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

Abstract

The invention provides a vehicle control method, a vehicle, a storage medium and a computer program product. The method comprises the steps that first position information and vehicle speed information of a target vehicle and second position information of a dangerous target object are acquired, and speed information of the dangerous target object is acquired; based on the first position information, the vehicle speed information, the second position information and the dangerous target object speed information, performing verification processing to obtain a target verification result, the target verification result being used for determining a relative position change condition and a relative speed change condition between the target vehicle and the dangerous target object; according to the target verification result, a collision prediction result is determined, and the collision prediction result is used for determining 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. According to the vehicle control method and device, the technical problems of low safety and poor adaptability of a vehicle control method provided in the related technology are solved.

Description

Technical Field

[0001] 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 Art

[0002] As a key component of intelligent driving vehicles, the automatic emergency braking system can effectively reduce the occurrence of traffic accidents. The vehicle control method in the related art relies on the vehicle's forward sensors, such as radar or camera, to sense dangerous targets in front, thereby achieving 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, making it difficult to provide reliable collision avoidance protection in complex and changing traffic environments.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[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 methods provided in the related art.

[0005] According to one embodiment of the present disclosure, a vehicle control method is provided, comprising: obtaining first position information of a target vehicle, vehicle speed information, second position information of a dangerous target, and speed information of the dangerous target, 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, and the speed information of the dangerous target is used to represent the moving speed of the dangerous target 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 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.

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

[0007] Optionally, verification processing is performed 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 including: 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 obtained by extending from the outer contour of the target vehicle to the front and both sides of the target vehicle; tracking and detecting the dangerous target based on the target tracking identifier to obtain position tracking information; in response to determining that the dangerous target enters the second target area based on the position tracking information, verification processing is performed based on the first position information, the vehicle speed information, the position tracking information and the speed information of the dangerous target to obtain a target verification result, wherein the second target area is the perception and identification area of ​​the target vehicle.

[0008] Optionally, verification processing is performed 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, including: performing a 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 a 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 based on the position verification result and the speed verification result.

[0009] Optionally, determining a collision prediction result based on the target verification result includes: generating a predicted driving trajectory based on the target verification result and a current steering wheel angle of the target vehicle; and analyzing and processing the predicted driving trajectory to obtain a collision prediction result.

[0010] Optionally, controlling the driving of the target vehicle based on the collision prediction result includes: 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.

[0011] The vehicle control method in the disclosed embodiment also includes: acquiring target road structure information, wherein the target road structure information is used to represent road feature information during the driving process of the target vehicle; and determining a first target area based on the first position information and the target road structure information.

[0012] Optionally, the dangerous target is tracked and detected based on the target tracking identifier to obtain position tracking information including: obtaining real-time position information of the dangerous target within a first target area based on the target tracking identifier; determining movement attribute change information of the dangerous target 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; and determining the position tracking information based on the movement attribute change information.

[0013] According to one embodiment of the present disclosure, a vehicle control device is also provided, including: an acquisition module, used to acquire first position information of a target vehicle, vehicle speed information, second position information of a dangerous target, and speed information of the dangerous target, 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, and the speed information of the dangerous target is used to represent the moving speed of the dangerous target acquired by the mobile positioning terminal; a processing module, used to perform 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; a determination module, used to determine 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 a control module, used to control the braking of the target vehicle based on the collision prediction result.

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

[0015] Optionally, the processing module is also used to: in response to determining that a dangerous target enters a first target area based on the second position information, generate a target tracking identifier corresponding to the dangerous target, wherein the first target area is a potential collision risk area obtained by extending from the outer contour of the target vehicle to the front and both sides of the target vehicle; track and detect the dangerous target based on the target tracking identifier to obtain position tracking information; in response to determining that the dangerous target enters a second target area based on the position tracking information, perform verification processing based on the first position information, vehicle speed information, position tracking information and dangerous target speed information to obtain a target verification result, wherein the second target area is the perception and identification area of ​​the target vehicle.

[0016] Optionally, the processing module is also used to: perform a 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; perform a 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; determine the target verification result based on the position verification result and the speed verification result.

