Vehicle travel control method, device, terminal, storage medium, and vehicle

Abstract

The present disclosure relates to a vehicle driving control method, device, terminal, storage medium and vehicle. In the present disclosure, the image and point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located are obtained; type recognition is performed based on the image, point cloud data and temperature data to obtain the driving control type corresponding to the obstacle; a target driving control rule corresponding to the driving control type is determined based on a first mapping relationship between the driving control type and the driving control rule; and the vehicle is controlled to drive according to the target driving control rule, so that the obstacle can be accurately identified, the accuracy of obstacle identification and vehicle driving control is improved, and the driving safety of the vehicle is ensured.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of intelligent driving, and particularly relates to a vehicle driving control method and device, a terminal, a storage medium and a vehicle. BACKGROUND

[0002] With the development of intelligent driving technology, vehicles are rapidly developing towards intelligent and automatic technology, bringing better driving experience to users.

[0003] At present, vehicles can identify obstacles in the driving direction through various installed sensors, and then generate corresponding instructions to control the safe driving of the vehicle. However, the accuracy of identifying obstacles in the related technology is low, and in many cases, there will be false judgments of obstacles, resulting in deviations in the control of the vehicle, affecting the driving safety and the driving experience of users. SUMMARY

[0004] In order to solve the above technical problems, the present disclosure provides a vehicle driving control method, device, terminal, storage medium and vehicle.

[0005] A first aspect of the embodiments of the present disclosure provides a vehicle driving control method, which comprises:

[0006] obtaining image and point cloud data of an obstacle in the driving direction of the vehicle, and temperature data of the obstacle and the current environment where the obstacle is located;

[0007] performing type identification based on the image, the point cloud data and the temperature data to obtain a driving control type corresponding to the obstacle;

[0008] determining a target driving control rule corresponding to the driving control type based on a first mapping relationship between the driving control type and the driving control rule;

[0009] controlling the vehicle to drive according to the target driving control rule.

[0010] A second aspect of the embodiments of the present disclosure provides a vehicle driving control device, which comprises:

[0011] an obtaining module configured to obtain image and point cloud data of an obstacle in the driving direction of the vehicle, and temperature data of the obstacle and the current environment where the obstacle is located;

[0012] an identifying module configured to perform type identification based on the image, the point cloud data and the temperature data to obtain a driving control type corresponding to the obstacle;

[0013] a determining module configured to determine a target driving control rule corresponding to the driving control type based on a first mapping relationship between the driving control type and the driving control rule;

[0014] a control module configured to control the vehicle to travel according to a target driving control rule.

[0015] A third aspect of the embodiments of the present disclosure provides a vehicle terminal, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the vehicle driving control method of the first aspect can be implemented.

[0016] A fourth aspect of the embodiments of the present disclosure provides a computer readable storage medium, and the storage medium stores a computer program, and when the computer program is executed by a processor, the vehicle driving control method of the first aspect can be implemented.

[0017] A fifth aspect of the embodiments of the present disclosure provides a vehicle, comprising the vehicle driving control device of the second aspect, and the vehicle driving control method of the first aspect can be implemented.

[0018] Compared with the prior art, the technical solutions provided by the embodiments of the present disclosure have the following advantages:

[0019] In the embodiments of the present disclosure, the image and point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located are obtained; type recognition is performed based on the image, point cloud data and temperature data to obtain the driving control type corresponding to the obstacle; the target driving control rule corresponding to the driving control type is determined based on the first mapping relationship between the driving control type and the driving control rule; and the vehicle is controlled to travel according to the target driving control rule. The driving control type corresponding to the obstacle can be determined according to the image, point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located, and the vehicle is controlled to travel based on the target driving control rule corresponding to the driving control type. The obstacle can be accurately identified, the accuracy of obstacle identification and vehicle driving control is improved, and the driving safety of the vehicle is ensured. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and serve to explain the principles of the present disclosure together with the specification.

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced here. Obviously, for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0022] Figure 1 is a flowchart of a vehicle driving control method provided by the embodiments of the present disclosure;

[0023] Figure 2 is a flowchart of another vehicle driving control method provided by an embodiment of the present disclosure;

[0024] Figure 3 is a flowchart of still another vehicle driving control method provided by an embodiment of the present disclosure;

[0025] Figure 4 is a structural schematic diagram of a vehicle driving control device provided by an embodiment of the present disclosure;

[0026] Figure 5 is a structural schematic diagram of a vehicle-mounted terminal provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] In order to more clearly understand the above-mentioned purposes, features and advantages of the present disclosure, the schemes of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0028] In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present disclosure, but the present disclosure can also be implemented in other manners different from those described herein; obviously, the embodiments described in the specification are only a part of the embodiments of the present disclosure, and not all the embodiments.

[0029] It should be understood that each of the steps recorded in the method embodiments of the present disclosure can be executed in different orders and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the execution of the steps shown. The scope of the present disclosure is not limited in this respect.

[0030] It should be noted that, in this document, relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action, without necessarily requiring or implying any actual such relationship or order between or among the entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without more limitations, an element defined by the phrase "comprising a... " does not exclude the existence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0031] It should be noted that the modification of "one" and "multiple" mentioned in the present disclosure is illustrative and not restrictive, and those skilled in the art should understand that, unless otherwise explicitly indicated in the context, it should be understood as "one or more".

[0032] With the development of intelligent driving technology, vehicles are rapidly developing towards intelligent and automated technology, bringing better driving experience to users.

[0033] Currently, vehicles can identify obstacles in the driving direction through various installed sensors, and then generate corresponding instructions to control the safe driving of the vehicle. However, the related art has low accuracy in identifying obstacles, and in many cases, it will make false judgments about obstacles, resulting in deviations in the control of the vehicle, affecting driving safety and user driving experience.

[0034] In view of the defects of the related art in obstacle identification, the embodiments of the present disclosure provide a vehicle driving control method, device, terminal, storage medium and vehicle, which can determine the driving control type corresponding to the obstacle according to the image and point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the current environment where the obstacle is located, control the vehicle driving based on the target driving control rule corresponding to the driving control type, accurately identify the obstacle, improve the accuracy of obstacle identification and vehicle driving control, and ensure the driving safety of the vehicle.

[0035] The vehicle driving control method provided by the embodiments of the present disclosure can be executed by a vehicle terminal, which can be understood as any electronic device with processing and computing capabilities.

[0036] In order to better understand the inventive concept of the embodiments of the present disclosure, the technical solutions of the embodiments of the present disclosure will be described below in conjunction with exemplary embodiments.

