An automatic driving vehicle control method, device, equipment and storage medium

Abstract

The application relates to an automatic driving vehicle control method, device and equipment and a storage medium, and comprises an automatic driving vehicle control method. The method comprises the following steps: acquiring target top ambient light information corresponding to the top of an automatic driving vehicle and target bottom ambient light information corresponding to the bottom of the automatic driving vehicle; determining target light difference information between the target top ambient light information and the target bottom ambient light information; determining that the automatic driving vehicle is in an abnormal driving state when the target light difference information meets a preset condition; acquiring the duration of the automatic driving vehicle in the abnormal driving state; and performing automatic driving control processing on the automatic driving vehicle according to the duration, so that the ambient light of the automatic driving vehicle is perceived, the safety of the automatic driving vehicle is determined, and the safety of automatic driving is improved.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to an autonomous vehicle control method, device, equipment and storage medium. Background Technology

[0002] Currently, environmental perception for autonomous driving is achieved through camera sensors, supplemented by LiDAR and millimeter-wave radar sensors, to detect and perceive the environment in order to regulate autonomous driving.

[0003] Different sensors have different advantages and disadvantages due to their different working principles, and are suitable for different application scenarios:

[0004] 1) Visual sensors (cameras) have the advantages of long detection distance, high resolution, and the ability to recognize road signs and traffic lights. However, their disadvantages are also obvious: they are highly dependent on light conditions and are easily affected by weather.

[0005] 2) Millimeter-wave radar has the advantages of long detection range, high sensitivity and strong penetration, but its disadvantages are that it is not sensitive to non-metals, has weak stationary ranging capability and is difficult to detect the size and shape of objects.

[0006] 3) Ultrasonic radar has the advantages of low cost and high accuracy, but its disadvantage is long feedback time and it is only suitable for short-distance scenarios such as reversing.

[0007] 4) LiDAR has the best overall performance. It is not only highly sensitive and has a wide detection angle, but it can also detect most objects. It is also highly accurate and can perform 3D modeling. However, its disadvantages are high cost and great susceptibility to weather.

[0008] 5) Infrared sensors have the advantage of night vision, but their sensitivity, stationary ranging, and detection angle are relatively average.

[0009] The sensors mentioned above enable the perception of the environment, but they cannot determine the driving status of autonomous vehicles, thus failing to improve the safety of autonomous vehicles. Summary of the Invention

[0010] In view of this, this application proposes an autonomous vehicle control method, device, equipment and storage medium, which can at least realize the perception of ambient light around the autonomous vehicle, thereby determining the driving status of the autonomous vehicle and improving the driving safety of the autonomous vehicle.

[0011] According to one aspect of this application, an autonomous vehicle control method is provided, the method comprising:

[0012] Obtain the target top ambient light information corresponding to the top of the autonomous vehicle, and the target bottom ambient light information corresponding to the bottom of the autonomous vehicle; the top of the autonomous vehicle is the outer area of ​​the roof of the autonomous vehicle, and the bottom of the autonomous vehicle is the outer area of ​​the chassis of the autonomous vehicle.

[0013] Determine the target light difference information between the ambient light information at the top of the target and the ambient light information at the bottom of the target;

[0014] If the above target light difference information meets the preset conditions, it is determined that the above autonomous vehicle is in an abnormal driving state;

[0015] Obtain the duration of the aforementioned abnormal driving state of the autonomous vehicle;

[0016] Based on the aforementioned duration, autonomous driving control processing is performed on the aforementioned autonomous vehicle.

[0017] Furthermore, the aforementioned autonomous vehicle has multiple top ambient light sensors installed on the outer side of its roof and multiple bottom ambient light sensors installed on the outer side of its chassis. The acquisition of target top ambient light information corresponding to the top of the autonomous vehicle and target bottom ambient light information corresponding to the bottom of the autonomous vehicle includes:

[0018] Based on the above multiple top ambient light sensors, obtain the current top ambient light information corresponding to each of the above multiple top ambient light sensors;

[0019] Based on the current top ambient light information corresponding to each of the above-mentioned multiple top ambient light sensors, the target top ambient light information is determined;

[0020] Based on the aforementioned multiple bottom ambient light sensors, the current bottom ambient light information corresponding to each of the aforementioned multiple bottom ambient light sensors is obtained;

[0021] Based on the current bottom ambient light information corresponding to each of the above-mentioned multiple bottom ambient light sensors, the bottom ambient light information of the target is determined.

[0022] Furthermore, the determination of the target's top ambient light information based on the current top ambient light information corresponding to each of the aforementioned multiple top ambient light sensors includes:

[0023] Obtain the weight information corresponding to each of the above-mentioned multiple top ambient light sensors; the weight information corresponding to each of the above-mentioned multiple top ambient light sensors is a preset weight threshold, or the weight information corresponding to each of the above-mentioned multiple top ambient light sensors is determined based on the position information corresponding to each of the above-mentioned multiple top ambient light sensors, or the weight information corresponding to each of the above-mentioned multiple top ambient light sensors is determined based on the bell curve.

[0024] Based on the current top ambient light information corresponding to each of the above-mentioned multiple top ambient light sensors, and the weight information corresponding to each of the above-mentioned multiple top ambient light sensors, the target top ambient light information is determined.