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

[0018] Optionally, the processing module is further used to: obtain target road structure information, wherein the target road structure information is used to represent road feature information during the 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 also used to: obtain real-time position information of the dangerous target within the first target area based on the target tracking identifier; use the real-time position information to determine the movement attribute change information of the dangerous target, wherein the movement attribute change information includes: position change information, speed change information and direction change information of the dangerous target; determine the position tracking information based on the movement attribute change information.

[0020] Optionally, the control module is further used 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 maintain a normal driving state.

[0021] According to one embodiment of the present disclosure, a vehicle is also provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the vehicle control method in the embodiment of the present disclosure.

[0022] According to one embodiment of the present disclosure, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program runs, the device where the storage medium is located is controlled to execute the vehicle control method in the embodiment of the present disclosure.

[0023] According to one embodiment of the present disclosure, a computer program product is also provided. The computer program product includes computer instructions. When the computer instructions are executed by a processor, the vehicle control method in the embodiment of the present disclosure is implemented.

[0024] In the disclosed embodiment, by collecting the first position information and speed information of the target vehicle, the second position information associated with the mobile positioning terminal and the speed information of the dangerous target are obtained simultaneously, and then the above information is used for verification processing to obtain a target verification result, and based on the target verification result, a collision prediction result is further determined. Finally, the driving of the target vehicle is controlled according to the collision prediction result, so as to achieve the purpose of identifying dangerous targets in advance and avoiding collision risks, thereby achieving 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 THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present disclosure and constitute a part of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure. In the drawings:

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

[0027] Figure 2 is a flow chart of a vehicle control method according to one embodiment of the present disclosure;

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

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

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

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

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

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

[0034] In order to enable those skilled in the art to better understand the scheme of the present disclosure, the technical scheme in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present disclosure.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, 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 "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may 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 relies on the vehicle's forward sensors, such as radar or camera, to sense dangerous objects ahead, thereby achieving 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 a complex and changing traffic environment.

[0037] Specifically, the automatic emergency braking system mainly relies on the vehicle's own sensors to detect dangerous targets in front. These sensors may be affected by factors such as weather, light, and the shape and size of dangerous targets, resulting in limited perception or inaccurate target recognition. For example, in a "ghosting" scenario, when pedestrians or vehicles suddenly appear from the driver's blind spot, the sensors may not be able to perceive these targets in real time, and thus fail to trigger the automatic emergency braking in time, increasing the risk of collision. In addition, for atypical dangerous targets such as overturned vehicles and fallen pedestrians, traditional automatic emergency braking systems may not be able to accurately identify them, resulting in untimely braking or false triggering, affecting driving safety.

[0038] According to an embodiment 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 a 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.

[0039] The method embodiment can be executed in an electronic device or a similar computing device including a memory and a processor. Taking running on a computer terminal as an example, the computer terminal may include one or more processors (processors may include but are not limited to central processing units (CPU), graphics processing units (GPU), digital signal processing (DSP) chips, microprocessors (MCU), programmable logic devices (Field Programmable Gate Array, FPGA), neural network processors (Neural-network Processor Unit, NPU), tensor processors (TensorProcessing Unit, TPU), artificial intelligence (Artificial Intelligence, AI) type processors and other processing devices) and a memory for storing data. Optionally, the above-mentioned computer terminal may also include a transmission device, an input and output device, and a display device for communication functions. It can be understood by those of ordinary skill in the art that the above-mentioned structural description is only for illustration, and it does not limit the structure of the above-mentioned computer terminal. For example, the computer terminal may also include more or fewer components than the above-mentioned structural description, or have a configuration different from the above-mentioned 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 embodiment of the present disclosure. The processor executes various functional applications and data processing by running the computer program stored in the memory, that is, realizing the above-mentioned vehicle control method. The memory may include a high-speed random access memory, and may also include a 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 a memory remotely arranged relative to the processor, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0041] The transmission device is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0042] The display device may 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 may enable a user to interact with a user interface of a mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), and a user may interact with the GUI by finger contacts and / or gestures on a touch-sensitive surface, wherein the human-computer interaction functions here may optionally include the following interactions: creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital videos, playing digital music and / or web browsing, etc. The executable instructions for executing the above human-computer interaction functions are configured / stored in a computer program product or readable storage medium executable by one or more processors.

