A vehicle driving environment recognition method and device, electronic equipment, and storage medium

Abstract

The application relates to a vehicle driving environment prompting method and device, electronic equipment and a storage medium. The method comprises the following steps: collecting an image in front of a vehicle, identifying the image to obtain an image identification result representing image definition; if the image definition is less than a preset threshold, sending the image identification result and current positioning information of the vehicle to a server; obtaining a driving environment identification result returned by the server; and prompting according to the driving environment identification result. The method can collect the image in front of the vehicle, identify the image definition, and if the image definition is less than the preset threshold, it indicates that the driving environment in front is abnormal. The image identification result and the current positioning information of the vehicle are sent to the server. The server obtains the driving environment identification result by combining the environment information obtained according to the current positioning information with the image identification result. The method can prompt the driving environment in front in advance during driving, and improves the driving safety.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle auxiliary technology, and particularly relates to a vehicle driving environment identification method and device, an electronic device and a storage medium. BACKGROUND

[0002] With the gradual improvement of people's living standards, the number of cars is also increasing year by year, and the safety problem in the driving process of the vehicle has been paid more and more attention by people.

[0003] At present, fog or low-visibility weather has always been one of the reasons for frequent accidents. Sudden natural weather such as fog and heavy rain can be seen everywhere in life. Therefore, how to identify the driving environment in front of the vehicle in advance and prompt the driver during high-speed driving has become a problem to be solved. SUMMARY

[0004] In order to solve the technical problem of how to prompt the driving environment in front of the vehicle in advance, the present application provides a vehicle driving environment identification method, device, electronic device and storage medium.

[0005] In a first aspect, the present application provides a vehicle driving environment prompting method applied to a vehicle, the method comprising:

[0006] Collecting an image in front of the vehicle, identifying the image to obtain an image identification result representing image definition;

[0007] If the image definition is less than a preset threshold, sending the image identification result and current positioning information of the vehicle to a server;

[0008] Obtaining a driving environment identification result returned by the server; the driving environment identification result is generated by the server according to the image identification result and environment information obtained based on the current positioning information;

[0009] Prompting according to the driving environment identification result;

[0010] Optionally, collecting an image in front of the vehicle comprises:

[0011] Obtaining a driving speed of the vehicle;

[0012] Adjusting a shooting frequency and a focal length of a camera according to the driving speed to obtain a target shooting frequency and a target focal length;

[0013] Collecting an image in front of the vehicle according to the target shooting frequency and the target focal length;

[0014] Optionally, adjusting a shooting frequency and a focal length of a camera according to the driving speed to obtain a target shooting frequency and a target focal length comprises:

[0015] obtaining a preset speed threshold value;

[0016] if the driving speed is less than or equal to the speed threshold value, determining that a target shooting frequency of the camera is a fixed first frequency and a target focal length is a fixed first focal length;

[0017] if the driving speed is greater than the speed threshold value, the target shooting frequency of the camera is a second frequency and the target focal length is a second focal length; the second frequency is positively correlated with the driving speed, the second focal length is positively correlated with the driving speed, the second frequency is greater than the first frequency, and the second focal length is greater than the first focal length;

[0018] Optionally, before the image recognition result and the current positioning information of the vehicle are sent to the server, the method further comprises:

[0019] determining whether the communication with the server is normal;

[0020] if the communication with the server is normal, sending the image recognition result and the current positioning information of the vehicle to the server;

[0021] if the server cannot be connected, determining the driving environment recognition result according to the image recognition result and prompting according to the driving environment recognition result;

[0022] Optionally, before the image recognition result and the current positioning information of the vehicle are sent to the server after the communication with the server is normal, the method further comprises:

[0023] obtaining current vehicle positioning information;

[0024] determining whether the vehicle passes through a light-dim area according to the current vehicle positioning information, and if the vehicle passes through the light-dim area, determining a first correction coefficient;

[0025] correcting the image recognition result according to the first correction coefficient, and taking the corrected image recognition result as the image recognition result;

[0026] Optionally, determining whether the vehicle passes through a light-dim area according to the current vehicle positioning information comprises:

[0027] extracting tunnel information in the current vehicle positioning information, and determining whether the vehicle passes through a light-dim area according to the tunnel information;

