Low-speed driving assisting method based on value judgment and risk assessment of targets around vehicle

Abstract

The embodiment of the invention provides a low-speed driving auxiliary method based on value judgment and risk assessment of targets around a vehicle, and the method comprises the steps: obtaining the speed of a target vehicle, and judging whether the speed is greater than a first preset speed threshold value or not; if the vehicle speed is larger than a first preset vehicle speed threshold value, environment monitoring data sent by an ultrasonic radar, a millimeter wave radar, a camera and a laser radar in a target vehicle are collected and processed within first preset time; target objects around the vehicle are recognized according to the environment monitoring data, and the recognized target objects around the vehicle are divided based on a preset target object judgment criterion; and performing risk assessment according to a division result, and executing a corresponding auxiliary strategy based on a risk assessment result. According to the method, low-value targets and high-value targets can be distinguished based on the target value judgment criterion, different targets are distinguished, different response measures are taken according to different risk assessment results, and the acceptability and credibility of a driver to the low-speed vehicle periphery auxiliary system are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of assisted driving technology, and in particular to a low-speed driving assistance method based on value determination and risk assessment of targets around a vehicle. Background Art

[0002] Traditional blind spot detection systems mainly rely on sensors such as parking radar and millimeter-wave radar to supplement the detection of vehicle blind spots in the interior and exterior rearview mirrors, front and rear windshields, etc. When a vehicle is detected crossing the blind spot of the vehicle and there is a risk of collision with the main vehicle, the driver will be reminded by flashing lights in the exterior rearview mirror or the A-pillar of the vehicle. Today, with the rapid development of intelligent driving technology, more sensors are used for vehicle assisted driving, and the sensor detection distance and accuracy have also made significant progress. Based on the early blind spot alarm, some vehicles can avoid collisions with high-speed moving and large targets such as vehicles through active steering or emergency braking based on the early alarm, which greatly improves the driving safety of the vehicle. However, there is no system for static targets, low-speed moving targets, adult balance cars, and children's scooters, etc., as shown in the following: 1. The same value standard is used for obstacles around the vehicle, or obstacles are simply screened out after a simple right or wrong judgment, and the target value level cannot be determined according to the specific situation of the obstacles. 2. The same alarm or braking strategy is used for different obstacles without making a clear distinction. The same strategy is used for low-value targets as for high-value targets, which often results in the forced inclusion of some unnecessary vehicles, which is not conducive to improving the driver's sense of identity and acceptance, and further affects some drivers to ignore the intervention of vehicle signal lights during actual driving or even directly turn off the function. Summary of the invention

[0003] Based on this, the purpose of the embodiment of the present application is to propose a low-speed driving assistance method based on value judgment and risk assessment of targets around the vehicle, aiming to fully explore the types of different obstacles in real scenes, and distinguish them into low-value targets and high-value targets according to the target value judgment criteria, and adopt different types of risk assessment and safety assistance system strategies respectively, so as to effectively improve the driver's trust and satisfaction with this function.

[0004] In a first aspect, an embodiment of the present application proposes a low-speed driving assistance method based on value determination and risk assessment of surrounding objects, the method comprising: After the vehicle is powered on, the speed of the target vehicle is obtained, and it is determined whether the speed is greater than a first preset speed threshold; If the vehicle speed is greater than a first preset vehicle speed threshold, collecting and processing environmental monitoring data sent by ultrasonic radar, millimeter wave radar, camera, and laser radar in the target vehicle within a first preset time; Identifying the target objects around the vehicle according to the environmental monitoring data, and classifying the identified target objects around the vehicle based on preset target object determination criteria; Perform risk assessment based on the segmentation results, and execute corresponding auxiliary strategies based on the risk assessment results.

