CN119590415A

CN119590415A - Vehicle control method, vehicle, storage medium and computer program product

Info

Publication number: CN119590415A
Application number: CN202411757935.4A
Authority: CN
Inventors: 骆肖跃
Original assignee: Guangzhou Xiaopeng Motors Technology Co Ltd
Current assignee: Guangzhou Xiaopeng Motors Technology Co Ltd
Priority date: 2024-12-02
Filing date: 2024-12-02
Publication date: 2025-03-11

Abstract

The present disclosure provides a vehicle control method, a vehicle, a storage medium and a computer program product. The method includes: obtaining the first position information of the target vehicle, the vehicle speed information, the second position information of the dangerous target, and the speed information of the dangerous target; performing verification processing based on the first position information, the vehicle speed information, the second position information and the speed information of the dangerous target to obtain a target verification result, wherein the target verification result is used to determine the relative position change and relative speed change between the target vehicle and the dangerous target; determining a collision prediction result based on the target verification result, wherein the collision prediction result is used to determine whether there is a collision risk between the target vehicle and the dangerous target; and controlling the braking of the target vehicle based on the collision prediction result. The present disclosure solves the technical problems of low safety and poor adaptability of the vehicle control method provided in the related art.

Description

Vehicle control method, vehicle, storage medium, and computer program product

Technical Field

The present disclosure relates to the field of intelligent driving technology, and in particular, to a vehicle control method, a vehicle, a storage medium, and a computer program product.

Background

The automatic emergency braking system is used as a key component of the intelligent driving vehicle, so that traffic accidents can be effectively reduced. The vehicle control method in the related art senses a dangerous object in front by relying on a vehicle forward sensor such as a radar or a camera, thereby realizing automatic emergency braking of the vehicle. However, the vehicle control method provided in the related art has problems of low safety and poor adaptability, and thus it is difficult to provide reliable collision avoidance protection in complex and diverse traffic environments.

In view of the above problems, no effective solution has been proposed at present.

Disclosure of Invention

The embodiment of the disclosure provides a vehicle control method, a vehicle, a storage medium and a computer program product, which at least solve the technical problems of low safety and poor adaptability of the vehicle control method provided in the related art.

According to one embodiment of the disclosure, a vehicle control method is provided, which comprises the steps of obtaining first position information of a target vehicle, vehicle speed information, second position information of a dangerous target object and dangerous target object speed information, wherein the first position information is used for representing real-time position information collected through a position sensor of the target vehicle, the second position information is used for representing shared position information of a mobile positioning terminal associated with the dangerous target object, the dangerous target object speed information is used for representing the moving speed of the dangerous target object obtained through the mobile positioning terminal, checking processing is conducted on the basis of the first position information, the vehicle speed information, the second position information and the dangerous target object speed information to obtain target checking results, the target checking results are used for determining a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object, the collision prediction results are determined according to the target checking results, the collision prediction results are used for determining whether collision risks exist between the target vehicle and the dangerous target object, and braking of the target vehicle is controlled on the basis of the collision prediction results.

Optionally, the obtaining the second location information includes obtaining the second location information from a cloud server, where the cloud server is configured to transmit the shared location information uploaded by the mobile positioning terminal.

Optionally, performing verification processing based on the first position information, the vehicle speed information, the second position information and the dangerous object speed information to obtain a target verification result comprises responding to determining that a dangerous object enters a first target area based on the second position information, generating a target tracking identifier corresponding to the dangerous object, wherein the first target area is a potential collision risk area which is obtained by extending to the front and two sides of the target vehicle with the self-vehicle outer contour of the target vehicle as a starting point, performing tracking detection on the dangerous object based on the target tracking identifier to obtain position tracking information, responding to determining that the dangerous object enters a second target area based on the position tracking information, and performing verification processing based on the first position information, the vehicle speed information, the position tracking information and the dangerous object speed information to obtain the target verification result, wherein the second target area is a perception identification area of the target vehicle.

Optionally, performing verification processing based on the first position information, the vehicle speed information, the position tracking information and the dangerous object speed information to obtain a target verification result, wherein the target verification result comprises performing position verification based on the first position information and the position tracking information to obtain a position verification result, wherein the position verification result is used for determining the relative position between the target vehicle and the dangerous object, performing speed verification based on the vehicle speed information and the dangerous object speed information to obtain a speed verification result, wherein the speed verification result is used for determining the relative speed between the target vehicle and the dangerous object, and determining the target verification result according to the position verification result and the speed verification result.

Optionally, determining the collision prediction result according to the target verification result includes generating a predicted travel track based on the target verification result and a current steering wheel angle of the target vehicle, and analyzing the predicted travel track to obtain the collision prediction result.

Optionally, controlling the travel of the target vehicle based on the collision prediction result includes controlling the target vehicle to remain in a normal travel state in response to determining that there is no risk of collision between the target vehicle and the dangerous target object based on the collision prediction result.

The vehicle control method in the embodiment of the disclosure further comprises the steps of obtaining target road structure information, wherein the target road structure information is used for representing road characteristic information in the running process of the target vehicle, and determining a first target area based on the first position information and the target road structure information.

Optionally, tracking and detecting the dangerous target object based on the target tracking identifier to obtain the position tracking information comprises the steps of acquiring real-time position information of the dangerous target object in the first target area based on the target tracking identifier, determining movement attribute change information of the dangerous target object by utilizing the real-time position information, wherein the movement attribute change information comprises position change information, speed change information and direction change information of the dangerous target object, and determining the position tracking information based on the movement attribute change information.

