Vehicle control method, device, medium, equipment, chip and vehicle

Abstract

The present disclosure relates to a vehicle control method, apparatus, medium, device, chip, and vehicle. The method includes: determining one or more pending objects on a target lane; the target lane includes a first lane where the target vehicle is currently located, and / or a second lane adjacent to the first lane; obtaining a predicted trajectory of the pending object within a first preset time period based on the historical movement trajectory of the pending object; determining a target object from the pending objects based on the predicted trajectory; the target object is used to characterize an object that affects the driving of the target vehicle and is closest to the target vehicle; and controlling the driving of the target vehicle based on the target object. In this way, the target object that affects the driving safety of the vehicle and is closest to the target vehicle can be determined based on the predicted trajectory of the pending object, the target object can be accurately identified, and the vehicle driving can be controlled based on the target object, thereby improving the safety and reliability of autonomous driving.

Description

Technical Field

[0001] The present disclosure relates to the field of autonomous driving technology, and in particular, to a vehicle control method, apparatus, medium, device, chip, and vehicle. Background Art

[0002] When autonomous vehicles are driving on the road, vehicles or obstacles that may interact with the vehicle can significantly impact its movement and require special attention. CIPV (Closest In-Path Vehicle) can be used to identify the closest moving objects in the lane to the autonomous vehicle, such as motor vehicles, non-motor vehicles, pedestrians, and animals. In related technologies, there is a problem with incorrect CIPV determination, which can affect the operation of autonomous vehicles. Summary of the Invention

[0003] In order to overcome the above-mentioned problems existing in the related art, the present disclosure provides a vehicle control method, device, medium, equipment, chip and vehicle.

[0004] According to a first aspect of an embodiment of the present disclosure, a vehicle control method is provided, the method comprising:

[0005] A vehicle control method, the method comprising:

[0006] Determine one or more pending objects on a target lane; the target lane includes a first lane where the target vehicle is currently located, and / or a second lane adjacent to the first lane;

[0007] Obtaining a predicted trajectory of the object to be determined within a first preset time period based on the historical movement trajectory of the object to be determined;

[0008] Determining a target object from the undetermined objects according to the predicted trajectory; the target object is used to represent an object that affects the driving of the target vehicle and is closest to the target vehicle;

[0009] The target vehicle is controlled to travel according to the target object.

[0010] In some embodiments, when the target lane includes a first lane in which the target vehicle is currently located, the pending object includes a first moving object in the first lane; and determining the target object from the pending objects based on the predicted trajectory includes:

[0011] determining, based on the predicted trajectory of the first moving object, whether the first moving object moves out of the first lane within the first preset time period;

[0012] If it is determined that the first moving object has not moved out of the first lane within the first preset time period, taking the first moving object as a first candidate object;

[0013] The target object is determined according to the distance between the first candidate object and the target vehicle.

[0014] In some embodiments, determining, based on the predicted trajectory of the first moving object, whether the first moving object moves out of the first lane within the first preset time period includes one or more of the following:

[0015] If the predicted trajectory of the first moving object does not intersect the lane line of the first lane, determining that the first moving object has not moved out of the first lane within the first preset time period;

[0016] A first degree of overlap between first position information of the first moving object and the first lane is determined based on the predicted trajectory of the first moving object. When the first degree of overlap is greater than or equal to a first overlap threshold, it is determined that the first moving object has not moved out of the first lane within the first preset time period.

[0017] In some embodiments, when the target lane includes the second lane, the pending object includes a second moving object on the second lane; and determining the target object from the pending objects based on the predicted trajectory includes:

[0018] determining, based on the predicted trajectory of the second moving object, whether the second moving object moves to the first lane within the first preset time period;

[0019] In a case where the second moving object moves to the first lane within the first preset time period, taking the second moving object as a second candidate object;

[0020] The target object is determined according to the distance between the second candidate object and the target vehicle.

[0021] In some embodiments, determining whether the second moving object moves to the first lane within the first preset time period based on the predicted trajectory of the second moving object includes one or more of the following:

[0022] When the predicted trajectory of the second moving object intersects the lane line of the first lane, determining that the second moving object moves to the first lane within the first preset time period;

[0023] If the predicted trajectory of the second moving object intersects the lane line of the first lane and the moving direction of the second moving object is to enter the first lane, determining that the second moving object moves into the first lane within the first preset time period;

[0024] A second degree of overlap between the second position information of the second moving object and the first lane is determined based on the predicted trajectory of the second moving object. When the second degree of overlap is greater than or equal to a second overlap threshold, it is determined that the second moving object has moved to the first lane within the first preset time period.

[0025] In some embodiments, determining the target object from the pending objects according to the predicted trajectory includes:

[0026] Obtaining a predicted trajectory of the target vehicle within the first preset time period;

[0027] In a case where the predicted trajectory of the undetermined object intersects the predicted trajectory of the target vehicle, taking the undetermined object as a third candidate object;

[0028] The target object is determined according to the distance between the third candidate object and the target vehicle.

[0029] In some embodiments, the target lane is obtained by:

[0030] Obtaining lane line information of the road where the target vehicle is located;

[0031] The target lane is determined according to the lane line information and the current position of the target vehicle.

[0032] In some embodiments, obtaining lane line information of the road where the target vehicle is located includes:

[0033] Acquire the lane line information according to the high-precision map corresponding to the road where the target vehicle is located; or

[0034] The lane line information is obtained according to an environment image of the target vehicle, where the environment image is an image obtained by photographing the driving environment of the target vehicle through a photographing device.