[0005] In some embodiments, the steps of identifying the target objects around the vehicle according to the environmental monitoring data and dividing the identified target objects around the vehicle based on preset target object determination criteria include: According to the target determination criteria, the targets are divided into low-value targets and high-value targets; The low-value targets include plastic barrels, cone barrels, and low plants. The high-value targets are divided into high-value repair objects of the vehicle itself and high-value damaged objects outside the vehicle. The high-value repair objects of the vehicle itself include walls, stone piers, pillars, cars, trees, and telephone poles. The high-value damaged objects outside the vehicle include children and pedestrians.

[0006] In some embodiments, the step of performing risk assessment according to the segmentation results and executing a corresponding auxiliary strategy based on the risk assessment results includes: If the target object around the vehicle is a low-value target object, a first distance between the low-value target object and the target vehicle is obtained, and it is determined whether the first distance is less than a first preset distance threshold; If the first distance is less than a first preset distance threshold, it is determined that the low-value target has entered the first-level alarm range, and a first-level sound and light alarm is actively triggered, and timing is started; If the duration of the first-level sound and light alarm reaches the first preset duration threshold, the first-level sound and light alarm is stopped.

[0007] In some embodiments, the step of performing risk assessment according to the segmentation results and executing a corresponding auxiliary strategy based on the risk assessment results includes: If the target object around the vehicle is a high-value target object, the spatial coordinates of the high-value target object are obtained every second preset time, and the motion state of the high-value target object is determined according to the spatial coordinates of adjacent periods; If the high-value target is stationary, it will enter the first-level alarm range and actively trigger the first-level sound and light alarm; Collect signals to determine whether the driver has intervened. If so, cancel the first-level sound and light alarm; If the driver does not intervene, it determines whether the high-value target has entered the secondary alarm range; If the high-value target enters the secondary alarm range, it is determined again whether the driver intervenes. If not, it is determined whether the high-value target enters the emergency braking range; If a high-value target enters the emergency braking range, the vehicle emergency braking will be actively triggered.

[0008] In some embodiments, if the target object around the vehicle is a high-value target object, the step of obtaining the spatial coordinates of the high-value target object every second preset time, and judging the motion state of the high-value target object according to the spatial coordinates of adjacent periods further includes: If the high-value target is in motion, it will enter the first-level alarm range and actively trigger the first-level sound and light alarm; Determine whether the high-value target has left the first-level alarm range. If it has not left the first-level alarm range, collect signals to determine whether the driver has intervened; If the driver does not intervene, it determines whether the high-value target has entered the secondary alarm range; If it does not enter the second-level alarm range, it will enter the first-level alarm range again and actively trigger the first-level sound and light alarm; If it enters the secondary alarm range, it will automatically trigger the secondary sound and light alarm; Determine whether the high-value target has left the secondary alarm range; If the vehicle has not left the secondary alarm range, the system determines whether the driver has intervened. If the driver has not intervened, the system determines whether the high-value target has entered the emergency braking range. If a high-value target enters the emergency braking range, the vehicle emergency braking will be actively triggered.

[0009] In some embodiments, the method further comprises: If the driver intervenes, the corresponding alarm is cancelled; If you leave the first-level alarm range, the first-level sound and light alarm will be cancelled; If you leave the secondary alarm range, the secondary sound and light alarm will be cancelled.

[0010] In some embodiments, the method further comprises: If the vehicle speed is less than or equal to a first preset vehicle speed threshold, it is determined that the vehicle has not started; If the first distance is greater than or equal to a first preset distance threshold, it is determined that the low-value target has not entered the first-level alarm range.

[0011] In a second aspect, the present application also proposes a low-speed driving assistance system based on value determination and risk assessment of surrounding objects, the system comprising: A vehicle speed acquisition module, used to acquire the speed of the target vehicle after the vehicle is powered on, and determine whether the speed is greater than a first preset vehicle speed threshold; An environmental information monitoring module, for collecting and processing environmental monitoring data sent by ultrasonic radar, millimeter wave radar, camera, and laser radar in the target vehicle within a first preset time if the vehicle speed is greater than a first preset vehicle speed threshold; A target object classification module, used to identify the target objects around the vehicle according to the environmental monitoring data, and classify the identified target objects around the vehicle based on preset target object determination criteria; The assisted driving module is used to perform risk assessment according to the division results and execute corresponding auxiliary strategies based on the risk assessment results.