[0037] Figure 1 is a flowchart of a vehicle driving control method provided by the embodiments of the present disclosure, as Figure 1 shown, the vehicle driving control method provided by the embodiments of the present disclosure can include steps 110-140:

[0038] Step 110, obtain the image and point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the current environment where the obstacle is located.

[0039] In the embodiments of the present disclosure, an image acquisition device, a point cloud acquisition device and a temperature sensing device are installed on the vehicle. The image acquisition device can acquire images of obstacles in the driving direction of the vehicle, and the image acquisition device can include common camera devices such as high-fidelity cameras, 3D cameras, infrared cameras, and blue light cameras. The point cloud acquisition device can acquire point cloud data of obstacles in the driving direction of the vehicle by emitting radar signals or pulse signals to the obstacles and then receiving reflected signals of the obstacles, and the point cloud acquisition device can include common scanning devices such as radar scanning devices, pulse scanning devices, and laser scanning devices. The temperature sensing device can acquire temperature data of obstacles in the driving direction of the vehicle and temperature data of the current environment in which the obstacles are located, and the temperature sensing device can include common temperature sensors such as infrared temperature sensors and acoustic temperature sensors. The temperature data of the obstacles can be understood as temperature data generated by the obstacles themselves, and the temperature data of the current environment can be understood as air temperature data of the current environment.

[0040] In the embodiments of the present disclosure, a vehicle-mounted terminal is installed on the vehicle, and the vehicle-mounted terminal can communicate with the image acquisition device, the point cloud acquisition device and the temperature sensing device installed on the vehicle. The vehicle-mounted terminal can acquire images of obstacles in the driving direction of the vehicle from the image acquisition device, acquire point cloud data of obstacles in the driving direction of the vehicle from the point cloud acquisition device, and acquire temperature data of obstacles in the driving direction of the vehicle and temperature data of the current environment in which the obstacles are located from the temperature sensing device.

[0041] In step 120, type identification is performed based on the images, the point cloud data and the temperature data to obtain a driving control type corresponding to the obstacles.

[0042] The driving control type in the embodiments of the present disclosure can be understood as a control type for driving control of the vehicle, and the driving control type of the obstacles can include at least one of a negligible type, a need-to-turn-around type, an emergency braking type and a prompt type.

[0043] The negligible type can be understood as an obstacle that does not affect the normal driving of the vehicle, and the vehicle can ignore the obstacle for normal driving. For example, the negligible type obstacle can be a leaf, a plastic bag, etc. The need-to-turn-around type can be understood as an obstacle that affects the normal driving of the vehicle, and the vehicle needs to turn around the obstacle when driving. For example, the need-to-turn-around type obstacle can be a stone, a paper box, etc. The emergency braking type can be understood as an obstacle that requires emergency braking of the vehicle when the vehicle faces the obstacle. For example, the emergency braking type obstacle can be a person, an animal, etc. The prompt type can be understood as an obstacle that requires prompting when the vehicle approaches the obstacle, which can include sound prompting, light prompting, etc. For example,

[0044] The prompt can be performed by controlling the sound emitted by the horn on the vehicle, the light prompt can be performed by controlling the on-off or brightness of the 5 lights on the vehicle, and the prompt type obstacle can be a bird or the like.

[0045] In the embodiments of the present disclosure, after obtaining the image and point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located, the vehicle terminal can perform type identification based on the image, the point cloud data, and the temperature data to obtain the driving control type corresponding to the obstacle.

[0046] 0Step 130, based on the first mapping relationship between the driving control type and the driving control rule

[0047] , determine the target driving control rule corresponding to the driving control type.

[0048] The driving control rule in the embodiments of the present disclosure can be understood as a rule for controlling the driving of the vehicle, and can include continuing driving, changing driving direction, emergency braking, starting the vehicle light and horn, etc.

[0049] In the embodiments of the present disclosure, the vehicle terminal can pre-construct and store the first mapping relationship between various driving control types and driving control rules, i.e., the one-to-one correspondence between the driving control type and the driving control rule. After obtaining the driving control type corresponding to the obstacle, the vehicle terminal can determine the driving control rule corresponding to the driving control type based on the first mapping relationship between the driving control type and the driving control rule, and determine the driving control rule corresponding to the driving control type as the target driving control rule.

[0050] In the embodiments of the present disclosure, the vehicle terminal can pre-construct and store the first mapping relationship between various driving control types and driving control rules, i.e., the one-to-one correspondence between the driving control type and the driving control rule. After obtaining the driving control type corresponding to the obstacle, the vehicle terminal can determine the driving control rule corresponding to the driving control type based on the first mapping relationship between the driving control type and the driving control rule, and determine the driving control rule corresponding to the driving control type as the target driving control rule.

[0051] 0Step 140, control the driving of the vehicle according to the target driving control rule.

[0052] In the embodiments of the present disclosure, after the vehicle terminal obtains the target driving control rule corresponding to the obstacle, the vehicle terminal can control the driving of the vehicle according to the target driving control rule.

[0053] In some embodiments, controlling the driving of the vehicle according to the target driving control rule can include

[0054] Step 1401-1402:

[0055] 5Step 1401, obtain the control parameter corresponding to the target driving control rule.

[0056] In the embodiments of the present disclosure, each driving control rule has a corresponding control parameter, and the control parameters corresponding to each driving control rule are pre-stored in the vehicle terminal. After obtaining the target driving control rule, the vehicle terminal can obtain the control parameter corresponding to the target driving control rule. The control parameter can be understood as a parameter for controlling the vehicle to perform the operation corresponding to the driving control rule. For example, when the target driving control rule is emergency braking, the control parameter can be the braking time and braking force of the braking system.

[0057] Step 1402, controlling the vehicle to drive according to the control parameter.

[0058] In the embodiments of the present disclosure, when the vehicle is in an intelligent driving state or an automatic driving state, the vehicle terminal can control the vehicle to drive according to the control parameter corresponding to the target driving control rule.

[0059] In other embodiments, according to the target driving control rule, the vehicle terminal can send a prompt information to the driver of the vehicle, and the prompt information can include the target driving control rule, so that the driver controls the vehicle to drive based on the target driving control rule.

[0060] In the embodiments of the present disclosure, by obtaining the image and point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located, performing type identification based on the image, the point cloud data and the temperature data to obtain the driving control type corresponding to the obstacle, determining the target driving control rule corresponding to the driving control type based on the first mapping relationship between the driving control type and the driving control rule, and controlling the vehicle to drive according to the target driving control rule, the driving control type corresponding to the obstacle can be determined according to the image, the point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located, and the vehicle can be controlled to drive based on the target driving control rule corresponding to the driving control type. The accuracy of obstacle identification and vehicle driving control can be improved, and the driving safety of the vehicle can be ensured.

