A training scenario generation method based on driving test simulator

Abstract

The present invention relates to the technical field of scene generation, and specifically discloses a training scene generation method based on a driving test simulator, comprising the following steps: S1: obtaining the light intensity at the current time, and determining the corresponding standard brightness, and setting the standard brightness range; S2: periodically obtaining the light intensity and determining the corresponding standard brightness, and drawing a standard brightness change curve; determining the reference point on the standard brightness change curve, and calculating the evaluation score according to the time interval between two adjacent reference points; when the evaluation score is greater than or equal to a preset score threshold, determining the fluctuation curve; S3: calculating the tangent slope of each point on the fluctuation curve and calculating the absolute value, and generating an ordered set; obtaining the maximum fluctuation, calculating the sensitivity correction coefficient; calculating the sensitivity correction value. The present invention can automatically adjust the sensitivity of the training scene brightness adjustment according to the change of light intensity, which is convenient and quick.

Description

Technical Field

[0001] The present invention relates to the technical field of scene generation, and in particular to a method for generating a training scene based on a driving test simulator. Background Art

[0002] A driving test simulator is a device that simulates a real driving environment and is used to help students train their driving skills. It usually includes a large-screen display to show simulated road environments, such as urban roads and highways, allowing students to train in different road environments. It can also simulate various training scenarios, such as special weather conditions such as rainy and snowy days, to help students improve their ability to cope with various driving scenarios.

[0003] When the driving test simulator generates training scenes, it is very important to control the brightness of the training scenes. Too high brightness may put pressure on the user's eyes and may cause visual fatigue or even headaches after long-term training; too low brightness may cause the driver to be unable to effectively identify details in the simulated environment, such as road conditions and traffic signals. At the same time, long-term viewing of low-brightness training scenes may also cause the driver's vision adaptation to deteriorate.

[0004] Most of the prior art uses a method of automatically adjusting the brightness of the training scene according to the ambient brightness to adjust the brightness of the training scene. However, when using this method to adjust the brightness of the training scene, the brightness of the training scene may change frequently due to frequent changes in the external environment. Such frequent brightness changes may have an adverse effect on the driver's visual experience, causing unnecessary interference and discomfort. Therefore, it is possible to choose to reduce the sensitivity of brightness adjustment to reduce the discomfort caused by frequent brightness adjustment. However, the sensitivity of brightness adjustment is generally set and adjusted manually, which is not convenient enough. Summary of the invention

[0005] The purpose of the present invention is to provide a training scenario generation method based on a driving test simulator to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A method for generating a training scenario based on a driving test simulator comprises the following steps:

[0008] S1: Get the light intensity at the current time and determine the corresponding standard brightness G cur The standard brightness is the optimal brightness under the corresponding light intensity. The standard brightness range is set as [G cur -G',G cur +G'], where G' is the preset standard brightness deviation value;

[0009] S2: Set the monitoring period [Tsta , T end ], during the monitoring period, the light intensity is periodically obtained and the corresponding standard brightness is determined, and a standard brightness change curve f(t) is drawn, where t represents time, t∈[T sta , T end ];

[0010] Determine the reference point on the standard brightness change curve, the reference point is the standard brightness on the standard brightness change curve. cur -G' and G cur +G', and calculate the evaluation score P according to the time interval between two adjacent reference points;

[0011] When the evaluation score P is greater than or equal to a preset score threshold, the curve between the 2i-th reference point and the 2i-1-th reference point of the standard brightness change curve is used as a fluctuation curve, i∈[1,n];

[0012] S3: Calculate the tangent slope of each point on the fluctuation curve and calculate the absolute value D, and generate an ordered set D'=(D 1 , D 2 , …, D j ), where D j represents the slope of the tangent line at the jth point on the fluctuation curve;

[0013] Get the maximum fluctuation G max =maxf(t), t∈[t 2i-1 , t 2i ], calculate the sensitivity correction coefficient K, the calculation formula is:

[0014]

[0015] Calculate the sensitivity correction value S for the brightness adjustment of the training scene = S ini *K, where S ini It represents the preset initial sensitivity, and α is the preset correction constant.

[0016] As a further solution of the present invention: in step S2, when there is a preset time interval t int There is no light intensity corresponding to the standard brightness that exceeds the standard brightness range [G cur -G',G cur +G'], adjust the monitoring period to [T sta +t int , T end +t int ].

[0017] As a further solution of the present invention: in step S2, the process of preparing the standard brightness change curve specifically includes:

[0018] Data points corresponding to the standard brightness are generated in the coordinate system, starting from the data point corresponding to the starting point of the monitoring period, all the data points are connected by a smooth curve to obtain a standard brightness change curve.