[0028] and / or,

[0029] obtaining sunrise and sunset time of the current vehicle positioning information, and determining whether the vehicle passes through a light-dim area according to real-time time and the sunrise and sunset time;

[0030] Optionally, the method further comprises: if the vehicle does not pass through the light dim area, determining whether the current weather is abnormal weather; if yes, obtaining a vehicle state and prompting to adjust the vehicle state;

[0031] The obtaining of the vehicle state and the prompting to adjust the vehicle state comprise at least one of the following situations:

[0032] querying vehicle window information and prompting to close side windows and sunroofs;

[0033] querying vehicle light information and prompting to turn on lights;

[0034] querying vehicle temperature information and prompting to turn on air conditioning heating and seat heating;

[0035] querying vehicle driving mode information and prompting to turn on abnormal weather driving mode;

[0036] Optionally, before the image in front of the vehicle is collected, the method further comprises:

[0037] determining that the vehicle starts to drive;

[0038] Correspondingly, after the prompting according to the driving environment recognition result, the method further comprises:

[0039] after it is determined that the vehicle stops driving, stopping collecting the image in front of the vehicle.

[0040] In a second aspect, the application provides a vehicle driving environment prompting method applied to a server, the method comprising:

[0041] obtaining an image recognition result of a target vehicle, the image recognition result being obtained by recognizing an image collected in front of the target vehicle, and being sent when the target vehicle determines that the image is less than a preset threshold;

[0042] obtaining current positioning information of the target vehicle;

[0043] generating a driving environment recognition result of the target vehicle according to the image recognition result and environment information obtained based on the current positioning information;

[0044] sending the driving environment recognition result to the target vehicle to prompt the driving environment of the target vehicle;

[0045] Optionally, after the driving environment recognition result of the target vehicle is generated according to the image recognition result and the environment information obtained based on the current positioning information, the method further comprises:

[0046] obtaining other vehicles within a preset range centered on the current positioning information.

[0047] send the driving environment recognition result to the other vehicle to prompt the other vehicle according to the driving environment recognition result.

[0048] In a third aspect, the present application provides a vehicle driving environment prompting device applied to a vehicle, the device comprising:

[0049] a collection module configured to collect an image in front of the vehicle, recognize the image, and obtain an image recognition result representing image definition;

[0050] a first sending module configured to send the image recognition result and current positioning information of the vehicle to a server if the image definition is less than a preset threshold;

[0051] a first obtaining module configured to obtain a driving environment recognition result returned by the server, the driving environment recognition result being generated by the server according to the image recognition result and environment information obtained based on the current positioning information;

[0052] a prompting module configured to prompt according to the driving environment recognition result.

[0053] In a fourth aspect, the present application provides a vehicle driving environment prompting device applied to a server, the device comprising:

[0054] a second obtaining module configured to obtain an image recognition result representing image definition of a target vehicle, the image recognition result being obtained by the target vehicle collecting an image in front of the vehicle and recognizing the image, and being sent when the target vehicle determines that the image definition is less than a preset threshold;

[0055] a third obtaining module configured to obtain current positioning information of the target vehicle;

[0056] a generating module configured to generate a driving environment recognition result of the target vehicle according to the image recognition result and environment information obtained based on the current positioning information;

[0057] a second sending module configured to send the driving environment recognition result to the target vehicle to prompt a driving environment of the target vehicle.

[0058] In a fifth aspect, the present application provides an electronic device comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus;

[0059] the memory is configured to store a computer program;

[0060] A processor is configured to execute a program stored in a memory to implement the steps of the vehicle driving environment prompting method according to any one of the first aspect or any one of the second aspect.

[0061] In a sixth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is configured to implement the steps of the vehicle driving environment prompting method according to any one of the first aspect or any one of the second aspect when executed by a processor.

[0062] The present application has the following beneficial effects:

[0063] The method provided by the embodiments of the present application collects an image in front of a vehicle, identifies the image to obtain an image identification result representing image definition, sends the image identification result and current positioning information of the vehicle to a server if the image definition is less than a preset threshold, acquires a driving environment identification result returned by the server, the driving environment identification result is generated by the server according to the image identification result and environment information obtained based on the current positioning information, and a prompt is given according to the driving environment identification result. The method can collect an image in front of a vehicle, identify the image to obtain an image definition, and send the image identification result and current positioning information of the vehicle to a server if the image definition is less than a preset threshold, which indicates that there is an abnormal driving environment in front of the vehicle. The server combines the environment information obtained based on the current positioning information with the image identification result to obtain a driving environment identification result. The method can give a prompt for the driving environment in front of the vehicle in advance during driving, and improves the safety of driving. BRIEF DESCRIPTION OF DRAWINGS

[0064] The accompanying drawings, which are incorporated herein and constitute part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without any creative effort.