[0043] According to an embodiment 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 a 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 disclosed embodiments 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 scenarios may include the following scenarios in the vehicle field: commuting automatic driving scenarios, artificial intelligence (AI) driving scenarios for family cars, automatic parking assist (APA) scenarios (such as memory parking for owned parking spaces in garages, smart parking for designated parking spaces in parking lots, etc.), and intelligent navigation assistance (Navigation Guided Pilot, NGP) scenarios in urban areas or high-speed areas. In addition, the preset application scenarios may also include, but are not limited to: automatic distribution collision avoidance scenarios of smart driving trucks or unmanned trucks in the field of logistics and transportation, intelligent farming collision avoidance scenarios of self-driving agricultural vehicles in the field of agricultural machinery, automatic collision avoidance scenarios of drones, automatic collision avoidance scenarios of intelligent robots (such as cleaning robots, service robots, delivery robots, etc.), and automatic collision avoidance scenarios of unmanned / manned aircraft.

[0045] When the above-mentioned preset application scenario is a scenario in a field other than the vehicle field, those skilled in the art should be able to understand that the vehicle in the above-mentioned vehicle control method can be replaced with other objects (such as agricultural machinery, drones, robots, etc.), and correspondingly, the control method can be replaced with technical methods related to other objects. On this basis, the specific implementation of the above-mentioned vehicle control method is exemplified in the embodiment of the present disclosure, taking the field of intelligent driving technology as an example.

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

[0047] Exemplarily, terminal devices generally refer to intelligent devices that can participate in communication and provide positioning information, including but not limited to the target vehicle itself, mobile positioning terminals equipped with GPS positioning systems (such as smart phones, smart wearable devices), and other vehicles with positioning data sharing functions). The above-mentioned devices collect environmental data through built-in sensors, or collect information through user interaction, and then transmit the collected data to the cloud server or the on-board control unit of the target vehicle through the network for analysis and processing. The network includes but is not limited to cellular networks (such as 4G, 5G), Wi-Fi, Bluetooth, Vehicle-to-Everything (V2X) and other technologies, which are responsible for real-time data transmission to ensure that the vehicle can receive the location information and status data shared by other vehicles, pedestrians, roadside equipment, etc. in real time. Roadside equipment refers to equipment installed on the side of the road for monitoring and sensing the road environment, including but not limited to radars, cameras, infrared sensors, meteorological sensors, traffic light controllers, etc. The data collected by the roadside equipment is transmitted to the vehicle or cloud server through the network for vehicle control and traffic management. In order to ensure that the vehicle control method in the embodiment of the present disclosure obtains target information more accurately, and tracks and controls in real time, the mobile terminal needs to ensure the real-time transmission of information and data.

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

[0049] Figure 2 is a flow chart of a vehicle control method according to one embodiment of the present disclosure, such as Figure 2 As shown, the method comprises the following steps:

[0050] Step S11, obtaining first position information of the target vehicle, vehicle speed information, second position information of the dangerous target, and speed information of the dangerous target, 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, and the speed information of the dangerous target is used to represent the moving speed of the dangerous target obtained by the mobile positioning terminal;

[0051] Step S12, 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 to determine the relative position change and relative speed change between the target vehicle and the dangerous target;

[0052] Step S13, 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;

[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 acquired by the target vehicle through its vehicle positioning system, including but not limited to the current latitude and longitude coordinates, driving direction and other information of the target vehicle, which is a direct reflection of the position status of the target vehicle itself.

[0055] The above-mentioned mobile positioning terminal refers to an intelligent device with location sharing function, which can determine its own location autonomously or through an integrated positioning module, such as the Global Positioning System (GPS), Beidou Navigation System, or other satellite positioning systems, and upload and share its location information in real time through wireless communication technology or cloud servers. Mobile positioning terminals include but are not limited to vehicles, smart phones, and smart wearable devices equipped with GPS or other satellite positioning systems.