[0035] In some embodiments, determining the target lane based on the lane line information and the current position of the target vehicle includes:

[0036] According to the lane line information and the current position of the target vehicle, the lane where the target vehicle is currently located is used as the first lane;

[0037] The second lane is determined based on a pending lane adjacent to the first lane.

[0038] In some embodiments, determining the second lane based on a pending lane adjacent to the first lane includes:

[0039] Use the pending lane as the second lane; or

[0040] When the driving direction of the vehicle on the pending lane is the same as the driving direction of the target vehicle, the pending lane is used as the second lane.

[0041] According to a second aspect of an embodiment of the present disclosure, there is provided a vehicle control device, the device comprising:

[0042] A first determination module is configured to determine one or more pending objects on a target lane; the target lane includes a first lane where the target vehicle is currently located, and / or a second lane adjacent to the first lane;

[0043] a trajectory acquisition module configured to acquire a predicted trajectory of the object to be determined within a first preset time period based on a historical movement trajectory of the object to be determined;

[0044] A second determination module is configured to determine a target object from the undetermined objects according to the predicted trajectory; the target object is used to represent an object that affects the driving of the target vehicle and is closest to the target vehicle;

[0045] The vehicle control module is configured to control the target vehicle to travel according to the target object.

[0046] In some embodiments, when the target lane includes the first lane where the target vehicle is currently located, the to-be-determined object includes a first moving object on the first lane; the second determination module is configured to determine whether the first moving object moves out of the first lane within the first preset time period based on the predicted trajectory of the first moving object; if it is determined that the first moving object has not moved out of the first lane within the first preset time period, the first moving object is used as a first candidate object; and the target object is determined based on the distance between the first candidate object and the target vehicle.

[0047] In some embodiments, the second determination module is configured to determine that the first moving object has not moved out of the first lane within the first preset time period when the predicted trajectory of the first moving object does not intersect the lane line of the first lane; or to determine a first degree of overlap between the first position information of the first moving object and the first lane based on the predicted trajectory of the first moving object, and determine that the first moving object has not moved out of the first lane within the first preset time period when the first degree of overlap is greater than or equal to a first overlap threshold.

[0048] In some embodiments, when the target lane includes the second lane, the to-be-determined object includes a second moving object on the second lane; the second determination module is configured to determine whether the second moving object moves to the first lane within the first preset time period based on the predicted trajectory of the second moving object; if the second moving object moves to the first lane within the first preset time period, the second moving object is used as a second candidate object; and the target object is determined based on the distance between the second candidate object and the target vehicle.

[0049] In some embodiments, the second determination module is configured to determine that the second moving object moves to the first lane within the first preset time period when the predicted trajectory of the second moving object intersects the lane line of the first lane; or, determine that the second moving object moves to the first lane within the first preset time period when the predicted trajectory of the second moving object intersects the lane line of the first lane and the moving direction of the second moving object is to enter the first lane; or, determine a second degree of overlap between the second position information of the second moving object and the first lane based on the predicted trajectory of the second moving object, and determine that the second moving object moves to the first lane within the first preset time period when the second degree of overlap is greater than or equal to a second overlap threshold.

[0050] In some embodiments, the second determination module is configured to obtain a predicted trajectory of the target vehicle within the first preset time period; if the predicted trajectory of the undetermined object intersects with the predicted trajectory of the target vehicle, use the undetermined object as a third candidate object; and determine the target object based on the distance between the third candidate object and the target vehicle.

[0051] In some embodiments, the apparatus further comprises:

[0052] The lane acquisition module is configured to obtain lane line information of the road where the target vehicle is located; and determine the target lane based on the lane line information and the current position of the target vehicle.

[0053] In some embodiments, the lane acquisition module is configured to obtain the lane line information based on a high-precision map corresponding to the road where the target vehicle is located; or, to obtain the lane line information based on an environmental image of the target vehicle, where the environmental image is an image obtained by photographing the driving environment of the target vehicle through a photographing device.

[0054] In some embodiments, the lane acquisition module is configured to use the lane where the target vehicle is currently located as the first lane based on the lane line information and the current position of the target vehicle; and determine the second lane based on the pending lane adjacent to the first lane.

[0055] In some embodiments, the lane acquisition module is configured to use the pending lane as the second lane; or, when the driving direction of the vehicle on the pending lane is the same as the driving direction of the target vehicle, use the pending lane as the second lane.

[0056] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0057] processor;

[0058] a memory for storing processor-executable instructions;

[0059] The processor is configured to execute the steps of the vehicle control method provided in the first aspect of the present disclosure.

[0060] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the steps of the vehicle control method provided in the first aspect of the present disclosure are implemented.

[0061] According to a fifth aspect of an embodiment of the present disclosure, a chip is provided, comprising a processor and an interface; the processor is used to read instructions to execute the steps of the vehicle control method provided in the first aspect of the present disclosure.

[0062] According to a sixth aspect of an embodiment of the present disclosure, a vehicle is provided, which includes the electronic device provided by the third aspect of the present disclosure.

[0063] The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects: determining one or more pending objects on a target lane; the target lane includes the first lane where the target vehicle is currently located, and / or a second lane adjacent to the first lane; obtaining a predicted trajectory of the pending object within a first preset time period based on the historical movement trajectory of the pending object; determining a target object from among the pending objects based on the predicted trajectory; the target object is used to represent an object that affects the driving of the target vehicle and is closest to the target vehicle; and controlling the driving of the target vehicle based on the target object. In this way, the target object that affects the driving safety of the ego vehicle and is closest to the target vehicle can be determined based on the predicted trajectory of the pending object, the target object can be accurately identified, and the vehicle's driving can be controlled based on the target object, thereby improving the safety and reliability of autonomous driving.