According to one embodiment of the disclosure, a vehicle control device is further provided, which comprises an acquisition module, a processing module and a determination module, wherein the acquisition module is used for acquiring first position information, vehicle speed information and second position information of a dangerous target object of a target vehicle, the first position information is used for representing real-time position information acquired by a position sensor of the target vehicle, the second position information is used for representing real-time shared position information of a mobile positioning terminal associated with the dangerous target object, the dangerous target object speed information is used for representing the moving speed of the dangerous target object acquired by the mobile positioning terminal, the processing module is used for performing verification processing based on the first position information, the vehicle speed information, the second position information and the dangerous target object speed information to obtain a target verification result, the target verification result is used for determining a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object, the determination module is used for determining a collision prediction result according to the target verification result, the collision prediction result is used for determining whether collision risk exists between the target vehicle and the dangerous target object, and the control module is used for controlling braking of the target vehicle based on the collision prediction result.

Optionally, the obtaining module is further configured to obtain second location information from a cloud server, where the cloud server is configured to transmit the shared location information uploaded by the mobile positioning terminal.

Optionally, the processing module is further configured to generate a target tracking identifier corresponding to the dangerous target object in response to determining that the dangerous target object enters the first target area based on the second position information, wherein the first target area is a potential collision risk area obtained by extending to the front and the two sides of the target vehicle with the vehicle outer contour of the target vehicle as a starting point, track and detect the dangerous target object based on the target tracking identifier to obtain position tracking information, and perform verification processing based on the first position information, the vehicle speed information, the position tracking information and the dangerous target object speed information in response to determining that the dangerous target object enters the second target area based on the position tracking information to obtain a target verification result, wherein the second target area is a perception identification area of the target vehicle.

Optionally, the processing module is further configured to perform position verification based on the first position information and the position tracking information to obtain a position verification result, wherein the position verification result is used for determining a relative position between the target vehicle and the dangerous target object, perform speed verification based on the vehicle speed information and the dangerous target object speed information to obtain a speed verification result, wherein the speed verification result is used for determining a relative speed between the target vehicle and the dangerous target object, and determine the target verification result according to the position verification result and the speed verification result.

Optionally, the determining module is further used for generating a predicted running track based on the target verification result and the current steering wheel angle of the target vehicle, and analyzing and processing the predicted running track to obtain a collision prediction result.

Optionally, the processing module is further configured to acquire target road structure information, where the target road structure information is used to represent road feature information during driving of the target vehicle, and determine the first target area based on the first location information and the target road structure information.

Optionally, the processing module is further used for acquiring real-time position information of the dangerous object in the first target area based on the target tracking identification, determining moving attribute change information of the dangerous object by utilizing the real-time position information, wherein the moving attribute change information comprises position change information, speed change information and direction change information of the dangerous object, and determining the position tracking information based on the moving attribute change information.

Optionally, the control module is further configured to control the target vehicle to maintain a normal driving state in response to determining that there is no risk of collision between the target vehicle and the dangerous target object based on the collision prediction result.

There is also provided, in accordance with an embodiment of the present disclosure, a vehicle including a processor, a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement a vehicle control method in an embodiment of the present disclosure.

According to one embodiment of the present disclosure, there is also provided a computer-readable storage medium including a stored executable program, wherein a device on which the executable program is controlled to execute the vehicle control method in the embodiment of the present disclosure is located when the executable program is run.

According to one embodiment of the present disclosure, there is also provided a computer program product comprising computer instructions which, when executed by a processor, implement the vehicle control method of the embodiments of the present disclosure.

In the embodiment of the disclosure, the first position information and the speed information of the target vehicle are acquired, the second position information related to the mobile positioning terminal and the speed information of the dangerous target object are acquired at the same time, then, the target verification result is obtained by utilizing the information to carry out verification processing, the collision prediction result is further determined based on the target verification result, and finally, the running of the target vehicle is controlled according to the collision prediction result, so that the purposes of identifying the dangerous target object in advance and avoiding the collision risk are achieved, the technical effects of improving the safety and the adaptability of the vehicle control are achieved, and the technical problems of low safety and poor adaptability of the vehicle control method provided in the related art are solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate and explain the present disclosure, and together with the description serve to explain the present disclosure. In the drawings:

Fig. 1 is a hardware configuration diagram of a vehicle control method according to one embodiment of the present disclosure;

FIG. 2 is a flow chart of a vehicle control method according to one embodiment of the present disclosure;

FIG. 3 is a schematic illustration of a first target area according to one embodiment of the present disclosure;

FIG. 4 is a schematic illustration of a vehicle control method according to one embodiment of the present disclosure;

FIG. 5 is a schematic illustration of a vehicle control method according to one embodiment of the present disclosure;

FIG. 6 is a schematic diagram of an automatic emergency control system according to one embodiment of the present disclosure;

FIG. 7 is a schematic illustration of a vehicle control method according to one embodiment of the present disclosure;

fig. 8 is a block diagram of a vehicle control apparatus according to one embodiment of the present disclosure.

Detailed Description

In order that those skilled in the art will better understand the present disclosure, a technical solution in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present disclosure, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without inventive effort, based on the embodiments in this disclosure, shall fall within the scope of the present disclosure.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

The vehicle control method in the related art senses a dangerous object in front by relying on a vehicle forward sensor such as a radar or a camera, thereby realizing automatic emergency braking of the vehicle. However, the vehicle control method provided in the related art has problems of low safety and poor adaptability, and thus it is difficult to provide reliable collision avoidance protection in complex and diverse traffic environments.

In particular, automatic emergency braking systems rely primarily on sensors of the vehicle itself to detect dangerous objects in front, which may be affected by weather, light, dangerous object shape and size, etc., resulting in limited perception or inaccurate object identification. For example, in a "ghost probe" scenario, where a pedestrian or vehicle suddenly appears from a driver's line of sight blind spot, the sensor may not be able to sense these targets in real time, thereby failing to trigger automatic emergency braking in time, increasing the risk of collision. In addition, for atypical dangerous objects such as rollover vehicles, falling pedestrians and the like, the traditional automatic emergency braking system can not accurately identify, so that the braking is not timely or is triggered by mistake, and the driving safety is affected.

According to the disclosed embodiments, a method embodiment of a vehicle control method is provided, it being noted that the steps shown in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that herein.