[0025] Furthermore, the determination of the target's bottom ambient light information based on the current bottom ambient light information corresponding to each of the aforementioned multiple bottom ambient light sensors includes:

[0026] Obtain the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors; the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is a preset weight threshold, or the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is determined based on the position information corresponding to each of the above-mentioned multiple bottom ambient light sensors, or the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is determined based on the bell curve.

[0027] Based on the current bottom ambient light information corresponding to each of the above-mentioned bottom ambient light sensors, and the weight information corresponding to each of the above-mentioned bottom ambient light sensors, the bottom ambient light information of the target is determined.

[0028] Furthermore, the determination of the target light difference information between the ambient light information at the top of the target and the ambient light information at the bottom of the target includes:

[0029] The difference between the ambient light information at the top of the target and the ambient light information at the bottom of the target is calculated to obtain the target light difference information.

[0030] Furthermore, determining that the autonomous vehicle is in an abnormal driving state when the aforementioned target light difference information meets preset conditions includes:

[0031] Obtain a preset ambient light relationship curve; the preset ambient light relationship curve represents the relationship between the historical top ambient light information and the historical light difference information of the above-mentioned autonomous vehicle.

[0032] The relationship between the above target light difference information and the above target top ambient light information is compared with the above preset ambient light relationship curve to obtain the comparison result;

[0033] If the relationship between the target light difference information and the target top ambient light information, as indicated by the above comparison results, does not satisfy the above preset ambient light relationship curve, it is determined that the above autonomous vehicle is in an abnormal driving state.

[0034] Furthermore, the process of generating the aforementioned preset ambient light relationship curve includes:

[0035] Acquire historical vehicles; the roof of the aforementioned historical vehicles is equipped with multiple historical top ambient light sensors, and the chassis of the aforementioned historical vehicles is equipped with multiple historical bottom ambient light sensors.

[0036] Based on the above-mentioned multiple historical top ambient light sensors and multiple historical bottom ambient light sensors, the historical top ambient light information corresponding to each of the above-mentioned multiple historical top ambient light sensors and the historical bottom ambient light information corresponding to each of the above-mentioned multiple historical bottom ambient light sensors are obtained respectively.

[0037] Based on the historical top ambient light information corresponding to each of the above-mentioned historical top ambient light sensors, the target historical top ambient light information is obtained;

[0038] Based on the historical bottom ambient light information corresponding to each of the above-mentioned historical bottom ambient light sensors, the target historical bottom ambient light information is obtained;

[0039] Based on the above-mentioned target historical top ambient light information and the above-mentioned target historical bottom ambient light information, the target historical ambient light difference information is obtained;

[0040] Based on the above-mentioned target historical top ambient light information and the above-mentioned target historical ambient light difference information, the above-mentioned preset ambient light curve is generated.

[0041] Furthermore, the above-mentioned autonomous driving control processing for the autonomous vehicle based on the aforementioned duration includes:

[0042] If the above duration is less than or equal to a preset time threshold, control the above autonomous vehicle to brake or control the above autonomous vehicle to issue a safe driving warning to the driver.

[0043] If the duration exceeds the preset time threshold, the autonomous vehicle will be controlled to issue an alarm.

[0044] According to another aspect of this application, an autonomous vehicle control device is provided, the device comprising:

[0045] The information acquisition module is used to acquire the ambient light information of the top of the target corresponding to the top of the autonomous vehicle, and the ambient light information of the bottom of the target corresponding to the bottom of the autonomous vehicle; the top of the autonomous vehicle is the outer area of ​​the roof of the autonomous vehicle, and the bottom of the autonomous vehicle is the outer area of ​​the chassis of the autonomous vehicle.

[0046] The difference information determination module is used to determine the target light difference information between the above-mentioned target top ambient light information and the above-mentioned target bottom ambient light information;

[0047] The vehicle status determination module is used to determine that the above-mentioned autonomous vehicle is in an abnormal driving state when the above-mentioned target light difference information meets the preset conditions.

[0048] The duration acquisition module is used to acquire the duration of the aforementioned autonomous vehicle being in the aforementioned abnormal driving state;

[0049] The control processing module is used to perform autonomous driving control processing on the aforementioned autonomous vehicle based on the aforementioned duration.

[0050] According to another aspect of this application, an electronic device for controlling an autonomous vehicle is provided. The electronic device includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the above-described autonomous vehicle control method.

[0051] According to another aspect of this application, a computer-readable storage medium is provided, wherein at least one instruction or at least one program is stored in the computer-readable storage medium, wherein the at least one instruction or at least one program is loaded and executed by a processor to implement the above-described autonomous vehicle control method.

[0052] According to another aspect of this application, a computer program product is provided, comprising a computer program, characterized in that the computer program, when executed by a processor, implements the above-described autonomous vehicle control method.

[0053] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this application.

[0054] Implementing this application will have the following beneficial effects:

[0055] This application embodiment senses the ambient light around the autonomous vehicle and obtains information on differences in ambient light, thereby enabling the determination of the autonomous vehicle's driving status and improving the safety of autonomous vehicle operation.

[0056] Other features and aspects of this application will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0057] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this application together with the specification and serve to explain the principles of this application.

[0058] Figure 1 This is a flowchart of an autonomous vehicle control method provided in this application.

[0059] Figure 2 This is a schematic diagram of sensor installation for an autonomous vehicle provided in this application.

[0060] Figure 3 This is a flowchart illustrating an autonomous vehicle control method provided in this application. Figure 1 .