[0064] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0066] Figure 1 The figure is a flow chart showing a vehicle control method according to an exemplary embodiment.

[0067] Figure 2 is a block diagram of a vehicle control device according to an exemplary embodiment.

[0068] Figure 3 is a block diagram of another vehicle control device according to an exemplary embodiment.

[0069] Figure 4 It is a block diagram of an electronic device according to an exemplary embodiment.

[0070] Figure 5 is a block diagram of a vehicle according to an exemplary embodiment. DETAILED DESCRIPTION

[0071] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0072] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the corresponding data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0073] In the description of the present disclosure, terms such as "first" and "second" are used to distinguish similar objects and are not necessarily to be understood as implying a specific order or precedence. In addition, in the description with reference to the accompanying drawings, the same reference numerals in different drawings represent the same elements unless otherwise indicated.

[0074] In the description of this disclosure, unless otherwise specified, "plurality" refers to two or more than two, and other quantifiers are similar; "at least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural; "and / or" is a type of association relationship that describes associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

[0075] Although operations are described in a particular order in the accompanying drawings in the disclosed embodiments, this should not be understood as requiring that the operations be performed in the particular order shown or in a serial order, or that all of the operations shown be performed to obtain the desired results. In certain circumstances, multitasking and parallel processing may be advantageous.

[0076] First, the application scenarios of the present disclosure are explained. The present disclosure can be applied to autonomous driving scenarios, especially control scenarios of autonomous driving vehicles based on CIPV identification. During the driving process of an autonomous vehicle, determining whether an obstacle is a CIPV is an important issue that affects the safety and reliability of the vehicle. In related technologies, an autonomous vehicle can use a front camera and radar to identify the nearest vehicle in front as a CIPV, but it does not consider whether the vehicle or moving object will affect the driving safety of the vehicle itself, and there is a problem that errors in CIPV determination may affect the driving of the autonomous vehicle.

[0077] To address the aforementioned issues, the present disclosure provides a vehicle control method, apparatus, medium, device, chip, and vehicle. These methods can identify one or more pending objects in a target lane; obtain a predicted trajectory of the pending objects within a first preset time period based on their historical movement trajectories; and, based on the predicted trajectory, identify a target object (e.g., a CIPV) from among the pending objects that represents an impact on the target vehicle's travel and is closest to the target vehicle, and control the target vehicle's travel based on the target object. This allows accurate identification of the target object and control of vehicle travel based on the target object, improving the safety and reliability of autonomous driving.

[0078] The present disclosure is described below with reference to specific embodiments.

[0079] Figure 1 This is a vehicle control method according to an exemplary embodiment, which can be applied to electronic devices, such as terminal devices, such as smart phones, smart wearable devices, smart speakers, smart tablets, PDAs (Personal Digital Assistants), CPEs (Customer Premise Equipment), personal computers, and vehicle-mounted terminal devices; the electronic devices can also include servers, such as local servers or cloud servers. Figure 1 As shown, the method may include:

[0080] S101: Determine one or more pending objects on a target lane.

[0081] The target lane may include one or more lanes. For example, the target lane may include the first lane where the target vehicle is currently located, and / or a second lane adjacent to the first lane. For example, the target lane may include the first lane where the target vehicle is currently located. For another example, the target lane may include the second lane adjacent to the first lane. For another example, the target lane may include both the first lane and the second lane.

[0082] The target vehicle may be a vehicle with an automatic driving function or an assisted driving function, for example, a vehicle equipped with the above-mentioned terminal device; the target vehicle may also be a vehicle that maintains a communication connection with the above-mentioned server and is controlled by the above-mentioned server.

[0083] The above-mentioned pending object can be any one or more moving objects located in front of or to the side of the target vehicle on the target lane in the direction of travel. For example, it can include one or more moving vehicles, motor vehicles, non-motor vehicles, pedestrians and animals on the target lane.

[0084] In some embodiments, the pending object can be a moving object located in front of or to the side of the target vehicle in the direction of travel on the target lane, and within a certain distance range from the target vehicle, as detected by a camera set by the target vehicle itself; or it can be a moving object located in front of or to the side of the target vehicle in the direction of travel on the target lane, and within a certain distance range from the target vehicle, as detected by a camera outside the target vehicle. For example, the camera outside the target vehicle can include a road camera, or a camera of a target drone corresponding to the target vehicle. For example, the road camera can transmit the captured image to the electronic device, and the electronic device detects and obtains the above-mentioned pending object based on the image. For another example, the target vehicle can be equipped with a drone, and the drone follows the target vehicle and obtains an environmental image at a greater distance through the camera of the drone. The drone can transmit the environmental image to the electronic device via a wireless communication network, and the electronic device can detect and obtain the above-mentioned pending object based on the environmental image.

[0085] S102: Obtain a predicted trajectory of the object to be determined within a first preset time period according to the historical movement trajectory of the object to be determined.

[0086] Among them, the historical movement trajectory may include the movement trajectory of the pending object within a second preset time period, and the second preset time period may be any time range before the current time. For example, the time period within 10 seconds or 30 seconds before the current time may be used as the second preset time period.

[0087] In some embodiments, the historical movement trajectory of the pending object can be input into a pre-trained trajectory prediction model to obtain a predicted trajectory of the pending object within a first preset time period output by the trajectory prediction model. The trajectory prediction model can include any neural network model, such as a convolutional neural network model.

[0088] In other embodiments, the pending heading angle and the pending speed of the pending object may be calculated based on the historical movement trajectory of the pending object, and the predicted trajectory of the pending object within the first preset time period may be predicted based on the pending heading angle and the pending speed.