[0012] In a third aspect, an embodiment of the present application further provides a storage medium, including one or more programs stored in the storage medium, which, when executed, implements the low-speed driving assistance method based on value judgment and risk assessment of targets around the vehicle as described above.

[0013] In a fourth aspect, an embodiment of the present application further provides an electronic device, the electronic device comprising a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute the computer program stored in the memory, the low-speed driving assistance method based on the value judgment and risk assessment of the target objects around the vehicle as described above is implemented.

[0014] Compared with the prior art, the embodiments of the present application have the following advantages: The present invention mainly proposes a risk assessment and safety assistance method for vehicles traveling at low speeds, such as entering and exiting parking spaces at low speeds, passing intersections, and dynamic conditions such as children and pedestrians of different shapes passing around the vehicle, and collisions between vehicles and rigid objects such as walls and rigid columns. Specifically, by fully exploring the types of different obstacles in real scenes, they are distinguished into low-value targets and high-value targets according to the target object value judgment criteria, and different types of risk assessment and safety assistance system strategies are used respectively, which can effectively improve the driver's trust and satisfaction with the function.

[0015] Additional aspects and advantages of the embodiments of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through examples of the embodiments of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of a low-speed driving assistance method based on value determination and risk assessment of vehicle surrounding objects proposed in the first embodiment of the present application; Figure 2 This is a schematic diagram of target determination criteria in the first embodiment of the present application; Figure 3This is a flow chart of risk assessment in the first embodiment of the present application; Figure 4 This is a schematic diagram of the structure of a low-speed driving assistance system based on value judgment and risk assessment of targets around the vehicle proposed in the second embodiment of the present application.

[0017] The following specific implementation manner will further illustrate the embodiments of the present application in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0018] In order to facilitate understanding of the embodiments of the present application, the embodiments of the present application will be described more fully below with reference to the relevant drawings. Several embodiments of the embodiments of the present application are provided in the drawings. However, the embodiments of the present application can be implemented in many different forms and are not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the embodiments of the present application more thorough and comprehensive.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the technical field of the embodiments of the present application. The terms used herein in the description of the embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to limit the embodiments of the present application. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0020] See also Figure 1 , which is a flow chart of a low-speed driving assistance method based on value determination and risk assessment of surrounding objects in the first embodiment of the present application, the method includes steps S101 to S104, wherein: Step S101: After the vehicle is powered on, the speed of the target vehicle is obtained, and it is determined whether the speed is greater than a first preset speed threshold; It should be pointed out that the purpose of judging whether the vehicle speed is greater than the first preset speed threshold is to determine whether the vehicle has started. If it is less than or equal to the first preset speed threshold, it means that the vehicle has not started yet, and no assisted driving monitoring is required at this time.

[0021] Step S102: if the vehicle speed is greater than a first preset vehicle speed threshold, collecting and processing environmental monitoring data sent by ultrasonic radar, millimeter wave radar, camera, and laser radar in the target vehicle within a first preset time; Step S103: identifying the target objects around the vehicle according to the environmental monitoring data, and classifying the identified target objects around the vehicle based on preset target object determination criteria; It should be noted that in this step, the targets are divided into low-value targets and high-value targets according to the target determination criteria; See also Figure 2The low-value targets include but are not limited to plastic barrels, cone barrels, and low plants. The high-value targets are divided into high-value repair objects of the vehicle itself and high-value damaged objects outside the vehicle. The high-value repair objects of the vehicle itself are but are not limited to walls, stone piers, pillars, cars, trees, and telephone poles. The high-value damaged objects outside the vehicle include children and pedestrians. Children are divided into single children and children riding. Children riding are divided into children scooters, children balance bikes, and children bicycle targets according to the children scooter judgment criteria, children balance bike judgment criteria, and children bicycle judgment criteria; adults are divided into single adults and adult riding. Adult riding is divided into adult balance bikes, adult scooters, adult bicycles, and adult electric vehicle targets according to the adult balance bike judgment criteria, adult scooter judgment criteria, adult bicycle judgment criteria, and adult electric vehicle judgment criteria.