[0061] Figure 4 This is a flowchart illustrating an autonomous vehicle control method provided in this application. Figure 2 .

[0062] Figure 5 This is a flowchart illustrating an autonomous vehicle control method provided in this application. Figure 3 .

[0063] Figure 6 This application provides an ambient light relationship diagram for an autonomous vehicle.

[0064] Figure 7 This application provides an ambient light relationship for an autonomous vehicle. Figure 1 .

[0065] Figure 8 This is a schematic diagram of the structure of an autonomous vehicle control device provided in this application. Detailed Implementation

[0066] Various exemplary embodiments, features, and aspects of this application will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0067] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0068] Furthermore, to better illustrate this application, numerous specific details are provided in the following detailed embodiments. Those skilled in the art should understand that this application can be implemented without certain specific details. In some instances, methods, means, components, and circuits well-known to those skilled in the art have not been described in detail in order to highlight the main points of this application.

[0069] This specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual system or server products, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0070] Figure 1 This is a flowchart of an autonomous vehicle control method provided in this application. Figure 1 As shown, the method may include:

[0071] S101. Obtain the target top ambient light information corresponding to the top of the autonomous vehicle, and the target bottom ambient light information corresponding to the bottom of the autonomous vehicle; the top of the autonomous vehicle is the outer area of ​​the roof of the autonomous vehicle, and the bottom of the autonomous vehicle is the outer area of ​​the chassis of the autonomous vehicle.

[0072] Figure 2 This is a schematic diagram of sensor installation for an autonomous vehicle provided in this application, as shown below. Figure 2 As shown, in an optional embodiment, the exterior of the roof of the aforementioned autonomous vehicle is equipped with multiple top ambient light sensors, for example, such as... Figure 2 As shown, there can be four top ambient light sensors, which can be named T1, T2, T3, and T4 respectively. The aforementioned autonomous vehicle has multiple bottom ambient light sensors installed on the outer side of its chassis, including four bottom ambient light sensors, which can be named B1, B2, B3, and B4 respectively. It should be noted that the number of top ambient light sensors is not limited to four, nor is the number of bottom ambient light sensors limited to four. Figure 2 This is merely a schematic diagram illustrating one embodiment; in actual use, the position of the ambient light sensor can be set as needed. Figure 3 This is a flowchart illustrating an autonomous vehicle control method provided in this application. Figure 1 ,like Figure 3 As shown, S101 may include:

[0073] S301. Based on the above-mentioned multiple top ambient light sensors, obtain the current top ambient light information corresponding to each of the multiple top ambient light sensors;

[0074] Specifically, based on the four top ambient light sensors mentioned above, the current top ambient light information corresponding to each of the four top ambient light sensors can be obtained, and the current top ambient light information corresponding to each of the four top ambient light sensors can be named t1, t2, t3, and t4 respectively.

[0075] S303. Based on the current top ambient light information corresponding to each of the above-mentioned multiple top ambient light sensors, determine the target top ambient light information;

[0076] In an optional embodiment, S303 may include:

[0077] Obtain the weight information corresponding to each of the above-mentioned multiple top ambient light sensors; the weight information corresponding to each of the above-mentioned multiple top ambient light sensors is a preset weight threshold, or the weight information corresponding to each of the above-mentioned multiple top ambient light sensors is determined based on the position information corresponding to each of the above-mentioned multiple top ambient light sensors, or the weight information corresponding to each of the above-mentioned multiple top ambient light sensors is determined based on the bell curve.

[0078] Based on the current top ambient light information corresponding to each of the above-mentioned multiple top ambient light sensors, and the weight information corresponding to each of the above-mentioned multiple top ambient light sensors, the target top ambient light information is determined.

[0079] The weight information corresponding to each of the aforementioned top ambient light sensors can be represented as qt1, qt2, qt3, and qt4. The weight information corresponding to each of these sensors is a preset weight threshold. For example, the preset weight threshold could be that the weight of each of the four top ambient light sensors is 20%. Alternatively, the weight information corresponding to each of the aforementioned top ambient light sensors can be determined based on the position information of each sensor. For example, sensors closer to the front of the vehicle have a higher weight, sensors closer to the rear have a lower weight, sensors closer to the driver have a higher weight, and sensors closer to the passenger side have a lower weight. For example, T1 has a weight of 10%, T2 has a weight of 20%, T3 has a weight of 30%, and T4 has a weight of 40%. Or, the weight information corresponding to each of the aforementioned top ambient light sensors can be determined based on a bell curve. The target top ambient light information can be represented as TargetTL. The target top ambient light information can be calculated using the following formula:

[0080] TargetTL=qt1·t1+qt2·t2+qt3·t3+qt4·t4

[0081] Through the above calculation process, ambient light information of the roof and the outer area of ​​the roof of the autonomous vehicle can be obtained.

[0082] S305. Based on the above-mentioned multiple bottom ambient light sensors, obtain the current bottom ambient light information corresponding to each of the above-mentioned multiple bottom ambient light sensors;

[0083] Specifically, based on the four bottom ambient light sensors mentioned above, the current bottom ambient light information corresponding to the four bottom ambient light sensors can be obtained, and the current bottom ambient light information corresponding to the four bottom ambient light sensors can be named b1, b2, b3, and b4 respectively.