[0089] S103: Determine the target object from the pending objects according to the predicted trajectory.

[0090] The target object may be used to represent an object that affects the driving of the target vehicle and is closest to the target vehicle. For example, the target object may include the CIPV mentioned above.

[0091] S104: Control the target vehicle to travel according to the target object.

[0092] For example, the target vehicle can be controlled to travel according to the relative position relationship between the target object and the target vehicle and the speed of the target object.

[0093] When the distance between the target object and the target vehicle is less than or equal to a first distance threshold, and the target object's speed is less than or equal to the first target speed, the target vehicle can be controlled to decelerate to a speed less than or equal to the first target speed. The first distance threshold can be any predetermined distance, such as 10 meters, 20 meters, or 50 meters. Alternatively, the first distance threshold can be a distance determined based on the speed difference between the target vehicle and the target object, such as the product of the speed difference and a predetermined time. The predetermined time can be any time greater than 2 seconds, such as 3 seconds, 5 seconds, or 10 seconds. Alternatively, the first target speed can be any predetermined speed, such as 10 kilometers per hour or 5 kilometers per hour. Alternatively, the first target speed can be determined based on the target vehicle's current speed, such as the target vehicle's current speed or the value obtained by subtracting the predetermined speed difference from the target vehicle's current speed. For example, the first distance threshold can be 50 meters or 20 meters, and the first target speed can be 10 kilometers per hour or 5 kilometers per hour.

[0094] If the target object is a preceding vehicle traveling in the same first lane as the target vehicle, the distance between the target object and the target vehicle is greater than a first distance threshold, and the target object's speed is less than or equal to a second target speed, the target vehicle may be controlled to enter a lane change decision state, and a lane change decision may be made based on the status of vehicles in adjacent lanes (e.g., speed and distance). The second target speed may be a predetermined arbitrary speed or determined based on the target vehicle's current speed, for example, an arbitrary speed less than or equal to half the target vehicle's current speed.

[0095] If the target object is a preceding vehicle traveling in the same first lane as the target vehicle, and the target object's speed is greater than or equal to a third target speed, the target object can be used as a following vehicle, and the target vehicle can be controlled to follow the target object. The third target speed can be any pre-set speed or determined based on the target vehicle's current speed, for example, any speed within a range of plus or minus 10% of the target vehicle's current speed.

[0096] Using the above method, one or more pending objects in a target lane are identified; the target lane includes the first lane currently occupied by the target vehicle and / or a second lane adjacent to the first lane; based on the historical movement trajectory of the pending objects, a predicted trajectory of the pending objects within a first preset time period is obtained; based on the predicted trajectory, a target object is identified from among the pending objects; the target object is used to represent an object that affects the target vehicle's driving and is closest to the target vehicle; and the target vehicle's driving is controlled based on the target object. In this way, the target object that affects the driving safety of the ego vehicle and is closest to the target vehicle can be determined based on the predicted trajectory of the pending object, the target object can be accurately identified, and the vehicle's driving can be controlled based on the target object, thereby improving the safety and reliability of autonomous driving.

[0097] In another embodiment of the present disclosure, the method of determining the target object from the pending objects according to the predicted trajectory in step S103 may include one or more of the following:

[0098] Method 1: Determine a first candidate object based on the pending object on the first lane, and determine a target object based on the first candidate object.

[0099] For example, when the target lane includes the first lane where the target vehicle is currently located, the to-be-determined object may include a first moving object in the first lane; the first method may include the following steps:

[0100] First, based on the predicted trajectory of the first moving object, it is determined whether the first moving object moves out of the first lane within a first preset time period.

[0101] Secondly, when it is determined that the first moving object has not moved out of the first lane within the first preset time period, the first moving object is used as a first candidate object.

[0102] Finally, the target object is determined according to the distance between the first candidate object and the target vehicle.

[0103] For example, the first candidate object closest to the target vehicle may be used as the target object; or, N first candidate objects closest to the target vehicle may be used as the target object, where N is a preset positive integer greater than 1.

[0104] In this way, the first candidate object on the first lane where the target vehicle is currently located can be determined, and the target object can be determined based on the distance between the first candidate object and the target vehicle.

[0105] In an embodiment of the present disclosure, there are multiple ways to determine whether the first moving object moves out of the first lane within the first preset time period. For example:

[0106] In one embodiment, it may be determined that the first moving object has not moved out of the first lane within the first preset time period when the predicted trajectory of the first moving object does not cross the lane line of the first lane.

[0107] It should be noted that if the predicted trajectory does not intersect the lane line of the first lane, it means that the first moving object will continue to travel in the first lane within the first preset time period. Therefore, it can be determined that the first moving object has not moved out of the first lane within the first preset time period.

[0108] In another embodiment, a first degree of overlap between the first position information of the first moving object and the first lane can be determined based on the predicted trajectory of the first moving object. When the first degree of overlap is greater than or equal to a first overlap threshold, it is determined that the first moving object has not moved out of the first lane within the first preset time period.

[0109] For example, the first position information may include a vertical projection area of ​​the first moving object on the ground. Based on the first position information, the projection area of ​​the first moving object can be determined. Based on the first position information and the first lane information, the overlap area of ​​the first moving object within the first lane can be determined. The quotient of the overlap area and the projection area can be used as the first degree of overlap. The first overlap threshold can be any preset value between 0% and 100%, such as 30%, 50%, or 80%.