[0066] Figure 1 A system architecture diagram of a vehicle driving environment prompting method provided by an embodiment of the present application;

[0067] Figure 2 A flowchart of a vehicle driving environment prompting method provided by an embodiment of the present application;

[0068] Figure 3 A flowchart of a vehicle driving environment prompting method provided by another embodiment of the present application;

[0069] Figure 4 A flowchart of a vehicle driving environment prompting method according to another embodiment of the present application;

[0070] Figure 5 A structural diagram of a vehicle driving environment prompting device according to an embodiment of the present application;

[0071] Figure 6 A structural diagram of a vehicle driving environment prompting device according to an embodiment of the present application;

[0072] Figure 7 A structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0073] The advantages and effects of the present application can be easily understood by those skilled in the art from the above description. The present application can also be implemented or applied in other different specific embodiments, and the details in the description can be modified or changed based on different views and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application, but not for limiting the protection scope of the present application.

[0074] The first embodiment of the present application provides a vehicle driving environment prompting method, which can be applied to the system architecture as shown in Figure 1 The number of vehicles 101 connected to the server 102 is not limited.

[0075] The method can be applied to the vehicle 101 or the server 102 in the system architecture, wherein the type of the vehicle 101 is not limited, such as a gasoline car, a pure electric car, a hybrid car or a fuel cell car, etc. The vehicle 101 applying the method can be referred to as a target vehicle, and the server 102 can be a local server, a cloud server or a server cluster.

[0076] Next, based on the system architecture, the vehicle driving environment prompting method is described in detail. When applied to a vehicle, the vehicle driving environment prompting method comprises: Figure 2

[0077] Step 201, collecting an image in front of the vehicle, identifying the image to obtain an image identification result representing the image definition.

[0078] ​The image in front of the vehicle can be collected by a camera. The camera can be fixedly installed to collect the image in front of the vehicle. To ensure the usability of the collected image, the image in the front of the vehicle can be collected. During the driving of the vehicle, the camera remains in the shooting state, and can continuously shoot or can continuously shoot for a second preset time interval after a first preset time interval. Of course, the image recognition result can be the recognition result of the clarity of the continuous multiple images.

[0079] In one embodiment, the image in front of the vehicle is collected, including: obtaining the driving speed of the vehicle, adjusting the shooting frequency and the focal length of the camera according to the driving speed, obtaining the target shooting frequency and the target focal length, and collecting the image in front of the vehicle according to the target shooting frequency and the target focal length.

[0080] To ensure that the vehicle can collect the image in front of the vehicle at different driving speeds (vehicle speed), so that the driver still has enough reaction time after obtaining the image recognition result and the driving environment recognition result returned by the server, in the embodiment, the shooting frequency and the focal length of the camera can be adjusted according to the driving speed of the vehicle.

[0081] In one specific embodiment, the shooting frequency and the focal length of the camera are adjusted according to the driving speed to obtain the target shooting frequency and the target focal length, including: obtaining a preset speed threshold, if the driving speed is less than or equal to the speed threshold, determining that the target shooting frequency of the camera is a fixed first frequency and the target focal length is a fixed first focal length, if the driving speed is greater than the speed threshold, the target shooting frequency of the camera is a second frequency and the target focal length is a second focal length; the second frequency is positively correlated with the driving speed, the second focal length is positively correlated with the driving speed, the second frequency is greater than the first frequency, and the second focal length is greater than the first focal length.

[0082] In the embodiment, the shooting frequency and the focal length of the camera change with the vehicle speed. Taking 40 km / h as an example, when the vehicle speed is less than or equal to 40 km / h, the image in front of the vehicle is collected with the fixed first frequency and the fixed first focal length as the shooting parameters, and the driver also has enough reaction time. When the vehicle speed is greater than 40 km / h, the shooting frequency is positively correlated with the vehicle speed, that is, the faster the vehicle speed, the higher the shooting frequency, and at the same time, the focal length is farther, and the image in front of a farther distance can be collected, so as to ensure that the driver has enough reaction time when a sudden situation such as fog occurs in front of the vehicle.