[0084] S307. Based on the current bottom ambient light information corresponding to each of the above-mentioned multiple bottom ambient light sensors, determine the bottom ambient light information of the target.

[0085] In an optional embodiment, S307 may include:

[0086] Obtain the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors; the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is a preset weight threshold, or the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is determined based on the position information corresponding to each of the above-mentioned multiple bottom ambient light sensors, or the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is determined based on the bell curve.

[0087] Based on the current bottom ambient light information corresponding to each of the above-mentioned bottom ambient light sensors, and the weight information corresponding to each of the above-mentioned bottom ambient light sensors, the bottom ambient light information of the target is determined.

[0088] The weight information corresponding to each of the aforementioned bottom ambient light sensors can be represented as qb1, qb2, qb3, and qb4. The weight information corresponding to each of these sensors is a preset weight threshold. This preset weight threshold could be that the weight of each of the four bottom ambient light sensors is 20%, or the weight information corresponding to each of the bottom ambient light sensors can be based on their respective position information. For example, sensors closer to the front of the vehicle have a higher weight, sensors closer to the rear have a lower weight, sensors closer to the driver have a higher weight, and sensors closer to the passenger side have a lower weight. For example, B1 has a weight of 10%, B2 has a weight of 20%, B3 has a weight of 30%, and B4 has a weight of 40%. Alternatively, the weight information corresponding to each of the bottom ambient light sensors can be determined based on a bell curve. The target bottom ambient light information can be represented as TargetBL. The target bottom ambient light information can be calculated using the following formula:

[0089] TargetBL=qb1·b1+qb2·b2+qb3·b3+qb4·b4

[0090] Through the above calculation process, the ambient light information of the chassis and the outer area of ​​the chassis of the aforementioned autonomous vehicle can be obtained.

[0091] S102. Determine the target light difference information between the above-mentioned target bottom ambient light information and the above-mentioned target bottom ambient light information;

[0092] In an optional embodiment, S102 may include:

[0093] The difference between the ambient light information at the top of the target and the ambient light information at the bottom of the target is calculated to obtain the target light difference information.

[0094] The aforementioned target light difference information can be represented as Δlight, and this target light difference information can be calculated using the following formula:

[0095] Δlight = TargetTL - TargetBL

[0096] By calculating the above-mentioned target light difference information, a connection can be established between the above-mentioned target top ambient light information and the above-mentioned target bottom ambient light information.

[0097] S103. If the above target light difference information meets the preset conditions, determine that the above autonomous vehicle is in an abnormal driving state;

[0098] The aforementioned abnormal driving conditions could include bumping, vehicle rollover, or grounding. The driving status of the autonomous vehicle can be determined by judging whether the aforementioned target light difference information meets preset conditions.

[0099] Figure 4 This is a flowchart illustrating an autonomous vehicle control method provided in this application. Figure 2 ,like Figure 4 As shown, in an optional embodiment, S103 may include:

[0100] S401. Obtain a preset ambient light relationship curve; the preset ambient light relationship curve represents the relationship between the historical top ambient light information and the historical light difference information of the above-mentioned autonomous vehicle.

[0101] Figure 5 This is a flowchart illustrating an autonomous vehicle control method provided in this application. Figure 3 ,like Figure 5 As shown, the process of generating the aforementioned preset ambient light relationship curve includes:

[0102] S501. Obtain historical vehicles; the roof of the aforementioned historical vehicles is equipped with multiple historical top ambient light sensors, and the chassis of the aforementioned historical vehicles is equipped with multiple historical bottom ambient light sensors.

[0103] The aforementioned historical vehicles and the aforementioned autonomous vehicles should belong to the same vehicle model. The positions of the multiple historical top ambient light sensors located on the outer side of the roof of the historical vehicle are the same as those on the roof of the autonomous vehicle. Similarly, the positions of the multiple historical top ambient light sensors located on the outer side of the chassis of the historical vehicle are the same as those on the chassis of the autonomous vehicle. The model, parameter settings, and quantity of the historical top ambient light sensors and the top ambient light sensors of the autonomous vehicle are identical. The model, parameter settings, and quantity of the historical bottom ambient light sensors are also identical to those of the bottom ambient light sensors of the autonomous vehicle. In an optional embodiment, there can be four historical top ambient light sensors, which can be named HT1, HT2, HT3, and HT4, respectively, and four historical bottom ambient light sensors, which can be named HB1, HB2, HB3, and HB4, respectively.

[0104] S503. Based on the above-mentioned multiple historical top ambient light sensors and multiple historical bottom ambient light sensors, respectively acquire the historical top ambient light information corresponding to each of the multiple historical top ambient light sensors and the historical bottom ambient light information corresponding to each of the multiple historical bottom ambient light sensors;

[0105] Specifically, based on the four historical top ambient light sensors mentioned above, the current historical top ambient light information corresponding to each of the four historical top ambient light sensors can be obtained. This current historical top ambient light information can be named ht1, ht2, ht3, and ht4, respectively. Similarly, based on the four historical bottom ambient light sensors mentioned above, the current historical bottom ambient light information corresponding to each of the four historical bottom ambient light sensors can be obtained. This current historical bottom ambient light information can be named hb1, hb2, hb3, and hb4, respectively.

