阅读说明：本技术 车辆交互信息校验方法、装置、电子设备和可读介质 (Vehicle interaction information verification method and device, electronic equipment and readable medium ) 是由 陈雨青 倪凯 于 2021-09-28 设计创作，主要内容包括：本公开的实施例公开了车辆交互信息校验方法、装置、电子设备和可读介质。该方法的一具体实施方式包括：获取当前车辆的当前车辆信息和目标车辆的目标车辆信息；生成当前车辆预测轨迹和目标车辆预测轨迹；基于当前车辆信息、目标车辆信息、当前车辆预测轨迹和目标车辆预测轨迹,生成车辆交互信息和车辆冲突时长；根据车辆交互信息,生成车辆速度值序列集；响应于确定车辆冲突时长大于预设时长阈值,对车辆速度值序列集中每个车辆速度值序列进行校验以生成第一校验值,得到第一校验值集合；将第一校验值集合中满足第一预设条件的第一校验值对应的车辆速度值序列确定为车辆交互信息校验结果。该实施方式可以提高对车辆交互信息校验的效率。(The embodiment of the disclosure discloses a vehicle interaction information checking method and device, electronic equipment and a readable medium. One embodiment of the method comprises: acquiring current vehicle information of a current vehicle and target vehicle information of a target vehicle; generating a current vehicle predicted track and a target vehicle predicted track; generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted track and the target vehicle predicted track; generating a vehicle speed value sequence set according to the vehicle interaction information; in response to the fact that the vehicle conflict duration is larger than a preset duration threshold, verifying each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value, and obtaining a first verification value set; and determining a vehicle speed value sequence corresponding to a first check value meeting a first preset condition in the first check value set as a vehicle interactive information check result. The embodiment can improve the efficiency of vehicle interactive information verification.)

1. A vehicle interaction information verification method comprises the following steps:

acquiring current vehicle information of a current vehicle and target vehicle information of a target vehicle;

inputting the current vehicle information and the target vehicle information into a preset track prediction model to generate a current vehicle predicted track and a target vehicle predicted track;

generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted track and the target vehicle predicted track;

generating a vehicle speed value sequence set according to the vehicle interaction information;

in response to the fact that the vehicle conflict duration is larger than a preset duration threshold, verifying each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value, and obtaining a first verification value set;

and determining a vehicle speed value sequence corresponding to a first check value meeting a first preset condition in the first check value set as a vehicle interactive information check result.

2. The method of claim 1, wherein the method further comprises:

in response to the fact that the vehicle conflict time length is determined to be smaller than or equal to the preset time length threshold value, verifying each vehicle speed value sequence in the vehicle speed value sequence set to generate a second verification value, and obtaining a second verification value set;

and determining a vehicle speed value sequence corresponding to a second check value meeting a second preset condition in the second check value set as a vehicle interactive information check result.

3. The method according to one of claims 1-2, wherein the method further comprises:

and sending a control instruction to a control terminal of the current vehicle according to the vehicle speed value sequence included in the vehicle interaction information verification result so as to control the current vehicle to move.

4. The method of claim 1, wherein the current vehicle information includes a current vehicle coordinate value, a current vehicle velocity value, and a current vehicle acceleration value, and the target vehicle information includes a target vehicle coordinate value, a target vehicle velocity value, a target vehicle length value, and a target vehicle acceleration value; and

generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory and the target vehicle predicted trajectory, comprising:

determining an overlapping trajectory between the current vehicle predicted trajectory and the target vehicle predicted trajectory;

determining a distance value between the current vehicle and the overlapping track as a current vehicle distance value by using the current vehicle coordinate value;

and generating the vehicle conflict time length based on the current vehicle distance value, the current vehicle speed value and a preset time length parameter group.

5. The method of claim 4, wherein generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory, further comprises:

generating a predicted target vehicle running distance value according to the target vehicle speed value, the target vehicle acceleration value and a preset risk duration;

generating a predicted target vehicle running speed value according to the target vehicle speed value, the target vehicle acceleration value and the preset risk duration;

determining a distance value between the target vehicle and the overlapped track according to the target vehicle coordinate value and the target vehicle length value;

generating first interaction execution information in response to determining that the predicted target vehicle travel distance value and the predicted target vehicle travel speed value meet a first preset interaction condition, wherein the first preset interaction condition is that the predicted target vehicle travel distance value is smaller than the distance value, and the predicted target vehicle travel speed value is smaller than or equal to zero;

and determining the first interaction execution information as the vehicle interaction information.

6. The method of claim 5, wherein generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory, further comprises:

generating second interaction execution information in response to determining that the predicted target vehicle travel distance value meets a second preset interaction condition, wherein the second preset interaction condition is that the predicted target vehicle travel distance value is greater than or equal to the distance value and is smaller than the sum of the target vehicle length value, the distance value and the length value of the overlapping track in the target vehicle predicted track direction;

and determining the second interaction execution information as the vehicle interaction information.