[0083] It should be noted that the above preset threshold of 40 km / h is only for example and does not represent a limitation.

[0084] In step 202, if the image clarity is less than a preset threshold, the image recognition result and the current positioning information of the vehicle are sent to the server.

[0085] The preset threshold is a preset threshold of definition. When image recognition is performed, an image recognition result representing definition of an image can be obtained according to definition of the image. When the vehicle determines that the definition of the image is less than the preset definition threshold, the image recognition result and current positioning information of the vehicle are sent to the server, so that the server retrieves environmental information of the current positioning information. The environmental information can include traffic information, sunshine information, weather information, and the like, without limitation.

[0086] Since the data needs to be sent to the server, it can be understood that before the image recognition result and the current positioning information of the vehicle are sent to the server, the method further includes: determining whether communication with the server is normal.

[0087] If the communication with the server is normal, the image recognition result and the current positioning information of the vehicle are continued to be sent to the server, and steps 203 and 204 are executed.

[0088] If the server cannot be connected, the vehicle determines a driving environment recognition result in front of the vehicle according to the current image recognition result, and prompts according to the driving environment recognition result. Of course, the current network can also be prompted to be poor and unable to connect the server, so as to remind the driver to pay attention to the road conditions in front of the vehicle and drive carefully, and the safety of driving can also be improved.

[0089] Before the image recognition result and the current positioning information of the vehicle are sent to the server after the communication with the server is normal, the vehicle can analyze the reason why the definition of the image in the image recognition result is less than the preset threshold, such as whether it is caused by light.

[0090] Specifically, it includes: obtaining current vehicle positioning information, determining whether the vehicle passes through a light dark area according to the current vehicle positioning information, determining a first correction coefficient if the vehicle passes through the light dark area, correcting the image recognition result according to the first correction coefficient, and taking the corrected image recognition result as the image recognition result.

[0091] In the embodiment, the current vehicle positioning information (or current vehicle position information) can be positioned by a Beidou satellite positioning system, a global satellite positioning system, or a mobile network. Whether the image is not clear due to light can be determined. If it is determined that the image is not clear due to light dark, the image recognition result can be corrected, such as increasing the definition of the image recognition result by a correction coefficient, so as to improve the accuracy of the server when processing data.

[0092] The determination of whether the vehicle passes through the light dark area according to the current vehicle positioning information can include one of the following two ways or a combination of the two ways.

[0093] The first way is to extract the tunnel information in the current vehicle positioning information, and determine whether the vehicle passes through the light dim area according to the tunnel information.

[0094] If it is determined that the current vehicle is passing through the tunnel through the satellite positioning system or the mobile network positioning, it can be determined that the vehicle is passing through the light dim area.

[0095] The second way is to obtain the sunrise and sunset time of the current vehicle positioning information, and determine whether the vehicle passes through the light dim area according to the real-time time and the sunrise and sunset time.

[0096] If the current real-time time is in the sunset time of the current vehicle positioning information, that is, the vehicle is in the evening, it can also be determined that the vehicle passes through the light dim area.

[0097] After determining that the light causes the image to be unclear, the clarity of the image recognition result needs to be improved by a correction coefficient.

[0098] In one embodiment, the method further comprises: if the vehicle does not pass through the light dim area, determining whether the current weather is abnormal weather, and if so, obtaining the vehicle state and prompting to adjust the vehicle state.

[0099] The obtaining of the vehicle state and the prompting to adjust the vehicle state include at least one of the following cases:

[0100] Querying the vehicle window information and prompting to close the side window and the sunroof;

[0101] Querying the vehicle light information and prompting to turn on the light;

[0102] Querying the vehicle temperature information and prompting to turn on the air conditioning heating and the seat heating;

[0103] Querying the vehicle driving mode and prompting to turn on the abnormal weather driving mode.

[0104] In this embodiment, if the vehicle does not pass through the light dim area, that is, the reason for low clarity is not caused by light, it can be further determined whether the current weather is abnormal weather, and if so, the driver can be prompted to adjust the vehicle state. For example, whether the vehicle window is closed, whether the vehicle light is turned on, whether the temperature in the vehicle is appropriate, and whether the corresponding driving mode is turned on according to the type of abnormal weather, and the like, without limitation.