[0022] Step S104: Perform risk assessment according to the classification results, and execute corresponding auxiliary strategies based on the risk assessment results.

[0023] See also Figure 3 When conducting risk assessment, corresponding risk assessments are conducted for low-value targets, the motion state of high-value targets, and the static state of high-value targets, as detailed below: If the target position around the vehicle is a high-value target, the spatial coordinates of the high-value target are obtained every second preset time, and the motion state of the high-value target is judged according to the spatial coordinates of adjacent periods; if the motion state of the high-value target is stationary, it enters the first-level alarm range and actively triggers the first-level sound and light alarm; collect signals to determine whether the driver intervenes, and if so, cancel the first-level sound and light alarm; if the driver does not intervene, determine whether the high-value target enters the second-level alarm range; if the high-value target enters the second-level alarm range, determine again whether the driver intervenes, and if not, determine whether the high-value target enters the emergency braking range; if the high-value target enters the emergency braking range, actively trigger the vehicle emergency braking.

[0024] If the target object around the vehicle is a high-value target, the spatial coordinates of the high-value target are obtained every second preset time, and the motion state of the high-value target is judged according to the spatial coordinates of adjacent periods; if the motion state of the high-value target is stationary, it enters the first-level alarm range and actively triggers the first-level sound and light alarm; collect signals to determine whether the driver intervenes, and if so, cancel the first-level sound and light alarm; if the driver does not intervene, determine whether the high-value target enters the second-level alarm range; if the high-value target enters the second-level alarm range, determine again whether the driver intervenes, and if not, determine whether the high-value target enters the emergency braking range; if the high-value target enters the emergency braking range, actively trigger the vehicle emergency braking.

[0025] If the motion state of the high-value target is moving, it will enter the first-level alarm range and actively trigger the first-level sound and light alarm; determine whether the high-value target leaves the first-level alarm range. If it does not leave the first-level alarm range, collect signals to determine whether the driver intervenes; if the driver does not intervene, determine whether the high-value target enters the second-level alarm range; if it does not enter the second-level alarm range, repeatedly enter the first-level alarm range and actively trigger the first-level sound and light alarm; if it enters the second-level alarm range, actively trigger the second-level sound and light alarm; determine whether the high-value target leaves the second-level alarm range; if it does not leave the second-level alarm range, determine whether the driver intervenes. If the driver does not intervene, determine whether the high-value target enters the emergency braking range; if the high-value target enters the emergency braking range, actively trigger the vehicle emergency braking.

[0026] It should also be noted that no matter what kind of risk assessment is carried out, if the driver intervenes, the corresponding alarm will be cancelled; if the driver leaves the first-level alarm range, the first-level sound and light alarm will be cancelled; if the driver leaves the second-level alarm range, the second-level sound and light alarm will be cancelled.

[0027] In addition, if the first distance is greater than or equal to the first preset distance threshold, it is determined that the low-value target has not entered the first-level alarm range. Similarly, the second distance is obtained based on the same method, and whether the target has entered the second-level alarm range is determined according to the second distance. Of course, the second preset distance threshold is smaller than the first preset distance threshold. This ultimately achieves collision avoidance when the high-value target is in motion.

[0028] In summary, the present invention mainly proposes a risk assessment and safety assistance method for vehicles traveling at low speeds, such as entering and exiting parking spaces at low speeds, passing intersections, and dynamic conditions such as children and pedestrians of different shapes passing around the vehicle, and collisions between vehicles and rigid objects such as walls and rigid columns. Specifically, by fully exploring the types of different obstacles in real scenes, they are divided into low-value targets and high-value targets according to the target object value judgment criteria, and different types of risk assessment and safety assistance system strategies are used respectively, which can effectively improve the driver's trust and satisfaction with the function.