[0019] As a further solution of the present invention: in the step S2, the process of determining the reference point specifically includes:

[0020] Draw a line through the y-axis with the standard brightness G cur -G' and G cur +G' and a straight line parallel to the x-axis, and the intersection of the straight line and the standard brightness change curve is used as the reference point.

[0021] As a further solution of the present invention: in the step S2, in the process of determining the reference point, T end The corresponding points are also used as reference points.

[0022] As a further solution of the present invention: in step S2, the process of calculating the evaluation score P according to the time interval between two adjacent reference points specifically includes:

[0023] Calculate the evaluation score P, which is calculated as follows:

[0024] Among them, t 2i Indicates the time corresponding to the 2i-th reference point.

[0025] As a further solution of the present invention: the process of obtaining n specifically includes:

[0026] When the number of the reference points is an even number, n=m / 2, where m is the number of the reference points;

[0027] When the number of the reference points is an odd number, n=(m-1) / 2.

[0028] As a further solution of the present invention: in the step S2, when the evaluation score P is greater than or equal to the preset score threshold, the following steps are further performed:

[0029] Determine the standard brightness corresponding to each time the light intensity is obtained during the monitoring period, and sort them according to the time axis order;

[0030] Calculate the brightness reference value and adjusting the brightness of the training scene to the brightness reference value;

[0031] Among them, G crepresents the standard brightness corresponding to the cth acquisition of light intensity within the monitoring period, γ c is the preset proportional coefficient, and E is the total number of times the light intensity is obtained.

[0032] As a further solution of the present invention: in the process of calculating the brightness reference value, the following steps are further performed:

[0033] The average value of the standard brightness within the monitoring period is calculated, and when the difference between a certain standard brightness and the average value is greater than or equal to a preset value, the standard brightness is removed.

[0034] As a further solution of the present invention: in the proportionality coefficient, γ 1 <γ 2 <…<γ E .

[0035] Beneficial effects of the present invention: In the present invention, firstly, the light intensity at the current time is obtained, and the corresponding standard brightness is determined, and the standard brightness range is determined; it can be understood that the standard brightness range is determined to facilitate the subsequent monitoring of whether the standard brightness changes beyond a certain range, and no adjustment is required for the standard brightness that fluctuates within a certain range; then, a standard brightness change curve is drawn, and reference points are determined, and an evaluation score is calculated according to the time interval between the reference points; and it is worth noting that the reference points are determined to evaluate the changes in light intensity. By selecting reference points, it can be determined whether the light intensity fluctuates within a reasonable range, which is necessary for subsequent judgment on whether the standard brightness of the training scene needs to be adjusted and the brightness adjustment The sensitivity of the training scene is determined by the following method: the slope of each point on the fluctuation curve is determined and the absolute value is calculated, and the maximum fluctuation is obtained; it can be understood that the slope of the fluctuation curve represents the speed of change of the standard brightness. The larger the slope, the faster the standard brightness changes; the larger the maximum fluctuation, the greater the degree to which the standard brightness deviates from the standard brightness range; if the standard brightness changes faster and the degree of change is larger, the sensitivity correction coefficient should be reduced, so that the standard brightness of the training scene responds more slowly to changes in light intensity; if the standard brightness changes slower and the degree of change is smaller, the sensitivity correction coefficient should be increased, so that the standard brightness of the training scene responds more quickly to changes in light intensity. The present invention can automatically adjust the sensitivity of the training scene brightness adjustment according to changes in light intensity, which is convenient and quick. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below in conjunction with the accompanying drawings.

[0037] Figure 1 It is a flow chart of a training scenario generating method based on a driving test simulator of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] See also Figure 1 As shown, the present invention is a method for generating a training scenario based on a driving test simulator, comprising the following steps:

[0040] S1: Get the light intensity at the current time and determine the corresponding standard brightness G cur The standard brightness is the optimal brightness under the corresponding light intensity. The standard brightness range is set as [G cur -G',G cur +G'], where G' is the preset standard brightness deviation value;

[0041] S2: Set the monitoring period [T sta , T end ], during the monitoring period, the light intensity is periodically obtained and the corresponding standard brightness is determined, and a standard brightness change curve f(t) is drawn, where t represents time, t∈[T sta , T end ];

[0042] Determine the reference point on the standard brightness change curve, the reference point is the standard brightness on the standard brightness change curve. cur -G' and G cur +G', and calculate the evaluation score P according to the time interval between two adjacent reference points;

[0043] When the evaluation score P is greater than or equal to a preset score threshold, the curve between the 2i-th reference point and the 2i-1-th reference point of the standard brightness change curve is used as a fluctuation curve, i∈[1,n];

[0044] S3: Calculate the tangent slope of each point on the fluctuation curve and calculate the absolute value D, and generate an ordered set D'=(D 1 , D 2 , …, D j ), where Dx represents the tangent slope of the j-th point on the fluctuation curve;

[0045] Get the maximum fluctuation G max =maxf(t), t∈[t 2i-1 , t 2i ], calculate the sensitivity correction coefficient K, the calculation formula is:

[0046]

[0047] Calculate the sensitivity correction value S for the brightness adjustment of the training scene = S ini *K, where S ini It represents the preset initial sensitivity, and α is the preset correction constant.