The method embodiments may be performed in an electronic device or similar computing device that includes a memory and a processor. Taking an example of operation on a computer terminal, the computer terminal may include one or more processors (which may include, but are not limited to, a central Processing unit (Central Processing Unit, CPU), a graphics processor (Graphics Processing Unit, GPU), a Digital Signal Processing (DSP) chip, a microprocessor (Micro Controller Unit, MCU), a programmable logic device (Field Programmable GATE ARRAY, FPGA), a neural network processor (Neural-network Processor Unit, NPU), a tensor processor (Tensor Processing Unit, TPU), a processor of the artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) type, and the like Processing means and memory for storing data. Optionally, the above computer terminal may further include a transmission device for a communication function, an input-output device, and a display device. It will be appreciated by those of ordinary skill in the art that the above description of the structure is illustrative only and is not intended to limit the structure of the computer terminal described above. For example, the computer terminal may also include more or fewer components than the above structural description, or have a different configuration than the above structural description.

The memory may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to the vehicle control method in the embodiment of the present disclosure, and the processor executes the computer program stored in the memory, thereby performing various functional applications and data processing, that is, implementing the above-described vehicle control method. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid state memory. In some examples, the memory may further include memory remotely located with respect to the processor, the remote memory being connectable to the mobile terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission means is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission means comprises a network adapter (Network Interface Controller, simply referred to as NIC) that can be connected to other network devices via a base station to communicate with the internet. In one example, the transmission device may be a Radio Frequency (RF) module, which is used to communicate with the internet wirelessly.

Display devices may be, for example, touch screen type liquid crystal displays (Liquid Crustal Display, LCDs) and touch displays (also referred to as "touch screens" or "touch display screens"). The liquid crystal display may enable a user to interact with a user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GRAPHICAL USER INTERFACE, GUI) with which a user can interact with the GUI by touching finger contacts and/or gestures on the touch-sensitive surface, where the human-machine interaction functionality optionally includes interactions such as creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving electronic mail, talking interfaces, playing digital video, playing digital music and/or web browsing, etc., executable instructions for performing the human-machine interaction functionality described above are configured/stored in one or more processor-executable computer program products or readable storage mediums.

The embodiment of the disclosure provides a vehicle control method. The vehicle control method can be used for providing an automatic collision avoidance function for a preset application scene. The preset application scene may include a commute autopilot scene, an artificial intelligence (ARTIFICIAL INTELLIGENCE, AI for short) driving scene of a home automobile, an Automatic PARKING ASSIST (APA for short) scene (such as memory parking for an own parking space in a garage, intelligent parking for a specified parking space in a parking space, etc.), an intelligent navigation assistance (Navigation Guided Pilot, NGP for short) scene in a city area or a high-speed area in the vehicle field. In addition, the preset application scenes can also include, but are not limited to, an automatic distribution collision avoidance scene of an intelligent driving truck or an unmanned truck in the logistics transportation field, an intelligent cultivation collision avoidance scene of an automatic driving agricultural vehicle in the agricultural machinery field, an automatic collision avoidance scene of an unmanned aerial vehicle, an automatic collision avoidance scene of an intelligent robot (such as a cleaning robot, a service robot, a delivery robot and the like), and an automatic collision avoidance scene of an unmanned/unmanned aerial vehicle.

When the above-mentioned preset application scenario is a scenario in a field other than the vehicle field, it should be understood by those skilled in the art that the vehicle in the above-mentioned vehicle control method may be replaced with another object (such as an agricultural machine, an unmanned aerial vehicle, a robot, etc.), and accordingly, the control method may be replaced with a technical method related to the other object. On this basis, in the embodiment of the present disclosure, the field of intelligent driving technology is taken as an example, and a specific implementation manner of the vehicle control method is described by way of example.

Fig. 1 is a hardware configuration diagram of a vehicle control method according to one embodiment of the present disclosure. As shown in FIG. 1, the hardware structure comprises a terminal device, a vehicle and a road side device.

By way of example, terminal devices generally refer to smart devices capable of participating in communications and providing location information, including but not limited to the target vehicle itself, mobile location terminals equipped with GPS location systems (e.g., smartphones, smart wearable devices), and other vehicles equipped with location data sharing functionality, and the like. The device collects environmental data through built-in sensors or collects information through user interaction, and then the collected data is transmitted to a cloud server or a vehicle-mounted control unit of a target vehicle through a network for analysis and processing. The network includes, but is not limited to, cellular networks (such as 4G, 5G), wi-Fi, bluetooth, vehicle-to-evaluation (V2X), etc. technologies, and is responsible for transmitting data in real time, so as to ensure that the Vehicle can receive shared location information and status data of other vehicles, pedestrians, road side devices, etc. in real time. Roadside devices refer to devices mounted on the side of a roadway for monitoring and sensing the environment of the roadway, including but not limited to radar, cameras, infrared sensors, weather sensors, traffic light controllers, and the like. The data collected by the road side equipment is transmitted to a vehicle or cloud server through a network and is used for vehicle control and traffic management. In order to ensure that the vehicle control method in the embodiment of the disclosure can acquire the target information more accurately and track and control the target information in real time, the mobile terminal needs to ensure the real-time performance of information and data transmission.

Further, a driving scene switching instruction may be issued through the terminal device, and the driving scene switching instruction may be sent to the vehicle through the network. The vehicle receives a driving scene switching instruction sent by the terminal equipment, sends an information subscription request to the road side equipment, receives the information subscription request from the vehicle, and returns continuously collected road side perception information to the vehicle.