7. The method of claim 5, wherein generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory, further comprises:

generating third interaction execution information in response to determining that the predicted target vehicle travel distance value and the predicted target vehicle travel speed value do not satisfy the first preset interaction condition and the predicted target vehicle travel distance value does not satisfy the second preset interaction condition;

and determining the third interaction execution information as the vehicle interaction information.

8. The method of claim 4, wherein the verifying each vehicle speed value sequence of the set of vehicle speed value sequences to generate a first verification value in response to determining that the vehicle conflict duration is greater than a preset duration threshold comprises:

acquiring surrounding vehicle information of the current vehicle;

and in response to the fact that the vehicle conflict time length is larger than the preset time length threshold value, verifying each vehicle speed value sequence in the vehicle speed value sequence set based on the current vehicle acceleration value and the surrounding vehicle information to generate a first verification value, and obtaining a first verification value set.

9. A vehicle mutual information verification device includes:

an acquisition unit configured to acquire current vehicle information of a current vehicle and target vehicle information of a target vehicle;

an input unit configured to input the current vehicle information and the target vehicle information to a preset trajectory prediction model to generate a current vehicle predicted trajectory and a target vehicle predicted trajectory;

a first generating unit configured to generate vehicle interaction information and a vehicle collision duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory;

a second generating unit configured to generate a vehicle speed value sequence set according to the vehicle interaction information;

a third generating unit, configured to verify each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value in response to determining that the vehicle collision duration is greater than a preset duration threshold, resulting in a first verification value set;

the determining unit is configured to determine a vehicle speed value sequence corresponding to a first check value meeting a first preset condition in the first check value set as a vehicle interaction information check result.

10. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon,

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-8.

Technical Field

The embodiment of the disclosure relates to the technical field of computers, in particular to a vehicle interaction information verification method, a vehicle interaction information verification device, electronic equipment and a readable medium.

Background

The vehicle interactive information verifying method is one technology for verifying vehicle interactive information. At present, when vehicle interaction information is checked, the method generally adopted is as follows: the detected current vehicle data and other vehicle data are input into a preset vehicle behavior model (for example, a behavior decision model based on a Markov decision theory or a decision model based on reinforcement learning, etc.), vehicle interaction information is generated, and then the generated vehicle interaction information is verified, so that a vehicle interaction information verification result is obtained.

However, when the vehicle mutual information verification is performed in the above manner, the following technical problems often occur:

firstly, the dependency of the vehicle behavior model algorithm on training data is high, and driving knowledge needs to be sorted, managed and updated, so that the vehicle behavior model algorithm is high in complexity and weak in generalization capability, and the speed of outputting vehicle interaction information in a special scene (such as a traffic intersection scene) is low, so that the efficiency of generating vehicle interaction information is low, and further, the efficiency of checking the vehicle interaction information is reduced;

secondly, the intention of other vehicles and the structural characteristics of urban roads are not considered comprehensively, so that the accuracy of checking the vehicle interaction information is reduced.

Disclosure of Invention

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose a vehicle mutual information verification method, apparatus, electronic device and readable medium to solve one or more of the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a vehicle interaction information verification method, including: acquiring current vehicle information of a current vehicle and target vehicle information of a target vehicle; inputting the current vehicle information and the target vehicle information into a preset track prediction model to generate a current vehicle predicted track and a target vehicle predicted track; generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory and the target vehicle predicted trajectory; generating a vehicle speed value sequence set according to the vehicle interaction information; in response to the fact that the vehicle conflict duration is larger than a preset duration threshold value, verifying each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value, and obtaining a first verification value set; and determining a vehicle speed value sequence corresponding to a first check value meeting a first preset condition in the first check value set as a vehicle interactive information check result.

In a second aspect, some embodiments of the present disclosure provide a vehicle interaction information verification apparatus, including: an acquisition unit configured to acquire current vehicle information of a current vehicle and target vehicle information of a target vehicle; an input unit configured to input the current vehicle information and the target vehicle information to a preset trajectory prediction model to generate a current vehicle predicted trajectory and a target vehicle predicted trajectory; a first generating unit configured to generate vehicle interaction information and a vehicle collision duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory; the second generating unit is configured to generate a vehicle speed value sequence set according to the vehicle interaction information; the third generating unit is configured to verify each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value in response to the fact that the vehicle conflict duration is larger than a preset duration threshold value, and obtain a first verification value set; the determining unit is configured to determine a vehicle speed value sequence corresponding to a first check value meeting a first preset condition in the first check value set as a vehicle interaction information check result.

In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.

