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

Abstract

The present disclosure provides a vehicle control method, a vehicle, a storage medium and a computer program product. The method comprises: obtaining first position information of a target vehicle, vehicle speed information, second position information of a dangerous target object, and obtaining dangerous target object speed information; 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, wherein the target verification result is used to determine the relative position change and the relative speed change between the target vehicle and the dangerous target object; determining a collision prediction result according to 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 object; 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

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of intelligent driving, and in particular, to a vehicle control method, a vehicle, a storage medium and a computer program product. BACKGROUND

[0002] As a key component of intelligent driving vehicles, an automatic emergency braking system can effectively reduce the occurrence of traffic accidents. The vehicle control method in the related art perceives a dangerous target object in front by relying on a front sensor of the vehicle, such as a radar or a camera, and then realizes automatic emergency braking of the vehicle. However, the vehicle control method provided in the related art has the problems of low safety and poor adaptability, and thus it is difficult to provide reliable collision avoidance protection in complex and changeable traffic environments.

[0003] At present, no effective solution has been proposed for the above problems. SUMMARY

[0004] The embodiments of the present disclosure provide a vehicle control method, a vehicle, a storage medium and a computer program product to at least solve the technical problems of low safety and poor adaptability of the vehicle control method provided in the related art.

[0005] According to an embodiment of the present disclosure, a vehicle control method is provided, including: 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 to represent real-time position information collected by 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 represent a moving speed of the dangerous target object obtained 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 object speed information to obtain a target verification result, wherein the target verification result is used to determine a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object; determining a collision prediction result according to 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 object; and controlling braking of the target vehicle based on the collision prediction result.

[0006] Optionally, obtaining the second position information includes: obtaining the second position information from a cloud server, wherein the cloud server is used to transmit the shared position information uploaded by the mobile positioning terminal.

[0007] Optionally, the verifying based on the first position information, the vehicle speed information, the second position information, and the dangerous target speed information to obtain the target verification result comprises: in response to determining that the dangerous target enters the first target area based on the second position information, generating a target tracking identifier corresponding to the dangerous target, wherein the first target area is a potential collision risk area extending from the self-vehicle contour of the target vehicle to the front and both sides of the target vehicle; performing tracking detection on the dangerous target based on the target tracking identifier to obtain position tracking information; and in response to determining that the dangerous target enters the second target area based on the position tracking information, performing the verifying based on the first position information, the vehicle speed information, the position tracking information, and the dangerous target speed information to obtain the target verification result, wherein the second target area is a sensing recognition area of the target vehicle.

[0008] Optionally, the verifying based on the first position information, the vehicle speed information, the position tracking information, and the dangerous target speed information to obtain 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 to determine the relative position between the target vehicle and the dangerous target; performing speed verification based on the vehicle speed information and the dangerous target speed information to obtain a speed verification result, wherein the speed verification result is used to determine the relative speed between the target vehicle and the dangerous target; and determining the target verification result according to the position verification result and the speed verification result.

[0009] Optionally, the determining the collision prediction result according to the target verification result comprises: generating a predicted driving track based on the target verification result and the current steering wheel angle of the target vehicle; and performing analysis processing on the predicted driving track to obtain the collision prediction result.

[0010] Optionally, the controlling the driving of the target vehicle based on the collision prediction result comprises: in response to determining that there is no collision risk between the target vehicle and the dangerous target based on the collision prediction result, controlling the target vehicle to maintain a normal driving state.

[0011] The vehicle control method in the embodiments of the present disclosure further comprises: obtaining target road structure information, wherein the target road structure information is used to represent road feature information in the driving process of the target vehicle; and determining the first target area based on the first position information and the target road structure information.

[0012] Optionally, the tracking detection on the dangerous target based on the target tracking identifier to obtain the position tracking information comprises: obtaining real-time position information of the dangerous target in the first target area based on the target tracking identifier; determining movement attribute change information of the dangerous target by using 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; and determining the position tracking information based on the movement attribute change information.

[0013] According to an embodiment of the present disclosure, a vehicle control device is also provided, comprising: an acquisition module configured to acquire 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 to represent real-time position information collected by a position sensor of the target vehicle, the second position information is used to represent real-time shared position information of a mobile positioning terminal associated with the dangerous target object, and the dangerous target object speed information is used to represent a moving speed of the dangerous target object acquired by the mobile positioning terminal; a processing module configured to perform 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, wherein the target verification result is used to determine a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object; a determination module configured to determine a collision prediction result according to 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 object; and a control module configured to control braking of the target vehicle based on the collision prediction result.

[0014] Optionally, the acquisition module is further configured to acquire the second position information from a cloud server, wherein the cloud server is used to transmit shared position information uploaded by the mobile positioning terminal.

[0015] Optionally, the processing module is further configured to: in response to determining that the dangerous target object enters a first target area based on the second position information, generate a target tracking identifier corresponding to the dangerous target object, wherein the first target area is a potential collision risk area obtained by extending from an ego-vehicle contour of the target vehicle to a front and both sides of the target vehicle; perform tracking detection on the dangerous target object based on the target tracking identifier to obtain position tracking information; and in response to determining that the dangerous target object enters a second target area based on the position tracking information, perform 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 the target verification result, wherein the second target area is a sensing recognition area of the target vehicle.

[0016] 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 to determine 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 to determine 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.

[0017] Optionally, the determining module is further configured to generate a predicted driving track based on the target verification result and a current steering wheel angle of the target vehicle; and analyze and process the predicted driving track to obtain the collision prediction result.

[0018] Optionally, the processing module is further configured to obtain target road structure information, wherein the target road structure information is used to represent road feature information in a driving process of the target vehicle; and determine the first target area based on the first position information and the target road structure information.