Fig. 2 is a flowchart of a vehicle control method according to one embodiment of the present disclosure, as shown in fig. 2, including the steps of:

Step S11, acquiring first position information of a target vehicle, vehicle speed information and second position information of a dangerous target object, and acquiring speed information of the dangerous target object, wherein the first position information is used for representing real-time position information acquired by a position sensor of the target vehicle, the second position information is used for representing shared position information of a mobile positioning terminal associated with the dangerous target object, and the speed information of the dangerous target object is used for representing the moving speed of the dangerous target object acquired by the mobile positioning terminal;

step S12, performing verification processing based on the first position information, the vehicle speed information, the second position information and the dangerous object speed information to obtain a target verification result, wherein the target verification result is used for determining the relative position change condition and the relative speed change condition between the target vehicle and the dangerous object;

step S13, determining a collision prediction result according to the target verification result, wherein the collision prediction result is used for determining whether collision risk exists between the target vehicle and the dangerous target object;

Step S14 of controlling braking of the target vehicle based on the collision prediction result.

The first position information refers to real-time position data acquired by the target vehicle through the vehicle-mounted positioning system, and includes, but is not limited to, current longitude and latitude coordinates, running direction and other information of the target vehicle, and is a direct reflection of the position state of the target vehicle.

The mobile positioning terminal refers to an intelligent device with a position sharing function, and can determine its own position independently or through an integrated positioning module, such as a global positioning system (Global Positioning System, GPS), a beidou navigation system, or other satellite positioning systems, and upload and share its position information in real time through a wireless communication technology or a cloud server. Mobile positioning terminals include, but are not limited to, vehicles equipped with GPS or other satellite positioning systems, smart phones, smart wearable devices.

The position sensor is a sensor device which is arranged on a vehicle and used for monitoring and determining accurate geographic coordinates of the vehicle in real time, and comprises satellite positioning sensors such as a GPS receiver, a Beidou navigation system receiver and the like, and auxiliary positioning devices such as an inertial navigation system, an odometer, a wheel speed sensor, a dead reckoning system and the like.

The above-mentioned dangerous object refers to an object that may constitute a risk of collision to the target vehicle on the target vehicle travel path, including but not limited to pedestrians, bicycles, motorcycles, other motor vehicles, and any other external factor that may affect the safe travel of the vehicle.

As an alternative embodiment, assuming an autonomous car is traveling steadily on a busy city street, its onboard GPS sensor continuously records and updates the exact geographic location of the car, forming the first location information for subsequent analysis. Meanwhile, the real-time running speed of the target vehicle is obtained based on the vehicle-mounted wheel speed sensor, and real-time accuracy of vehicle speed information is ensured. In this period, a pedestrian uses the position sharing application on the mobile phone, and the mobile phone is used as a mobile positioning terminal to upload the position information of the pedestrian to the vehicle-mounted control unit of the automobile in real time through interconnection with the cloud server, so that the second position information is formed. The moving speed information of the pedestrians is captured and processed by a motion sensor arranged in the mobile phone of the pedestrians, and is also transmitted to the vehicle-mounted control unit for analysis. For the evaluation of the collision risk, the onboard control unit first integrates all the collected information, including the real-time position and speed of the target vehicle, and the position and speed data provided by the pedestrian. And then, the vehicle-mounted control unit starts a verification processing flow, and the relative position change and the relative speed between the target vehicle and the pedestrian are calculated through comparing and analyzing the data, so as to generate a target verification result. Next, the in-vehicle control unit accurately determines the presence or absence of a collision risk, and the time and place of a potential collision based on the travel path of the target vehicle, the current speed, and the moving direction and speed of the pedestrian, according to the target verification result. In case a collision risk is detected, the on-board control unit activates an automatic emergency braking system, controlling the vehicle to slow down or even stop completely, in order to avoid the collision. Otherwise, if the prediction result shows that no collision risk exists, the vehicle-mounted control unit maintains continuous monitoring on the surrounding environment, and safe running of the target vehicle is ensured.

Based on the steps S11 to S14, the position information and the speed information of the target vehicle are acquired, the position information and the speed information of the dangerous target object associated with the mobile positioning terminal are acquired at the same time, then, the target verification result is obtained by utilizing the information to carry out verification processing, the collision prediction result is further determined based on the target verification result, and finally, the running of the target vehicle is controlled according to the collision prediction result, so that the purpose of identifying and avoiding the collision risk in advance is achieved, the technical effects of improving the safety and the adaptability of the vehicle control are achieved, and the technical problems of low safety and poor adaptability of the vehicle control method provided in the related technology are solved.

The cloud server refers to a centralized network storage and processing platform, and is responsible for receiving, storing, processing and sharing the shared position information from various mobile positioning terminals in real time. The cloud server is used as a data transmission hub, can receive and transmit the position and speed information uploaded by the mobile intelligent device, such as a smart phone, a smart watch or other terminals with position sharing functions in real time, has strong data processing capacity, can analyze and manage the uploaded position information, and ensures the accuracy and timeliness of data. Common cloud servers include an ali cloud, a Tencent cloud, a Google cloud platform, and the like.

As an alternative implementation, the cloud server is responsible for transmitting and managing the shared location information uploaded by a mobile location terminal integrating the shared location function, such as a smart phone, a smart watch or a vehicle with location communication capability. The terminal equipment acquires the position data of the terminal equipment or the associated object through a built-in GPS module, encrypts the acquired position data and uploads the encrypted position data to the cloud server. And at the server side, the position data is verified and integrated to form a real-time position database. When the automatic driving vehicle approaches a certain traffic participant or a potential dangerous target object, the vehicle-mounted control unit sends a request to the cloud server to acquire the shared position information uploaded by the mobile positioning terminal in the area. The cloud server responds rapidly, retrieves the position information of the dangerous object associated with the requesting vehicle from the real-time position database transmitted by the cloud server, and feeds the position information back to the vehicle-mounted control unit as second position information.

Based on the above-mentioned alternative embodiment, the shared location information of the dangerous object is obtained from the cloud server, so that the vehicle-mounted control unit of the vehicle not only depends on the direct perception of the vehicle-mounted sensor such as the radar and the camera, but also can receive and integrate the real-time location data uploaded from the external mobile positioning terminal. Through the cloud server, the shared position information of the dangerous target object is immediately transmitted to the vehicle-mounted control unit, so that the vehicle can be prejudged in advance to the existence of traffic participants or dangerous target objects which are beyond the sensing range of the sensor or are limited, traffic accidents caused by the sensing limitation of the sensor are reduced, and the safety and the adaptability of vehicle control are improved.

