CN114898584A - Recommendation method, device and equipment for vehicle driving modes and storage medium - Google Patents

Abstract

The embodiments of the present application disclose a method, device, device, and storage medium for recommending a driving mode of a vehicle. The method includes: obtaining positioning information, historical driving data, and working status of a navigation device of a target vehicle; obtaining the target vehicle according to the positioning information According to the driving environment information of the target vehicle, and the number of vehicles in the automatic driving state whose distance from the target vehicle is within the preset range; obtain the driving intention information of the target vehicle according to the historical driving data of the target vehicle; according to the working status of the navigation equipment, The driving environment information, the number of vehicles, and the driving intention information are used to generate driving mode recommendation information. Therefore, using the above method of the present application, combined with the driving environment information of the vehicle, the historical driving data and the working state of the navigation device, the recommendation information of the driving mode of the vehicle is generated, so that the user can drive in a safer and more reasonable way based on the recommended information, which improves the user experience. sense of experience.

Description

Recommended method, apparatus, apparatus and storage medium for vehicle driving style

technical field

The present application relates to the technical field of vehicles, and more particularly, to a method, apparatus, device, and storage medium for recommending a driving mode of a vehicle.

Background technique

With the development of intelligence, car intelligence is becoming more and more common, and vehicle driving methods have also made significant progress. At present, the technology of self-driving vehicles has emerged, and the key perception, positioning, prediction, planning and control tasks from advanced assisted driving to unmanned tasks are completed through the autonomous driving system (ADS). At present, autonomous driving is mainly based on the calculation and judgment of vehicle-end sensor data and implements driving control. It belongs to near-field judgment and requires extremely high timeliness, requiring immediate judgment and control. However, in the related art, there is a problem of poor user experience due to the low rationality of the vehicle driving mode randomly set by humans.

SUMMARY OF THE INVENTION

Embodiments of the present application propose a method, device, device, and storage medium for recommending a driving mode of a vehicle, so as to improve the above-mentioned problems.

In a first aspect, an embodiment of the present application provides a method for recommending a driving mode of a vehicle. The method includes: obtaining positioning information of a target vehicle, historical driving data, and working status of a navigation device; obtaining a driving environment of the target vehicle according to the positioning information information, and obtain the number of vehicles whose distance from the target vehicle is within a preset range and are in an automatic driving state; obtain driving intention information for the target vehicle according to the historical driving data of the target vehicle; Environment information, number of vehicles, and driving intention information to generate recommended driving mode information.

Further, if the driving environment information satisfies the preset environmental conditions, the working state of the navigation device is ON, and the number of vehicles is greater than the first preset calibration value, or the driving environment information satisfies the preset environmental conditions, and the working state of the navigation device is ON , and the driving intention information is when automatic driving is intended to be turned on, or the driving environment information satisfies the preset environmental conditions, the number of vehicles is greater than the first preset calibration value, and the driving intention information is when automatic driving is intended to be turned on, the recommendation information of automatic driving is generated.

In a second aspect, an embodiment of the present application further provides an apparatus for recommending a driving mode of a vehicle. The apparatus includes: a positioning information acquisition unit, an environment information acquisition unit, an intention acquisition unit, and a recommendation information generation unit. Among them, the positioning information acquisition unit is used to acquire the positioning information of the target vehicle, the historical driving data and the working status of the navigation device; the environmental information acquisition unit is used to obtain the driving environment information of the target vehicle according to the positioning information, and obtain the information related to the target vehicle. The number of vehicles whose distance is within the preset range and in the automatic driving state; the intention acquisition unit is used to obtain the driving intention information of the target vehicle according to the historical driving data of the target vehicle; the recommendation information generation unit is used to obtain the driving intention information of the target vehicle according to the Working status, driving environment information, number of vehicles, and driving intention information to generate recommended driving mode information.

In a third aspect, an embodiment of the present application further provides an electronic device, including: one or more processors, a memory, and one or more application programs. Wherein, one or more application programs are stored in the memory and configured to be executed by one or more processors, and the one or more programs are configured to execute to implement the method as described in the first aspect above.

In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium, where program codes are stored in the computer-readable storage medium, and the program codes can be invoked by a processor to execute the method described in the first aspect.