[0110] In another embodiment, it is also possible to determine whether the first moving object has a lane-changing tendency based on the relative relationship between the moving direction of the first moving object and the first lane. If it is determined that the first moving object does not have a lane-changing tendency, it is determined that the first moving object has not moved out of the first lane within the first preset time period. For example, if the moving direction of the first moving object is to leave the first lane, it can be determined that the first moving object has a lane-changing tendency; otherwise, it is determined that the first moving object has no lane-changing tendency. The moving direction of the first moving object can be determined by the first heading angle of the first moving object. For example, the predicted heading angle of the first moving object at the end of the first preset time period can be used as the first heading angle.

[0111] It should be noted that in the related art, the preceding vehicle on the first lane that is closest to the target vehicle can be regarded as a CIPV, but only the possibility of misjudgment of the distance is considered; while using the above-mentioned method in the embodiment of the present disclosure, if the preceding vehicle that is closest has a tendency to change lanes, for example, it is about to change to another lane within the first preset time period, then the preceding vehicle can no longer be regarded as the target object, but the preceding vehicle of the preceding vehicle can be regarded as the target object (such as a CIPV).

[0112] In this way, through any one of the above embodiments, or a combination of any two or more of the above embodiments, it is possible to determine whether the first moving object moves out of the first lane within the first preset time period, thereby further determining the first candidate object on the first lane in which the target vehicle is currently traveling, and determining the target object based on the first candidate object.

[0113] Method 2: Determine a second candidate object based on the pending object in the second lane, and determine the target object based on the second candidate object.

[0114] For example, when the target lane includes the second lane, the object to be determined may include a second moving object on the second lane; the second method may include the following steps:

[0115] First, based on the predicted trajectory of the second moving object, it is determined whether the second moving object moves to the first lane within a first preset time period.

[0116] Secondly, when the second moving object moves to the first lane within the first preset time period, the second moving object is taken as a second candidate object.

[0117] Finally, the target object is determined according to the distance between the second candidate object and the target vehicle.

[0118] For example, the second candidate object closest to the target vehicle may be used as the target object; or, M second candidate objects closest to the target vehicle may be used as the target object, where M is a preset positive integer greater than 1.

[0119] In this way, a second candidate object on the second lane can be determined, and the target object can be determined based on the distance between the second candidate object and the target vehicle.

[0120] In the embodiment of the present disclosure, there are also multiple ways to determine whether the second moving object moves to the first lane within the first preset time period. For example:

[0121] In one embodiment, when the predicted trajectory of the second moving object intersects the lane line of the first lane, it can be determined that the second moving object moves to the first lane within the first preset time period.

[0122] In another embodiment, when the predicted trajectory of the second moving object intersects the lane line of the first lane and the moving direction of the second moving object is to enter the first lane, it can be determined that the second moving object moves to the first lane within the first preset time period.

[0123] It should be noted that if the second moving object's moving direction is toward the first lane, this indicates that the second moving object has a lane-changing tendency toward the first lane. Conversely, if the second moving object's moving direction is away from the first lane, this indicates that the second moving object has no lane-changing tendency toward the first lane. The moving direction of the second moving object can be determined by the second heading angle of the second moving object. For example, the predicted heading angle of the second moving object at the end of the first preset time period can be used as the second heading angle.

[0124] In another embodiment, the second position information of the second moving object and the second overlap of the first lane can be determined based on the predicted trajectory of the second moving object. When the second overlap is greater than or equal to the second overlap threshold, it can be determined that the second moving object moves to the first lane within the first preset time period.

[0125] In this way, through any one of the above embodiments, or a combination of any two or more of the above embodiments, it is possible to determine whether the second moving object moves to the first lane within the first preset time period, thereby further determining a second candidate object on the second lane (that is, an adjacent lane to the lane in which the target vehicle is currently traveling), and determining the target object based on the second candidate object.

[0126] Method 3: Determine a third candidate object based on whether the predicted trajectory of the pending object intersects with the predicted trajectory of the target vehicle, and then determine the target object based on the third candidate object.

[0127] For example, the third method may include the following steps:

[0128] First, the predicted trajectory of the target vehicle within a first preset time period is obtained.

[0129] Secondly, when the predicted trajectory of the pending object intersects with the predicted trajectory of the target vehicle, the pending object is taken as the third candidate object.

[0130] Finally, the target object is determined according to the distance between the third candidate object and the target vehicle.

[0131] For example, the third candidate object closest to the target vehicle may be used as the target object; or, K third candidate objects closest to the target vehicle may be used as the target object, where K is a preset positive integer greater than 1.

[0132] In this way, a third candidate object can be determined, and the target object can be determined according to the distance between the third candidate object and the target vehicle.

[0133] It should be noted that in order to determine the target object from the undetermined objects based on the predicted trajectory, it can be determined by any one of the above methods 1, 2, and 3, or any two or three of the above methods 1, 2, and 3 can be used in combination. For example:

[0134] The first candidate object can be determined according to method one, the second candidate object can be determined according to method two, and then the target object can be determined based on the first candidate object and the second candidate object. For example, the object closest to the target vehicle among the first candidate object and the second candidate object can be used as the target object.

[0135] Similarly, the first candidate object can be determined according to method one, the second candidate object can be determined according to method two, and the third candidate object can be determined according to method three. Then, the target object can be determined based on the first candidate object, the second candidate object, and the third candidate object. For example, the object closest to the target vehicle among the first candidate object, the second candidate object, and the third candidate object can be used as the target object.

[0136] In another embodiment of the present disclosure, the target lane is obtained by:

[0137] First, obtain the lane line information of the road where the target vehicle is located.

[0138] In one embodiment, lane line information can be obtained based on a high-precision map corresponding to the road where the target vehicle is located.