[0105] Step 203, obtaining the driving environment recognition result returned by the server, which is generated by the server according to the image recognition result and the environment information obtained based on the current positioning information.

[0106] Step 204, prompting according to the driving environment recognition result.

[0107] The prompting mode is not limited, and can be voice broadcast, display on a display interface, etc.

[0108] The method can collect images in front of the vehicle, identify the image definition, and if the image definition is less than a preset threshold, it indicates that the driving environment in front is abnormal. The image recognition result and the current positioning information of the vehicle are sent to the server. The server obtains the driving environment recognition result by combining the image recognition result with the environment information obtained according to the current positioning information. The method can prompt the driving environment in front in the driving process, and improves the driving safety.

[0109] In one embodiment, the image in front of the vehicle is collected only when the vehicle stops driving. Therefore, before collecting the image in front of the vehicle, it can be determined that the vehicle starts driving. After the driving environment recognition result is prompted, if it is determined that the vehicle stops driving, the collection of the image in front of the vehicle is stopped, so as to save the power consumption of the vehicle.

[0110] When applied to the server, the vehicle driving environment prompting method, such as Figure 3 , comprises:

[0111] Step 301: obtaining an image recognition result of a target vehicle, the image recognition result representing image definition, the image recognition result being obtained by identifying an image collected in front of the target vehicle, and being sent when the target vehicle determines that the image definition is less than a preset threshold.

[0112] Step 302: obtaining current positioning information of the target vehicle.

[0113] Step 303: generating a driving environment recognition result of the target vehicle according to the image recognition result and environment information obtained based on the current positioning information.

[0114] Step 304: sending the driving environment recognition result to the target vehicle to prompt the driving environment of the target vehicle.

[0115] The method, the server obtains the image recognition result representing the image definition of the target vehicle, and obtains the current positioning information of the target vehicle. The driving environment recognition result is obtained by combining the image recognition result with the environment information obtained based on the current positioning information. The driving environment recognition result is sent to the target vehicle to prompt the driving environment of the target vehicle. The method can prompt the driving environment in front of the target vehicle in the driving process, and improves the driving safety of the target vehicle.

[0116] In one embodiment, after the driving environment recognition result of the target vehicle is generated according to the image recognition result and the environment information obtained based on the current positioning information, the method further comprises: acquiring other vehicles within a preset range centered on the current positioning information; and sending the driving environment recognition result to the other vehicles to prompt the other vehicles according to the driving environment recognition result.

[0117] The method can prompt other vehicles within a preset range of the target vehicle, thereby improving the driving safety of the other vehicles. Even if the image collected by the other vehicles has normal clarity, the other vehicles can also be prompted in advance about the abnormal driving environment, thereby ensuring the safety of the driver and passengers.

[0118] In one specific embodiment, the vehicle driving environment prompting method comprises: Figure 4

[0119] Step 401, the vehicle drives.

[0120] Step 402, the shooting frequency and focal length of the camera are adjusted according to the driving speed of the vehicle.

[0121] When the vehicle speed is below a fixed speed (for example, 40 km / h), the shooting frequency and focal length of the camera can be fixed, and the driver has sufficient reaction time. When the vehicle drives at a speed of 40 km / h or higher, the shooting frequency and focal length of the camera should be increased to ensure that the driver has sufficient braking distance and reaction time.

[0122] Step 403, continuous shooting and monitoring. The camera continuously shoots images in front and analyzes and processes the images.

[0123] Step 404, it is determined whether the driving environment in front is abnormal. It is determined whether the driving environment in front is abnormal. If a plurality of continuous images are not clear, it is considered to be abnormal. If there is no abnormality, return to continuously execute step 403. If there is an abnormality, execute step 405.

[0124] Step 405, it is determined whether the current abnormality is caused by light through image analysis and processing. If yes, execute step 406. If no, execute step 407.

[0125] The current vehicle position information can be obtained through satellite positioning system positioning or network positioning, and it is determined whether the vehicle is passing through a tunnel or other light-dark area. If the vehicle is not passing through an area that will affect the light at this time, the sunset and sunrise time of this place is obtained through networking to assist in verifying the recognition result. If the cloud cannot be connected, the camera recognition result is directly used as the reference.