[0019] Optionally, the processing module is further configured to obtain real-time position information of the dangerous target object in the first target area based on the target tracking identifier; determine movement attribute change information of the dangerous target object by using 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 determine the position tracking information based on the movement attribute change information.

[0020] Optionally, the control module is further configured to, in response to determining that there is no collision risk between the target vehicle and the dangerous target object based on the collision prediction result, control the target vehicle to keep a normal driving state.

[0021] According to an embodiment of the present disclosure, a vehicle is also provided, comprising a processor, a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the vehicle control method in the embodiments of the present disclosure.

[0022] According to an embodiment of the present disclosure, a computer readable storage medium is also provided, which comprises a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute the vehicle control method in the embodiments of the present disclosure.

[0023] According to an embodiment of the present disclosure, a computer program product is also provided, which comprises computer instructions, and when the computer instructions are executed by a processor, the vehicle control method in the embodiments of the present disclosure is implemented.

[0024] In the embodiments of the present disclosure, by collecting the first position information and the speed information of the target vehicle, and simultaneously obtaining the second position information associated with the mobile positioning terminal and the speed information of the dangerous target object, then performing verification processing by using the above information to obtain a target verification result, and further determining a collision prediction result based on the target verification result, finally controlling the driving of the target vehicle according to the collision prediction result, the purpose of identifying the dangerous target object in advance and avoiding collision risk is achieved, thereby realizing the technical effect of improving the safety and adaptability of vehicle control, and further solving the technical problems of low safety and poor adaptability of the vehicle control method provided in the related art. BRIEF DESCRIPTION OF DRAWINGS

[0025] The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this disclosure, illustrate embodiments of the present disclosure and together with the description serve to explain the present disclosure. In the drawings:

[0026] Figure 1 is a hardware structure diagram of a vehicle control method according to an embodiment of the present disclosure;

[0027] Figure 2 is a flowchart of a vehicle control method according to an embodiment of the present disclosure;

[0028] Figure 3 is a schematic diagram of a first target area according to an embodiment of the present disclosure;

[0029] Figure 4 is a schematic diagram of a vehicle control method according to an embodiment of the present disclosure;

[0030] Figure 5 is a schematic diagram of a vehicle control method according to an embodiment of the present disclosure;

[0031] Figure 6 is a schematic diagram of an automatic emergency control system according to an embodiment of the present disclosure;

[0032] Figure 7 is a schematic diagram of a vehicle control method according to an embodiment of the present disclosure;

[0033] Figure 8 is a structural block diagram of a vehicle control device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0034] In order to enable persons skilled in the art to better understand the present disclosure scheme, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by persons skilled in the art without creative labor should fall within the scope of protection of the present disclosure.

[0035] It should be noted that the terms "first", "second", and the like in the description and in the claims of the present disclosure and the above-described accompanying drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0036] The vehicle control method in the related art perceives the dangerous target object in front by relying on the vehicle forward sensor such as radar or camera, and then realizes automatic emergency braking of the vehicle. However, the vehicle control method provided in the related art has the problems of low safety and poor adaptability, so it is difficult to provide reliable collision avoidance protection in complex and variable traffic environments.

[0037] Specifically, the automatic emergency braking system mainly relies on the sensors of the vehicle itself to detect the dangerous target object in front, which may be affected by factors such as weather, light, shape and size of the dangerous target object, resulting in limited perception or inaccurate target recognition. For example, in the "ghost probe" scenario, that is, when pedestrians or vehicles suddenly appear from the driver's blind area, the sensor may not be able to perceive these targets in real time, so the automatic emergency braking cannot be triggered in time, increasing the risk of collision. In addition, for non-typical dangerous target objects such as overturned vehicles and fallen pedestrians, the traditional automatic emergency braking system may not be able to accurately identify, resulting in delayed braking or false triggering, affecting driving safety.

[0038] According to the embodiments of the present disclosure, a method embodiment of a vehicle control method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that herein.

[0039] The method embodiments can be executed in an electronic device or similar computing device comprising a memory and a processor. Taking a computer terminal as an example, the computer terminal can include one or more processors (the processor can include, but is not limited to, a processing device such as a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a Digital Signal Processing (DSP) chip, a Micro Controller Unit (MCU), a Field Programmable Gate Array (FPGA), a Neural-network Processor Unit (NPU), a Tensor Processing Unit (TPU), an Artificial Intelligence (AI) type processor, etc.) and a memory for storing data. Optionally, the above computer terminal can also include a transmission device for communication function, an input and output device, and a display device. Those skilled in the art can understand that the above structural description is only illustrative, and does not limit the structure of the above computer terminal. For example, the computer terminal can include more or less components than the above structural description, or have a different configuration from the above structural description.

[0040] The memory can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the vehicle control method in the embodiments of the present disclosure. The processor executes various functions and data processing by running the computer program stored in the memory, that is, implements the vehicle control method described above. The memory can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory can further include a memory remotely disposed with respect to the processor, which can be connected to the mobile terminal through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0041] The transmission device is configured to receive or transmit data via a network. The network can include, for example, a wireless network provided by a mobile terminal's communication provider. In one example, the transmission device includes a network interface controller (NIC) that can connect to other network devices through a base station to communicate with the Internet. In one example, the transmission device can be a radio frequency (RF) module that is configured to communicate with the Internet via wireless means.