[0061] Figure 2 FIG. 1 is a flowchart of a vehicle driving control method provided by an embodiment of the present disclosure, as shown in the figure, the vehicle driving control method provided by the present embodiment can include steps 210-270: Figure 2

[0062] Step 210, obtaining the image and point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located.

[0063] The steps in the embodiments of the present disclosure can refer to the content of step 110 described above, which will not be repeated here.

[0064] ​In step 220, the image of the obstacle is subjected to object recognition to obtain an object type of the obstacle.

[0065] In the embodiments of the present disclosure, the object type can be understood as the category of the object, and can include an animal type and a non-animal type. The animal type can be understood as a type of the object whose shape is an animal shape, and the non-animal type can be understood as a type of the object whose shape is not an animal shape.

[0066] In the embodiments of the present disclosure, the vehicle terminal can perform object recognition on the image of the obstacle to obtain the object type of the obstacle. For example, when the obstacle is a person, the object type of the obstacle is the animal type; when the obstacle is an animal toy, the object type of the obstacle is the animal type; and when the obstacle is a stone, the object type of the obstacle is the non-animal type.

[0067] In some embodiments, the object recognition on the image of the obstacle to obtain the object type of the obstacle can include steps 2201-2202.

[0068] In step 2201, the image is compared with object images in an object database to identify a target object image matched with the image.

[0069] In the embodiments of the present disclosure, the object database stores images of various objects and object types corresponding to the respective object images. After obtaining the image of the obstacle, the vehicle terminal can compare the image of the obstacle with the object images in the object database to identify a target object image matched with the image of the obstacle.

[0070] In step 2202, an object type corresponding to the target object image is determined as the object type of the obstacle.

[0071] In the embodiments of the present disclosure, the vehicle terminal can determine the object type corresponding to the target object image in the object database, and determine the object type corresponding to the target object image as the object type of the obstacle.

[0072] In other embodiments, the object recognition on the image of the obstacle to obtain the object type of the obstacle can include that the vehicle terminal inputs the image of the obstacle into a preset object type recognition model, performs object type recognition based on the object type recognition model, and obtains the object type of the obstacle. The object type recognition model can be understood as a kind of deep learning neural model. A data set including the image of the obstacle and the object type of the obstacle can be constructed in advance, and the model training, verification and testing are performed based on the data set to obtain an accurate object type recognition model. The specific training method can refer to related technologies, and will not be described here.

[0073] In step 230, the contour size of the obstacle is calculated based on the point cloud data of the obstacle.

[0074] In the embodiments of the present disclosure, the point cloud data of the obstacle includes the three-dimensional coordinates (x, y, z) of each surface point of the obstacle in the system coordinate system of the point cloud collection device, and the vehicle terminal can obtain the boundary point cloud data corresponding to the boundary of the obstacle based on the point cloud data of the obstacle, and then calculate the contour size of the obstacle according to the boundary point cloud data.

[0075] In step 240, life identification is performed based on the temperature difference between the first temperature data of the surface of the obstacle and the second temperature data of the current environment in which the obstacle is located, and the biological characteristics of the obstacle are determined.

[0076] In the embodiments of the present disclosure, the biological characteristics can be understood as characteristics of living things, including passive temperature-changing objects and autonomous constant-temperature objects. The passive temperature-changing object can be understood as an object whose temperature changes with the change of the ambient temperature, such as stones, plastic bags, temperature-changing animals, etc., and the temperature-changing animals can include reptiles, etc. The autonomous constant-temperature object can be understood as an object whose temperature does not change with the change of the ambient temperature, i.e., an object whose temperature can be kept within a constant range, such as mammals, etc., and the mammals can include humans, cats, dogs, birds, etc.

[0077] In the embodiments of the present disclosure, the vehicle terminal can perform life identification based on the temperature difference between the first temperature data of the surface of the obstacle and the second temperature data of the current environment in which the obstacle is located, and determine the biological characteristics of the obstacle, i.e., determine whether the obstacle has life.

[0078] In some embodiments, performing life identification based on the temperature difference between the first temperature data of the surface of the obstacle and the second temperature data of the current environment in which the obstacle is located to determine the biological characteristics of the obstacle can include steps 2401-2405:

[0079] In step 2401, a first temperature curve of the surface of the obstacle is constructed based on the first temperature data of each surface point of the obstacle.

[0080] In the embodiments of the present disclosure, the vehicle terminal can fuse the three-dimensional coordinates of each surface point of the obstacle with the first temperature data of each surface point of the obstacle to construct the first temperature curve of the surface of the obstacle. The first temperature curve includes the temperature data of each surface point of the obstacle.

[0081] In step 2402, a second temperature curve of the current environment in which the obstacle is located is constructed based on the second temperature data of the current environment in which each surface point of the obstacle is located.

[0082] In the embodiments of the present disclosure, for each surface point of the obstacle, the vehicle terminal can determine second temperature data of the current environment in which each surface point is located, and then fuse the three-dimensional coordinates of each surface point of the obstacle with the second temperature data of the current environment in which each surface point of the obstacle is located, to construct a second temperature curve of the current environment in which the obstacle is located. The second temperature curve includes the second temperature data of the current environment in which each surface point of the obstacle is located.

[0083] In step 2403, the fitting degree of the first temperature curve and the second temperature curve is calculated.

[0084] In the embodiments of the present disclosure, the fitting degree of the first temperature curve and the second temperature curve can be understood as the degree of fit between the first temperature curve and the second temperature curve, and can evaluate the size of the temperature difference between the first temperature data of the surface of the obstacle and the second temperature data of the current environment in which the obstacle is located. The greater the fitting degree, the closer the first temperature curve and the second temperature curve, that is, the smaller the temperature difference between the surface temperature of the obstacle and the temperature of the current environment in which the obstacle is located; the smaller the fitting degree, the more distant the first temperature curve and the second temperature curve, that is, the greater the temperature difference between the surface temperature of the obstacle and the temperature of the current environment in which the obstacle is located.

[0085] In the embodiments of the present disclosure, the vehicle terminal can calculate the fitting degree of the first temperature curve and the second temperature curve.