[0126] ​Step 406, if it is caused by light, connect the vehicle, query the vehicle state, remind the driver to turn on and off the light, and then return to repeat step 403.

[0127] Step 407, if it is not caused by light, analyze whether the image processing is caused by weather (rain, snow, sandstorm, fog, etc.). If yes, execute step 408, if not, execute step 410. Specifically, obtain the current vehicle location information through the satellite positioning system or network positioning, and then obtain the weather condition of this place through network information to assist in verifying the type of abnormal weather. If there is no abnormal weather information in the current area through cloud query, it may be a sudden weather condition. If it cannot be connected to the cloud, the camera recognition result is directly used as the reference.

[0128] Step 408, connect the vehicle, query the vehicle state, and remind the driver to adjust the vehicle state. Specifically, query the vehicle window information and remind the driver to close the window and sunroof; query the vehicle light information and remind the driver to turn on the correct light (fog light, wide light); query the vehicle temperature information and remind the driver whether to turn on the air conditioner or seat heating; query the vehicle driving mode, if it is a rainy and snowy weather, remind the driver to switch to snow mode or turn on the vehicle anti-skid mode, and at the same time, the rainy and snowy weather should pay attention to the opening of the vehicle wiper, etc.

[0129] Step 409, report the current location and abnormal information to the cloud. If the current abnormal information has not been recorded by the cloud, after the cloud records the abnormal information at this place, it can remind the nearby vehicles that there is abnormal weather at this place, and then return to repeat step 403.

[0130] Step 410, the abnormal reason is unknown, remind the driver that the front driving environment is abnormal, please drive carefully, and then return to repeat step 403.

[0131] Step 411, the vehicle stops driving and interrupts shooting.

[0132] In this embodiment, the vehicle camera takes a photo of the front photo, analyzes it, and sends the camera abnormal result and the current vehicle location information to the cloud if the front driving environment is abnormal. If it cannot be connected to the cloud, the camera recognition result is directly used as the reference. The vehicle receives the warning information from the cloud or the camera and warns the driver through various ways (voice, image) etc.

[0133] The cloud receives the recognition result and the location information sent by the vehicle, queries the traffic information, sunshine information, and weather information of this place through the location information, and considers the comprehensive factors to obtain the abnormal result. If the current abnormal result is caused by sudden abnormal weather, record this information, which can push the warning to remind other nearby vehicles.

[0134] Through the above steps, the driver can effectively help to predict the driving environment change in front of the vehicle in advance during driving, thereby effectively ensuring the life and property safety of passengers in the vehicle, and reminding other nearby vehicles to pay attention to the abnormal weather condition.

[0135] Based on the same technical concept, the second embodiment of the present application provides a vehicle driving environment prompting device, which is applied to a vehicle and comprises: Figure 5 , and the device comprises:

[0136] The collection module 501 is configured to collect an image in front of the vehicle, identify the image, and obtain an image identification result representing image definition;

[0137] The first sending module 502 is configured to send the image identification result and current positioning information of the vehicle to a server if the image definition is less than a preset threshold value;

[0138] The first acquisition module 503 is configured to acquire a driving environment identification result returned by the server; the driving environment identification result is generated by the server based on the image identification result and environment information obtained based on the current positioning information;

[0139] The prompting module 504 is configured to prompt based on the driving environment identification result.

[0140] The device can collect an image in front of the vehicle, identify the image definition, and send the image identification result and current positioning information of the vehicle to a server if the image definition is less than a preset threshold value, indicating that the driving environment in front is abnormal. The driving environment identification result is obtained by the server based on the environment information obtained based on the current positioning information and the image identification result. The device can prompt the driving environment in front in advance during driving, thereby improving the driving safety.

[0141] The device comprises: Figure 6 , and the device comprises:

[0142] The second acquisition module 601 is configured to acquire an image identification result representing image definition of a target vehicle; the image identification result is obtained by the target vehicle by collecting an image in front of the vehicle, identifying the image, and sending the image identification result when the target vehicle determines that the image definition is less than a preset threshold value;

[0143] The third acquisition module 602 is configured to acquire current positioning information of the target vehicle;

[0144] The generation module 603 is configured to generate a driving environment identification result of the target vehicle based on the image identification result and environment information obtained based on the current positioning information;

[0145] The second sending module 604 is configured to send the driving environment recognition result to the target vehicle to prompt the driving environment of the target vehicle.