[0042] The display device can be, for example, a touch screen type liquid crystal display (LCD) and a touch display (also referred to as a "touch screen" or "touch display screen"). The liquid crystal display can enable a user to interact with a user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI) with which a user can interact with the GUI through finger contacts and / or gestures on the touch-sensitive surface, where the human-machine interface functions optionally include one or more of the following: creating a webpage, drawing, text editing, preparing an electronic document, playing a game, video conferencing, instant messaging, composing an email, a call interface, playing digital video, playing digital music, and / or web browsing, and executable instructions for performing the human-machine interface functions are configured / stored in one or more computer program products or readable storage media executable by one or more processors.

[0043] According to the embodiments of the present disclosure, a method embodiment of a vehicle control method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0044] The embodiments of the present disclosure provide a vehicle control method. The vehicle control method can be used to provide an automatic collision avoidance function for a preset application scenario. The preset application scenario can include the following scenarios in the vehicle field: a commuting automatic driving scenario, an artificial intelligence (AI) chauffeur scenario for a family car, an automatic parking assist (APA) scenario (such as memory parking for a self-owned parking space in a garage, intelligent parking for a designated parking space in a parking lot, etc.), and a navigation guided pilot (NGP) scenario in an urban area or a high-speed area. In addition, the preset application scenario can also include, but is not limited to, an automatic distribution collision avoidance scenario of an intelligent driving truck or an unmanned truck in the logistics transportation field, an intelligent farming collision avoidance scenario of an automatic driving agricultural vehicle in the agricultural machinery field, an automatic collision avoidance scenario of a drone, an automatic collision avoidance scenario of an intelligent robot (such as a cleaning robot, a service robot, a delivery robot, etc.), and an automatic collision avoidance scenario of an unmanned / manned aerial vehicle.

[0045] When the preset application scenario is a scenario in other fields except the vehicle field, those skilled in the art should understand that the vehicle in the vehicle control method can be replaced by other objects (such as agricultural machinery, drones, robots, etc.), and the control method can be replaced by a technical method related to the other objects. On this basis, the embodiments of the present disclosure take the intelligent driving technology field as an example to exemplarily illustrate the specific implementation of the vehicle control method.

[0046] Figure 1 FIG. 1 is a hardware structure diagram of a vehicle control method according to an embodiment of the present disclosure. As shown in FIG. 1, the hardware structure includes a terminal device, a vehicle, and a roadside device. Figure 1

[0047] ​Exemplarily, the terminal device generally refers to a smart device capable of participating in communication and providing positioning information, including but not limited to the target vehicle itself, a mobile positioning terminal (such as a smart phone, a smart wearable device) equipped with a GPS positioning system, and other vehicles with a positioning data sharing function, etc. The above-mentioned devices collect environmental data through built-in sensors or collect information through user interaction, and then transmit the collected data to a cloud server or a vehicle control unit of the target vehicle through a network for analysis and processing. The network includes but is not limited to cellular network (such as 4G, 5G), Wi-Fi, Bluetooth, vehicle-to-everything (V2X) technology, etc., which is responsible for real-time data transmission to ensure that the vehicle can receive real-time position information and state data shared by other vehicles, pedestrians, roadside devices, etc. The roadside device refers to a device installed on the side of the road for monitoring and sensing the road environment, including but not limited to radar, camera, infrared sensor, meteorological sensor, traffic signal controller, etc. The data collected by the roadside device is transmitted to the vehicle or the cloud server through the network for vehicle control and traffic management. In order to ensure that the vehicle control method in the embodiments of the present disclosure can more accurately obtain target information and track and control in real time, the mobile terminal needs to ensure the real-time transmission of information and data.

[0048] Further, the terminal device can send a driving scene switching instruction, and send the driving scene switching instruction to the vehicle through the network. The vehicle receives the driving scene switching instruction sent by the terminal device, sends an information subscription request to the roadside device, and the roadside device receives the information subscription request from the vehicle, and transmits the continuously collected roadside perception information to the vehicle.

[0049] Figure 2 is a flowchart of a vehicle control method according to an embodiment of the present disclosure, as shown in Figure 2 The method comprises the following steps:

[0050] In step S11, the first position information of the target vehicle, the vehicle speed information, the second position information of the dangerous target object, and the dangerous target object speed information are obtained, wherein the first position information is used to represent the real-time position information collected by the position sensor of the target vehicle, the second position information is used to represent the shared position information of the mobile positioning terminal associated with the dangerous target object, and the dangerous target object speed information is used to represent the moving speed of the dangerous target object obtained by the mobile positioning terminal;

[0051] In step S12, the first position information, the vehicle speed information, the second position information, and the dangerous target object speed information are verified to obtain a target verification result, wherein the target verification result is used to determine the relative position change and the relative speed change between the target vehicle and the dangerous target object;

[0052] Step S13, determining the collision prediction result according to 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 object;

[0053] Step S14, controlling the braking of the target vehicle based on the collision prediction result.

[0054] The first position information refers to the real-time position data obtained by the vehicle positioning system of the target vehicle, including but not limited to the current latitude and longitude coordinates, driving direction, etc. of the target vehicle, which is a direct reflection of the position state of the target vehicle itself.

[0055] The mobile positioning terminal refers to a smart device with a position sharing function, which can determine its own position autonomously or through an integrated positioning module such as a Global Positioning System (GPS), Beidou navigation system, or other satellite positioning systems, and upload and share its position information in real time through 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, smartphones, and smart wearable devices.

[0056] The position sensor refers to a sensor device installed on a vehicle for real-time monitoring and determining the precise geographic coordinates of the vehicle, including but not limited to GPS receivers, Beidou navigation system receivers, and other satellite positioning sensors, as well as inertial navigation systems, odometers, wheel speed sensors, dead reckoning systems, and other auxiliary positioning devices.

[0057] The dangerous target object refers to an object that may pose a collision risk to the target vehicle on its driving path, including but not limited to pedestrians, bicycles, motorcycles, other motor vehicles, and any other external factors that may affect the safe driving of the vehicle.