[0106] S505. Based on the historical top ambient light information corresponding to each of the above-mentioned historical top ambient light sensors, the target historical top ambient light information is obtained;

[0107] The acquisition and calculation of the aforementioned historical top ambient light information and the acquisition and calculation of the aforementioned top ambient light information are performed in the same way. The weight information corresponding to each of the aforementioned historical top ambient light sensors can be represented as qht1, qht2, qht3, and qht4. The weight information corresponding to each of the aforementioned historical top ambient light sensors is a preset weight threshold. The preset weight threshold can be that the weight of each of the four historical top ambient light sensors is 20%, or the weight information corresponding to each of the aforementioned historical top ambient light sensors can be based on the position information of each of the aforementioned historical top ambient light sensors. For example, sensors closer to the front of the vehicle have a higher weight, sensors closer to the rear of the vehicle have a lower weight, sensors closer to the driver's side have a higher weight, sensors closer to the passenger side have a lower weight, etc. For example, HT1 has a weight of 10%, HT2 has a weight of 20%, HT3 has a weight of 30%, and HT4 has a weight of 40%. Alternatively, the weight information corresponding to each of the aforementioned historical top ambient light sensors can be determined based on a bell curve. The weight information corresponding to each of the aforementioned historical top ambient light sensors should be consistent with or change in a predetermined ratio with the weight information corresponding to each of the aforementioned top ambient light sensors. The aforementioned target historical top ambient light information can be represented as a FrontLight sensor. The aforementioned target historical top ambient light information can be calculated using the following formula:

[0108] Front Light sensor=qht1·ht1+qht2·ht2+qht3·ht3+qht4·ht4

[0109] Through the above calculations, ambient light information of the same area relative to the vehicle itself can be obtained for the aforementioned historical vehicles and the aforementioned autonomous vehicles.

[0110] S507. Based on the historical bottom ambient light information corresponding to each of the above-mentioned historical bottom ambient light sensors, the target historical bottom ambient light information is obtained;

[0111] The acquisition and calculation of the aforementioned historical bottom ambient light information is performed in the same way as the acquisition and calculation of the aforementioned bottom ambient light information. The weight information corresponding to each of the aforementioned historical bottom ambient light sensors can be represented as qhb1, qhb2, qhb3, and qhb4. The weight information corresponding to each of the aforementioned historical bottom ambient light sensors is a preset weight threshold. This preset weight threshold can be that the weight of each of the four historical bottom ambient light sensors is 20%, or the weight information corresponding to each of the aforementioned historical bottom ambient light sensors can be based on the position information of each of the aforementioned historical bottom ambient light sensors. For example, sensors closer to the front of the vehicle have a higher weight, sensors closer to the rear of the vehicle have a lower weight, sensors closer to the driver's side have a higher weight, and sensors closer to the passenger side have a lower weight, etc. For example, HB1 has a weight of 10%, HB2 has a weight of 20%, HB3 has a weight of 30%, and HB4 has a weight of 40%. Alternatively, the weight information corresponding to each of the aforementioned historical bottom ambient light sensors can be determined based on a bell curve. The weight information corresponding to each of the aforementioned historical bottom ambient light sensors should be consistent with or change in a predetermined ratio to the weight information corresponding to each of the aforementioned historical bottom ambient light sensors. The aforementioned target historical bottom ambient light information can be represented as the BackLight sensor. The aforementioned target historical bottom ambient light information can be calculated using the following formula:

[0112] Back Light sensor=qhb1·hb1+qhb2·hb2+qhb3·hb3+qhb4·hb4

[0113] Through the above calculations, ambient light information of the same area relative to the vehicle itself can be obtained for the aforementioned historical vehicles and the aforementioned autonomous vehicles.

[0114] Figure 6 This application provides an ambient light relationship diagram for an autonomous vehicle. Figure 6 This application provides an ambient light relationship diagram for an autonomous vehicle. Based on the aforementioned historical top ambient light information and historical bottom ambient light information of the target, through deep learning using a large amount of data, a relationship curve between the aforementioned historical top ambient light information and historical bottom ambient light information of the target can be obtained, as shown below. Figure 6 As shown, the curves displaying the relationship between the ambient light information at the top and bottom of the target's historical data are illustrated. Lux is the unit of luminance. The horizontal axis represents the front light sensor, indicating the ambient light information at the top of the target's historical data, and the vertical axis represents the back light sensor, indicating the ambient light information at the bottom of the target's historical data. Figure 6It can be seen that there is a certain mathematical relationship between the above-mentioned target historical top ambient light information and the above-mentioned target historical bottom ambient light information.

[0115] S509. Based on the above-mentioned target historical top ambient light information and the above-mentioned target historical bottom ambient light information, obtain the target historical ambient light difference information;

[0116] The aforementioned historical ambient light difference information of the target can be expressed as Δlux, and this information can be calculated using the following formula:

[0117] Δlux=Front Light sensor-Back Light sensor

[0118] By calculating the above-mentioned historical ambient light difference information of the target, the relationship between the above-mentioned historical top ambient light information and the above-mentioned historical bottom ambient light information of the target can be established.

[0119] S5011. Based on the above-mentioned target historical top ambient light information and the above-mentioned target historical ambient light difference information, generate the above-mentioned preset ambient light curve.

[0120] By generating the aforementioned preset ambient light curve, a connection is established between the aforementioned target historical top ambient light information and the aforementioned target historical ambient light difference information, providing a reference object for the aforementioned autonomous vehicle.