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

[0057] The above-mentioned dangerous targets refer to objects that may pose a collision risk to the target vehicle on the target vehicle's 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, assume that an autonomous vehicle is driving smoothly on a busy city street, and its on-board GPS sensor continuously records and updates the precise geographic location of the vehicle, forming the first location information for subsequent analysis. At the same time, the real-time driving speed of the target vehicle is obtained based on the on-board wheel speed sensor to ensure the real-time and accurate vehicle speed information. During this period, a pedestrian is using a location sharing application on his mobile phone. The mobile phone, as a mobile positioning terminal, uploads the pedestrian's location information to the vehicle's on-board control unit in real time through the interconnection with the cloud server, forming the second location information. The pedestrian's moving speed information is captured and processed by the built-in motion sensor of his mobile phone and is also transmitted to the on-board control unit for analysis. In order to assess the risk of collision, the on-board control unit first integrates all the collected information, including the real-time position and speed of the target vehicle, as well as the position and speed data provided by the pedestrian. Subsequently, the on-board control unit starts its verification processing process, and by comparing and analyzing the above data, calculates the relative position change and relative speed between the target vehicle and the pedestrian, and generates a target verification result. Next, the vehicle control unit accurately determines the existence of collision risk, as well as the time and location of potential collision based on the target verification results, the target vehicle's driving path, current speed, and the direction and speed of pedestrians. If a collision risk is detected, the vehicle control unit activates the automatic emergency braking system to control the vehicle to slow down or even stop completely to avoid collision. Conversely, if the prediction results show no collision risk, the vehicle 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, the position information and speed information of the dangerous target object associated with the mobile positioning terminal are obtained at the same time, and then the above information is used for verification processing to obtain the target verification result, and based on the target verification result, the collision prediction result is further determined. Finally, the driving of the target vehicle is controlled according to the collision prediction result, so as to achieve the purpose of identifying and avoiding collision risks in advance, thereby achieving 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 relevant technology.

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

[0061] The above-mentioned cloud server refers to a centralized network storage and processing platform, which is responsible for receiving, storing, processing and sharing shared location information from various mobile positioning terminals in real time. As a data transmission hub, the cloud server can receive and transmit in real time the location and speed information uploaded by mobile smart devices such as smartphones, smart watches or other terminals with location sharing functions. At the same time, it has powerful data processing capabilities and can analyze and manage the uploaded location information to ensure the accuracy and timeliness of the data. Commonly used cloud servers include Alibaba 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 with integrated shared location functions, such as smart phones, smart watches or vehicles with positioning communication capabilities. The above-mentioned terminal device obtains the location data of itself or an associated object through its built-in GPS module, and then encrypts the acquired location data and uploads it to the cloud server. On the server side, the location data is verified and integrated to form a real-time location database. When the autonomous driving vehicle approaches a traffic participant or a potentially dangerous target, the on-board control unit will send a request to the cloud server to obtain the shared location information uploaded by the mobile positioning terminal in the area. The cloud server responds quickly, retrieves the location information of the dangerous target associated with the requesting vehicle from the real-time location database it transmits, and feeds it back to the on-board control unit as the second location information.

[0063] Based on the above optional embodiment, the shared location information of dangerous targets is obtained from the cloud server, so that the vehicle-mounted control unit of the vehicle not only relies on the direct perception of vehicle-mounted sensors such as radar and cameras, 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 dangerous targets is instantly transmitted to the vehicle-mounted control unit, so that the vehicle can predict in advance the existence of traffic participants or dangerous targets that are outside or restricted from the sensor perception range, reduce traffic accidents caused by sensor perception limitations, and thus improve the safety and adaptability of vehicle control.

[0064] Optionally, in step S12, verification processing is performed based on the first position information, the vehicle speed information, the second position information and the dangerous target speed information, and the target verification result obtained includes:

[0065] Step S121, in response to determining that the dangerous target enters the first target area based on the second position information, generating a target tracking mark corresponding to the dangerous target, wherein the first target area is a potential collision risk area obtained by extending from the outer contour of the target vehicle to the front and both sides of the target vehicle;

[0066] Step S122, tracking and detecting 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 enters the second target area based on the position tracking information, verification processing is performed based on the first position information, vehicle speed information, position tracking information and dangerous target speed information to obtain a target verification result, wherein the second target area is the perception and recognition area of ​​the target vehicle.

[0068] The first target area refers to a potential collision risk area that is calibrated with the outer contour of the target vehicle itself as the reference point and extends to the front and both sides of the vehicle, and is used to obtain information about dangerous targets and traffic participants that are outside the perception range of the vehicle's existing sensors, such as radars and cameras, or that may exist under sensor-restricted conditions. By real-time monitoring of the positioning signal source within the first target area, it is possible to pre-evaluate the potential collision risk, that is, by receiving and analyzing data from terminal devices with the function of sharing location information (such as other vehicles, smart phones, smart wearable devices, etc.), even when the on-board sensors are limited or fail, the traffic dynamics in front and on the side can be identified in real time.