[0086] In some embodiments, calculating the fitting degree of the first temperature curve and the second temperature curve can include steps 240301-240305:

[0087] In step 240301, based on the first temperature data of each surface point of the obstacle, a first temperature component value corresponding to each surface point of the obstacle at a unit distance in each spatial coordinate axis direction is obtained.

[0088] In the embodiments of the present disclosure, the vehicle terminal can obtain the first temperature component value corresponding to each surface point of the obstacle at a unit distance in each spatial coordinate axis direction from the first temperature data of each surface point of the obstacle. The spatial coordinate axis can be understood as a coordinate axis in a three-dimensional coordinate system, and can include an x-axis in a horizontal direction, a y-axis in a vertical direction, and a z-axis in a vertical direction. The x-axis, the y-axis, and the z-axis are perpendicular to each other.

[0089] In some embodiments, for any surface point of the obstacle, a first unit target point at a unit distance in the x-axis direction of the surface point can be determined, and a temperature of the first unit target point is determined as a first temperature component value corresponding to a unit distance in the x-axis direction of the surface point; a second unit target point at a unit distance in the y-axis direction of the surface point can be determined, and a temperature of the second unit target point is determined as a first temperature component value corresponding to a unit distance in the y-axis direction of the surface point; a third unit target point at a unit distance in the z-axis direction of the surface point can be determined, and a temperature of the third unit target point is determined as a first temperature component value corresponding to a unit distance in the z-axis direction of the surface point.

[0090] In other embodiments, for any surface point of the obstacle, a first distance target point at a first preset distance in the x-axis direction of the surface point can be determined, and a ratio of a temperature of the first distance target point to the first preset distance is determined as a first temperature component value corresponding to a unit distance in the x-axis direction of the surface point; a second distance target point at the first preset distance in the y-axis direction of the surface point can be determined, and a ratio of a temperature of the second distance target point to the first preset distance is determined as a first temperature component value corresponding to a unit distance in the y-axis direction of the surface point; a third distance target point at the first preset distance in the z-axis direction of the surface point can be determined, and a ratio of a temperature of the third distance target point to the first preset distance is determined as a first temperature component value corresponding to a unit distance in the z-axis direction of the surface point. The first preset distance can be set as needed, which is not specifically limited here.

[0091] In step 240302, based on the second temperature data of the current environment where each surface point of the obstacle is located, a second temperature component value corresponding to a unit distance in each spatial coordinate axis direction of a current environment point corresponding to each surface point of the obstacle is obtained.

[0092] In the embodiments of the present disclosure, the vehicle terminal can obtain a second temperature component value corresponding to a unit distance in each spatial coordinate axis direction of a current environment point corresponding to each surface point of the obstacle from the second temperature data of the current environment where each surface point of the obstacle is located. The current environment point corresponding to the surface point can be a current environment point closest to the surface point, or a current environment point at a second preset distance from the surface point. The second preset distance can be set as needed, which is not specifically limited here.

[0093] In some embodiments, for a current environment point corresponding to any surface point of the obstacle, a fourth unit target point at a unit distance in the x-axis direction of the current environment point can be determined, and a temperature of the fourth unit target point is determined as a second temperature component value corresponding to the current environment point at a unit distance in the x-axis direction; a fifth unit target point at a unit distance in the y-axis direction of the current environment point can be determined, and a temperature of the fifth unit target point is determined as a second temperature component value corresponding to the current environment point at a unit distance in the y-axis direction; a sixth unit target point at a unit distance in the z-axis direction of the current environment point can be determined, and a temperature of the sixth unit target point is determined as a second temperature component value corresponding to the current environment point at a unit distance in the z-axis direction.

[0094] In some embodiments, for a current environment point corresponding to any surface point of the obstacle, a fourth unit target point at a unit distance in the x-axis direction of the current environment point can be determined, and a temperature of the fourth unit target point is determined as a second temperature component value corresponding to the current environment point at a unit distance in the x-axis direction; a fifth unit target point at a unit distance in the y-axis direction of the current environment point can be determined, and a temperature of the fifth unit target point is determined as a second temperature component value corresponding to the current environment point at a unit distance in the y-axis direction; a sixth unit target point at a unit distance in the z-axis direction of the current environment point can be determined, and a temperature of the sixth unit target point is determined as a second temperature component value corresponding to the current environment point at a unit distance in the z-axis direction.

[0095] In step 240303, for each surface point of the obstacle, a difference value between the first temperature component value and the corresponding second temperature component value in the spatial coordinate axis direction of the surface point is calculated.

[0096] In the embodiments of the present disclosure, after obtaining the first temperature component value and the second temperature component value of each surface point of the obstacle in the spatial coordinate axis direction, the vehicle terminal can calculate, for each surface point of the obstacle, a difference value between the first temperature component value and the corresponding second temperature component value in the spatial coordinate axis direction of the surface point. Specifically, a difference value dx between the first temperature component value in the x-axis direction of the surface point and the second temperature component value in the x-axis direction of the surface point can be calculated, a difference value dy between the first temperature component value in the y-axis direction of the surface point and the second temperature component value in the y-axis direction of the surface point can be calculated, and a difference value dz between the first temperature component value in the z-axis direction of the surface point and the second temperature component value in the z-axis direction of the surface point can be calculated. The difference values of the three temperature components corresponding to the surface point can be represented as (dx, dy, dz).

[0097] In step 240304, the vehicle terminal sums up the difference values corresponding to each spatial coordinate axis direction of each surface point of the obstacle to obtain a difference sum corresponding to each spatial coordinate axis direction.

[0098] In the embodiments of the present disclosure, after obtaining the difference values of the first temperature component values and the second temperature component values corresponding to each spatial coordinate axis direction of each surface point of the obstacle, the vehicle terminal can sum up the difference values corresponding to each spatial coordinate axis direction of each surface point of the obstacle to obtain a difference sum corresponding to each spatial coordinate axis direction. Specifically, the vehicle terminal can sum up the difference dx between the first temperature component value and the second temperature component value of each surface point of the obstacle in the x-axis direction to obtain a difference sum Dx corresponding to the x-axis direction, sum up the difference dy between the first temperature component value and the second temperature component value of each surface point of the obstacle in the y-axis direction to obtain a difference sum Dy corresponding to the y-axis direction, and sum up the difference dz between the first temperature component value and the second temperature component value of each surface point of the obstacle in the z-axis direction to obtain a difference sum Dz corresponding to the z-axis direction.

[0099] In step 240305, the vehicle terminal sums up the difference sums corresponding to each spatial coordinate axis direction to obtain the fitting degree.