Optionally, in step S12, performing a verification process based on the first location information, the vehicle speed information, the second location information, and the dangerous target speed information, where obtaining a target verification result includes:

step S121, responding to the determination that the dangerous target object enters a first target area based on the second position information, and generating a target tracking mark corresponding to the dangerous target object, wherein the first target area is a potential collision risk area which is obtained by taking the self-vehicle outline of the target vehicle as a starting point and extending to the front and two sides of the target vehicle;

step S122, tracking and detecting dangerous target objects based on the target tracking identification to obtain position tracking information;

Step S123, in response to determining that the dangerous target object enters the second target area based on the position tracking information, performing verification processing based on the first position information, the vehicle speed information, the position tracking information and the dangerous target object speed information to obtain a target verification result, wherein the second target area is a perception identification area of the target vehicle.

The first target area refers to a potential collision risk area extending and calibrating to the front and two sides of the vehicle by taking the outer contour of the target vehicle as a reference point, and is used for acquiring information of dangerous targets and traffic participants which are located outside the sensing range of existing sensors of the vehicle, such as radar and cameras, or possibly exist under the limited condition of the sensors. By monitoring the positioning signal source in the first target area in real time, the potential collision risk can be pre-estimated, namely by receiving and analyzing data from terminal equipment (such as other vehicles, smart phones, intelligent wearable equipment and the like) with the function of sharing the position information, the traffic dynamics in front and at the side can be identified in real time even if the vehicle-mounted sensor is limited or fails.

Fig. 3 is a schematic view of a first target area according to one embodiment of the present disclosure, as shown in fig. 3, showing the first target area 100 meters in front of the vehicle, 10 meters outside the width edge.

The target tracking identifier refers to a unique code or mark (corresponding to a target unique ID transmitted by the cloud) allocated to a dangerous target when the cloud server or the vehicle-mounted control unit determines that the dangerous target enters the first target area based on the second position information of the dangerous target, and is used for continuously tracking and identifying the dangerous target in subsequent tracking detection, so that the target vehicle can accurately lock and continuously monitor the dynamic change of the dangerous target, the target can be effectively prevented from being lost even in a complex environment, and the problems of radar point drift, radar point divergence, ghost and the like of a moving target existing in a sensor such as a radar can be effectively avoided.

The position tracking information refers to position information of dangerous target objects, which is collected along with time change after continuous tracking detection of dangerous target objects based on target tracking identification, and comprises accurate coordinates of dangerous target objects at different time points, and the movement track of the dangerous target objects relative to a target vehicle is reflected.

The second target area refers to a perception recognition area of the target vehicle, namely, an area where sensors such as a vehicle forward radar and a camera can directly perceive and acquire information. The second target area is set according to performance parameters of the sensor, such as detection distance, angle, precision and the like, and covers the area right in front of the vehicle and part of the area in front of the side, so that the vehicle can respond to dangerous targets or traffic participants appearing on a driving path in real time, collision risk is estimated, and corresponding collision avoidance measures, such as automatic emergency braking, are adopted.

As an alternative embodiment, the first target area is defined as a range of 100 meters in front of the vehicle and 10 meters beyond the width edge during travel of the target vehicle. At a certain moment, a pedestrian wearing the intelligent watch appears in front, the target vehicle receives the pedestrian speed information shared by the intelligent watch in real time, and meanwhile, the cloud server receives the real-time position information shared by the intelligent watch, and displays that the pedestrian is located at the position 80 m in front of the vehicle and 6m on the right side, namely, the second position information is located at the position 80 m in front of the vehicle and 6m on the right side. Based on the second position information uploaded by the intelligent watch, the vehicle-mounted control unit judges that the pedestrian enters the first target area of the target vehicle, and generates a specific target tracking identifier 'TID 5014' for the pedestrian, wherein the specific target tracking identifier is used for updating the relative positions of the two parties in real time. The automatic emergency braking system confirms that the pedestrian is crossing the road based on the relative positions of the target vehicle and the pedestrian, determines that the pedestrian and the target vehicle have collision risk based on the relative position information and the speed information, executes automatic emergency collision prevention control, and decelerates the vehicle in advance. Then, when the pedestrian continues to move towards the center of the road and enters a vehicle forward perception and identification area, the vehicle-mounted perception sensor perceives the pedestrian target, and the automatic emergency braking system synchronously receives the collision risk of the pedestrian and the target vehicle input by the sensor, so that the double verification of the collision avoidance control accuracy of the current automatic emergency braking system by the system is ensured. Meanwhile, collision avoidance control can be effectively executed on targets which cross roads, rollover bicycles, pedestrians and the like and are input by a front line sensing sensor based on accurate positioning sharing of terminal positioning information.

Based on the above-mentioned alternative embodiment, when the dangerous target object enters the first target area, the target tracking identifier corresponding to the dangerous target object is generated, and then the dangerous target object is tracked and detected based on the target tracking identifier, so as to obtain the position tracking information, finally, the dangerous target object is determined to enter the second target area according to the position tracking information, and the verification processing is performed based on the first position information, the vehicle speed information, the position tracking information and the dangerous target object speed information, so as to obtain the target verification result, and the potential collision risk can be early warned and accurately judged, the misjudgment and omission rate of the automatic emergency braking system are reduced, and especially under burst scenes such as ghost probes, more real-time and effective collision early warning can be provided for drivers and vehicles, and the driving safety is ensured.

Fig. 4 is a schematic diagram of a vehicle control method according to an embodiment of the disclosure, as shown in fig. 4, when it is determined that a dangerous object enters a first target area according to second position information of the dangerous object during driving of the vehicle, the dangerous object is immediately locked, and a target tracking identifier of the dangerous object is generated for subsequent continuous detection and tracking. And when the dangerous target object is detected to enter the second target area, performing verification processing to obtain a target verification result.