[0139] For example, the high-precision map may include lane line information of the road where the target vehicle is located, and the lane line information may include lane edge lines, and the lane line information may also include lane center lines.

[0140] In another embodiment, the lane line information may be acquired based on an environment image of the target vehicle, where the environment image is an image obtained by photographing the driving environment of the target vehicle using a photographing device.

[0141] For example, lane edge lines (e.g., solid white lines, dashed white lines, solid yellow lines, double yellow lines, etc.) on a road can be determined from an environmental image and used as the lane line information. For example, the environmental image can be input into a pre-trained lane line recognition model to obtain the lane edge lines output by the lane line recognition model.

[0142] In this way, in the absence of high-precision maps, the target object (such as CIPV) can be determined through lane lines and trajectory prediction, so that the control of the autonomous driving vehicle is not affected by the map.

[0143] It should be noted that the lane lines obtained in the above two embodiments can be combined to obtain lane line information.

[0144] Then, the target lane is determined based on the lane line information and the current position of the target vehicle.

[0145] In this step, the lane in which the target vehicle is currently located can be determined based on the lane line information and the current position of the target vehicle, and the lane in which the target vehicle is currently located can be used as the first lane.

[0146] Furthermore, the second lane may be determined based on a pending lane adjacent to the first lane.

[0147] For example, the pending lane adjacent to the first lane can be used as the second lane; the adjacent lane in the same direction can also be used as the second lane; for example, when the driving direction of the vehicle on the pending lane is the same as the driving direction of the target vehicle, the pending lane is used as the second lane.

[0148] In this way, the target lane can be determined in the above manner, so that the target object can be determined according to the target lane, and the target vehicle can be controlled to travel according to the target object.

[0149] Figure 2 is a block diagram of a vehicle control device 200 according to an exemplary embodiment. Figure 2 As shown, the apparatus 200 may include:

[0150] The first determination module 201 is configured to determine one or more pending objects on a target lane; the target lane includes a first lane where the target vehicle is currently located, and / or a second lane adjacent to the first lane;

[0151] The trajectory acquisition module 202 is configured to acquire a predicted trajectory of the object to be determined within a first preset time period based on the historical movement trajectory of the object to be determined;

[0152] The second determination module 203 is configured to determine a target object from the undetermined objects according to the predicted trajectory; the target object is used to represent an object that affects the driving of the target vehicle and is closest to the target vehicle;

[0153] The vehicle control module 204 is configured to control the target vehicle to travel according to the target object.

[0154] In some embodiments, when the target lane includes the first lane where the target vehicle is currently located, the to-be-determined object includes a first moving object on the first lane; the second determination module 203 is configured to determine whether the first moving object moves out of the first lane within the first preset time period based on the predicted trajectory of the first moving object; when it is determined that the first moving object has not moved out of the first lane within the first preset time period, the first moving object is used as a first candidate object; and the target object is determined based on the distance between the first candidate object and the target vehicle.

[0155] In some embodiments, the second determination module 203 is configured to determine that the first moving object has not moved out of the first lane within the first preset time period when the predicted trajectory of the first moving object does not intersect the lane line of the first lane; or to determine a first degree of overlap between the first position information of the first moving object and the first lane based on the predicted trajectory of the first moving object, and determine that the first moving object has not moved out of the first lane within the first preset time period when the first degree of overlap is greater than or equal to a first overlap threshold.

[0156] In some embodiments, when the target lane includes the second lane, the to-be-determined object includes a second moving object on the second lane; the second determination module 203 is configured to determine whether the second moving object moves to the first lane within the first preset time period based on the predicted trajectory of the second moving object; if the second moving object moves to the first lane within the first preset time period, the second moving object is used as a second candidate object; and the target object is determined based on the distance between the second candidate object and the target vehicle.

[0157] In some embodiments, the second determination module 203 is configured to determine that the second moving object moves to the first lane within the first preset time period when the predicted trajectory of the second moving object intersects the lane line of the first lane; or, determine that the second moving object moves to the first lane within the first preset time period when the predicted trajectory of the second moving object intersects the lane line of the first lane and the moving direction of the second moving object is to enter the first lane; or, determine a second degree of overlap between the second position information of the second moving object and the first lane based on the predicted trajectory of the second moving object, and determine that the second moving object moves to the first lane within the first preset time period when the second degree of overlap is greater than or equal to a second overlap threshold.

[0158] In some embodiments, the second determination module 203 is configured to obtain the predicted trajectory of the target vehicle within the first preset time period; if the predicted trajectory of the undetermined object intersects with the predicted trajectory of the target vehicle, use the undetermined object as a third candidate object; and determine the target object based on the distance between the third candidate object and the target vehicle.

[0159] Figure 3 is a block diagram of another vehicle control device according to an exemplary embodiment. Figure 3 As shown, the device may also include:

[0160] The lane acquisition module 205 is configured to acquire lane line information of the road where the target vehicle is located; and determine the target lane according to the lane line information and the current position of the target vehicle.

[0161] In some embodiments, the lane acquisition module 205 is configured to obtain the lane line information based on a high-precision map corresponding to the road where the target vehicle is located; or, to obtain the lane line information based on an environmental image of the target vehicle, where the environmental image is an image obtained by photographing the driving environment of the target vehicle through a photographing device.

[0162] In some embodiments, the lane acquisition module 205 is configured to use the lane where the target vehicle is currently located as the first lane based on the lane line information and the current position of the target vehicle; and determine the second lane based on the pending lane adjacent to the first lane.