[0058] As an optional implementation, assuming that an autonomous vehicle is smoothly driving on a busy urban street, the vehicle's onboard GPS sensor continuously records and updates the precise geographic position of the vehicle, forming the first position information for subsequent analysis. At the same time, the target vehicle's real-time driving speed is obtained based on the vehicle's onboard wheel speed sensor, ensuring the real-time accuracy of the vehicle speed information. During this period, a pedestrian uses the location sharing application on his mobile phone as a mobile positioning terminal, which is interconnected with the cloud server to upload the pedestrian's location information to the vehicle's onboard control unit in real time, forming the second position information. The pedestrian's movement speed information, captured and processed by the motion sensor built-in his mobile phone, is also transmitted to the vehicle's onboard control unit for analysis. In order to assess the collision risk, the vehicle's onboard control unit first integrates all the collected information, including the target vehicle's real-time position and speed, as well as the location and speed data provided by the pedestrian. Subsequently, the vehicle's onboard control unit starts its verification process by comparing and analyzing the above data to calculate the relative position change and relative speed between the target vehicle and the pedestrian, generating a target verification result. Then, based on the target verification result, the vehicle's onboard control unit accurately determines whether there is a collision risk and the time and location of potential collision based on the target vehicle's driving path, current speed, and the pedestrian's moving direction and speed. In the case of detecting a collision risk, the vehicle's onboard control unit activates the automatic emergency braking system to control the vehicle to slow down or even stop to avoid collision. Conversely, if the prediction result shows no collision risk, the vehicle's onboard control unit maintains continuous monitoring of the surrounding environment to ensure the safe driving of the target vehicle.

[0059] Based on the above steps S11 to S14, by collecting the position information and speed information of the target vehicle, and simultaneously obtaining the position information and speed information of the dangerous target object associated with the mobile positioning terminal, then using the above information for verification processing, the target verification result is obtained, and based on the target verification result, the collision prediction result is further determined, finally, according to the collision prediction result, the driving of the target vehicle is controlled, the purpose of identifying and avoiding collision risk in advance is achieved, thereby realizing the technical effect of improving the safety and adaptability of vehicle control, and further solving the technical problems of low safety and poor adaptability of the vehicle control method provided in the related art.

[0060] Optionally, obtaining the second position information comprises: obtaining the second position information from a cloud server, wherein the cloud server is configured to transmit the shared location information uploaded by the mobile positioning terminal.

[0061] The cloud server mentioned above refers to a centralized network storage and processing platform responsible for receiving, storing, processing and real-time sharing of shared location information from various mobile positioning terminals. As the hub of data transmission, the cloud server can receive and transmit location and speed information uploaded by mobile intelligent devices such as smartphones, smartwatches or other terminals with location sharing functions in real time, while having powerful data processing capabilities to analyze and manage uploaded location information, ensuring data accuracy and timeliness. Common cloud servers include Ali Cloud, Tencent Cloud, Google Cloud Platform, etc.

[0062] As an optional implementation, the cloud server is responsible for transmitting and managing shared location information uploaded by mobile positioning terminals integrated with sharing location functions, such as smartphones, smartwatches or vehicles with positioning and communication capabilities. The terminal device obtains its own or associated object's location data through its built-in GPS module, then encrypts and uploads the obtained location data to the cloud server. On the server side, after verification and integration, the location data forms a real-time location database. When an autonomous vehicle approaches a traffic participant or a potential dangerous target, the vehicle control unit sends a request to the cloud server to obtain the shared location information uploaded by mobile positioning terminals in the area. The cloud server responds quickly, retrieves the location information of the dangerous target associated with the requesting vehicle from its transmitted real-time location database, and feeds it back to the vehicle control unit as the second location information.

[0063] Based on the above optional embodiment, the shared location information of the dangerous target is obtained from the cloud server, so that the vehicle's vehicle control unit not only relies on direct perception of on-board sensors such as radar and camera, but also can receive and integrate real-time location data uploaded from external mobile positioning terminals. Through the cloud server, the shared location information of the dangerous target is transmitted to the vehicle control unit in real time, enabling the vehicle to predict the existence of traffic participants or dangerous targets outside the sensor perception range or limited by sensors, reducing traffic accidents caused by sensor perception limitations, and improving the safety and adaptability of vehicle control.

[0064] Optionally, in step S12, a verification process is performed based on the first location information, vehicle speed information, second location information and dangerous target speed information to obtain a target verification result, which includes:

[0065] In step S121, in response to determining that the dangerous target enters the first target area based on the second location information, a target tracking identifier corresponding to the dangerous target is generated, wherein the first target area is a potential collision risk area obtained by extending from the self-vehicle outline of the target vehicle to the front and both sides of the target vehicle.

[0066] Step S122, tracking detection of the dangerous target object based on the target tracking identifier, to obtain position tracking information;

[0067] 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, vehicle speed information, position tracking information, and dangerous target object speed information to obtain a target verification result, wherein the second target area is a sensing recognition area of the target vehicle.

[0068] The first target area refers to a potential collision risk area extending forward and to the sides of the target vehicle based on the outer contour of the target vehicle as the reference point, which is used to obtain information about dangerous target objects and road users that may exist outside the sensing range of existing vehicle sensors such as radar and cameras, or under limited sensor conditions. By monitoring the positioning signal source in the first target area in real time, potential collision risks can be pre-evaluated, i.e., by receiving and analyzing data from terminal devices with shared location information function (such as other vehicles, smartphones, smart wearables, etc.), even in the case of limited or failed vehicle-mounted sensors, the traffic dynamics in front and on the sides can be identified in real time.