[0100] In the embodiments of the present disclosure, after obtaining the difference sums corresponding to each spatial coordinate axis direction, the vehicle terminal can sum up the difference sums corresponding to each spatial coordinate axis direction to obtain the fitting degree. Specifically, the fitting degree DIFF=Dx+Dy+Dz.

[0101] In some embodiments, summing up the difference sums corresponding to each spatial coordinate axis direction to obtain the fitting degree can include S11-S13:

[0102] S11, determining a target coordinate component weight corresponding to the object type of the obstacle based on a third mapping relationship between the object type and the coordinate component weight.

[0103] In the embodiments of the present disclosure, the vehicle terminal pre-stores a third mapping relationship between the object type and the coordinate component weight, i.e., the object type and the coordinate component weight correspond one-to-one. The coordinate component can be understood as an orthogonal component in each coordinate axis direction. The vehicle terminal can determine a target coordinate component weight corresponding to the object type of the obstacle based on the third mapping relationship between the object type and the coordinate component weight. Specifically, the coordinate component weight corresponding to the non-animal type is lower than the coordinate component weight corresponding to the non-animal type, so as to increase the fitting degree corresponding to the obstacle of the non-animal type and reduce the fitting degree corresponding to the obstacle of the animal type.

[0104] S12, determining a target component weight corresponding to the difference sum of each spatial coordinate axis direction based on the target coordinate component weight.

[0105] In the embodiments of the present disclosure, the vehicle terminal can determine the difference value and the corresponding target component weight of each spatial coordinate axis direction based on the target coordinate component weight. Specifically, the difference value and the corresponding target component weight of the x-axis direction are Ax, the difference value and the corresponding target component weight of the y-axis direction are Ay, and the difference value and the corresponding target component weight of the z-axis direction are Az.

[0106] In the embodiments of the present disclosure, the vehicle terminal can determine the difference value and the corresponding target component weight of each spatial coordinate axis direction based on the target coordinate component weight. Specifically, the difference value and the corresponding target component weight of the x-axis direction are Ax, the difference value and the corresponding target component weight of the y-axis direction are Ay, and the difference value and the corresponding target component weight of the z-axis direction are Az.

[0107] In the embodiments of the present disclosure, the vehicle terminal can determine the difference value and the corresponding target component weight of each spatial coordinate axis direction based on the target coordinate component weight. Specifically, the difference value and the corresponding target component weight of the x-axis direction are Ax, the difference value and the corresponding target component weight of the y-axis direction are Ay, and the difference value and the corresponding target component weight of the z-axis direction are Az.

[0108] In the embodiments of the present disclosure, the vehicle terminal can determine the difference value and the corresponding target component weight of each spatial coordinate axis direction based on the target coordinate component weight. Specifically, the difference value and the corresponding target component weight of the x-axis direction are Ax, the difference value and the corresponding target component weight of the y-axis direction are Ay, and the difference value and the corresponding target component weight of the z-axis direction are Az.

[0109] In the embodiments of the present disclosure, if the fitting degree is greater than the preset threshold value, it indicates that the temperature of the obstacle is close to the current environment temperature, and the vehicle terminal can determine that the biological characteristics of the obstacle is a passive temperature object. The preset threshold value can be set as needed, which is not limited here.

[0110] In the embodiments of the present disclosure, if the fitting degree is less than or equal to the preset threshold value, it indicates that the temperature of the obstacle is greatly different from the current environment temperature, and the vehicle terminal can determine that the biological characteristics of the obstacle is an autonomous constant temperature object.

[0111] In the embodiments of the present disclosure, if the fitting degree is less than or equal to the preset threshold value, it indicates that the temperature of the obstacle is greatly different from the current environment temperature, and the vehicle terminal can determine that the biological characteristics of the obstacle is an autonomous constant temperature object.

[0112] In the embodiments of the present disclosure, after obtaining the article type, the contour size and the biological characteristics of the obstacle, the vehicle terminal can determine the driving control type corresponding to the obstacle based on the article type, the contour size and the biological characteristics of the obstacle.

[0113] In the embodiments of the present disclosure, after obtaining the article type, the contour size and the biological characteristics of the obstacle, the vehicle terminal can determine the driving control type corresponding to the obstacle based on the article type, the contour size and the biological characteristics of the obstacle.

[0114] In some embodiments, if the article type of the obstacle is a non-animal type, the contour size is less than or equal to the preset size threshold value, and the biological characteristics is a passive temperature object, the vehicle terminal can determine that the driving control type corresponding to the obstacle is an ignorable type. For example, the obstacle is a leaf, a plastic bag, etc. The preset size threshold value can be set as needed, which is not limited here.

[0115] In some embodiments, if the object type of the obstacle is a non-animal type, the contour size is greater than the preset size threshold, and the biological feature is a passive variable temperature object, the vehicle terminal can determine that the driving control type corresponding to the obstacle is a need-to-turn type or an emergency braking type. For example, the obstacle is a stone, a paper box, or the like.

[0116] In some embodiments, if the object type of the obstacle is an animal type, the contour size is less than or equal to the preset size threshold, and the biological feature is an autonomous constant temperature object, the driving control type corresponding to the obstacle is determined to be a prompt type. For example, the obstacle is a small bird or the like.

[0117] In some embodiments, if the object type of the obstacle is an animal type, the contour size is greater than the preset size threshold, and the biological feature is an autonomous constant temperature object, the driving control type corresponding to the obstacle is determined to be an emergency braking type. For example, the obstacle is a human or the like.

[0118] Step 260, determining a target driving control rule corresponding to the driving control type based on a first mapping relationship between the driving control type and the driving control rule.

[0119] Step 270, controlling the vehicle to drive according to the target driving control rule.

[0120] The steps 260-270 in the embodiments of the present disclosure can refer to the content of the steps 130-140 described above, which will not be repeated here.

[0121] Therefore, the object type, the contour size, and the biological feature of the obstacle can be determined according to the image, the point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located. Then, the driving control type corresponding to the obstacle is determined according to the object type, the contour size, and the biological feature of the obstacle. The vehicle is controlled to drive based on the target driving control rule corresponding to the driving control type. The obstacle can be accurately identified, the accuracy of obstacle identification and vehicle driving control is improved, and the driving safety of the vehicle is ensured.

[0122] Figure 3 is a flowchart of a vehicle driving control method provided by the embodiments of the present disclosure, as Figure 3 shown, the vehicle driving control method provided by the embodiments of the present disclosure can include steps 301-310:

[0123] Step 301, obtaining the image and the point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located.