[0048] It should be noted that the light intensity at the current time is first obtained, and the corresponding standard brightness and standard brightness range are determined; it can be understood that the standard brightness range is determined to facilitate the subsequent monitoring of whether the standard brightness changes beyond a certain range. For the standard brightness that fluctuates within a certain range, no adjustment is required; then the standard brightness change curve is drawn, and the reference points are determined, and the evaluation score is calculated according to the time interval between the reference points; and it is worth noting that the reference points are determined to evaluate the changes in light intensity. By selecting the reference points, it can be determined whether the light intensity fluctuates within a reasonable range. This is for the subsequent judgment of whether the standard brightness of the training scene needs to be adjusted and the sensitivity of the brightness adjustment on the basis; then determine the slope of each point on the fluctuation curve and calculate the absolute value, and obtain the maximum fluctuation; it can be understood that the slope of the fluctuation curve represents the speed of change of the standard brightness. The larger the slope, the faster the standard brightness changes; the larger the maximum fluctuation, the greater the degree of deviation of the standard brightness from the standard brightness range; if the standard brightness changes faster and the degree of change is large, the sensitivity correction coefficient should be reduced, so that the standard brightness of the training scene responds more slowly to changes in light intensity; if the standard brightness changes slower and the degree of change is small, the sensitivity correction coefficient should be increased, so that the standard brightness of the training scene responds faster to changes in light intensity.

[0049] In another preferred embodiment of the present invention, in step S2, when there is a preset time interval t int There is no light intensity corresponding to the standard brightness that exceeds the standard brightness range [G cur -G',G cur +G'], adjust the monitoring period to [T sta +t int , T end +t int ].

[0050] It is worth noting that the monitoring period is adjusted to ensure that there is enough data for analysis when the standard brightness exceeds the standard brightness range and subsequent steps are carried out.

[0051] In another preferred implementation of the present invention, in step S2, the process of preparing the standard brightness change curve specifically includes:

[0052] Data points corresponding to the standard brightness are generated in the coordinate system, starting from the data point corresponding to the starting point of the monitoring period, all the data points are connected by a smooth curve to obtain a standard brightness change curve.

[0053] In another preferred implementation of the present invention, in step S2, the process of determining the reference point specifically includes:

[0054] Draw a line through the y-axis with the standard brightness G cur -G' and G cur +G' and a straight line parallel to the x-axis, and the intersection of the straight line and the standard brightness change curve is used as the reference point.

[0055] In another preferred embodiment of the present invention, in the process of determining the reference point, T end The corresponding points are also used as reference points.

[0056] In another preferred implementation of the present invention, in step S2, the process of calculating the evaluation score P according to the time interval between two adjacent reference points specifically includes:

[0057] Calculate the evaluation score P, which is calculated as follows:

[0058] Among them, t 2i Indicates the time corresponding to the 2i-th reference point.

[0059] In another preferred implementation of the present invention, the process of obtaining n specifically includes:

[0060] When the number of the reference points is an even number, n=m / 2, where m is the number of the reference points;

[0061] When the number of the reference points is an odd number, n=(m-1) / 2.

[0062] It is worth noting that the standard brightness initially belongs to the standard brightness range, so the curve between the first reference point and the second reference point does not belong to the standard brightness range, and the reference points at the even positions and the reference points at the odd positions do not belong to the standard brightness range.

[0063] In another preferred implementation of the present invention, in step S2, when the evaluation score P is greater than or equal to a preset score threshold, the following steps are further performed:

[0064] Determine the standard brightness corresponding to each time the light intensity is obtained during the monitoring period, and sort them according to the time axis order;

[0065] Calculate the brightness reference value and adjusting the brightness of the training scene to the brightness reference value;

[0066] Among them, G c represents the standard brightness corresponding to the cth acquisition of light intensity within the monitoring period, γ c is the preset proportional coefficient, and E is the total number of times the light intensity is obtained.

[0067] It is worth noting that the higher the evaluation score, the higher the proportion of time corresponding to the standard brightness exceeding the standard brightness range during the monitoring period, so the standard brightness of the training scene should be adjusted to an appropriate level first.

[0068] In another preferred implementation of the present invention, in the process of calculating the brightness reference value, the following steps are further performed:

[0069] The average value of the standard brightness within the monitoring period is calculated, and when the difference between a certain standard brightness and the average value is greater than or equal to a preset value, the standard brightness is removed.