[0069] Figure 3 is a schematic diagram of a first target area according to an embodiment of the present disclosure, as shown in Figure 3 The first target area is shown as 100 meters in front of the vehicle and 10 meters outside the width edge.

[0070] The target tracking identifier refers to a unique code or mark assigned to the dangerous target object when the cloud server or vehicle-mounted control unit determines that it has entered the first target area based on the second position information of the dangerous target object (corresponding to the target unique ID transmitted by the cloud), which is used to continuously track and identify the dangerous target object in subsequent tracking detection, ensuring that the target vehicle can accurately lock and continuously monitor the dynamic changes of the dangerous target object, effectively avoiding target loss even in complex environments, and effectively avoiding problems such as radar point drift, radar point divergence, and ghosting of moving targets with radar sensors.

[0071] The position tracking information refers to the position information of the dangerous target object collected over time after continuous tracking detection of the dangerous target object based on the target tracking identifier, including the precise coordinates of the dangerous target object at different time points, reflecting the motion trajectory of the dangerous target object relative to the target vehicle.

[0072] The second target area refers to a target vehicle's sensing recognition area, i.e., an area that can be directly sensed and information obtained by sensors such as vehicle forward radar and camera. The second target area is set according to the performance parameters of the sensors, such as detection distance, angle and accuracy, covering the area in front of the vehicle and part of the side front, ensuring that the vehicle can respond to dangerous target objects or traffic participants appearing on the driving path in real time, assess the collision risk and take corresponding collision avoidance measures, such as automatic emergency braking.

[0073] As an optional implementation, during the driving of the target vehicle, the first target area is defined as a range of 100 meters in front of the vehicle and 10 meters outside the width edge. At a certain moment, a pedestrian wearing a smart watch appears in front. The target vehicle receives the real-time speed information of the pedestrian shared by the smart watch, and at the same time, the cloud server receives the real-time position information shared by the smart watch, showing that the pedestrian is located at a position of 80 meters in front of the vehicle and 6 meters to the right, i.e., the second position information is located at a position of 80 meters in front of the vehicle and 6 meters to the right. Based on the second position information uploaded by the smart watch, the vehicle control unit determines that the pedestrian has entered the first target area of the target vehicle, and generates a specific target tracking identifier "TID5014" for the pedestrian, which is used to update the relative positions of the two parties in real time. Based on the relative positions of the target vehicle and the pedestrian, the automatic emergency braking system confirms that the pedestrian is crossing the road, and based on the relative position information and speed information, determines that the pedestrian and the target vehicle have a collision risk, and executes automatic emergency collision avoidance control, and the vehicle decelerates in advance. Subsequently, when the pedestrian continues to move to the center of the road and enters the vehicle's forward sensing recognition area, the vehicle sensing sensor senses the pedestrian target, and the automatic emergency braking system synchronously receives the sensor input that the pedestrian and the target vehicle have a collision risk, ensuring the double verification of the accuracy of the current automatic emergency braking system collision avoidance control. At the same time, for pedestrians, bicycles and pedestrians crossing the road, even if there is no target input by the front sensing sensor, based on the accurate positioning of the terminal positioning information, the collision avoidance control can be effectively executed.

[0074] Based on the above optional embodiment, when the dangerous target enters the first target area, a target tracking identifier corresponding to the dangerous target is generated, and then the dangerous target is tracked and detected based on the target tracking identifier to obtain position tracking information. Finally, according to the position tracking information, it is determined that the dangerous target enters the second target area, and a target verification result is obtained by verifying the first position information, the vehicle speed information, the position tracking information and the speed information of the dangerous target, which can early warning and accurately judge the potential collision risk, reduce the misjudgment and omission rate of the automatic emergency braking system, especially in the sudden scene of ghost probe, can provide more real-time and effective collision warning for the driver and the vehicle, and ensure the safety of driving.

[0075] Figure 4is a schematic diagram of a vehicle control method according to an embodiment of the present disclosure, as Figure 4 As shown, during the driving of the vehicle, when it is determined according to the second position information of the dangerous target object that the dangerous target object enters the first target area, the dangerous target object is immediately locked, and a target tracking identifier of the dangerous target object is generated for subsequent continuous detection and tracking. When it is detected that the dangerous target object enters the second target area, a verification process is performed to obtain a target verification result.

[0076] As an optional implementation, the vehicle camera or sensor such as radar detects that the dangerous target object enters the second target area, and the vehicle control module performs double verification on the position and speed of the dangerous target object based on the current position and speed of the dangerous target object detected by the sensor. For example, there is a rollover vehicle 100 meters in front of the target vehicle, and the first position information of the target vehicle obtained by the GPS positioning system of the target vehicle and the second position information of the target obstacle continuously detected, the system detects that the target vehicle continuously approaches the front rollover vehicle, and there is a collision risk, and performs deceleration collision avoidance control. At 50 meters, the radar can identify the dangerous target object, which can be used as a double verification of the system to confirm the dangerous target object, thereby improving the identification accuracy of the dangerous target object.

[0077] Optionally, at step S123, a verification process is performed 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, which includes:

[0078] At step S1231, position verification is performed based on the first position information and the position tracking information to obtain a position verification result, wherein the position verification result is used to determine the relative position between the target vehicle and the dangerous target object.

[0079] At step S1232, speed verification is performed 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 to determine the relative speed between the target vehicle and the dangerous target object.

[0080] At step S1233, the target verification result is determined according to the position verification result and the speed verification result.