[0121] Figure 7 This application provides an ambient light relationship for an autonomous vehicle. Figure 1 ,like Figure 7 As shown, the preset ambient light curve illustrates the relationship between the target's historical top ambient light information and the target's historical ambient light difference information. The horizontal axis represents the front light sensor, indicating the target's historical top ambient light information, and the vertical axis represents Δlux, indicating the target's historical ambient light difference information.

[0122] In an optional embodiment, the preset ambient light curve can also be generated based on the target's historical bottom ambient light information and the target's historical ambient light difference information.

[0123] In an optional embodiment, the above-mentioned target historical bottom ambient light information and the above-mentioned target historical top ambient light information can be combined to obtain the historical processing result. Based on the historical processing result and the above-mentioned target historical ambient light difference information, the above-mentioned preset ambient light curve II can be generated.

[0124] S403. Compare the relationship between the above target light difference information and the above target top ambient light information with the above preset ambient light relationship curve to obtain the comparison result;

[0125] In an optional embodiment, the relationship between the above-mentioned target light difference information and the above-mentioned target bottom ambient light information can also be compared with the above-mentioned preset ambient light relationship curve to obtain comparison result one;

[0126] In an optional embodiment, the above-mentioned target top ambient light information and target bottom ambient light information can also be processed to obtain a processing result. The relationship between the above-mentioned target light difference information and the above-mentioned processing result can be compared with the above-mentioned preset ambient light relationship curve two to obtain comparison result two.

[0127] S405. If the relationship between the target light difference information and the target top ambient light information indicated by the above comparison results does not satisfy the above preset ambient light relationship curve, it is determined that the above autonomous driving vehicle is in an abnormal driving state.

[0128] Specifically, the failure to meet the above-mentioned preset ambient light curve may be that the point with coordinates (TargetTL, Δlight) does not fall on the above-mentioned preset ambient light curve, or that the distance between the point with coordinates (TargetTL, Δlight) and the above-mentioned preset ambient light curve exceeds a preset threshold range.

[0129] S104. Obtain the duration of the aforementioned abnormal driving state of the autonomous vehicle;

[0130] The aforementioned duration indicates the time during which the autonomous vehicle maintains its abnormal driving state. By obtaining this duration, it can be determined whether the autonomous vehicle experiences a short period of bumping or a long period of overturning.

[0131] S105. Based on the aforementioned duration, perform autonomous driving control processing on the aforementioned autonomous vehicle.

[0132] In an optional embodiment, S105 may include:

[0133] If the above duration is less than or equal to a preset time threshold, control the above autonomous vehicle to brake or control the above autonomous vehicle to issue a safe driving warning to the driver.

[0134] If the duration exceeds the preset time threshold, the autonomous vehicle will be controlled to issue an alarm.

[0135] By comparing the relationship between the target light difference information and the target top ambient light information with the preset ambient light relationship curve, a comparison result is obtained. Combined with the duration of the abnormal state, if the duration is less than or equal to a preset time threshold, the autonomous vehicle is controlled to brake or issue a safety driving warning to the driver; if the duration is greater than the preset time threshold, the autonomous vehicle is controlled to sound an alarm. This achieves the judgment of the autonomous vehicle's body state and improves the safety of autonomous driving by braking in time and issuing warnings or alarms.

[0136] Figure 8 This is a structural schematic diagram of an autonomous vehicle control device provided in this application, such as... Figure 8 As shown in the figure, this application embodiment also provides an autonomous driving vehicle control device, which may include:

[0137] The information acquisition module 801 is used to acquire the target top ambient light information corresponding to the top of the autonomous vehicle and the target bottom ambient light information corresponding to the bottom of the autonomous vehicle; the top of the autonomous vehicle is the outer area of ​​the roof of the autonomous vehicle and the bottom of the autonomous vehicle is the outer area of ​​the chassis of the autonomous vehicle.

[0138] The difference information determination module 802 is used to determine the target light difference information between the above-mentioned target top ambient light information and the above-mentioned target bottom ambient light information;

[0139] The vehicle status determination module 803 is used to determine that the above-mentioned autonomous driving vehicle is in an abnormal driving state when the above-mentioned target light difference information meets the preset conditions.

[0140] Duration acquisition module 804 is used to acquire the duration of the above-mentioned autonomous driving vehicle being in the above-mentioned abnormal driving state;

[0141] The control processing module 805 is used to perform autonomous driving control processing on the aforementioned autonomous vehicle based on the aforementioned duration.

[0142] In an optional embodiment, the roof of the aforementioned autonomous vehicle is provided with a plurality of top ambient light sensors, and the chassis of the aforementioned autonomous vehicle is provided with a plurality of bottom ambient light sensors. The aforementioned information acquisition module 801 includes:

[0143] Acquisition Unit 1 is used to acquire the current top ambient light information corresponding to each of the multiple top ambient light sensors based on the multiple top ambient light sensors mentioned above;

[0144] Information determination unit one is used to determine the target top ambient light information based on the current top ambient light information corresponding to each of the above-mentioned multiple top ambient light sensors;

[0145] The second acquisition unit is used to acquire the current bottom ambient light information corresponding to each of the above-mentioned bottom ambient light sensors based on the above-mentioned multiple bottom ambient light sensors;

[0146] Information determination unit two is used to determine the target bottom ambient light information based on the current bottom ambient light information corresponding to each of the above-mentioned multiple bottom ambient light sensors.