The above embodiments of the present disclosure have the following advantages: by the vehicle interaction information verification method of some embodiments of the present disclosure, the efficiency of verifying vehicle interaction information can be improved. Specifically, the reason why the efficiency of verifying the vehicle interaction information is reduced is that: the vehicle behavior model algorithm has a high dependency on training data and needs to sort, manage and update driving knowledge, so that the vehicle behavior model algorithm has high complexity and weak generalization capability, and the speed of outputting vehicle interaction information in a special scene (for example, a traffic intersection scene) is low, so that the efficiency of generating vehicle interaction information is low. Based on this, the vehicle interaction information verification method of some embodiments of the present disclosure first obtains current vehicle information of a current vehicle and target vehicle information of a target vehicle. Then, the current vehicle information and the target vehicle information are input into a preset track prediction model to generate a current vehicle predicted track and a target vehicle predicted track. And then generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted track and the target vehicle predicted track. The current vehicle information of the current vehicle and the target vehicle information of the target vehicle are introduced to generate a vehicle predicted track and a target vehicle predicted track, and the generated vehicle predicted track and the target vehicle predicted track are reused to generate vehicle interaction information. Thus, the dependency of the vehicle trajectory prediction model on the training data is reduced. And avoid the consolidation, management and updating of driving knowledge. Therefore, the complexity of a vehicle track prediction model used for generating vehicle interaction information can be reduced to a certain extent, the generalization capability of a vehicle behavior model is improved, and the better output speed of the vehicle interaction information can be kept in a special scene. Thus, the efficiency of generating the vehicle traffic information can be improved. Furthermore, the efficiency of checking the vehicle interactive information can be improved.

Drawings

The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.

FIG. 1 is a schematic diagram of one application scenario of a vehicle mutual information verification method of some embodiments of the present disclosure;

FIG. 2 is a flow diagram of some embodiments of a vehicle interaction information verification method according to the present disclosure;

FIG. 3 is a flow chart of further embodiments of a vehicle mutual information verification method according to the present disclosure;

FIG. 4 is a schematic block diagram of some embodiments of a vehicle mutual information verification apparatus according to the present disclosure;

FIG. 5 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.

It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.

It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.

It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.

The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Fig. 1 is a schematic diagram of an application scenario of a vehicle mutual information verification method according to some embodiments of the present disclosure.

In the application scenario of fig. 1, first, the computing device 101 may acquire current vehicle information 102 of a current vehicle and target vehicle information 103 of a target vehicle. Next, the computing device 101 may input the current vehicle information 102 and the target vehicle information 103 to a preset trajectory prediction model 104 to generate a current vehicle predicted trajectory 105 and a target vehicle predicted trajectory 106. Next, the computing device 101 may generate vehicle interaction information 107 and a vehicle conflict duration 108 based on the current vehicle information 102, the target vehicle information 103, the current vehicle predicted trajectory 105, and the target vehicle predicted trajectory 106. The computing device 101 may then generate a vehicle speed value sequence set 109 from the vehicle interaction information 107 described above. Thereafter, in response to determining that the vehicle collision duration 108 is greater than the preset duration threshold, the computing device 101 may verify each vehicle speed value sequence in the vehicle speed value sequence set 109 to generate a first verification value, resulting in a first verification value set 110. Finally, the computing device 101 may determine, as the vehicle interaction information verification result 111, a vehicle speed value sequence corresponding to a first verification value satisfying a first preset condition in the first verification value set 110.

The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.

It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.

With continued reference to fig. 2, a flow 200 of some embodiments of a vehicle interaction information verification method according to the present disclosure is shown. The process 200 of the vehicle interactive information verification method comprises the following steps:

in step 201, current vehicle information of a current vehicle and target vehicle information of a target vehicle are acquired.

In some embodiments, an executing subject (such as the computing device 101 shown in fig. 1) of the vehicle mutual information verification method may acquire the current vehicle information of the current vehicle and the target vehicle information of the target vehicle in a wired manner or a wireless manner. The current vehicle information may include a first vehicle information group for characterizing vehicle information of the current vehicle within a historical time period (e.g., within 3 seconds of the end of the current time). Each first vehicle information in the first vehicle information group may correspond to each time point within the above-described historical time period. The first vehicle information may include: coordinate values, velocity values, heading angles, acceleration values, angular velocity values, and the like of the vehicle. The above-mentioned target vehicle information may be a vehicle detected in advance, having the highest probability of collision with the current vehicle for a certain period of time (for example, for 3 seconds). The target vehicle information may include a second vehicle information group. Each second vehicle information in the second vehicle information group may be for each time point within one of the above-mentioned historical time periods. Vehicle information characterizing one other vehicle at various points in time within the historical time period. The respective second vehicle information in each second vehicle information group may correspond to a time point of the respective first vehicle information in the first vehicle information group. The second vehicle information may also include coordinate values, velocity values, heading angles, acceleration values, and angular velocity values of the vehicle.

As an example, in the scenario of an intersection, when the current vehicle is traveling straight, a situation is encountered where the oncoming vehicle turns left. At this time, the probability of collision between the vehicle closest to the current vehicle and the current vehicle is highest. Therefore, it can be determined as the target vehicle.

Step 202, inputting the current vehicle information and the target vehicle information into a preset track prediction model to generate a predicted track of the current vehicle and a predicted track of the target vehicle.