[0124] The steps in the embodiments of the present disclosure can refer to the content of the step 110 described above, which will not be repeated here.

[0125] Step 302, based on the point cloud data of the obstacle, the distance between the obstacle and the vehicle is calculated.

[0126] In the embodiments of the present disclosure, the vehicle terminal can obtain the first three-dimensional coordinates of each surface point of the obstacle in the system coordinate system of the point cloud collection device from the point cloud data of the obstacle, then convert the first three-dimensional coordinates in the system coordinate system into the second three-dimensional coordinates in the vehicle coordinate system according to the conversion relationship between the system coordinate system and the vehicle coordinate system, and calculate the distance between the obstacle and the vehicle according to the second three-dimensional coordinates of the surface points of the obstacle.

[0127] Step 303, based on the second mapping relationship between the distance and the adjustment ratio, the adjustment ratio corresponding to the distance is determined as the target adjustment ratio of the image.

[0128] The adjustment ratio in the embodiments of the present disclosure can be understood as the ratio of adjusting the image size of the obstacle.

[0129] In the embodiments of the present disclosure, the second mapping relationship between the distance and the adjustment ratio is pre-stored in the vehicle terminal, that is, the distance and the adjustment ratio are one-to-one corresponding. After obtaining the distance between the obstacle and the vehicle, the vehicle terminal can determine the adjustment ratio corresponding to the distance based on the second mapping relationship between the distance and the adjustment ratio, and determine the adjustment ratio corresponding to the distance as the target adjustment ratio of the image.

[0130] Step 304, orthodontic processing is performed on the image of the obstacle based on the target adjustment ratio, to obtain an orthodontically processed image.

[0131] In the embodiments of the present disclosure, after obtaining the target adjustment ratio, the vehicle terminal can perform orthodontic processing on the image of the obstacle based on the target adjustment ratio, to obtain the orthodontically processed image of the obstacle. For example, when the image of the obstacle is smaller than the actual size of the obstacle, each size in the image of the obstacle can be enlarged by the same ratio according to the target adjustment ratio, so that the image of the obstacle conforms to the actual size of the obstacle, and similarly, when the image of the obstacle is larger than the actual size of the obstacle, each size in the image of the obstacle can be reduced by the same ratio according to the target adjustment ratio, so that the image of the obstacle conforms to the actual size of the obstacle.

[0132] Therefore, the image of the obstacle can be orthodontically processed, so that the obtained image of the obstacle conforms to the actual size of the obstacle, which can prevent the near-large and far-small from affecting the subsequent identification of the object of the obstacle, and improve the accuracy of identification.

[0133] Step 305, object identification is performed on the image of the obstacle, to obtain the object type of the obstacle.

[0134] Step 306, based on the point cloud data of the obstacle, the contour size of the obstacle is calculated.

[0135] Step 307, determining the biological feature of the obstacle based on a temperature difference between the first temperature data of the obstacle surface and the second temperature data of the current environment where the obstacle is located.

[0136] Step 308, determining the driving control type corresponding to the obstacle based on the article type, the contour size, and the biological feature of the obstacle.

[0137] Step 309, determining the target driving control rule corresponding to the driving control type based on a first mapping relationship between the driving control type and the driving control rule.

[0138] Step 310, controlling the vehicle to drive according to the target driving control rule.

[0139] The steps 305-310 in the embodiments of the present disclosure can refer to the content of the steps 220-270 described above, which will not be repeated here.

[0140] Therefore, the article type, the contour size, and the biological feature of the obstacle can be determined according to the image, the point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located, and then the driving control type corresponding to the obstacle can be determined according to the article type, the contour size, and the biological feature of the obstacle, the vehicle can be controlled to drive based on the target driving control rule corresponding to the driving control type, the obstacle can be accurately identified, the accuracy of obstacle identification and vehicle driving control can be improved, and the driving safety of the vehicle can be ensured.

[0141] Figure 4 is a structural schematic diagram of a vehicle driving control device provided by an embodiment of the present disclosure. The device can be understood as the vehicle-mounted terminal described above or part of the functional modules in the vehicle-mounted terminal. As shown in the figure, the vehicle driving control device 400 can include: Figure 4

[0142] The acquisition module 410 is configured to acquire the image and the point cloud data of the obstacle in the driving direction of the vehicle, and the temperature data of the obstacle and the current environment where the obstacle is located.

[0143] The identification module 420 is configured to perform type identification based on the image, the point cloud data, and the temperature data to obtain the driving control type corresponding to the obstacle.

[0144] The determination module 430 is configured to determine the target driving control rule corresponding to the driving control type based on a first mapping relationship between the driving control type and the driving control rule.

[0145] The control module 440 is configured to control the vehicle to drive according to the target driving control rule.

[0146] Optionally, the identification module 420 can include:​

[0147] The identification sub-module is configured to perform object identification on the image of the obstacle to obtain an object type of the obstacle.

[0148] The calculation sub-module is configured to calculate a contour size of the obstacle based on the point cloud data of the obstacle.

[0149] The first determination sub-module is configured to determine a biological feature of the obstacle based on a temperature difference between the first temperature data of the surface of the obstacle and second temperature data of a current environment in which the obstacle is located.

[0150] The second determination sub-module is configured to determine a driving control type corresponding to the obstacle based on the object type, the contour size, and the biological feature of the obstacle.

[0151] Optionally, the identification sub-module can include:

[0152] The comparison unit is configured to compare the image with object images in an object database to identify a target object image matching the image.

[0153] The first determination unit is configured to determine an object type corresponding to the target object image as the object type of the obstacle.

[0154] Optionally, the identification sub-module can include:

[0155] The identification unit is configured to input the image of the obstacle into a preset object type identification model, perform object identification based on the object type identification model, and obtain the object type of the obstacle.

[0156] Optionally, the identification module 420 can include:

[0157] The calculation sub-module is configured to calculate a distance between the obstacle and the vehicle based on the point cloud data of the obstacle.

[0158] The third determination sub-module is configured to determine an adjustment ratio corresponding to the distance as a target adjustment ratio of the image based on a second mapping relationship between the distance and the adjustment ratio.

[0159] The processing sub-module is configured to perform orthodontic processing on the image of the obstacle based on the target adjustment ratio to obtain an orthodontically processed image.

[0160] Optionally, the first determination sub-module can include:

[0161] The first construction unit is configured to construct a first temperature curve of the surface of the obstacle based on the first temperature data of each surface point of the obstacle.