[0147] In an optional embodiment, the information determination unit one includes:

[0148] The first weight information acquisition unit is used to acquire the weight information corresponding to each of the multiple top ambient light sensors; the weight information corresponding to each of the multiple top ambient light sensors is a preset weight threshold, or the weight information corresponding to each of the multiple top ambient light sensors is determined based on the position information corresponding to each of the multiple top ambient light sensors, or the weight information corresponding to each of the multiple top ambient light sensors is determined based on a bell curve.

[0149] The determining unit 1 is used to determine the target top ambient light information based on the current top ambient light information corresponding to each of the multiple top ambient light sensors and the weight information corresponding to each of the multiple top ambient light sensors.

[0150] In an optional embodiment, the information determination unit two includes:

[0151] The second weight information acquisition unit is used to acquire the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors; the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is a preset weight threshold, or the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is determined based on the position information corresponding to each of the above-mentioned multiple bottom ambient light sensors, or the weight information corresponding to each of the above-mentioned multiple bottom ambient light sensors is determined based on the bell curve.

[0152] The second determining unit is used to determine the target bottom ambient light information based on the current bottom ambient light information corresponding to each of the multiple bottom ambient light sensors and the weight information corresponding to each of the multiple bottom ambient light sensors.

[0153] In an optional embodiment, the difference information determination module 802 includes:

[0154] The calculation unit is used to calculate the difference between the ambient light information at the top of the target and the ambient light information at the bottom of the target, and obtain the target light difference information.

[0155] In an optional embodiment, the vehicle status determination module 803 includes:

[0156] The curve acquisition unit is used to acquire a preset ambient light relationship curve; the preset ambient light relationship curve represents the relationship between the historical top ambient light information and the historical light difference information of the autonomous vehicle.

[0157] The comparison unit is used to compare the relationship between the above target light difference information and the above target top ambient light information with the above preset ambient light relationship curve to obtain the comparison result;

[0158] The state determination unit is used to determine that the autonomous vehicle is in an abnormal driving state when the relationship between the target light difference information and the target top ambient light information indicated by the comparison results does not meet the preset ambient light relationship curve.

[0159] In an optional embodiment, the above-mentioned autonomous vehicle control device further includes a preset ambient light relationship curve generation module, which includes:

[0160] A historical vehicle acquisition module is used to acquire historical vehicles; multiple historical top ambient light sensors are installed on the outer side of the roof of the aforementioned historical vehicles, and multiple historical bottom ambient light sensors are installed on the outer side of the chassis of the aforementioned historical vehicles.

[0161] The historical information acquisition module is used to acquire, based on the above-mentioned multiple historical top ambient light sensors and multiple historical bottom ambient light sensors, the historical top ambient light information corresponding to each of the above-mentioned multiple historical top ambient light sensors and the historical bottom ambient light information corresponding to each of the above-mentioned multiple historical bottom ambient light sensors respectively.

[0162] The historical top information acquisition module is used to obtain the target historical top ambient light information based on the historical top ambient light information corresponding to each of the above-mentioned multiple historical top ambient light sensors.

[0163] The historical bottom information acquisition module is used to obtain the target historical bottom ambient light information based on the historical bottom ambient light information corresponding to each of the above-mentioned multiple historical bottom ambient light sensors.

[0164] The difference information determination module is used to obtain the target historical ambient light difference information based on the above-mentioned target historical top ambient light information and the above-mentioned target historical bottom ambient light information;

[0165] The curve generation module is used to generate the preset ambient light curve based on the above-mentioned target historical top ambient light information and the above-mentioned target historical ambient light difference information.

[0166] In an optional embodiment, the control processing module 805 includes:

[0167] The brake warning unit is used to control the braking of the autonomous vehicle or to control the autonomous vehicle to issue a safe driving warning to the driver when the duration is less than or equal to a preset time threshold.

[0168] An alarm unit is used to control the autonomous vehicle to sound an alarm when the duration exceeds the preset time threshold.

[0169] This application may be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this application.

[0170] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0171] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0172] The computer program instructions used to perform the operations of this application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing state information from the computer-readable program instructions. These electronic circuits can execute the computer-readable program instructions to implement various aspects of this application.

[0173] Various aspects of this application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0174] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0175] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0176] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0177] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. An automatic driving vehicle control method characterized by, The method comprises: obtaining target top ambient light information corresponding to the top of the autonomous vehicle and target bottom ambient light information corresponding to the bottom of the autonomous vehicle; the top of the autonomous vehicle is the area outside the roof of the autonomous vehicle, and the bottom of the autonomous vehicle is the area outside the chassis of the autonomous vehicle; determining target light difference information between the target top ambient light information and the target bottom ambient light information; obtaining a preset ambient light relationship curve; the preset ambient light relationship curve represents the relationship between historical top ambient light information and historical light difference information of the autonomous vehicle; comparing the relationship between the target light difference information and the target top ambient light information with the preset ambient light relationship curve to obtain a comparison result; in a case where the comparison result indicates that the relationship between the target light difference information and the target top ambient light information does not satisfy the preset ambient light relationship curve, determining that the autonomous vehicle is in an abnormal driving state; obtaining the duration of the autonomous vehicle in the abnormal driving state; performing autonomous driving control processing on the autonomous vehicle according to the duration.