In some embodiments, the executing entity may input the current vehicle information and the target vehicle information to a preset trajectory prediction model to generate a predicted trajectory of the current vehicle and a predicted trajectory of the target vehicle. Wherein, the trajectory prediction model may be: deep convolutional neural networks or semi-markov models, etc. For example, the travel track of the vehicle may be predicted by the half-markov model with each first vehicle information in the first vehicle information group including the coordinate value, the velocity value, the heading angle, the acceleration value, and the angular velocity value of the vehicle as the vehicle state at each time in the history period.

And step 203, generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted track and the target vehicle predicted track.

In some embodiments, the execution subject may generate the vehicle interaction information and the vehicle collision duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory. The vehicle interaction information may be used to represent a motion state adjustment manner of the current vehicle (for example, an adjustment manner for uniformly decelerating the current vehicle, an adjustment manner for uniformly accelerating the current vehicle, an adjustment manner for maintaining the current vehicle at a constant speed, or the like) generated in the case where the current motion state of the target vehicle is generated. The vehicle interaction information may be generated by:

the method comprises the following steps of firstly, determining an overlapping area between the current vehicle predicted track and the target vehicle predicted track. The overlapping area may be a rectangular area or a diamond area. One pair of opposite sides of the rectangular area or the diamond-shaped area may be the length value of the target vehicle, and the other pair of opposite sides may be the length value of the current vehicle.

And secondly, determining a minimum distance value between the coordinate value included in the current vehicle information and the overlapped area. Wherein the minimum distance value may be used to characterize a distance between the current vehicle and the overlap region. In addition, a minimum distance value between a coordinate value included in the target vehicle information and a side length of the overlap region from the near end of the target vehicle may be determined.

And thirdly, determining the ratio of the minimum distance value to the speed value included by the current vehicle information as the collision duration of the front vehicle. Wherein the preceding vehicle conflict duration may be used to characterize a duration of time for which the current vehicle arrives at the conflict area. Similarly, the target vehicle conflict period may also be generated by the above steps.

And fourthly, responding to the fact that the collision time length of the front vehicle and/or the collision time length of the target vehicle are smaller than or equal to a preset collision time length threshold value, and generating first interaction information. The first interaction information may include a danger indicator for indicating that there is a great risk of collision between the target vehicle and the current vehicle at a certain time.

And fifthly, responding to the situation that the vehicle conflict time length is larger than a preset conflict time length threshold value, and generating second interactive information. The second interactive information may include a safety indication for indicating that there is a smaller risk of collision between the target vehicle and the current vehicle at a certain time.

And step 204, generating a vehicle speed value sequence set according to the vehicle interaction information.

In some embodiments, the execution subject may generate a vehicle speed value sequence set according to the vehicle interaction information. And if the current vehicle interaction execution information comprises a danger identifier. And inputting the speed value and the acceleration value included by the first vehicle information of the current vehicle at the current moment and the minimum distance value between the current vehicle and the overlapping area into a preset kinematics model to generate a speed value sequence. The sequence of speed values may be such that the current vehicle speed is reduced to zero before reaching the overlap region. Specifically, the kinematic model may adjust the acceleration within a preset acceleration range (e.g., an acceleration variation amount less than 3 meters per second). The vehicle speed value prediction may be performed with the speed value of the above-described current vehicle as an initial value after each adjustment so that the speed is reduced to zero before the current vehicle reaches the overlap area. While recording the predicted speed value of the vehicle at the same time interval (e.g., 0.05 seconds). Thereby, a sequence of vehicle speed values may be generated.

Step 205, in response to determining that the vehicle conflict duration is greater than the preset duration threshold, verifying each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value, so as to obtain a first verification value set.

In some embodiments, the executing entity may verify each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value in response to determining that the vehicle collision duration is greater than a preset duration threshold, so as to obtain a first verification value set. Wherein a vehicle conflict duration greater than a preset duration threshold (e.g., 3 seconds) may be indicative of a lack of a risk of collision between the target vehicle and the current and vehicle corresponding to the predicted conflict duration. The verification may be that the acceleration value corresponding to each vehicle speed value in the vehicle speed value sequence set is determined as a first verification value.

Step 206, determining a vehicle speed value sequence corresponding to a first check value meeting a first preset condition in the first check value set as a vehicle interaction information check result.

In some embodiments, the executing entity may determine, as the vehicle interaction information verification result, a vehicle speed value sequence corresponding to a first verification value satisfying a first preset condition in the first verification value set. The first preset condition may be a minimum first check value in the first check value set. In particular, the selected minimum first check value (i.e., acceleration value) may be used to characterize that the current vehicle needs to decelerate to zero at a minimum rate before reaching the overlap region. Therefore, the condition of vehicle runaway caused by overlarge speed change can be avoided, and the driving safety is improved.