[0029] See also Figure 4 , shown is a low-speed driving assistance system based on value determination and risk assessment of surrounding objects in a second embodiment, the system comprising: The vehicle speed acquisition module 10 is used to acquire the vehicle speed of the target vehicle after the vehicle is powered on, and to determine whether the vehicle speed is greater than a first preset vehicle speed threshold; The environmental information monitoring module 20 is used to collect and process the environmental monitoring data sent by the ultrasonic radar, millimeter wave radar, camera, and laser radar in the target vehicle within a first preset time if the vehicle speed is greater than a first preset vehicle speed threshold; The target object classification module 30 is used to identify the target objects around the vehicle according to the environmental monitoring data, and classify the identified target objects around the vehicle based on the preset target object determination criteria; The auxiliary driving module 40 is used to perform risk assessment according to the classification results and execute corresponding auxiliary strategies based on the risk assessment results.

[0030] On the other hand, the embodiment of the present application further proposes a computer storage medium on which one or more programs are stored, which, when executed by a processor, implement the above-mentioned low-speed driving assistance method based on value judgment and risk assessment of targets around the vehicle.

[0031] On the other hand, an embodiment of the present application further proposes an electronic device, including a memory and a processor, wherein the memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory, so as to implement the above-mentioned low-speed driving assistance method based on value judgment and risk assessment of targets around the vehicle.

[0032] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, "computer-readable medium" may be any device that can contain storage, communication, propagation or transmission of a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0033] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0034] It should be understood that the various parts of the embodiments of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0035] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0036] The above-described embodiments only express several implementation methods of the embodiments of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the embodiments of the present application. It should be noted that, for those of ordinary skill in the art, without departing from the concept of the embodiments of the present application, several variations and improvements can also be made, which all belong to the protection scope of the embodiments of the present application. Therefore, the protection scope of the embodiments of the present application shall be subject to the attached claims.

Claims

1. A low-speed driving assistance method based on value judgment and risk assessment of surrounding objects, characterized in that: The method comprises: After the vehicle is powered on, the speed of the target vehicle is obtained, and it is determined whether the speed is greater than a first preset speed threshold; If the vehicle speed is greater than a first preset vehicle speed threshold, collecting and processing environmental monitoring data sent by ultrasonic radar, millimeter wave radar, camera, and laser radar in the target vehicle within a first preset time; Identifying the target objects around the vehicle according to the environmental monitoring data, and classifying the identified target objects around the vehicle based on preset target object determination criteria; Perform risk assessment based on the segmentation results, and execute corresponding auxiliary strategies based on the risk assessment results.

2. The low-speed driving assistance method based on vehicle surrounding object value judgment and risk assessment according to claim 1 is characterized in that: The step of identifying the target objects around the vehicle according to the environmental monitoring data and dividing the identified target objects around the vehicle based on the preset target object determination criteria includes: According to the target determination criteria, the targets are divided into low-value targets and high-value targets; The low-value targets include plastic barrels, cone barrels, and low plants. The high-value targets are divided into high-value repair objects of the vehicle itself and high-value damaged objects outside the vehicle. The high-value repair objects of the vehicle itself include walls, stone piers, pillars, cars, trees, and telephone poles. The high-value damaged objects outside the vehicle include children and pedestrians.

3. The low-speed driving assistance method based on vehicle surrounding object value judgment and risk assessment according to claim 2 is characterized in that: The steps of performing risk assessment according to the division results and executing corresponding auxiliary strategies based on the risk assessment results include: If the target object around the vehicle is a low-value target object, a first distance between the low-value target object and the target vehicle is obtained, and it is determined whether the first distance is less than a first preset distance threshold; If the first distance is less than a first preset distance threshold, it is determined that the low-value target has entered the first-level alarm range, and a first-level sound and light alarm is actively triggered, and timing is started; If the duration of the first-level sound and light alarm reaches the first preset duration threshold, the first-level sound and light alarm is stopped.