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

[0070] The above-mentioned target tracking identification refers to the unique code or mark (corresponding to the target unique ID transmitted from the cloud) assigned to the dangerous target when the cloud server or the vehicle-mounted control unit determines that the dangerous target has entered the first target area based on the second position information of the dangerous target. It is used to continuously track and identify the dangerous target in subsequent tracking and detection, ensuring that the target vehicle can accurately lock and continuously monitor the dynamic changes of the dangerous target, and effectively avoid target loss even in complex environments. It can effectively avoid radar point drift, radar point divergence, ghosting and other problems that occur in mobile targets of radar and other sensors.

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

[0072] The second target area refers to the perception and recognition area of ​​the target vehicle, that is, the area where the vehicle's forward radar, camera and other sensors can directly perceive and obtain information. The second target area is set based on the performance parameters of the sensor, such as detection distance, angle and accuracy, covering the area directly in front of the vehicle and part of the side front, ensuring that the vehicle can respond to dangerous targets or traffic participants on the driving path in real time, assess the risk of collision and take corresponding collision avoidance measures, such as automatic emergency braking.

[0073] As an optional implementation, during the driving process of the target vehicle, its first target area is defined as 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, and the target vehicle receives the pedestrian speed information shared in real time by the smart watch. At the same time, the cloud server receives the real-time location information shared by the smart watch, showing that the pedestrian is 80 meters in front of the vehicle and 6 meters to the right, that is, the second location information is located 80 meters in front of the vehicle and 6 meters to the right. Based on the second location information uploaded by the smart watch, the on-board 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 position of both parties in real time. Based on the relative position 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 there is a risk of collision between the pedestrian and the target vehicle, executes automatic emergency collision avoidance control, and the vehicle slows down in advance. Then, when the pedestrian continues to move toward the center of the road and enters the vehicle's forward perception and recognition area, the onboard perception sensor perceives the pedestrian target, and the automatic emergency braking system simultaneously receives sensor input that there is a risk of collision between the pedestrian and the target vehicle, ensuring that the system double-checks the accuracy of the current automatic emergency braking system's collision avoidance control. At the same time, for people crossing the road, overturned bicycles, pedestrians, etc., even if there is no target input from the front-line perception sensor, the precise positioning sharing based on the terminal positioning information can effectively perform collision avoidance control.

[0074] Based on the above optional embodiments, when a 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, it is determined that the dangerous target enters the second target area based on the position tracking information, and verification processing is performed based on the first position information, vehicle speed information, position tracking information and dangerous target speed information to obtain a target verification result, which can provide early warning and accurately judge potential collision risks, reduce the misjudgment and missed judgment rate of the automatic emergency braking system, especially in sudden scenarios such as ghosting, and can provide drivers and vehicles with more real-time and effective collision warnings to ensure driving safety.

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

[0076] As an optional implementation, when a sensor such as a vehicle camera or radar detects that a dangerous target has entered the second target area, the on-board control module performs a double check on the position and speed of the dangerous target based on the current position and speed of the dangerous target detected by the sensor. For example, there is an overturned vehicle 100 meters in front of the target vehicle. Through 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 continuously detected target obstacle, the system detects that the target vehicle continues to approach the overturned vehicle in front and there is a risk of collision. The system performs deceleration and collision avoidance control. At 50 meters, the radar can identify the dangerous target, which can be used as a double check for the system to confirm the dangerous target and improve the accuracy of dangerous target identification.

[0077] Optionally, in step S123, verification processing is performed based on the first position information, the vehicle speed information, the position tracking information and the dangerous target speed information, and the target verification result obtained includes:

[0078] Step S1231, performing a 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 object;

[0079] Step S1232, 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;

[0080] Step S1233, determining the target verification result according to the position verification result and the speed verification result.

[0081] As an optional implementation, when a dangerous target enters the second target area of ​​the vehicle, the vehicle-mounted control system will immediately compare the first position information of the target vehicle and the position tracking information of the dangerous target, and calculate the relative position data between the two in real time. Subsequently, a speed check is performed, combining the driving speed of the target vehicle and the moving speed of the dangerous target, and the relative speed between the two is checked in real time to determine the possibility of a collision. After comprehensively considering the position check results and the speed check results, the vehicle-mounted control unit determines that there is a risk of collision between the moving trajectory of the dangerous target and the moving trajectory of the vehicle.