The technical solution provided by this application is to obtain the positioning information of the target vehicle, the historical driving data and the working status of the navigation device; according to the positioning information, the driving environment information of the target vehicle is obtained, and the distance to the target vehicle is within a preset range and The number of vehicles in the automatic driving state; according to the historical driving data of the target vehicle, the driving intention information of the target vehicle is obtained; according to the working status of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the recommendation information of the driving mode is generated. Therefore, using the above method of the present application, combined with the driving environment information of the vehicle, the historical driving data and the working status of the navigation device, the recommendation information of the driving mode of the vehicle is generated, so that the user can drive in a safer and more reasonable way based on the recommended information, which improves the user experience. sense of experience.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the drawings that are used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those skilled in the art, other drawings can also be obtained from these drawings without creative effort.

FIG. 1 shows a schematic diagram of an application scenario of a method for recommending a driving mode of a vehicle provided by an embodiment of the present application;

FIG. 2 shows a schematic flowchart of a method for recommending a driving mode of a vehicle provided by an embodiment of the present application;

FIG. 3 shows a schematic flowchart of implementing a method for recommending a driving mode of a vehicle provided by an embodiment of the present application;

FIG. 4 shows a schematic flowchart of a method for recommending a driving mode of a vehicle provided by another embodiment of the present application;

FIG. 5 shows a structural block diagram of a target vehicle for implementing a method for recommending a driving mode of a vehicle provided by another embodiment of the present application;

FIG. 6 shows a structural block diagram of a device for recommending a driving mode of a vehicle provided by an embodiment of the present application;

FIG. 7 shows a structural block diagram of an electronic device provided by an embodiment of the present application;

FIG. 8 shows a structural block diagram of a computer storage medium provided by an embodiment of the present application.

Detailed ways

In order to make those skilled in the art better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

In order to alleviate the above problems, the inventor of the present application proposes a method, device, device, and storage medium for recommending a driving mode of a vehicle provided by an embodiment of the present application. The method includes: acquiring positioning information of a target vehicle, historical driving data, and The working status of the navigation device; according to the positioning information, the driving environment information of the target vehicle is obtained, and the number of vehicles in the automatic driving state whose distance from the target vehicle is within the preset range; according to the historical driving data of the target vehicle, the target vehicle is obtained. The driving intention information of the vehicle; according to the working state of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the recommendation information of the driving mode is generated. Therefore, using the above method of the present application, combined with the driving environment information of the vehicle, the historical driving data and the working state of the navigation device, the recommendation information of the driving mode of the vehicle is generated, so that the user can drive in a safer and more reasonable way based on the recommended information, which improves the user experience. sense of experience.

FIG. 1 is a schematic diagram of an application scenario according to an embodiment of the present application. As shown in FIG. 1 , the application scenario includes a terminal 10 and a server 20 communicatively connected to the terminal 10 through a network. The network may be a wide area network or a local area network, or two combination of. The terminal 10 may be a vehicle, a robot, a boat, an aircraft, an intelligent voice navigation device, or a device with a mobile function. FIG. 1 only shows a schematic diagram in which the terminal 10 is a vehicle.

Among them, the vehicle communicates with the server 20 through the network. Vehicles can have localization capabilities and autonomous driving systems. Among them, the automatic driving system refers to the vehicle operation system with fully automated and highly centralized control of the work performed by the vehicle driver. .

Specifically, when the terminal 10 is a vehicle, the vehicle can be identified as the target vehicle, and the central processing unit of the target vehicle obtains the positioning information, historical driving data and the working status of the navigation device of the target vehicle, and sends them to the server 20 . The server 20 obtains the driving environment information of the target vehicle according to the positioning information, and obtains the number of vehicles whose distance from the target vehicle is within a preset range and is in an automatic driving state; and obtains the driving intention of the target vehicle according to the historical driving data of the target vehicle information, where the driving intention information includes the intention to start automatic driving or the intention to start manual driving; according to the working status of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the recommendation information of the driving mode is generated, wherein the recommendation information includes automatic driving. Recommendations for , or recommendations for manual driving. After generating the recommendation information, the server 20 may also feed back the recommendation information to the target vehicle; and make the target vehicle drive based on the driving style included in the recommendation information.