Optionally, the executing main body may further perform the following steps:

in response to the fact that the vehicle conflict time length is smaller than or equal to the preset time length threshold value, verifying each vehicle speed value sequence in the vehicle speed value sequence set to generate a second verification value, and obtaining the second verification value set. The collision duration is smaller than or equal to the preset duration threshold value, and the collision risk between the target vehicle corresponding to the predicted collision duration and the current vehicle can be represented. The verification may be to determine the acceleration value corresponding to each vehicle speed value in the vehicle speed value sequence set as the second verification value.

And secondly, determining a vehicle speed value sequence corresponding to a second check value meeting a second preset condition in the second check value set as a vehicle interactive information check result. The second preset condition may be a minimum second check value in the second check value set.

Optionally, the execution main body may further send a control instruction to the control terminal of the current vehicle according to the vehicle speed value sequence included in the vehicle interaction information verification result to control the current vehicle to move. The vehicle control terminal may be configured to send a control instruction according to the vehicle speed value sequence included in the vehicle interaction information verification result, so that the speed of the current vehicle may be changed according to each speed value in the speed value sequence. Thus, it is possible to control the movement of the vehicle and to avoid the occurrence of a collision of the vehicle. Further, safety of vehicle driving is improved.

The above embodiments of the present disclosure have the following advantages: by the vehicle interaction information verification method of some embodiments of the present disclosure, the efficiency of verifying vehicle interaction information can be improved. Specifically, the reason why the efficiency of verifying the vehicle interaction information is reduced is that: the vehicle behavior model algorithm has a high dependency on training data and needs to sort, manage and update driving knowledge, so that the vehicle behavior model algorithm has high complexity and weak generalization capability, and the speed of outputting vehicle interaction information in a special scene (for example, a traffic intersection scene) is low, so that the efficiency of generating vehicle interaction information is low. Based on this, the vehicle interaction information verification method of some embodiments of the present disclosure first obtains current vehicle information of a current vehicle and target vehicle information of a target vehicle. Then, the current vehicle information and the target vehicle information are input into a preset track prediction model to generate a current vehicle predicted track and a target vehicle predicted track. And then generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted track and the target vehicle predicted track. The current vehicle information of the current vehicle and the target vehicle information of the target vehicle are introduced to generate a vehicle predicted track and a target vehicle predicted track, and the generated vehicle predicted track and the target vehicle predicted track are reused to generate vehicle interaction information. Thus, the dependency of the vehicle trajectory prediction model on the training data is reduced. And avoid the consolidation, management and updating of driving knowledge. Therefore, the complexity of a vehicle track prediction model used for generating vehicle interaction information can be reduced to a certain extent, the generalization capability of a vehicle behavior model is improved, and the better output speed of the vehicle interaction information can be kept in a special scene. Thus, the efficiency of generating the vehicle traffic information can be improved. Furthermore, the efficiency of checking the vehicle interactive information can be improved.

With further reference to FIG. 3, a flow 300 of further embodiments of a vehicle mutual information verification method is shown. The process 300 of the vehicle interaction information verification method includes the following steps:

step 301, obtaining current vehicle information of a current vehicle and target vehicle information of a target vehicle.

Step 302, inputting the current vehicle information and the target vehicle information into a preset track prediction model to generate a predicted track of the current vehicle and a predicted track of the target vehicle.

In some embodiments, the specific implementation manner and technical effects of the steps 301 and 302 can refer to the steps 201 and 202 in the embodiments corresponding to fig. 2, which are not described herein again.

Step 303, generating vehicle interaction information and vehicle collision duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory and the target vehicle predicted trajectory.

In some embodiments, an executing subject (e.g., the computing device 101 shown in fig. 1) of the vehicle interaction information verification method may generate the vehicle interaction information and the vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory. The current vehicle information may include a current vehicle coordinate value, a current vehicle velocity value, and a current vehicle acceleration value, and the target vehicle information may include a target vehicle coordinate value, a target vehicle velocity value, a target vehicle length value, and a target vehicle acceleration value. The vehicle conflict duration may be generated by:

first, an overlapping trajectory between the predicted trajectory of the current vehicle and the predicted trajectory of the target vehicle is determined. First, the vehicle width value of the current vehicle may be used as the track width value of the predicted travel track of the current vehicle. Then, the target vehicle width value may be set as a track width value of the target travel track. Finally, the overlapping area of two tracks with width values can be determined as overlapping tracks. The overlapping traces may be rectangular regions or diamond-shaped regions. One pair of opposite sides of the rectangular area or the diamond-shaped area may be the length value of the target vehicle, and the other pair of opposite sides may be the length value of the current vehicle.

And secondly, determining the distance value between the current vehicle and the overlapped track as the current vehicle distance value by using the current vehicle coordinate value. Wherein the current vehicle distance value may be determined as a shortest distance between the current vehicle coordinates and the overlapping trajectory.

And thirdly, generating a vehicle conflict time length based on the current vehicle distance value, the current vehicle speed value and a preset time length parameter group. The preset time duration parameter group may include two time duration parameters. One may be a time duration factor and the other may be a time duration constant. The vehicle collision duration may be obtained by determining a product of a ratio of the current vehicle distance value to the current vehicle speed value and a duration coefficient, and adding the duration constant.