[0082] Based on the above optional embodiments, the target verification result is determined according to the position verification result and the speed verification result, so that the early prediction and immediate response to the potential collision risk can be achieved, ensuring that the target vehicle and the dangerous target object with the risk of collision can make fast and accurate collision avoidance control based on accurate relative position and relative speed information.

[0083] Figure 5 is a schematic diagram of a vehicle control method according to one embodiment of the present disclosure, such as Figure 5 As shown, there are two dangerous objects in the target vehicle's driving path.

[0084] As an optional implementation, the on-board control unit identifies whether the dangerous target is approaching or moving away from the target vehicle based on the changes in the relative position and relative speed of the target vehicle and the dangerous target, determines whether there is a risk of collision between the target vehicle and the dangerous target, and triggers control based on the original trigger threshold of the automatic emergency braking system.

[0085] Optionally, in step S13, determining the collision prediction result according to the target verification result 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 a collision prediction result.

[0088] As an optional implementation, during the driving of the target vehicle, the on-board control unit receives information transmitted by the cloud server, which shows that a truck suddenly overturned 200 meters ahead and directly in front of the vehicle's driving trajectory. The on-board control unit also monitors the current steering wheel angle of the target vehicle and determines that there is a rolled-over vehicle in the current direction of the vehicle. After receiving the rollover information of the truck, the on-board control unit immediately detects that the target vehicle will have a high risk of colliding with the truck if it continues to drive in its current state based on the relative position and relative speed of the truck and the target vehicle and the target vehicle's driving trajectory.

[0089] Based on the above optional embodiments, by generating a predicted driving trajectory in real time and performing a collision risk assessment, it is ensured that the vehicle can respond to environmental changes instantly and make the safest driving decisions, 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 risk of collision between the target vehicle and a dangerous target object based on the collision prediction result, turning on an automatic emergency braking function of the target vehicle to control the target vehicle to enter a braking driving state.

[0091] As an optional implementation, when there is a risk of collision, the on-board control unit immediately activates the automatic emergency braking function of the target vehicle. The braking system responds to the command of the on-board control unit, performs emergency braking, reduces the speed of the target vehicle, and adjusts the steering wheel angle according to the current driving environment of the target vehicle to guide the target vehicle to an area without interference from dangerous targets, thereby avoiding direct collision with dangerous targets.

[0092] Based on the above optional embodiments, when the collision prediction results show that there is a risk of collision between the target vehicle and the dangerous target object, the automatic emergency braking function of the target vehicle is immediately activated, and the target vehicle is controlled to quickly enter a braking driving state, which can significantly reduce or avoid the occurrence of an actual collision, thereby protecting the safety of the vehicle occupants and reducing potential traffic accident damage.

[0093] Optionally, controlling the driving of the target vehicle based on the collision prediction result includes: 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 results show that the predicted driving route of the target vehicle has no intersection with the location of the dangerous target object, that is, there is no risk of collision between the two. The on-board control unit maintains the normal driving state of the target vehicle, and there is no need for emergency braking or adjustment of the steering wheel angle of the target vehicle, thereby avoiding unnecessary emergency braking.

[0095] Based on the above optional embodiments, 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 caused to passengers 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 disclosed embodiment also includes: acquiring target road structure information, wherein the target road structure information is used to represent road feature information during the driving process of the target vehicle; and determining a first target area based on the first position information and the target road structure information.

[0097] As an optional implementation, during the driving process of the target vehicle, the sensor continuously collects structural information such as the length, width, curvature, slope, intersections, traffic signs, lane divisions, etc. of the target road, and obtains the real-time position information of the target vehicle through GPS or other positioning technologies, and then combines the real-time position information of the target vehicle with the road structure information to determine the first target area.

[0098] Based on the above optional embodiments, by combining the position information of the 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 targets, thereby improving the accuracy of collision prediction.

[0099] Optionally, the dangerous target is tracked and detected based on the target tracking identifier to obtain position tracking information including: obtaining real-time position information of the dangerous target within a first target area based on the target tracking identifier; determining movement attribute change information of the dangerous target 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; and determining the position tracking information based on the movement attribute change information.