4. The low-speed driving assistance method based on vehicle surrounding object value judgment and risk assessment according to claim 3 is characterized in that: The steps of performing risk assessment according to the division results and executing corresponding auxiliary strategies based on the risk assessment results include: If the target position around the vehicle is a high-value target, the spatial coordinates of the high-value target are obtained every second preset time, and the motion state of the high-value target is determined according to the spatial coordinates of adjacent periods; If the high-value target is stationary, it will enter the first-level alarm range and actively trigger the first-level sound and light alarm; Collect signals to determine whether the driver has intervened. If so, cancel the first-level sound and light alarm; If the driver does not intervene, it determines whether the high-value target has entered the secondary alarm range; If the high-value target enters the secondary alarm range, it is determined again whether the driver intervenes. If not, it is determined whether the high-value target enters the emergency braking range; If a high-value target enters the emergency braking range, the vehicle emergency braking will be actively triggered.

5. The low-speed driving assistance method based on vehicle surrounding object value judgment and risk assessment according to claim 4 is characterized in that: If the target object around the vehicle is a high-value target object, the step of obtaining the spatial coordinates of the high-value target object every second preset time, and judging the motion state of the high-value target object according to the spatial coordinates of adjacent periods also includes: If the high-value target is in motion, it will enter the first-level alarm range and actively trigger the first-level sound and light alarm; Determine whether the high-value target has left the first-level alarm range. If it has not left the first-level alarm range, collect signals to determine whether the driver has intervened; If the driver does not intervene, it determines whether the high-value target has entered the secondary alarm range; If it does not enter the second-level alarm range, it will enter the first-level alarm range again and actively trigger the first-level sound and light alarm; If it enters the secondary alarm range, it will automatically trigger the secondary sound and light alarm; Determine whether the high-value target has left the secondary alarm range; If the vehicle has not left the secondary alarm range, the system determines whether the driver has intervened. If the driver has not intervened, the system determines whether the high-value target has entered the emergency braking range. If a high-value target enters the emergency braking range, the vehicle emergency braking will be actively triggered.

6. The low-speed driving assistance method based on value determination and risk assessment of surrounding objects according to any one of claims 1 to 5, characterized in that: The method further comprises: If the driver intervenes, the corresponding alarm is cancelled; If you leave the first-level alarm range, the first-level sound and light alarm will be cancelled; If you leave the secondary alarm range, the secondary sound and light alarm will be cancelled.

7. The low-speed driving assistance method based on value judgment and risk assessment of surrounding objects according to any one of claims 1 to 5, characterized in that: The method further comprises: If the vehicle speed is less than or equal to a first preset vehicle speed threshold, it is determined that the vehicle has not started; If the first distance is greater than or equal to a first preset distance threshold, it is determined that the low-value target has not entered the first-level alarm range.

8. A low-speed driving assistance system based on value judgment and risk assessment of surrounding objects, characterized in that: The system comprises: A vehicle speed acquisition module, used to acquire the speed of the target vehicle after the vehicle is powered on, and determine whether the speed is greater than a first preset vehicle speed threshold; An environmental information monitoring module, for collecting and processing environmental monitoring data sent by ultrasonic radar, millimeter wave radar, camera, and laser radar in the target vehicle within a first preset time if the vehicle speed is greater than a first preset vehicle speed threshold; A target object classification module, used to identify the target objects around the vehicle according to the environmental monitoring data, and classify the identified target objects around the vehicle based on preset target object determination criteria; The assisted driving module is used to perform risk assessment according to the division results and execute corresponding auxiliary strategies based on the risk assessment results.

9. A storage medium, characterized in that: include: The storage medium stores one or more programs, which, when executed by the processor, implement the low-speed driving assistance method based on value judgment and risk assessment of vehicle surrounding objects as described in any one of claims 1-7.

10. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein: The memory is used to store computer programs; When the processor is used to execute the computer program stored in the memory, it implements the low-speed driving assistance method based on value judgment and risk assessment of vehicle surrounding objects as described in any one of claims 1-7.

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