[0081] As an optional implementation, when the dangerous target object enters the second target area of the vehicle, the vehicle control system immediately compares the first position information of the target vehicle and the position tracking information of the dangerous target object, and calculates the relative position data between the two in real time. Subsequently, speed verification is performed, and the relative speed between the two is verified in real time in combination with the driving speed of the target vehicle and the moving speed of the dangerous target object to determine the possibility of collision. After comprehensively considering the position verification result and the speed verification result, the vehicle control unit determines that the moving trajectory of the dangerous target object and the running trajectory of the vehicle exist a collision risk.

[0082] Based on the above optional embodiment, the target verification result is determined according to the position verification result and the speed verification result, which can realize early prediction and immediate response to potential collision risk, and ensure that the target vehicle and the dangerous target object with collision risk can be based on accurate relative position and relative speed information to make quick and accurate collision avoidance control.

[0083] Figure 5 is a schematic diagram of a vehicle control method according to an embodiment of the present disclosure, as shown in Figure 5 The target vehicle driving path contains two dangerous target objects.

[0084] As an optional implementation, the vehicle control unit identifies the dangerous target object approaching or moving away from the target vehicle according to the relative position change and the relative speed change between the target vehicle and the dangerous target object, judges whether the target vehicle and the dangerous target object exist collision risk, and triggers the control based on the original trigger threshold of the automatic emergency braking system.

[0085] Optionally, in step S13, the collision prediction result is determined according to the target verification result, which includes:

[0086] Step S131, generating a predicted driving trajectory based on the target verification result and the current steering wheel angle of the target vehicle;

[0087] Step S132, analyzing and processing the predicted driving trajectory to obtain the collision prediction result.

[0088] As an optional implementation, during the driving of the target vehicle, the vehicle control unit receives the information transmitted by the cloud server, and displays that a truck suddenly rolls over in front of the vehicle driving trajectory in front of the vehicle driving trajectory. The vehicle control unit also monitors the current steering wheel angle of the target vehicle and judges that there is a rolled-over vehicle in the current vehicle driving direction. After receiving the truck rollover information, the vehicle control unit immediately verifies that the target vehicle will collide with the truck at high risk based on the relative position and relative speed between the truck and the target vehicle and the target vehicle driving trajectory.

[0089] Based on the above optional embodiment, by generating a predicted driving trajectory in real time and evaluating the collision risk, it ensures that the vehicle can respond to environmental changes immediately and make the safest driving decision, thereby improving the safety of vehicle control.

[0090] Optionally, controlling the driving of the target vehicle based on the collision prediction result includes: in response to determining that there is a collision risk between the target vehicle and the dangerous target object based on the collision prediction result, starting the automatic emergency braking function of the target vehicle to control the target vehicle to enter the braking driving state.

[0091] As an optional implementation, when there is a collision risk, the vehicle control unit immediately activates the automatic emergency braking function of the target vehicle, and the braking system responds to the instruction of the vehicle control unit to perform emergency braking to reduce the speed of the target vehicle, while adjusting the steering wheel angle according to the current driving environment of the target vehicle to guide the target vehicle to deviate to an area without interference from dangerous target objects, thereby avoiding direct collision with dangerous target objects.

[0092] Based on the above optional 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 quickly enter a braking driving state, which can significantly reduce or avoid the occurrence of actual collision, thereby protecting the safety of vehicle passengers and reducing potential traffic accident damage.

[0093] Optionally, controlling the driving of the target vehicle based on the collision prediction result comprises: in response to determining that there is no collision risk between the target vehicle and the dangerous target object based on the collision prediction result, controlling the target vehicle to maintain a normal driving state.

[0094] As an optional implementation, the collision prediction result shows that the predicted driving route of the target vehicle has no intersection with the position of the dangerous target object, that is, there is no collision risk between the two, and the vehicle control unit maintains the normal driving state of the target vehicle without the need for emergency braking or adjusting the steering wheel angle of the target vehicle, thereby avoiding unnecessary emergency braking.

[0095] Based on the above optional embodiment, when the collision prediction result shows that there is no collision risk between the target vehicle and the dangerous target object, the target vehicle is controlled to maintain a normal driving state, which not only reduces the discomfort of passengers caused by sudden deceleration or lane change due to misjudgment, but also improves traffic efficiency, avoids traffic congestion caused by frequent emergency braking, and ensures smooth road traffic.

[0096] The vehicle control method in the embodiments of the present disclosure further comprises: obtaining target road structure information, wherein the target road structure information is used to represent road feature information in the driving process of the target vehicle; and determining the first target area based on the first position information and the target road structure information.

[0097] As an optional implementation, in the driving process of the target vehicle, the sensor continuously collects structure information of the target road, such as length, width, curvature, slope, intersection, traffic sign, lane division, and obtains real-time position information of the target vehicle through GPS or other positioning technology, and then determines the first target area in combination with the real-time position information of the target vehicle and the road structure information.

[0098] Based on the above optional embodiment, by combining the position information of the ego vehicle and the road structure information, the target area around the target vehicle can be more accurately defined, which helps the system to more accurately identify and track potential dangerous target objects, thereby improving the accuracy of collision prediction.

[0099] Optionally, the tracking detection of the dangerous target object based on the target tracking identifier includes: obtaining 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 using the real-time position information, wherein the movement attribute change information includes: 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.

[0100] As an optional implementation, when the dangerous target object enters the first target area, the real-time position information of the dangerous target object in the first target area is continuously tracked through the set target tracking identifier of the dangerous target object, and the position change information, the speed change information and the direction change information of the dangerous target object are determined based on the obtained real-time position information, and then the position tracking information of the dangerous target object is determined based on the above movement attribute change information.

[0101] Based on the above optional embodiment, by continuously monitoring and analyzing the position tracking information, the motion state of the dangerous target object can be accurately obtained, thereby improving the accuracy and real-time performance of the collision avoidance control.