[0100] As an optional implementation, when a dangerous target enters the first target area, the real-time position information of the dangerous target at the first target position is continuously tracked by setting a target tracking identifier of the dangerous target, and the position change information, speed change information and direction change information of the dangerous target are determined based on the acquired real-time position information, and then the position tracking information of the dangerous target is determined based on the above-mentioned mobile attribute change information.

[0101] Based on the above optional embodiments, the motion state of the dangerous target can be accurately acquired through continuous monitoring and analysis of the position tracking information, 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 one embodiment of the present disclosure, such as Figure 6 As shown, the automatic emergency control system disclosed in the present invention includes the following components: a human-computer interaction interface, a braking module, a power module, a terminal sensing locator, a positioning system, a cloud server, and an on-board control module. Among them, the human-computer interaction interface can display the vehicle status, warning information and emergency operation guide in real time, and receive emergency instructions from the user, such as starting automatic emergency braking or requesting road rescue; the braking module is responsible for automatically applying braking force and slowing down the vehicle when a potential collision risk is detected, so as to avoid or mitigate the consequences of the collision as much as possible; the power module adjusts the engine output in an emergency to meet the needs of emergency braking or steering, ensuring that the vehicle can respond quickly in a dangerous environment; the terminal sensing locator cooperates with the positioning system to accurately obtain the geographic location information of the vehicle and dangerous targets. The cloud server receives and shares real-time data of all vehicles in real time, including but not limited to vehicle status, environmental information and positioning data.

[0103] Figure 7 is a schematic diagram of a vehicle control method according to one embodiment of the present disclosure, such as Figure 7As shown, first, the first position information and the position tracking information are checked to obtain the position check result. At the same time, the speed check is performed based on the vehicle speed information and the dangerous target speed information to obtain the speed check result. Secondly, the target check result is obtained according to the position check result and the speed check result, and the target vehicle predicted driving trajectory is judged according to the target check result and the current steering wheel angle of the target vehicle to obtain the collision prediction result. If there is a collision risk, the automatic emergency braking system is activated to avoid the collision; if there is no collision risk, the target vehicle still maintains the current driving direction and continues to move forward.

[0104] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present disclosure.

[0105] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0106] In the embodiments of the present disclosure, a vehicle control device is also provided, which is used to execute the above-mentioned vehicle control method, and the description has been made no further. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0107] Figure 8 is a structural block diagram of a vehicle control device according to one embodiment of the present disclosure, such as Figure 8 As shown, the device comprises:

[0108] The acquisition module 801 is used to acquire first position information of the target vehicle, vehicle speed information, second position information of the dangerous target, and speed information of the dangerous target, 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, and the speed information of the dangerous target is the moving speed of the dangerous target obtained by the mobile positioning terminal;

[0109] The processing module 802 is used to perform 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 to determine the relative position change and relative speed change between the target vehicle and the dangerous target;

[0110] A determination module 803 is used 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;

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

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

[0113] Optionally, the processing module 802 is also used to: in response to determining that a dangerous target enters a first target area based on the second position information, generate a target tracking identifier corresponding to the dangerous target, wherein the first target area is a potential collision risk area obtained by extending from the outer contour of the target vehicle to the front and both sides of the target vehicle; track and detect the dangerous target based on the target tracking identifier to obtain position tracking information; in response to determining that the dangerous target enters a second target area based on the position tracking information, perform verification processing based on the first position information, vehicle speed information, position tracking information and dangerous target speed information to obtain a target verification result, wherein the second target area is the perception and identification area of ​​the target vehicle.

[0114] Optionally, the processing module 802 is also used to: perform a 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; perform a 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; determine the target verification result based on the position verification result and the speed verification result.

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

[0116] Optionally, the processing module 802 is further used to: obtain target road structure information, wherein the target road structure information is used to represent road feature information during the 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 used to: obtain the real-time position information of the dangerous target in the first target area based on the target tracking identifier; determine the mobile attribute change information of the dangerous target using the real-time position information, wherein the mobile attribute change information includes: the position change information, speed change information and direction change information of the dangerous target; determine the position tracking information based on the mobile attribute change information. Optionally, the control module 804 is further used to: in response to determining that there is no collision risk between the target vehicle and the dangerous target based on the collision prediction result, control the target vehicle to maintain a normal driving state.