[0162] a second constructing unit configured to construct a second temperature curve of a current environment in which the obstacle is located based on second temperature data of the current environment in which each surface point of the obstacle is located;

[0163] a calculating unit configured to calculate a fitting degree of the first temperature curve and the second temperature curve;

[0164] a second determining unit configured to determine that a biological feature of the obstacle is a passive temperature-changing object if the fitting degree is greater than a preset threshold;

[0165] a third determining unit configured to determine that the biological feature of the obstacle is an autonomous constant-temperature object if the fitting degree is less than or equal to the preset threshold.

[0166] Optionally, the calculating unit can include:

[0167] a first obtaining sub-unit configured to obtain, based on first temperature data of each surface point of the obstacle, a first temperature component value corresponding to each surface point of the obstacle at a unit distance in each spatial coordinate axis direction;

[0168] a second obtaining sub-unit configured to obtain, based on second temperature data of a current environment in which each surface point of the obstacle is located, a second temperature component value corresponding to a current environment point corresponding to each surface point of the obstacle at a unit distance in each spatial coordinate axis direction;

[0169] a calculating sub-unit configured to calculate, for each surface point of the obstacle, a difference value between the first temperature component value of the surface point in each spatial coordinate axis direction and the corresponding second temperature component value;

[0170] a first summing sub-unit configured to sum up the difference values corresponding to each surface point of the obstacle in each spatial coordinate axis direction to obtain a difference sum corresponding to each spatial coordinate axis direction;

[0171] a second summing sub-unit configured to sum up the difference sums corresponding to each spatial coordinate axis direction to obtain the fitting degree.

[0172] Optionally, the second summing sub-unit can include:

[0173] a first determining component configured to determine a target coordinate component weight corresponding to an item type of the obstacle based on a third mapping relationship between the item type and the coordinate component weight;

[0174] a second determining component configured to determine a target component weight corresponding to the difference sum of each spatial coordinate axis direction based on the target coordinate component weight;

[0175] a summing component configured to perform weighted sum processing on the difference values corresponding to the spatial coordinate axes directions based on the target component weights, to obtain the fitting degree.

[0176] Optionally, the second determining sub-module can include:

[0177] The fourth determining unit is configured to determine that the driving control type corresponding to the obstacle is a negligible type if the object type of the obstacle is a non-animal type, the contour size is less than or equal to a preset size threshold, and the biological feature is a passive temperature-changing object.

[0178] The fifth determining unit is configured to determine that the driving control type corresponding to the obstacle is a need-to-avoid type or an emergency braking type if the object type of the obstacle is a non-animal type, the contour size is greater than the preset size threshold, and the biological feature is a passive temperature-changing object.

[0179] The sixth determining unit is configured to determine that the driving control type corresponding to the obstacle is a prompting type if the object type of the obstacle is an animal type, the contour size is less than or equal to a preset size threshold, and the biological feature is an autonomous constant-temperature object.

[0180] The seventh determining unit is configured to determine that the driving control type corresponding to the obstacle is an emergency braking type if the object type of the obstacle is an animal type, the contour size is greater than the preset size threshold, and the biological feature is an autonomous constant-temperature object.

[0181] Optionally, the driving control type of the obstacle includes at least one of a negligible type, a need-to-avoid type, an emergency braking type, and a prompting type.

[0182] Optionally, the control module 440 can include:

[0183] The acquisition sub-module is configured to acquire a control parameter corresponding to the target driving control rule.

[0184] The control sub-module is configured to control the vehicle to drive according to the control parameter; or

[0185] The prompting sub-module is configured to send a prompting information to a driver of the vehicle, the prompting information including the target driving control rule, so that the driver controls the vehicle to drive based on the target driving control rule.

[0186] The vehicle driving control device provided by the embodiments of the present disclosure can implement the method of any of the above-mentioned embodiments, and has similar implementation modes and beneficial effects, which will not be described here again.

[0187] The vehicle terminal in the embodiments of the present disclosure can be understood as any kind of device with processing and computing capabilities.

[0188] The vehicle terminal in the embodiments of the present disclosure can be understood as any kind of device with processing and computing capabilities.

[0189] Figure 5 is a structural schematic diagram of a vehicle terminal provided by the embodiments of the present disclosure, as Figure 5 shown, the vehicle terminal 500 can include a processor 510 and a memory 520, wherein the memory 520 stores a computer program 521, and when the computer program 521 is executed by the processor 510, the method provided by any of the above embodiments can be implemented, and the execution manner and beneficial effects are similar, which will not be repeated here.

[0190] Of course, in order to simplify, Figure 5 only some of the components of the vehicle terminal 500 related to the present disclosure are shown in the embodiments of the present disclosure, and components such as buses, input / output interfaces, input devices and output devices are omitted. In addition, according to specific application circumstances, the vehicle terminal 500 can also include any other appropriate components.

[0191] The embodiments of the present disclosure provide a computer readable storage medium, the storage medium stores a computer program, and when the computer program is executed by a processor, the method of any of the above embodiments can be implemented, and the execution manner and beneficial effects are similar, which will not be repeated here.

[0192] The above computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: electrical connections with one or more wires, portable disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any appropriate combination of the above.

[0193] The computer program above can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++, etc., and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer device, partly on the user's computer device, as a stand-alone software package, partly on the user's computer device and partly on a remote computer device or entirely on the remote computer device or server.

[0194] The vehicle according to the embodiments of the present disclosure can include the vehicle travel control device described above, and can implement the method according to any one of the embodiments described above, and have similar implementation manners and beneficial effects, which will not be described herein again.

[0195] The above descriptions are only specific embodiments of the present disclosure to enable a person skilled in the art to understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to these embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A vehicle travel control method characterized by comprising: The method comprises: obtaining image and point cloud data of an obstacle in a driving direction of a vehicle, and temperature data of the obstacle and a current environment where the obstacle is located; performing type identification based on the image, the point cloud data and the temperature data to obtain a driving control type corresponding to the obstacle; determining a target driving control rule corresponding to the driving control type based on a first mapping relationship between the driving control type and a driving control rule; controlling the vehicle to drive according to the target driving control rule; the type identification based on the image, the point cloud data and the temperature data to obtain the driving control type corresponding to the obstacle comprises: performing object identification on the image of the obstacle to obtain an object type of the obstacle; calculating a contour size of the obstacle based on the point cloud data of the obstacle; determining a biological feature of the obstacle based on a temperature difference between first temperature data of a surface of the obstacle and second temperature data of the current environment where the obstacle is located; determining the driving control type corresponding to the obstacle based on the object type, the contour size and the biological feature of the obstacle; the determination of the biological feature of the obstacle based on the temperature difference between the first temperature data of the surface of the obstacle and the second temperature data of the current environment where the obstacle is located comprises: constructing a first temperature curve of the surface of the obstacle based on the first temperature data of each surface point of the obstacle; constructing a second temperature curve of the current environment where the obstacle is located based on the second temperature data of the current environment where each surface point of the obstacle is located; calculating a fitting degree of the first temperature curve and the second temperature curve; if the fitting degree is greater than a preset threshold, determining that the biological feature of the obstacle is a passive temperature-changing object; if the fitting degree is less than or equal to the preset threshold, determining that the biological feature of the obstacle is an autonomous constant-temperature object.