[0102] Figure 6 is a schematic diagram of an automatic emergency control system according to an embodiment of the present disclosure, as shown in Figure 6 The automatic emergency control system of the present disclosure includes the following components: a human-computer interaction interface, a braking module, a power module, a terminal perception locator, a positioning system, a cloud server and a vehicle-mounted control module. The human-computer interaction interface can display the vehicle state, warning information and emergency operation guide in real time, and at the same time receive emergency instructions from the user, such as starting automatic emergency braking or requesting road rescue; the braking module is responsible for automatically applying brake force when detecting potential collision risk, slowing down the vehicle speed and trying to avoid or mitigate the consequences of collision; the power module adjusts the engine output in emergency situations to meet the needs of emergency braking or steering, ensuring that the vehicle can respond quickly in dangerous environments; the terminal perception locator and the positioning system cooperate to accurately obtain the geographic position information of the vehicle and the dangerous target object. The cloud server receives and shares the real-time data of all vehicles in real time, including but not limited to vehicle state, environmental information and positioning data.

[0103] Figure 7 is a schematic diagram of a vehicle control method according to an embodiment of the present disclosure, as shown in Figure 7As shown, first, the first position information and the position tracking information are subjected to position verification to obtain a position verification result, and meanwhile, the vehicle speed information and the dangerous target speed information are subjected to speed verification to obtain a speed verification result; second, the target verification result is obtained according to the position verification result and the speed verification result, and the target vehicle predicted trajectory is judged according to the target verification result and the current steering wheel angle of the target vehicle to obtain a collision prediction result. If there is a collision risk, the automatic emergency braking system is started to avoid collision; if there is no collision risk, the target vehicle still keeps the current driving direction to continue driving forward.

[0104] Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be realized by means of software and necessary general hardware platforms, and of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present disclosure can be embodied in the form of a software product in essence or in the form of a part of the prior art that makes a contribution. The computer software product is stored in a storage medium (such as a ROM / RAM, a magnetic disk, an optical disk), and includes a plurality of instructions for causing an end device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the method described in each embodiment of the present disclosure.

[0105] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present disclosure are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation portal for user to choose authorization or refusal.

[0106] In the embodiments of the present disclosure, a vehicle control device is also provided, which is used to execute the vehicle control method described above, and the description has been made and will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware, or a combination of software and hardware is also possible and contemplated.

[0107] Figure 8 is a structural block diagram of a vehicle control device according to an embodiment of the present disclosure, as shown in Figure 8 The device includes:

[0108] The acquisition module 801 is configured to acquire 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 to represent real-time position information collected by 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 a moving speed of the dangerous target object acquired by the mobile positioning terminal;

[0109] The processing module 802 is configured to perform checking 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 checking result, wherein the target checking result is used to determine a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object.

[0110] The determination module 803 is configured to determine a collision prediction result according to the target checking result, wherein the collision prediction result is used to determine whether there is a collision risk between the target vehicle and the dangerous target object.

[0111] The control module 804 is configured to control driving of the target vehicle based on the collision prediction result.

[0112] Optionally, the acquisition module 801 is further configured to acquire the second position information from a cloud server, wherein the cloud server is used to transmit shared position information uploaded by the mobile positioning terminal.

[0113] Optionally, the processing module 802 is further configured to: in response to determining that the dangerous target object enters a first target area based on the second position information, generate a target tracking identifier corresponding to the dangerous target object, wherein the first target area is a potential collision risk area obtained by extending from a self-vehicle contour of the target vehicle to front and both sides of the target vehicle; perform tracking detection on the dangerous target object based on the target tracking identifier to obtain position tracking information; and in response to determining that the dangerous target object enters a second target area based on the position tracking information, perform checking processing based on the first position information, the vehicle speed information, the position tracking information, and the dangerous target object speed information to obtain the target checking result, wherein the second target area is a sensing recognition area of the target vehicle.

[0114] Optionally, the processing module 802 is further configured to: perform position checking based on the first position information and the position tracking information to obtain a position checking result, wherein the position checking result is used to determine a relative position between the target vehicle and the dangerous target object; perform speed checking based on the vehicle speed information and the dangerous target object speed information to obtain a speed checking result, wherein the speed checking result is used to determine a relative speed between the target vehicle and the dangerous target object; and determine the target checking result according to the position checking result and the speed checking result.

[0115] Optionally, the determining module 803 is further configured to generate a predicted driving track based on the target verification result and a current steering wheel angle of the target vehicle; and analyze and process the predicted driving track to obtain the collision prediction result.

[0116] Optionally, the processing module 802 is further configured to obtain target road structure information, wherein the target road structure information is used to represent road feature information in a driving process of the target vehicle; and determine the first target area based on the first position information and the target road structure information.

[0117] Optionally, the processing module 802 is further configured to obtain real-time position information of the dangerous target object in the first target area based on the target tracking identifier; determine movement attribute change information of the dangerous target object by using the real-time position information, wherein the movement attribute change information includes position change information, speed change information and direction change information of the dangerous target object; and determine the position tracking information based on the movement attribute change information. Optionally, the control module 804 is further configured to control the target vehicle to keep a normal driving state in response to determining that there is no collision risk between the target vehicle and the dangerous target object based on the collision prediction result.

[0118] According to an embodiment of the present disclosure, a vehicle is also provided, which includes a processor, a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the vehicle control method in the embodiments of the present disclosure.