As an alternative implementation manner, the sensor such as the vehicle camera or the radar detects that the dangerous object enters the second target area, and the vehicle-mounted control module performs double verification on the position and the speed of the dangerous object based on the current position and the speed of the dangerous object detected by the sensor. For example, a rollover vehicle is arranged in front of a target vehicle by 100 meters, the first position information of the target vehicle and the second position information of a continuously detected target obstacle are acquired through a GPS positioning system of the target vehicle, the system detects that the target vehicle is continuously close to the rollover vehicle in front, collision risk exists, deceleration collision prevention control is executed, a radar can identify a dangerous target object at 50 meters, the radar can serve as double verification for confirming the target dangerous target object by the system, and the recognition accuracy of the dangerous target object is improved.

Optionally, in step S123, performing verification processing based on the first location information, the vehicle speed information, the location tracking information, and the dangerous object speed information, where obtaining the target verification result includes:

step S1231, performing position verification based on the first position information and the position tracking information to obtain a position verification result, wherein the position verification result is used for determining the relative position between the target vehicle and the dangerous target object;

step S1232, performing speed verification based on the vehicle speed information and the dangerous object speed information to obtain a speed verification result, wherein the speed verification result is used for determining the relative speed between the target vehicle and the dangerous object;

step S1233, determining a target verification result according to the position verification result and the speed verification result.

As an alternative implementation manner, when the dangerous object enters the second target area of the vehicle, the vehicle-mounted control system immediately compares the first position information of the target vehicle with the position tracking information of the dangerous object, and calculates the relative position data between the first position information and the position tracking information of the dangerous object in real time. And then, carrying out speed verification, and combining the running speed of the target vehicle and the moving speed of the dangerous target object, and verifying the relative speed between the running speed and the moving speed of the target vehicle in real time to judge the possibility of collision. And the vehicle-mounted control unit judges that the moving track of the dangerous target object and the travelling track of the vehicle have collision risks after integrating the position verification result and the speed verification result.

Based on the above-mentioned alternative embodiment, the target verification result is determined according to the position verification result and the speed verification result, so that the early pre-judgment and immediate response to the potential collision risk can be realized, the target vehicle and the dangerous target object with collision risk are ensured, and the quick and accurate collision avoidance control can be performed based on the accurate relative position and relative speed information.

Fig. 5 is a schematic diagram of a vehicle control method according to one embodiment of the present disclosure, where the target vehicle travel path includes two dangerous targets as shown in fig. 5.

As an optional implementation manner, the vehicle-mounted control unit identifies that the dangerous object is close to or far from the target vehicle according to the relative position change condition and the relative speed change condition of the target vehicle and the dangerous object, judges whether the target vehicle and the dangerous object have collision risk, and triggers control based on the original triggering threshold of the automatic emergency braking system.

Optionally, in step S13, determining the collision prediction result according to the target verification result includes:

Step S131, generating a predicted running track based on the target verification result and the current steering wheel angle of the target vehicle;

And step S132, analyzing and processing the predicted running track to obtain a collision prediction result.

As an alternative implementation manner, in the driving process of the target vehicle, the vehicle-mounted control unit receives information transmitted by the cloud server, displays 200 meters ahead, and suddenly turns over a truck from the front of the driving track. The vehicle-mounted control unit monitors the current steering wheel angle of the target vehicle at the same time, and judges that a rollover vehicle exists in the current vehicle traveling direction. And after receiving the side turning information of the truck, the vehicle-mounted control unit immediately detects that the target vehicle continues to run in the current state based on the relative position and the relative speed of the truck and the target vehicle and the track of the target vehicle, and the high risk of collision with the truck is detected.

Based on the above-mentioned alternative embodiment, by generating the predicted driving track in real time and performing the collision risk assessment, it is ensured that the vehicle can respond to the environmental change in real time and make the safest driving decision, thereby improving the safety of vehicle control.

Optionally, controlling travel of the target vehicle based on the collision prediction result includes turning on an automatic emergency braking function of the target vehicle to control the target vehicle to enter a braking travel state in response to determining that there is a risk of collision between the target vehicle and the dangerous target object based on the collision prediction result.

As an alternative implementation mode, when collision risk exists, the vehicle-mounted control unit immediately activates an automatic emergency braking function of the target vehicle, the braking system responds to an instruction of the vehicle-mounted control unit to perform emergency braking, the speed of the target vehicle is reduced, meanwhile, the steering wheel angle is adjusted according to the current driving environment of the target vehicle, the target vehicle is guided to deviate to an area without interference of dangerous targets, and direct collision with the dangerous targets is avoided.

Based on the above-mentioned alternative embodiment, when the collision prediction result shows that there is a collision risk between the target vehicle and the dangerous target object, the automatic emergency braking function of the target vehicle is immediately started, and the target vehicle is controlled to rapidly enter a braking running state, so that the occurrence of actual collision can be significantly reduced or avoided, thereby protecting the safety of vehicle occupants and reducing potential traffic accident damage.

As an alternative implementation manner, the collision prediction result shows that the predicted running route of the target vehicle and the position of the dangerous target object have no intersection, namely no collision risk exists between the predicted running route of the target vehicle and the position of the dangerous target object, the vehicle-mounted control unit maintains the normal running state of the target vehicle, emergency braking or adjustment of the steering wheel angle of the target vehicle is not needed, and unnecessary emergency braking is avoided.

Based on the above-mentioned alternative embodiment, when the collision prediction result shows that there is no collision risk between the target vehicle and the dangerous target object, the control target vehicle keeps a normal running state, which not only reduces uncomfortable feeling to passengers caused by sudden deceleration or lane change caused by erroneous judgment, but also improves traffic efficiency, avoids traffic jam caused by frequent emergency braking, and ensures smooth road traffic.