As an example, the above-described duration factor may be 2.737. The above-mentioned time duration constant may be 0.1512.

In some optional implementation manners of some embodiments, the executing entity generates the vehicle interaction information and the vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory, and may further include the following steps:

and step one, generating a predicted target vehicle running distance value according to the target vehicle speed value, the target vehicle acceleration value and a preset risk duration. Wherein the preset risk duration may be 3 seconds. The distance traveled by the target vehicle may be derived by inputting the target vehicle velocity value, the target vehicle acceleration value, and the risk period into a formula for calculating a trip (e.g., calculating a trip from velocity and acceleration).

And secondly, generating a predicted target vehicle running speed value according to the target vehicle speed value, the target vehicle acceleration value and the preset risk duration. The difference between the target vehicle speed value and the product of the target vehicle acceleration value and the preset risk duration can be determined as a predicted target vehicle running speed value.

And thirdly, determining a distance value between the target vehicle and the overlapped track according to the coordinate value of the target vehicle and the length value of the target vehicle. Wherein, the shortest distance value between the target vehicle coordinate and the overlapping track may be determined as the current vehicle distance value.

And fourthly, generating first interaction execution information in response to the fact that the predicted target vehicle running distance value and the predicted target vehicle running speed value meet a first preset interaction condition, wherein the first preset interaction condition can be that the predicted target vehicle running distance value is smaller than the distance value, and the predicted target vehicle running speed value is smaller than or equal to zero. The first interaction execution information may include a current vehicle interaction execution identifier, which is used to speed up the current vehicle to pass through the area where the overlapping track is located as soon as possible.

And fifthly, determining the first interaction execution information as the vehicle interaction information. Wherein the vehicle interaction information may be for an autonomous vehicle.

In some optional implementation manners of some embodiments, the executing entity generates the vehicle interaction information and the vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory, and may further include the following steps:

the method comprises a first step of generating second interaction execution information in response to determining that the predicted target vehicle travel distance value meets a second preset interaction condition, wherein the second preset interaction condition may be that the predicted target vehicle travel distance value is greater than or equal to the distance value and is smaller than the sum of the target vehicle length value, the distance value and the length value of the overlapping track in the target vehicle predicted track direction. The second interactive execution information may include a current vehicle defense execution identifier, which is used to decelerate and avoid the current vehicle, so that the target vehicle passes through the area where the overlapping area is located. Therefore, vehicle collision can be avoided, and safety of automatic driving is improved.

And secondly, determining the second interaction execution information as the vehicle interaction information.

In some optional implementation manners of some embodiments, the executing entity generates the vehicle interaction information and the vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory, and may further include the following steps:

in the first step, third interaction execution information is generated in response to the fact that the predicted target vehicle running distance value and the predicted target vehicle running speed value do not meet the first preset interaction condition and the predicted target vehicle running distance value does not meet the second preset interaction condition. The third interactive execution information may be used to determine that there is no conflict relationship between the current vehicle and the target vehicle within the scheduled time (e.g., within 3 seconds). Thus, the third interactive execution information may include a current vehicle normal execution flag for making the current vehicle travel at a uniform speed.

And secondly, determining the third interactive execution information as the vehicle interactive information.

And step 304, generating a vehicle speed value sequence set according to the vehicle interaction information.

In some embodiments, the execution subject may generate a vehicle speed value sequence set according to the vehicle interaction information. The vehicle speed value sequence set may be generated by:

in the first step, three alternative actions may be set. For example, [ [ action a: acceleration minus one]And [ action b: acceleration is not changed]And [ action c: acceleration plus 1]]. Wherein the acceleration unit may be m/s². The above actions may be used to adjust the acceleration value of the current vehicle to generate a sequence of velocity values.

In the second step, the acceleration of the current vehicle may be pre-adjusted in steps of the same time interval (e.g., 0.5 second) for the preset time period (e.g., 3 seconds). Thus, the number of vehicle speed values in each sequence of vehicle speed values may be 6. The pre-adjustment may be to add a different action to the acceleration values at each step.

As an example, the acceleration value of the current vehicle may be 0. The speed value may be 40. At the first step length, three post-addition acceleration values (i.e., -1 m/s) are generated²，0 m/s²，1 m/s²). Then, the velocity value corresponding to each acceleration value after the adding action can be obtained through the step size and the acceleration change amount and the velocity value. When the second step length is long, the actions can be added to the three acceleration values respectively for acceleration on the basis of the result of the previous step lengthThe value varies. Nine acceleration values and corresponding nine speed values can then be derived therefrom. Therefore, if all the speed values meet the screening condition, and the current speed value is taken as the root node, and each time one speed value is generated as the tree structure generation speed value of one sub-node, 729 leaf nodes, namely 729 speed values can be obtained in the last step. Thus, the current speed value (i.e. the root node) to the speed value corresponding to each node between each characterising leaf node may be taken as a sequence of vehicle speed values. In addition, the screening condition may be that the speed value corresponding to each step is greater than or equal to zero or less than a preset step speed threshold (e.g., 60 kilometers per hour). If the speed value corresponding to the child node or the leaf node does not meet the screening condition, the vehicle speed value sequence with the child node or the leaf node can be deleted. Thus, a vehicle speed value sequence set is obtained.