[0163] In some embodiments, the lane acquisition module 205 is configured to use the pending lane as the second lane; or, when the driving direction of the vehicle on the pending lane is the same as the driving direction of the target vehicle, use the pending lane as the second lane.

[0164] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0165] Figure 4 1 is a block diagram of an electronic device 2000 according to an exemplary embodiment. The electronic device 2000 may be a terminal device, such as a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, a router, an in-vehicle terminal device, etc. The electronic device 2000 may also be a server, such as a local server or a cloud server.

[0166] Reference Figure 4The electronic device 2000 may include one or more of the following components: a processing component 2002 , a memory 2004 , a power component 2006 , a multimedia component 2008 , an audio component 2010 , an input / output interface 2012 , a sensor component 2014 , and a communication component 2016 .

[0167] The processing component 2002 can be used to control the overall operation of the electronic device 2000, such as operations associated with display, phone calls, data communications, camera operation, and recording. The processing component 2002 can include one or more processors 2020 to execute instructions to complete all or part of the steps of the above-described vehicle control method. In addition, the processing component 2002 can include one or more modules to facilitate interaction between the processing component 2002 and other components. For example, the processing component 2002 can include a multimedia module to facilitate interaction between the multimedia component 2008 and the processing component 2002.

[0168] The memory 2004 is configured to store various types of data to support operations on the electronic device 2000. Examples of such data include instructions for any application or method operating on the electronic device 2000, contact data, phone book data, messages, pictures, videos, etc. The memory 2004 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0169] The power component 2006 provides power to the various components of the electronic device 2000. The power component 2006 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 2000.

[0170] The multimedia component 2008 includes a screen that provides an output interface between the electronic device 2000 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, it may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensors can detect not only the boundaries of a touch or slide action, but also the duration and pressure associated with the touch or slide action. In some embodiments, the multimedia component 2008 includes a front-facing camera and / or a rear-facing camera. When the electronic device 2000 is in an operating mode, such as a capture mode or a video mode, the front-facing camera and / or the rear-facing camera can receive external multimedia data. Each front-facing camera and the rear-facing camera can have a fixed optical lens system or have variable focal length and optical zoom capabilities.

[0171] The audio component 2010 is configured to output and / or input audio signals. For example, the audio component 2010 includes a microphone (MIC) that is configured to receive external audio signals when the electronic device 2000 is in an operating mode, such as a call mode, a recording mode, or a voice recognition mode. The received audio signals may be further stored in the memory 2004 or transmitted via the communication component 2016. In some embodiments, the audio component 2010 also includes a speaker for outputting audio signals.

[0172] The input / output interface 2012 provides an interface between the processing component 2002 and peripheral interface modules, such as a keyboard, a click wheel, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0173] The sensor assembly 2014 includes one or more sensors for providing various aspects of the status assessment of the electronic device 2000. For example, the sensor assembly 2014 can detect the open / closed state of the electronic device 2000, the relative positioning of components, such as the display and keypad of the electronic device 2000. The sensor assembly 2014 can also detect changes in the position of the electronic device 2000 or a component of the electronic device 2000, the presence or absence of user contact with the electronic device 2000, the orientation or acceleration / deceleration of the electronic device 2000, and changes in the temperature of the electronic device 2000. The sensor assembly 2014 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 2014 can also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 2014 can also include an accelerometer, a gyroscope, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0174] The communication component 2016 is configured to facilitate wired or wireless communication between the electronic device 2000 and other devices. The electronic device 2000 can access a wireless network based on a communication standard, such as Wi-Fi, 2G, 3G, 4G, 5G, 6G, NB-IOT, eMTC, etc., or a combination thereof. In an exemplary embodiment, the communication component 2016 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 2016 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0175] In an exemplary embodiment, the electronic device 2000 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the above-described vehicle control method.

[0176] The electronic device 2000 can be a standalone electronic device or part of a standalone electronic device. For example, in one embodiment, the electronic device can be an integrated circuit (IC) or a chip. The IC can be a single IC or a collection of multiple ICs. The chip can include, but is not limited to, the following types: a graphics processing unit (GPU), a central processing unit (CPU), a field programmable gate array (FPGA), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or a system-on-chip (SoC). The IC or chip can be used to execute executable instructions (or code) to implement the vehicle control method. The executable instructions can be stored in the IC or chip or obtained from other devices or equipment. For example, the IC or chip includes a processor, memory, and an interface for communicating with other devices. The executable instruction can be stored in the processor, and when the executable instruction is executed by the processor, the above-mentioned vehicle control method is implemented; alternatively, the integrated circuit or chip can receive the executable instruction through the interface and transmit it to the processor for execution, so as to implement the above-mentioned vehicle control method.

[0177] In an exemplary embodiment, the present disclosure further provides a computer-readable storage medium having computer program instructions stored thereon. When executed by a processor, these program instructions implement the steps of the vehicle control method provided by the present disclosure. For example, the computer-readable storage medium may be a non-transitory computer-readable storage medium including instructions, such as the aforementioned memory 2004 including instructions. These instructions may be executed by the processor 2020 of the electronic device 2000 to implement the vehicle control method described above. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0178] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program executable by a programmable device, and has a code portion for executing the above vehicle control method when executed by the programmable device.

[0179] Figure 5 is a block diagram of a vehicle according to an exemplary embodiment, as shown in FIG. Figure 5 As shown, the vehicle may include the electronic device 2000. It should be noted that the vehicle may be any type of vehicle, such as a car, truck, motorcycle, bus, ship, airplane, helicopter, recreational vehicle, train, etc., and the present disclosure does not impose any particular limitation thereto.