[0070] It is understandable that the purpose of doing so is to exclude abnormal values ​​that differ greatly from the standard brightness mean during the monitoring period to ensure that the calculated brightness reference value is more stable and reliable, reduce errors caused by individual extreme cases, and improve the accuracy of the brightness reference value.

[0071] In another preferred embodiment of the present invention, in the proportionality coefficient, γ 1 <γ 2 <…<γ E .

[0072] It should be noted that, the closer the standard brightness at the time of the end of the monitoring period is, the larger the proportionality coefficient is, so that the final brightness reference value can be closer to the standard brightness at the time of the end of the monitoring period.

[0073] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for generating training scenarios based on a driving test simulator, characterized in that: The following steps are involved: S1: Obtain the light intensity at the current time and determine the corresponding standard brightness Gcur, where the standard brightness is the optimal brightness under the corresponding light intensity, and set the standard brightness range [Gcur-G', Gcur+G'], where G' is the preset standard brightness deviation value; S2: Set a monitoring period [Tsta, Tend], within which the light intensity is periodically acquired and the corresponding standard brightness is determined, and a standard brightness variation curve f(t) is drawn, where t represents time and t∈[Tsta, Tend]; Determine reference points on the standard brightness change curve, the reference points are points on the standard brightness change curve where the standard brightness is Gcur-G' and Gcur+G', and calculate the evaluation score P according to the time interval between two adjacent reference points; When the evaluation score P is greater than or equal to a preset score threshold, the curve between the 2i-th reference point and the 2i-1-th reference point of the standard brightness change curve is used as a fluctuation curve, i∈[1,n]; S3: Calculate the tangent slope of each point on the fluctuation curve and calculate the absolute value D, and generate an ordered set D'=(D1, D2, ..., Dj), where Dj represents the tangent slope of the j-th point on the fluctuation curve; Get the maximum fluctuation Gmax=maxf(t), t∈[t2i-1, t2i], and calculate the sensitivity correction coefficient K. The calculation formula is: Calculate the sensitivity correction value S=Sini*K for brightness adjustment of the training scene, where Sini represents the preset initial sensitivity and α is the preset correction constant.

2. A method for generating training scenarios based on a driving test simulator according to claim 1, characterized in that: In the step S2, when there is no standard brightness corresponding to the light intensity exceeding the standard brightness range [Gcur-G', Gcur+G'] within the preset time interval tint, the monitoring period is adjusted to [Tsta+tint, Tend+tint].

3. The method for generating a training scenario based on a driving test simulator according to claim 1, characterized in that: In step S2, the process of preparing the standard brightness change curve specifically includes: Data points corresponding to the standard brightness are generated in the coordinate system, starting from the data point corresponding to the starting point of the monitoring period, all the data points are connected by a smooth curve to obtain a standard brightness change curve.

4. The method for generating a training scenario based on a driving test simulator according to claim 1, characterized in that: In step S2, the process of determining the reference point specifically includes: Draw a straight line through the standard brightness Gcur-G' and Gcur+G' on the y-axis and parallel to the x-axis, and use the intersection of the straight line and the standard brightness change curve as a reference point.

5. A method for generating training scenarios based on a driving test simulator according to claim 4, characterized in that: In the process of determining the reference point, the point corresponding to Tend is also used as a reference point.

6. The method for generating training scenarios based on a driving test simulator according to claim 1, characterized in that: In step S2, the process of calculating the evaluation score P according to the time interval between two adjacent reference points specifically includes: Calculate the evaluation score P, which is calculated as follows: Wherein, t2i represents the time corresponding to the 2i-th reference point.

7. A method for generating training scenarios based on a driving test simulator according to claim 6, characterized in that: The process of obtaining n specifically includes: When the number of the reference points is an even number, n=m / 2, where m is the number of the reference points; When the number of the reference points is an odd number, n=(m-1) / 2.

8. The method for generating training scenarios based on a driving test simulator according to claim 1, characterized in that: In step S2, when the evaluation score P is greater than or equal to a preset score threshold, the following steps are further performed: Determine the standard brightness corresponding to each time the light intensity is obtained during the monitoring period, and sort them according to the time axis order; Calculate the brightness reference value and adjusting the brightness of the training scene to the brightness reference value; Wherein, Gc represents the standard brightness corresponding to the cth acquisition of light intensity within the monitoring period, γc is a preset proportional coefficient, and E is the total number of times the light intensity is acquired.

9. A method for generating training scenarios based on a driving test simulator according to claim 8, characterized in that: In the process of calculating the brightness reference value, the following steps are also performed: The average value of the standard brightness within the monitoring period is calculated, and when the difference between a certain standard brightness and the average value is greater than or equal to a preset value, the standard brightness is removed.

10. The method for generating training scenarios based on a driving test simulator according to claim 8, characterized in that: Among the above-mentioned proportionality coefficients, γ1<γ2<…<γE.

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