[0119] Optionally, in the present embodiment, the processor can be configured to execute the following steps by means of a computer program:

[0120] S1, obtaining first position information of a target vehicle, vehicle speed information, second position information of a dangerous target object, and obtaining dangerous target object speed information, wherein the first position information is used to represent real-time position information collected by 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 represent a moving speed of the dangerous target object obtained by means of the mobile positioning terminal;

[0121] S2, 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, wherein the target verification result is used to determine relative position change and relative speed change between the target vehicle and the dangerous target object;

[0122] S3, determining a collision prediction result according to 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 object;

[0123] S4, controlling braking of the target vehicle based on the collision prediction result.

[0124] According to an embodiment of the present disclosure, a computer readable storage medium is also provided, which includes a stored executable program. When the executable program is executed, the device where the storage medium is located performs the vehicle control method in the embodiments of the present disclosure.

[0125] Optionally, in the embodiment, the storage medium can be configured to store a computer program for performing the following steps:

[0126] S1, obtaining first position information of a target vehicle, vehicle speed information, second position information of a dangerous target object, and obtaining dangerous target object speed information, wherein the first position information is used to represent real-time position information collected by 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 represent the moving speed of the dangerous target object obtained by the mobile positioning terminal;

[0127] S2, 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, wherein the target verification result is used to determine the relative position change and the relative speed change between the target vehicle and the dangerous target object;

[0128] S3, determining a collision prediction result according to 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 object;

[0129] S4, controlling the braking of the target vehicle based on the collision prediction result.

[0130] Optionally, in the embodiment, the storage medium can include, but is not limited to, a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various computer program storage media.

[0131] According to an embodiment of the present disclosure, a computer program product is also provided, which includes computer instructions. When the computer instructions are executed by a processor, the vehicle control method in the embodiments of the present disclosure is implemented.

[0132] Optionally, in the embodiment, the computer program product can be configured to execute the following steps:

[0133] S1, acquiring first position information of the target vehicle, vehicle speed information, and second position information of the dangerous target object, and acquiring dangerous target object speed information, wherein the first position information is used to represent real-time position information collected 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 represent a moving speed of the dangerous target object acquired via the mobile positioning terminal;

[0134] S2, performing a verification process 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, wherein the target verification result is used to determine a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object;

[0135] S3, determining a collision prediction result according to 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 object;

[0136] S4, controlling braking of the target vehicle based on the collision prediction result.

[0137] The above sequence numbers of the embodiments of the present disclosure are only for description, and do not represent the advantages or disadvantages of the embodiments.

[0138] In the above embodiments of the present disclosure, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0139] In several embodiments provided by the present disclosure, it should be understood that the disclosed technology can be implemented in other ways. Of course, the embodiment described above is only a schematic, for example, the division of units can be a logical function division, and actual implementation can be another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, unit or module, and can be electrical or other forms.

[0140] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0141] In addition, each function unit in various embodiments of the present disclosure can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit.

[0142] When the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present disclosure, essentially or in part, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present disclosure. The foregoing storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various other media that can store program codes.

[0143] The above description is only the preferred embodiments of the present disclosure, and it should be pointed out that, for those skilled in the art, without departing from the principles of the present disclosure, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present disclosure.

Claims

1. A vehicle control method characterized by, The method comprises the following steps: 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 to represent real-time position information collected by 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 represent a moving speed of the dangerous target object acquired by the mobile positioning terminal; in response to determining that the dangerous target object enters a first target area based on the second position information, generating a target tracking identifier corresponding to the dangerous target object, wherein the first target area is a potential collision risk area extending from a self-vehicle contour of the target vehicle to the front and both sides of the target vehicle; performing tracking detection on the dangerous target object based on the target tracking identifier to obtain position tracking information; in response to determining that the dangerous target object enters a 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 recognizable area of a sensor carried by the target vehicle, and the target verification result is used to determine a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object; determining a collision prediction result according to 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 object; controlling braking of the target vehicle based on the collision prediction result.

2. The vehicle control method according to claim 1, characterized by, The acquiring of the second position information comprises: acquiring the second position information from a cloud server, wherein the cloud server is used to transmit the shared position information uploaded by the mobile positioning terminal in real time.

3. The vehicle control method according to claim 1, characterized by, The 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 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 to determine a 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 to determine a relative speed between the target vehicle and the dangerous target object; determining the target verification result according to the position verification result and the speed verification result.

4. The vehicle control method according to claim 1, characterized by The determination of the collision prediction result according to the target verification result comprises: generating a predicted driving track based on the target verification result and a current steering wheel angle of the target vehicle; performing analysis processing on the predicted driving track to obtain the collision prediction result.

5. The vehicle control method according to claim 1, characterized by The control of driving of the target vehicle based on the collision prediction result comprises: In response to determining that there is no collision risk between the target vehicle and the dangerous target object based on the collision prediction result, the target vehicle is controlled to maintain a normal driving state.

6. The vehicle control method according to claim 1, characterized by The method further includes: obtaining target road structure information, wherein the target road structure information is used to represent road feature information in a driving process of the target vehicle; determining the first target area based on the first position information and the target road structure information.

7. The vehicle control method according to claim 1, characterized by tracking and detecting the dangerous target object based on the target tracking identifier to obtain position tracking information, including: obtaining real-time position information of the dangerous target object within the first target area based on the target tracking identifier; determining movement attribute change information of the dangerous target object using the real-time position information, wherein the movement attribute change information includes position change information, speed change information, and direction change information of the dangerous target object; determining the position tracking information based on the movement attribute change information.

8. A vehicle characterized by comprising: including: a processor; a memory for storing executable instructions of the processor; wherein the processor is configured to execute the instructions to implement the vehicle control method of any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium includes a stored executable program, wherein the executable program controls a device where the storage medium is located to execute the vehicle control method of any one of claims 1 to 7 when the executable program is running.

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