2. The method of claim 1, wherein, the object identification on the image of the obstacle to obtain the object type of the obstacle comprises: comparing the image with object images in an object database to identify a target object image matched with the image; determining an object type corresponding to the target object image as the object type of the obstacle.

3. The method of claim 1, wherein, the object identification on the image of the obstacle to obtain the object type of the obstacle comprises: inputting the image of the obstacle into a preset object type identification model to perform object identification based on the object type identification model to obtain the object type of the obstacle.

4. The method of claim 1, wherein, before the object identification on the image of the obstacle to obtain the object type of the obstacle, the method further comprises: calculating a distance between the obstacle and the vehicle based on the point cloud data of the obstacle; determining an adjustment ratio corresponding to the distance as a target adjustment ratio of the image based on a second mapping relationship between the distance and the adjustment ratio; performing orthodontic processing on the image of the obstacle based on the target adjustment ratio to obtain an orthodontically processed image.

5. The method of claim 1, wherein, the calculation of the fitting degree of the first temperature curve and the second temperature curve comprises: obtain, based on the first temperature data of each surface point of the obstacle, a first temperature component value corresponding to each surface point of the obstacle at a unit distance in each spatial coordinate axis direction; obtain, based on second temperature data of a current environment in which each surface point of the obstacle is located, a second temperature component value corresponding to each surface point of the obstacle at a unit distance in each spatial coordinate axis direction; for each surface point of the obstacle, calculate a difference value between the first temperature component value and the corresponding second temperature component value of the surface point in each spatial coordinate axis direction; sum the difference values corresponding to each surface point of the obstacle in each spatial coordinate axis direction to obtain a sum of difference values corresponding to each spatial coordinate axis direction; sum the sum of difference values corresponding to each spatial coordinate axis direction to obtain the fitting degree.

6. The method of claim 5, wherein, The summing processing of the sum of difference values corresponding to each spatial coordinate axis direction to obtain the fitting degree comprises: determining a target coordinate component weight corresponding to the object type of the obstacle based on a third mapping relationship between object types and coordinate component weights; determining a target component weight corresponding to the sum of difference values in each spatial coordinate axis direction based on the target coordinate component weight; performing weighted sum processing on the sum of difference values corresponding to each spatial coordinate axis direction based on the target component weight to obtain the fitting degree.

7. The method of claim 1, wherein, The determining of the driving control type corresponding to the obstacle based on the object type, the contour size, and the biological feature of the obstacle comprises: if the object type of the obstacle is a non-animal type, the contour size is less than or equal to a preset size threshold, and the biological feature is a passive temperature-changing object, determining that the driving control type corresponding to the obstacle is a negligible type; if the object type of the obstacle is a non-animal type, the contour size is greater than a preset size threshold, and the biological feature is a passive temperature-changing object, determining that the driving control type corresponding to the obstacle is a need-to-avoid type or an emergency braking type; if the object type of the obstacle is an animal type, the contour size is less than or equal to a preset size threshold, and the biological feature is an autonomous constant-temperature object, determining that the driving control type corresponding to the obstacle is a prompt type; if the object type of the obstacle is an animal type, the contour size is greater than a preset size threshold, and the biological feature is an autonomous constant-temperature object, determining that the driving control type corresponding to the obstacle is an emergency braking type.

8. The method of claim 1, wherein, The driving control type of the obstacle comprises at least one of a negligible type, a need-to-avoid type, an emergency braking type, and a prompt type.

9. The method of claim 1, wherein, The controlling of the vehicle to travel according to the target driving control rule comprises: obtaining a control parameter corresponding to the target driving control rule; controlling the vehicle to travel according to the control parameter; or, sending prompt information including the target driving control rule to a driver of the vehicle, so that the driver controls the vehicle to travel based on the target driving control rule.

10. A vehicle travel control device characterized by comprising: comprises: An acquisition module is configured to acquire image and point cloud data of an obstacle in a driving direction of a vehicle, and temperature data of the obstacle and a current environment where the obstacle is located; An identification module is configured to perform type identification based on the image, the point cloud data, and the temperature data to obtain a driving control type corresponding to the obstacle; A determination module is configured to determine a target driving control rule corresponding to the driving control type based on a first mapping relationship between the driving control type and the driving control rule; A control module is configured to control the vehicle to drive according to the target driving control rule. The type identification based on the image, the point cloud data, and the temperature data to obtain the driving control type corresponding to the obstacle includes: performing object identification on the image of the obstacle to obtain an object type of the obstacle; calculating a contour size of the obstacle based on the point cloud data of the obstacle; determining a biological feature of the obstacle based on a temperature difference between first temperature data of a surface of the obstacle and second temperature data of the current environment where the obstacle is located; determining the driving control type corresponding to the obstacle based on the object type, the contour size, and the biological feature of the obstacle. The determination of the biological feature of the obstacle based on the temperature difference between the first temperature data of the surface of the obstacle and the second temperature data of the current environment where the obstacle is located includes: constructing a first temperature curve of the surface of the obstacle based on the first temperature data of each surface point of the obstacle; constructing a second temperature curve of the current environment where the obstacle is located based on the second temperature data of the current environment where each surface point of the obstacle is located; calculating a fitting degree of the first temperature curve and the second temperature curve; if the fitting degree is greater than a preset threshold, determining that the biological feature of the obstacle is a passive temperature-changing object; if the fitting degree is less than or equal to the preset threshold, determining that the biological feature of the obstacle is an autonomous constant-temperature object.

11. A vehicle terminal, characterized by including: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the vehicle driving control method in any one of claims 1-9 is implemented.

12. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and when the computer program is executed by the processor, the vehicle driving control method in any one of claims 1-9 is implemented.

13. A vehicle characterized by comprising: The vehicle includes the vehicle driving control device of claim 10.

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