In step 305, the vehicle information around the current vehicle is acquired.

In some embodiments, the execution subject may acquire the vehicle information around the current vehicle. The surrounding vehicle information may be a stationary vehicle having a minimum distance value from the current vehicle. The above-described surrounding vehicle information may be used to avoid a stationary vehicle when the current vehicle moves. The above-mentioned surrounding vehicle information may include a static vehicle distance value between the current vehicle and the stationary vehicle whose distance value is the smallest. The surrounding vehicle information may further include a front vehicle speed value of a front vehicle (a vehicle followed by the current vehicle) at the position of the current vehicle, a rear vehicle speed value of a rear vehicle (a vehicle following the current vehicle), a left vehicle speed value of a left vehicle (a vehicle on the left side of the current vehicle), and a right vehicle speed value of a right vehicle (a vehicle on the right side of the current vehicle).

And step 306, in response to the fact that the vehicle collision time length is larger than the preset time length threshold value, verifying each vehicle speed value sequence in the vehicle speed value sequence set based on the current vehicle acceleration value and the surrounding vehicle information to generate a first verification value, and obtaining a first verification value set.

In some embodiments, the execution subject may verify each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value based on the current vehicle acceleration value and the surrounding vehicle information in response to determining that the vehicle collision duration is greater than the preset duration threshold, resulting in a first verification value set. The preset time threshold may be 3 seconds. For each vehicle speed value sequence, first, the vehicle acceleration value, the speed value and the vehicle acceleration change rate of the current vehicle corresponding to each moment in a preset time period when the vehicle speed value sequence is generated can be determined. Second, the first check value may be generated by the following formula:

。

wherein the content of the first and second substances,indicating an acceleration check value.Representing the acceleration value of the current vehicle as described above.Indicating the preset time period.Representing an acceleration change rate check value.Indicating the rate of change of vehicle acceleration.Representing a vehicle speed check value.Representing the current vehicle speed value.Indicating the preset currentVehicle maximum limit speed value.Representing a static vehicle check value.Representing the static vehicle distance value.The longitudinal check value is represented and can be used for representing the longitudinal distance value between the current vehicle and the surrounding vehicles.The above-described front vehicle speed value is indicated.Representing a preset maximum longitudinal acceleration value (e.g., 2 meters per square second).Representing a preset maximum longitudinal deceleration reaction duration.Representing a preset minimum longitudinal acceleration value (e.g., -4 meters per square second).The rear vehicle speed value is represented.A lateral check value is represented that can be used to characterize the lateral distance value between the current vehicle and the surrounding vehicle as described above.The right vehicle speed value is represented, and if the right vehicle speed value is smaller than zero, the right vehicle speed value can be adjusted to zero.The left vehicle velocity value is indicated.Representing a preset maximum lateral acceleration value (e.g., 2 meters per square second).Representing a preset minimum lateral acceleration value (e.g., -2 meters per square second).Indicating a preset maximum lateral acceleration period.Representing a preset acceleration check coefficient.Representing a preset jerk check factor.And representing a preset vehicle speed check coefficient.Representing a preset static vehicle check coefficient.Representing a preset longitudinal check coefficient.Representing a preset transverse check coefficient.Representing the first check value.

Alternatively, the second check value may be generated by the above formula. In addition, each check coefficient may be a safety check coefficient of the vehicle in a safe condition (i.e., the vehicle collision time period is greater than a preset time period threshold) generated in advance by a reverse reinforcement learning method. The risk check coefficient of the vehicle under the condition that the collision risk is large (namely, the collision time length of the vehicle is less than or equal to the preset time length threshold) can be generated by the method and used for generating the second check value.

The above formula and its related content are used as an invention point of the embodiment of the present disclosure, and the technical problem mentioned in the background art that "the intention of other vehicles and the structural characteristics of urban roads are not considered fully enough" is solved, so that the accuracy of checking the vehicle interaction information is reduced. The accuracy of checking the vehicle interaction information is improved. First, the dynamic characteristics of the current vehicle movement trajectory are considered. Thus, an acceleration check value is introduced. Then, the comfort of the autonomous vehicle is considered. Thus, an acceleration rate check value is introduced. Next, the efficiency of the vehicle movement is considered. Therefore, a preset current vehicle maximum speed limit value and a vehicle speed check value are introduced. Second, the safety of the vehicle is considered. Thus, a static vehicle check value is introduced. Ensuring that the current vehicle can maintain a safe distance while passing by a stationary vehicle. Then, the vehicle safety distance in the longitudinal direction (the direction in which the vehicle is currently in the lane) is considered. Thus, a longitudinal check value is introduced. Finally, the vehicle safety distance in the lateral direction (the direction perpendicular to the longitudinal horizontal direction) is considered. Thus, a lateral check value is introduced. Thus, the accuracy of the first check value or the second check value can be improved by a comprehensive consideration of the other vehicle intention and the structural characteristics of the road. Further, the accuracy of verifying the vehicle interaction information can be improved.