2. The method according to claim 1, characterized in that, The area outside the roof of the autonomous vehicle is provided with a plurality of top ambient light sensors, and the area outside the chassis of the autonomous vehicle is provided with a plurality of bottom ambient light sensors. The obtaining of the target top ambient light information corresponding to the top of the autonomous vehicle and the target bottom ambient light information corresponding to the bottom of the autonomous vehicle comprises: based on the plurality of top ambient light sensors, obtaining current top ambient light information corresponding to each of the plurality of top ambient light sensors; based on the current top ambient light information corresponding to each of the plurality of top ambient light sensors, determining the target top ambient light information; based on the plurality of bottom ambient light sensors, obtaining current bottom ambient light information corresponding to each of the plurality of bottom ambient light sensors; based on the current bottom ambient light information corresponding to each of the plurality of bottom ambient light sensors, determining the target bottom ambient light information.

3. The method according to claim 2, characterized in that, The determination of the target top ambient light information based on the current top ambient light information corresponding to each of the plurality of top ambient light sensors comprises: obtaining weight information corresponding to each of the plurality of top ambient light sensors; the weight information corresponding to each of the plurality of top ambient light sensors is a preset weight threshold, or the weight information corresponding to each of the plurality of top ambient light sensors is determined based on position information corresponding to each of the plurality of top ambient light sensors, or the weight information corresponding to each of the plurality of top ambient light sensors is determined based on a bell-shaped curve; based on the current top ambient light information corresponding to each of the plurality of top ambient light sensors and the weight information corresponding to each of the plurality of top ambient light sensors, determining the target top ambient light information.

4. The method according to claim 2, characterized in that, The determination of the target bottom ambient light information based on the current bottom ambient light information corresponding to each of the plurality of bottom ambient light sensors comprises: obtain weight information corresponding to each of the plurality of bottom ambient light sensors; the weight information corresponding to each of the plurality of bottom ambient light sensors is a preset weight threshold, or the weight information corresponding to each of the plurality of bottom ambient light sensors is determined based on position information corresponding to each of the plurality of bottom ambient light sensors, or the weight information corresponding to each of the plurality of bottom ambient light sensors is determined based on a clock curve; determine the target bottom ambient light information based on the current bottom ambient light information corresponding to each of the plurality of bottom ambient light sensors and the weight information corresponding to each of the plurality of bottom ambient light sensors.

5. The method of claim 1, characterized in that, The determination of the target light difference information between the target top ambient light information and the target bottom ambient light information includes: calculating the difference between the target top ambient light information and the target bottom ambient light information to obtain the target light difference information.

6. The method of claim 1, characterized in that, The generation process of the preset ambient light relationship curve includes: obtain a historical vehicle; the top of the historical vehicle is provided with a plurality of historical top ambient light sensors, and the bottom of the historical vehicle is provided with a plurality of historical bottom ambient light sensors; obtain historical top ambient light information corresponding to each of the plurality of historical top ambient light sensors and historical bottom ambient light information corresponding to each of the plurality of historical bottom ambient light sensors based on the plurality of historical top ambient light sensors and the plurality of historical bottom ambient light sensors; obtain target historical top ambient light information based on the historical top ambient light information corresponding to each of the plurality of historical top ambient light sensors; obtain target historical bottom ambient light information based on the historical bottom ambient light information corresponding to each of the plurality of historical bottom ambient light sensors; obtain target historical ambient light difference information based on the target historical top ambient light information and the target historical bottom ambient light information; generate the preset ambient light relationship curve based on the target historical top ambient light information and the target historical ambient light difference information.

7. The method according to any one of claims 1 to 5, characterized in that, The automatic driving control processing of the autonomous vehicle according to the duration includes: in the case that the duration is less than or equal to a preset time threshold, control the autonomous vehicle to brake or control the autonomous vehicle to issue a safe driving warning to a driving object; in the case that the duration is greater than the preset time threshold, control the autonomous vehicle to alarm.

8. An automatic driving vehicle control device characterized by comprising: The device includes: an information acquisition module configured to obtain target top ambient light information corresponding to a top of an autonomous vehicle and target bottom ambient light information corresponding to a bottom of the autonomous vehicle; the top of the autonomous vehicle is an outer region of a roof of the autonomous vehicle, and the bottom of the autonomous vehicle is an outer region of a chassis of the autonomous vehicle; a difference information determination module configured to determine target light difference information between the target top ambient light information and the target bottom ambient light information; and The curve acquisition unit is configured to acquire a preset ambient light relationship curve, the preset ambient light relationship curve representing a relationship between historical top ambient light information and historical light difference information of the autonomous vehicle; The comparison unit is configured to compare a relationship between the target light difference information and the target top ambient light information with the preset ambient light relationship curve to obtain a comparison result; The state determination unit is configured to determine that the autonomous vehicle is in an abnormal driving state when the comparison result indicates that the relationship between the target light difference information and the target top ambient light information does not satisfy the preset ambient light relationship curve; The duration acquisition module is configured to acquire a duration during which the autonomous vehicle is in the abnormal driving state; The control processing module is configured to perform autonomous driving control processing on the autonomous vehicle according to the duration. 9.An electronic device for controlling an autonomous vehicle, the electronic device comprising: The electronic device includes a processor and a memory, and the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the autonomous vehicle control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the autonomous vehicle control method according to any one of claims 1 to 7.

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