[0146] As shown in Figure 7 The third embodiment of the present application provides an electronic device, which comprises a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 are in communication with each other through the communication bus 114,

[0147] The memory 113 is configured to store a computer program.

[0148] In one embodiment, the processor 111 is configured to execute the program stored in the memory 113, thereby implementing the vehicle driving environment prompting method provided in any one of the preceding method embodiments.

[0149] The memory, the processor and the communication interface in the electronic device are in communication through the communication bus. The communication bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus and a control bus, etc.

[0150] The memory can include a Random Access Memory (RAM) and can also include a non-volatile memory such as at least one disk memory. Optionally, the memory can also be at least one storage device located away from the processor.

[0151] The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc. The processor can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0152] The fourth embodiment of the present application provides a computer readable medium having non-volatile program code executable by a processor.

[0153] Optionally, in the embodiments of the present application, the computer readable medium is configured to store program code for the processor to execute the above method.

[0154] Optionally, the specific examples in the embodiments can refer to the examples described in the above embodiments, and the embodiments will not be described here again.

[0155] When the embodiments of the present application are implemented, the above-mentioned various embodiments can be referred to, and have corresponding technical effects.

[0156] It can be understood that the embodiments described herein can be realized in hardware, software, firmware, middleware, microcode or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described in the embodiments of the present application, or a combination thereof.

[0157] For software implementation, the technologies herein can be implemented by units performing functions herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0158] Those skilled in the art can clearly understand that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0159] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-mentioned system, device and unit can refer to the corresponding processes in the above-mentioned method embodiments, which will not be described here again.

[0160] In the embodiments of the present application, it should be understood that the disclosed apparatus and method can be implemented in other manners. For example, the embodiments of the apparatus described above are merely schematic; for example, the division of the modules is merely logical function division; an actual implementation can be another division manner, for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, devices or units, and can be electrical, mechanical or in other forms.

[0161] The unit described as a separate component can or can not be physically separate, and the component shown as a unit can or can not be a physical unit, that is, can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment of the present application.

[0162] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can be physically present alone, or two or more units can be integrated into one unit.

[0163] If the function is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application essentially or say the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods in the embodiments of the present application. The foregoing storage medium includes: U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk, and various program codes that can be stored in the medium.

[0164] It has to be explained that, in this text, the relational terms such as "first" and "second" and the like are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or equipment including the element.

[0165] The above embodiments are only the preferred embodiments of the present application for fully illustrating the present application, and the protection scope of the present application is not limited thereto. Any equivalent substitutions or changes made by the skilled in the art based on the present application are within the protection scope of the present application.

Claims

1. A vehicle running environment prompting method characterized by comprising: The method is applied to a vehicle and comprises the following steps: Collecting an image in front of the vehicle, identifying the image to obtain an image identification result representing image definition; If the image definition is less than a preset threshold, sending the image identification result and current positioning information of the vehicle to a server; Obtaining a driving environment identification result returned by the server; the driving environment identification result is generated by the server based on the image identification result and environment information obtained based on the current positioning information; Providing a prompt based on the driving environment identification result.

2. The method of claim 1, wherein, Collecting an image in front of the vehicle comprises the following steps: Obtaining a driving speed of the vehicle; Adjusting a shooting frequency and a focal length of a camera based on the driving speed to obtain a target shooting frequency and a target focal length; Collecting an image in front of the vehicle based on the target shooting frequency and the target focal length.

3. The method of claim 2, wherein, Adjusting a shooting frequency and a focal length of a camera based on the driving speed to obtain a target shooting frequency and a target focal length comprises the following steps: Obtaining a preset speed threshold; If the driving speed is less than or equal to the speed threshold, determining that the target shooting frequency of the camera is a fixed first frequency and the target focal length is a fixed first focal length; If the driving speed is greater than the speed threshold, the target shooting frequency of the camera is a second frequency and the target focal length is a second focal length; the second frequency is positively correlated with the driving speed, the second focal length is positively correlated with the driving speed, the second frequency is greater than the first frequency, and the second focal length is greater than the first focal length.

4. The method of claim 1, wherein, Before sending the image identification result and the current positioning information of the vehicle to the server, the method further comprises the following steps: Determining whether communication with the server is normal; If the communication with the server is normal, sending the image identification result and the current positioning information of the vehicle to the server; If the server cannot be connected, determining the driving environment identification result based on the image identification result and providing a prompt based on the driving environment identification result.