[0180] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the present disclosure. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0181] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A vehicle control method, characterized in that: The method comprises: Determine one or more pending objects on a target lane; the target lane includes a first lane where the target vehicle is currently located, and / or a second lane adjacent to the first lane; Obtaining a predicted trajectory of the object to be determined within a first preset time period based on the historical movement trajectory of the object to be determined; Determining a target object from the undetermined objects according to the predicted trajectory; the target object is used to represent an object that affects the driving of the target vehicle and is closest to the target vehicle; Controlling the target vehicle to travel according to the target object; Wherein, in a case where the target lane includes a first lane where the target vehicle is currently located, the to-be-determined object includes a first moving object on the first lane; and determining the target object from the to-be-determined objects according to the predicted trajectory includes: determining, based on the predicted trajectory of the first moving object, whether the first moving object moves out of the first lane within the first preset time period; If it is determined that the first moving object has not moved out of the first lane within the first preset time period, taking the first moving object as a first candidate object; The target object is determined according to the distance between the first candidate object and the target vehicle.

2. The method according to claim 1, characterized in that Determining, based on the predicted trajectory of the first moving object, whether the first moving object moves out of the first lane within the first preset time period includes one or more of the following: If the predicted trajectory of the first moving object does not intersect the lane line of the first lane, determining that the first moving object has not moved out of the first lane within the first preset time period; A first degree of overlap between first position information of the first moving object and the first lane is determined based on the predicted trajectory of the first moving object. When the first degree of overlap is greater than or equal to a first overlap threshold, it is determined that the first moving object has not moved out of the first lane within the first preset time period.

3. The method according to claim 1, characterized in that In a case where the target lane includes the second lane, the to-be-determined object includes a second moving object on the second lane; and determining the target object from the to-be-determined objects according to the predicted trajectory includes: determining, based on the predicted trajectory of the second moving object, whether the second moving object moves to the first lane within the first preset time period; In a case where the second moving object moves to the first lane within the first preset time period, taking the second moving object as a second candidate object; The target object is determined according to the distance between the second candidate object and the target vehicle.

4. The method according to claim 3, characterized in that Determining, based on the predicted trajectory of the second moving object, whether the second moving object moves to the first lane within the first preset time period includes one or more of the following: When the predicted trajectory of the second moving object intersects the lane line of the first lane, determining that the second moving object moves to the first lane within the first preset time period; If the predicted trajectory of the second moving object intersects the lane line of the first lane and the moving direction of the second moving object is to enter the first lane, determining that the second moving object moves into the first lane within the first preset time period; A second degree of overlap between the second position information of the second moving object and the first lane is determined based on the predicted trajectory of the second moving object. When the second degree of overlap is greater than or equal to a second overlap threshold, it is determined that the second moving object has moved to the first lane within the first preset time period.

5. The method according to claim 1, wherein Determining the target object from the pending objects according to the predicted trajectory includes: Obtaining a predicted trajectory of the target vehicle within the first preset time period; In a case where the predicted trajectory of the undetermined object intersects the predicted trajectory of the target vehicle, taking the undetermined object as a third candidate object; The target object is determined according to the distance between the third candidate object and the target vehicle.

6. The method according to any one of claims 1 to 5, characterized in that The target lane is obtained by: Obtaining lane line information of the road where the target vehicle is located; The target lane is determined according to the lane line information and the current position of the target vehicle.

7. The method according to claim 6, characterized in that The obtaining of lane line information of the road where the target vehicle is located includes: Acquire the lane line information according to the high-precision map corresponding to the road where the target vehicle is located; or The lane line information is obtained according to an environment image of the target vehicle, where the environment image is an image obtained by photographing the driving environment of the target vehicle through a photographing device.

8. The method according to claim 6, characterized in that Determining the target lane according to the lane line information and the current position of the target vehicle includes: According to the lane line information and the current position of the target vehicle, the lane where the target vehicle is currently located is used as the first lane; The second lane is determined based on a pending lane adjacent to the first lane.

9. The method according to claim 8, characterized in that The determining the second lane according to the pending lane adjacent to the first lane includes: Use the pending lane as the second lane; or When the driving direction of the vehicle on the pending lane is the same as the driving direction of the target vehicle, the pending lane is used as the second lane.

10. A vehicle control device, characterized in that: The device comprises: A first determination module is configured to determine one or more pending objects on a target lane; the target lane includes a first lane where the target vehicle is currently located, and / or a second lane adjacent to the first lane; a trajectory acquisition module configured to acquire a predicted trajectory of the object to be determined within a first preset time period based on a historical movement trajectory of the object to be determined; A second determination module is configured to determine a target object from the undetermined objects according to the predicted trajectory; the target object is used to represent an object that affects the driving of the target vehicle and is closest to the target vehicle; a vehicle control module, configured to control the target vehicle to travel according to the target object; Wherein, in a case where the target lane includes a first lane where the target vehicle is currently located, the to-be-determined object includes a first moving object on the first lane; and determining the target object from the to-be-determined objects according to the predicted trajectory includes: determining, based on the predicted trajectory of the first moving object, whether the first moving object moves out of the first lane within the first preset time period; If it is determined that the first moving object has not moved out of the first lane within the first preset time period, taking the first moving object as a first candidate object; The target object is determined according to the distance between the first candidate object and the target vehicle.

11. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to: execute the steps of the method according to any one of claims 1 to 9.

12. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

13. A chip, characterized in that: The method comprises a processor and an interface; the processor is used to read instructions to execute the steps of the method according to any one of claims 1 to 9.

14. A vehicle, characterized in that: The vehicle includes the electronic device according to claim 11.

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