidate field of view based on a fixed headway distance corresponding to each of the simulated road scenes and a measured headway distance between the transit vehicle and the test vehicle within each of the simulated road scenes corresponding to the same candidate field of view in the smart driving system test results comprises:
determining errors between the measured vehicle-travelling distance between the traffic vehicle and the test vehicle and the corresponding fixed vehicle-travelling distance in each simulated road scene corresponding to the same field angle to be selected;
and determining the target field angle from the field angles to be selected based on the errors corresponding to the field angles to be selected.
3. The method of claim 2, wherein determining the target field of view from each of the candidate field of view based on each error corresponding to each of the candidate field of view comprises:
summing the errors corresponding to the same field angle to be selected to respectively obtain the error sum value of each field angle to be selected;
and determining the target field angle based on the magnitude of the error sum value of each field angle to be selected.
4. The method of claim 2, wherein determining the target field of view from each of the candidate field of view based on each error corresponding to each of the candidate field of view comprises:
multiplying the errors corresponding to the same field angle to be selected to obtain error product values of the field angles to be selected respectively;
and determining the target field angle based on the magnitude of the error product value of each field angle to be selected.
5. The method of claim 2, wherein determining the target field of view from each of the candidate field of view based on each error corresponding to each of the candidate field of view comprises:
distributing corresponding weights to all errors corresponding to the same to-be-selected field angle, and summing products of all the errors and the respective weights to respectively obtain a product sum value of all the to-be-selected field angles;
and determining the target field angle based on the magnitude of the product sum value of the field angles to be selected.
6. The method according to claim 5, characterized in that, for each error of the same view angle to be selected, a weight is assigned to each error according to the fixed inter-vehicle distance corresponding to each error;
or corresponding to each error of the same view angle to be selected, distributing weight to each error according to the fixed inter-vehicle distance corresponding to each error and the requirement of the test working condition, wherein the test working condition is related to the driving risk degree.
7. The method according to any one of claims 3-5, wherein the error between the measured inter-vehicle distance and the corresponding fixed inter-vehicle distance between the transit vehicle and the test vehicle is: relative error or absolute error.
8. The method according to any one of claims 1 to 6, wherein the step of controlling the simulation test system to test the intelligent driving system of the test vehicle by using a plurality of simulation road scenes under different angles of view to be selected comprises the following steps:
executing for each of the angles of view to be selected: adjusting the field angle of a camera of the simulation test system to the field angle to be selected, and controlling a display device of the simulation test system to sequentially play simulation road images corresponding to a plurality of simulation road scenes; when the display equipment plays the simulation road image corresponding to any simulation road scene, controlling the camera to acquire the simulation road image; and obtaining an intelligent driving system test result corresponding to the simulated road scene based on the acquired simulated road image.
9. The method according to any one of claims 1-6, further comprising:
acquiring a first sample field angle;
and setting a plurality of different angles of view to be selected at the set first step-length change rate based on the first sample angle of view.
10. The method of any of claims 1-6, wherein after determining a target field of view from each of the candidate field of views, the method further comprises:
determining the target field of view as a second sample field of view;
and resetting a plurality of different angles of view to be selected according to the set second step length change rate based on the second sample angle of view, and controlling the simulation test system to use a plurality of simulated road scenes to test the intelligent driving system of the test vehicle under the different angles of view to be selected.
11. An apparatus for determining a camera field angle, the apparatus comprising:
the test unit is used for controlling the simulation test system to test the intelligent driving system of the test vehicle by using a plurality of simulation road scenes under different angles of view to be selected, wherein a fixed driving distance exists between the traffic vehicle and the test vehicle in each simulation road scene;
the determining unit is used for determining a target field angle from each to-be-selected field angle based on a fixed driving distance corresponding to each simulated road scene and a measured driving distance between the traffic vehicle and the test vehicle in each simulated road scene corresponding to the same to-be-selected field angle in an intelligent driving system test result, wherein the measured driving distance is determined based on a simulated road image corresponding to the simulated road scene and shot by a camera of the simulated test system at the corresponding to-be-selected field angle.
12. A simulation test system, comprising: a camera, a display device, an intelligent driving system and the camera angle-of-view determining device of claim 11;
the display equipment is used for playing a simulated road image corresponding to any simulated road scene under the control of the camera field angle determining device, wherein a fixed traffic distance is reserved between a traffic vehicle and a test vehicle in the simulated road scene, and the simulated road image comprises the traffic vehicle;
the camera simulates a camera on the test vehicle and is used for shooting a simulated road image played by the display equipment according to the angle of view to be selected set by the device for determining the angle of view of the camera;
the intelligent driving system is used for obtaining an intelligent driving system test result corresponding to the simulated road scene based on the collected simulated road image, and feeding the intelligent driving system test result back to the camera field angle determining device, so that the camera field angle determining device can determine a target field angle required by the camera during intelligent driving system test, wherein the intelligent driving system test result comprises a measured driving distance between the traffic vehicle and the test vehicle in the simulated road scene based on the simulated road image collected by the camera.
13. The system of claim 12, wherein the intelligent driving system is an advanced driving assistance system.
14. A storage medium characterized by comprising a stored program, wherein a device on which the storage medium is located is controlled to execute the method for determining the angle of field of a camera according to any one of claims 1 to 10 when the program is executed.
15. A human-computer interaction device, characterized in that the device comprises a storage medium, and one or more processors, the storage medium being coupled to the processors, the processors being configured to execute program instructions stored in the storage medium; the program instructions when executed perform the method for determining the field angle of a camera according to any one of claims 1 to 10.
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