And 307, determining a vehicle speed value sequence corresponding to a first check value meeting a first preset condition in the first check value set as a vehicle interaction information check result.

In some embodiments, the specific implementation manner and technical effects of step 307 may refer to step 206 in those embodiments corresponding to fig. 2, and are not described herein again.

As can be seen from fig. 3, compared with the description of some embodiments corresponding to fig. 2, the flow 300 of the vehicle interaction information verification method in some embodiments corresponding to fig. 3 embodies the steps of generating the first verification value set of the vehicle interaction information, the vehicle collision duration, and the vehicle speed value sequence set. First, for the safety problem of vehicles, the text estimates the scene state from the real reaction of the driver to the crossroad by using real vehicle data, divides the dangerous scene and screens out the relevant vehicles (i.e. target vehicles). Compared with empirical formula modeling, the expression mode based on statistics is more consistent with the characteristics of human drivers. Secondly, under the environment of the crossroad, a semi-Markov model is adopted to analyze the intention estimation of other vehicles and the driving strategy (namely, interactive information) of the vehicle. The driving intention is used as a breakthrough, and the interactive behaviors are first interactive execution information, second interactive execution information and third interactive execution information. The semi-Markov model is utilized to correspond the intention and the driving interaction information, so that the ambiguity of the intention of the other vehicle in a real scene is adapted. And the interactive information is directly generated, so that the difficulty of generating the interactive information is reduced, and the solving efficiency of the model is improved. Finally, to achieve a high degree of driver-like behavior, a risk-preference-based evaluation function (i.e., the above formula) is established. The method collects real driving data of the driver and analyzes the driving characteristics of the driver. The driving scene is divided into a dangerous scene and a non-dangerous scene, and the evaluation functions of the operation of the driver are respectively learned by using the driving data of the driver under the two environments. And finally, the human-like evaluation function based on risk preference and the risk neutral evaluation function have smaller error in fitting human data and are more in line with human driving behaviors. Therefore, the efficiency of vehicle interactive information checking can be improved, and the accuracy of vehicle interactive information checking can be improved.

With further reference to fig. 4, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a vehicle mutual information verification apparatus, which correspond to those of the method embodiments shown in fig. 2, and which may be applied in various electronic devices.

As shown in fig. 4, the vehicle mutual information verification apparatus 400 of some embodiments includes: an acquisition unit 401, an input unit 402, a first generation unit 403, a second generation unit 404, a third generation unit 405, and a determination unit 406. Wherein the acquiring unit 401 is configured to acquire current vehicle information of a current vehicle and target vehicle information of a target vehicle; an input unit 402 configured to input the current vehicle information and the target vehicle information to a preset trajectory prediction model to generate a current vehicle predicted trajectory and a target vehicle predicted trajectory; a first generating unit 403 configured to generate vehicle interaction information and a vehicle collision duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory, and the target vehicle predicted trajectory; a second generating unit 404, configured to generate a vehicle speed value sequence set according to the vehicle interaction information; a third generating unit 405, configured to verify each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value in response to determining that the vehicle collision duration is greater than a preset duration threshold, so as to obtain a first verification value set; the determining unit 406 is configured to determine, as a vehicle interaction information verification result, a vehicle speed value sequence corresponding to a first verification value satisfying a first preset condition in the first verification value set.

It will be understood that the elements described in the apparatus 400 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 400 and the units included therein, and will not be described herein again.

Referring now to FIG. 5, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1) 500 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.

Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 5 may represent one device or may represent multiple devices as desired.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of some embodiments of the present disclosure.

It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.

The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring current vehicle information of a current vehicle and target vehicle information of a target vehicle; inputting the current vehicle information and the target vehicle information into a preset track prediction model to generate a current vehicle predicted track and a target vehicle predicted track; generating vehicle interaction information and vehicle conflict duration based on the current vehicle information, the target vehicle information, the current vehicle predicted trajectory and the target vehicle predicted trajectory; generating a vehicle speed value sequence set according to the vehicle interaction information; in response to the fact that the vehicle conflict duration is larger than a preset duration threshold value, verifying each vehicle speed value sequence in the vehicle speed value sequence set to generate a first verification value, and obtaining a first verification value set; and determining a vehicle speed value sequence corresponding to a first check value meeting a first preset condition in the first check value set as a vehicle interactive information check result.

Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, an input unit, a first generation unit, a second generation unit, a third generation unit, and a determination unit. Here, the names of these units do not constitute a limitation of the unit itself in some cases, and for example, the acquisition unit may also be described as a "unit that acquires current vehicle information of the current vehicle and target vehicle information of the target vehicle".

The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.