5. The method of claim 4, wherein, Before sending the image identification result and the current positioning information of the vehicle to the server after the communication with the server is normal, the method further comprises the following steps: Obtaining current vehicle positioning information; Determining whether the vehicle passes through a light-dim area based on the current vehicle positioning information, and determining a first correction coefficient if the vehicle passes through the light-dim area; Correcting the image identification result based on the first correction coefficient, and taking the corrected image identification result as the image identification result.

6. The method of claim 5, wherein, Determining whether the vehicle passes through a light-dim area based on the current vehicle positioning information comprises the following steps: Extracting tunnel information in the current vehicle positioning information, and determining whether the vehicle passes through the light-dim area based on the tunnel information; and / or Obtaining sunrise and sunset times of the current vehicle positioning information, and determining whether the vehicle passes through the light-dim area based on real-time time and the sunrise and sunset times. The method further comprises the following steps: if the vehicle does not pass through the light-dim area, determining whether the current weather is abnormal weather; if yes, obtaining a vehicle state, and providing a prompt to adjust the vehicle state; 7. The method of claim 5, wherein, The step of obtaining the vehicle state and providing a prompt to adjust the vehicle state comprises at least one of the following situations: ​ Query vehicle window information, prompt to close side window and sunroof; Query vehicle light information, prompt to turn on light; Query vehicle temperature information, prompt to turn on air conditioning heating and seat heating; Query vehicle driving mode, prompt to turn on abnormal weather driving mode.

8. The method of claim 1, wherein, Before collecting the image in front of the vehicle, the method further comprises: Determine that the vehicle starts driving; Correspondingly, after prompting according to the driving environment recognition result, the method further comprises: After determining that the vehicle stops driving, stop collecting the image in front of the vehicle.

9. A vehicle traveling environment prompting method characterized by comprising: Applied to a server, the method comprises: Obtain the image recognition result of the target vehicle representing the image definition; The image recognition result is obtained by the target vehicle collecting the image in front of the vehicle, and is obtained by identifying the image, and is sent when the target vehicle determines that the image definition is less than a preset threshold; Obtain the current positioning information of the target vehicle; According to the image recognition result and the environment information obtained based on the current positioning information, generate the driving environment recognition result of the target vehicle; Send the driving environment recognition result to the target vehicle to prompt the driving environment of the target vehicle.

10. The method of claim 9, wherein, After generating the driving environment recognition result of the target vehicle according to the image recognition result and the environment information obtained based on the current positioning information, the method further comprises: Obtain other vehicles within a preset range centered on the current positioning information; Send the driving environment recognition result to the other vehicles to prompt the other vehicles according to the driving environment recognition result.

11. A vehicle running environment prompting device characterized by comprising: Applied to a vehicle, the device comprises: A collection module for collecting an image in front of the vehicle, identifying the image, and obtaining an image recognition result representing the image definition; A first sending module for sending the image recognition result and the current positioning information of the vehicle to a server if the image definition is less than a preset threshold; A first obtaining module for obtaining the driving environment recognition result returned by the server; The driving environment recognition result is generated by the server according to the image recognition result and the environment information obtained based on the current positioning information; A prompt module for prompting according to the driving environment recognition result.

12. A vehicle running environment prompting device characterized by comprising: Applied to a server, the device comprises: A second obtaining module for obtaining the image recognition result of the target vehicle representing the image definition; The image recognition result is obtained by the target vehicle collecting the image in front of the vehicle, and is obtained by identifying the image, and is sent when the target vehicle determines that the image definition is less than a preset threshold; A third obtaining module for obtaining the current positioning information of the target vehicle; A generation module for generating the driving environment recognition result of the target vehicle according to the image recognition result and the environment information obtained based on the current positioning information; A second sending module for sending the driving environment recognition result to the target vehicle to prompt the driving environment of the target vehicle.

13. An electronic device, comprising: It comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus; The memory is used to store computer programs. A processor is configured to implement the method of any one of claims 1-10 when executing a program stored in a memory.

14. A computer-readable storage medium, characterized in that, A computer program is stored in the computer readable storage medium and configured to implement the method of any one of claims 1-10 when executed by a processor.

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