As an optional implementation manner, during the driving process of the target vehicle, the sensor continuously collects structural information such as the length, width, curvature, gradient, intersection, traffic sign, lane division and the like of the target road, and acquires real-time position information of the target vehicle through a GPS or other positioning technology, so that the first target area is determined by combining the real-time position information of the target vehicle with the road structural information.

Based on the above-mentioned alternative embodiment, by combining the position information of the own vehicle and the road structure information, the target area around the target vehicle can be defined more accurately, which is helpful for the system to identify and track the potentially dangerous target object more accurately, thereby improving the accuracy of collision prediction.

As an optional implementation manner, when the dangerous object enters the first target area, the real-time position information of the dangerous object at the first target position is continuously tracked through the set target tracking identifier of the dangerous object, the position change information, the speed change information and the direction change information of the dangerous object are determined based on the acquired real-time position information, and then the position tracking information of the dangerous object is determined based on the movement attribute change information.

Based on the above-mentioned alternative embodiment, through continuous monitoring and analysis of the position tracking information, the motion state of the dangerous target object can be accurately obtained, so that the accuracy and the instantaneity of collision avoidance control are improved.

Fig. 6 is a schematic diagram of an automatic emergency control system according to one embodiment of the present disclosure, as shown in fig. 6, the automatic emergency control system of the present disclosure includes a man-machine interaction interface, a braking module, a power module, a terminal perception locator, a locating system, a cloud server, and a vehicle-mounted control module. The system comprises a man-machine interaction interface, a braking module, a power module, a terminal perception locator and a locating system, wherein the man-machine interaction interface can display the state of a vehicle, warning information and an emergency operation guide in real time, receive emergency instructions from a user, such as starting automatic emergency braking or requesting road rescue, the braking module is responsible for automatically applying braking force when potential collision risks are detected, slowing down the speed of the vehicle, avoiding or reducing collision consequences as far as possible, the power module adjusts the output of an engine in emergency so as to meet the requirements of emergency braking or steering, the vehicle can be ensured to respond quickly in a dangerous environment, and the terminal perception locator cooperates with the locating system to accurately acquire geographic position information of the vehicle and dangerous objects. The cloud server receives and shares real-time data of all vehicles in real time, including but not limited to vehicle state, environment information and positioning data.

Fig. 7 is a schematic diagram of a vehicle control method according to an embodiment of the disclosure, as shown in fig. 7, firstly, performing position verification on first position information and position tracking information to obtain a position verification result, and meanwhile, performing speed verification on the basis of vehicle speed information and dangerous object speed information to obtain a speed verification result, secondly, obtaining a target verification result according to the position verification result and the speed verification result, and judging a target vehicle predicted running track according to the target verification result and a current steering wheel angle of a target vehicle to obtain a collision prediction result. If the collision risk exists, starting an automatic emergency braking system to avoid collision, and if the collision risk does not exist, keeping the current running direction of the target vehicle to continue.

From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present disclosure may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method described in the embodiments of the present disclosure.

It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) related to the present disclosure are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region, and be provided with corresponding operation entries for the user to select authorization or rejection.

The embodiment of the present disclosure also provides a vehicle control device, which is used for executing the vehicle control method, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

Fig. 8 is a block diagram of a vehicle control apparatus according to one embodiment of the present disclosure, as shown in fig. 8, including:

an acquiring module 801, configured to acquire first position information of a target vehicle, vehicle speed information, second position information of a dangerous target object, and acquire dangerous target object speed information, where the first position information is used to represent real-time position information acquired via a position sensor of the target vehicle, the second position information is used to represent shared position information of a mobile positioning terminal associated with the dangerous target object, and the dangerous target object speed information is used to obtain a moving speed of the dangerous target object via the mobile positioning terminal;

The processing module 802 is configured to perform verification processing based on the first location information, the vehicle speed information, the second location information, and the dangerous target speed information to obtain a target verification result, where the target verification result is used to determine a relative location change condition and a relative speed change condition between the target vehicle and the dangerous target;

a determining module 803, configured to determine a collision prediction result according to the target verification result, where the collision prediction result is used to determine whether there is a collision risk between the target vehicle and the dangerous target object;

A control module 804 for controlling the travel of the target vehicle based on the collision prediction result.

Optionally, the obtaining module 801 is further configured to obtain second location information from a cloud server, where the cloud server is configured to transmit the shared location information uploaded by the mobile positioning terminal.

Optionally, the processing module 802 is further configured to generate a target tracking identifier corresponding to the dangerous target object in response to determining that the dangerous target object enters the first target area based on the second position information, where the first target area is a potential collision risk area that is obtained by extending to the front and the two sides of the target vehicle with the vehicle outer contour of the target vehicle as a starting point, track and detect the dangerous target object based on the target tracking identifier to obtain position tracking information, and perform verification processing based on the first position information, the vehicle speed information, the position tracking information and the dangerous target object speed information in response to determining that the dangerous target object enters the second target area based on the position tracking information to obtain a target verification result, where the second target area is a perception identification area of the target vehicle.

Optionally, the processing module 802 is further configured to perform a position check based on the first position information and the position tracking information to obtain a position check result, where the position check result is used to determine a relative position between the target vehicle and the dangerous target object, perform a speed check based on the vehicle speed information and the dangerous target object speed information to obtain a speed check result, where the speed check result is used to determine a relative speed between the target vehicle and the dangerous target object, and determine the target check result according to the position check result and the speed check result.

Optionally, the determining module 803 is further configured to generate a predicted running track based on the target verification result and the current steering wheel angle of the target vehicle, and analyze the predicted running track to obtain a collision prediction result.

Optionally, the processing module 802 is further configured to obtain target road structure information, where the target road structure information is used to represent road feature information during driving of the target vehicle, and determine the first target area based on the first location information and the target road structure information.