[0118] According to one embodiment of the present disclosure, a vehicle is also provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the vehicle control method in the embodiment of the present disclosure.

[0119] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0120] S1, obtaining first position information of a target vehicle, vehicle speed information, second position information of a dangerous target, and speed information of the dangerous target, 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, and the speed information of the dangerous target is used to represent a moving speed of the dangerous target obtained by 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 speed information 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;

[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 the braking of the target vehicle based on the collision prediction result.

[0124] According to one embodiment of the present disclosure, a computer-readable storage medium is also provided, the computer-readable storage medium including 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 embodiment of the present disclosure.

[0125] Optionally, in this embodiment, the storage medium may 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 speed information of the dangerous target object, 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 speed information of the dangerous target object is used to represent a 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 speed information 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;

[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 this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

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

[0132] Optionally, in this embodiment, the computer program product may be configured as a computer program for executing the following steps:

[0133] S1, obtaining first position information of a target vehicle, vehicle speed information and second position information of a dangerous target object, and obtaining speed information of the dangerous target object, 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 speed information of the dangerous target object is used to represent a moving speed of the dangerous target object obtained by the mobile positioning terminal;

[0134] 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 to determine the relative position change and relative speed change between the target vehicle and the dangerous target;

[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 the braking of the target vehicle based on the collision prediction result.

[0137] The serial numbers of the above-mentioned 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 emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0139] In the several embodiments provided in the present disclosure, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

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

[0141] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0142] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0143] The above is only a preferred embodiment of the present disclosure. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present disclosure. These improvements and modifications should also be regarded as the scope of protection of the present disclosure.

Claims

1. A vehicle control method, characterized in that: include: Acquire first position information of a target vehicle, vehicle speed information, second position information of a dangerous target, and speed information of the dangerous target, 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, and the dangerous target speed information is used to represent a moving speed of the dangerous target 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 speed information 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 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; Braking of the target vehicle is controlled based on the collision prediction result.

2. The vehicle control method according to claim 1, characterized in that: Acquiring the second location information includes: The second location information is obtained from a cloud server, wherein the cloud server is used to transmit the shared location information uploaded by the mobile positioning terminal in real time.

3. The vehicle control method according to claim 1, characterized in that: The target verification result is obtained by performing verification processing based on the first position information, the vehicle speed information, the second position information and the dangerous target speed information, including: In response to determining that the dangerous target enters a first target area based on the second position information, a target tracking mark corresponding to the dangerous target is generated, wherein the first target area is a potential collision risk area extending from the outer contour of the target vehicle to the front and both sides of the target vehicle; Tracking and detecting 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, verification processing is performed 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 an area that can be perceived and identified by a sensor carried by the target vehicle.

4. The vehicle control method according to claim 3, characterized in that: The target verification result is obtained by performing verification processing based on the first position information, the vehicle speed information, the position tracking information and the dangerous target speed information, including: Performing a 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 object; Performing a speed check based on the vehicle speed information and the dangerous target speed information to obtain a speed check result, wherein the speed check result is used to determine the relative speed between the target vehicle and the dangerous target; The target verification result is determined 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 according to the target verification result includes: Generate a predicted driving trajectory based on the target verification result and the current steering wheel angle of the target vehicle; The predicted driving trajectory is analyzed and processed to obtain the collision prediction result.

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

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 to represent road feature information during the driving process of the target vehicle; The first target area is determined based on the first position information and the target road structure information.

8. The vehicle control method according to claim 3, characterized in that: Tracking and detecting the dangerous target based on the target tracking identifier to obtain position tracking information includes: Acquiring real-time position information of the dangerous target object in the first target area based on the target tracking identifier; Determine the movement attribute change information of the dangerous target object by using the real-time position information, wherein the movement attribute change information includes: the position change information, speed change information and direction change information of the dangerous target object; The location tracking information is determined based on the movement attribute change information.

9. A vehicle, characterized in that: include: processor; a memory for storing instructions executable by the processor; Wherein, the processor is configured to execute the instructions to implement the vehicle control method according to 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 when the executable program is executed, the device where the storage medium is located is controlled to execute the vehicle control method according to any one of claims 1 to 8.

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