Optionally, the processing module 802 is further configured to obtain real-time location information of the dangerous object within the first target area based on the target tracking identifier, determine movement attribute change information of the dangerous object using the real-time location information, where the movement attribute change information includes location change information, speed change information, and direction change information of the dangerous object, and determine location tracking information based on the movement attribute change information. Optionally, the control module 804 is further configured to control the target vehicle to maintain a normal driving state in response to determining that there is no risk of collision between the target vehicle and the dangerous target object based on the collision prediction result.

Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:

S1, acquiring first position information of a target vehicle, vehicle speed information and second position information of a dangerous target object, and acquiring speed information of the dangerous target object, wherein the first position information is used for representing real-time position information acquired by a position sensor of the target vehicle, the second position information is used for representing shared position information of a mobile positioning terminal associated with the dangerous target object, and the speed information of the dangerous target object is used for representing the moving speed of the dangerous target object acquired by the mobile positioning terminal;

s2, performing verification processing based on the first position information, the vehicle speed information, the second position information and the dangerous target speed information to obtain a target verification result, wherein the target verification result is used for determining the relative position change condition and the relative speed change condition between the target vehicle and the dangerous target;

S3, determining a collision prediction result according to the target verification result, wherein the collision prediction result is used for determining whether collision risk exists between the target vehicle and the dangerous target object;

and S4, controlling the braking of the target vehicle based on the collision prediction result.

Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:

Alternatively, in the present embodiment, the storage medium may include, but is not limited to, a USB flash disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, etc. various media in which a computer program may be stored.

Alternatively, in the present embodiment, the above-described computer program product may be provided as a computer program that performs the steps of:

The foregoing embodiment numbers of the present disclosure are merely for description and do not represent advantages or disadvantages of the embodiments.

In the foregoing embodiments of the present disclosure, the descriptions of the various embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In the several embodiments provided in the present disclosure, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present disclosure may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present disclosure. The storage medium includes a U disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, etc. which can store the program code.

The foregoing is merely a preferred embodiment of the present disclosure, and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present disclosure, which are intended to be comprehended within the scope of the present disclosure.

Claims

1. A vehicle control method characterized by comprising:

Acquiring first position information of a target vehicle, vehicle speed information, second position information of a dangerous target object and dangerous target object speed information, wherein the first position information is used for representing real-time position information acquired by a position sensor of the target vehicle, the second position information is used for representing shared position information of a mobile positioning terminal associated with the dangerous target object, and the dangerous target object speed information is used for representing the moving speed of the dangerous target object acquired by the mobile positioning terminal;

Performing verification processing based on the first position information, the vehicle speed information, the second position information and the dangerous target speed information to obtain a target verification result, wherein the target verification result is used for determining the relative position change condition and the relative speed change condition between the target vehicle and the dangerous target;

Determining a collision prediction result according to the target verification result, wherein the collision prediction result is used for determining whether collision risk exists between the target vehicle and the dangerous target object;

And controlling braking of the target vehicle based on the collision prediction result.

2. The vehicle control method according to claim 1, characterized in that acquiring the second position information includes:

and acquiring the second position information from a cloud server, wherein the cloud server is used for transmitting the shared position information uploaded by the mobile positioning terminal in real time.

3. The vehicle control method according to claim 1, characterized in that performing a verification process based on the first position information, the vehicle speed information, the second position information, and the dangerous object speed information, obtaining the object verification result includes:

Determining that the dangerous target object enters a first target area based on the second position information, and generating a target tracking mark corresponding to the dangerous target object, wherein the first target area is a potential collision risk area which is obtained by taking the self-vehicle outline of the target vehicle as a starting point and extending to the front and two sides of the target vehicle;

Tracking and detecting the dangerous target object based on the target tracking mark to obtain position tracking information;

And responding to the determination that the dangerous target enters a second target area based on the position tracking information, and performing verification processing based on the first position information, the vehicle speed information, the position tracking information and the dangerous target speed information to obtain a target verification result, wherein the second target area is a sensor-perceivable identification area carried by the target vehicle.

4. The vehicle control method according to claim 3, characterized in that performing a verification process based on the first position information, the vehicle speed information, the position tracking information, and the dangerous object speed information, obtaining the object verification result includes:

performing position verification based on the first position information and the position tracking information to obtain a position verification result, wherein the position verification result is used for determining the relative position between the target vehicle and the dangerous target object;

Performing speed verification based on the vehicle speed information and the dangerous target object speed information to obtain a speed verification result, wherein the speed verification result is used for determining the relative speed between the target vehicle and the dangerous target object;

and determining the target verification result according to the position verification result and the speed verification result.

5. The vehicle control method according to claim 1, characterized in that determining the collision prediction result from the target verification result includes:

generating a predicted running track based on the target verification result and the current steering wheel angle of the target vehicle;

And analyzing and processing the predicted running track to obtain the collision prediction result.

6. The vehicle control method according to claim 1, characterized in that controlling the travel of the target vehicle based on the collision prediction result includes:

And controlling the target vehicle to keep a normal running state in response to determining that no collision risk exists between the target vehicle and the dangerous target object based on the collision prediction result.

7. The vehicle control method according to claim 3, characterized in that the method further comprises:

Acquiring target road structure information, wherein the target road structure information is used for representing road characteristic information in the running process of the target vehicle;

the first target area is determined based on the first location information and the target road structure information.

8. The vehicle control method according to claim 3, wherein tracking detection of the dangerous target object based on the target tracking identifier includes:

acquiring real-time position information of the dangerous target object in the first target area based on the target tracking identifier;

Determining movement attribute change information of the dangerous object by utilizing the real-time position information, wherein the movement attribute change information comprises position change information, speed change information and direction change information of the dangerous object;

The location tracking information is determined based on the movement attribute change information.

9. A vehicle, characterized by comprising:

A processor;

a memory for storing the processor-executable instructions;

Wherein the processor is configured to execute the instructions to implement the vehicle control method of any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium includes a stored executable program, wherein the executable program, when run, controls a device in which the storage medium is located to perform the vehicle control method according to any one of claims 1 to 8.