It should be understood that after obtaining the positioning information of the target vehicle, the terminal 10 can also perform the subsequent recommendation information generation process, so as to feed back control instructions based on the recommendation information to control the driving mode of the target vehicle, that is, the terminal 10 can execute the above-mentioned server 20 Steps for a recommended approach to vehicle driving style.

The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

Please refer to FIG. 2. FIG. 2 shows a schematic flowchart of a method for recommending a driving mode of a vehicle provided by an embodiment of the present application. The method can be executed by a terminal with a navigation function and an automatic driving system, such as a vehicle, a robot, an intelligent Wearable devices and the like are not specifically limited here. Referring to Fig. 2, described from the terminal side, the method at least includes steps S110 to S140.

Step S110: Obtain the positioning information of the target vehicle, historical driving data and the working state of the navigation device.

In this embodiment of the present application, the target vehicle may include modules with high-precision positioning functions, such as GPS (Global Positioning System, global positioning system), Big Dipper positioning system, base station positioning system, WIFI positioning system, and Bluetooth positioning system. The positioning information of the target vehicle may be spatial positioning, geometric positioning, grid positioning and the like of the target vehicle.

Exemplarily, the target vehicle includes GPS, and obtaining the positioning information of the target vehicle may be that the target vehicle obtains its own spatial positioning and accurate universal coordination time through GPS. The spatial positioning includes the latitude and longitude information of the target vehicle; the accurate universal coordination time refers to the time at which the positioning information of the target vehicle is currently positioned, that is, the current travel time of the target vehicle.

In the embodiment of the present application, the acquisition of the historical driving data of the target vehicle may be to acquire the historical driving data of the target vehicle stored in the target vehicle storage unit; it may also be obtained from a wireless communication technology (such as WiFi, Bluetooth, zigbEE, etc.) The associated cloud or electronic device obtains the historical driving data of the target vehicle; it may also obtain the historical driving data of the target vehicle from the associated electronic device through a serial communication interface (eg, SPI interface), which is not limited here.

Specifically, the historical driving data of the target vehicle may include historical time when the target vehicle starts automatic driving, historical road sections, and historical driving environment information.

In the embodiment of the present application, the target vehicle may obtain the working status of the navigation device of the target vehicle through the central processing unit. Wherein, the working state of the navigation device of the target vehicle includes an on state or an off state.

Among them, the navigation equipment of the target vehicle refers to the navigation and guidance device used by the target vehicle in navigation, aviation, astronomy, hydrology, land transportation, etc.

Step S120: Obtain the driving environment information of the target vehicle according to the positioning information, and obtain the number of vehicles whose distance from the target vehicle is within a preset range and in an automatic driving state.

The driving environment information may include: atmospheric transparency under the current positioning information, road construction within a preset distance from the current positioning information of the target vehicle, lane line clarity, density of people, and density of vehicles.

In some embodiments, according to the positioning information, obtaining the atmospheric transparency under the current positioning information may be, capturing the image through a visual sensor, and then transmitting the image to the processing unit, through digital processing, according to pixel distribution and information such as brightness, color, etc. , to discriminate the size, shape and color, and obtain the front visibility of the target vehicle under the current positioning information according to the discrimination result; it is also possible to use an atmospheric transmissometer to directly measure the air column through the atmospheric column between the two fixed points. The transmittance can be used to obtain the value of the front visibility of the target vehicle under the current positioning information; the laser visibility automatic measuring instrument can also be used to obtain the value of the front visibility of the target vehicle under the current positioning information by measuring the atmospheric extinction coefficient by laser. Specifically, according to the positioning information, the manner of obtaining the atmospheric transparency under the current positioning information is not limited herein.

The forward visibility of the target vehicle refers to the distance at which the object can still be clearly seen when the target vehicle is far away from the object. Exemplarily, when the weather is heavy rain, the front visibility of the target vehicle is 8m; when the weather is heavy fog, the front visibility of the target vehicle is 5m.

Optionally, the preset distance can be pre-stored in the storage unit of the target vehicle, or obtained from an associated cloud or electronic device through a wireless communication technology (such as WiFi, Bluetooth, zigbEE, etc.), or through a serial communication interface. (eg, SPI) is obtained from the associated electronic device; the size of the preset distance can be set by the user, or obtained through third-party experimental data, such as 200m, 250m, 300m, etc. Exemplarily, the preset distance is pre-stored in the storage unit of the target vehicle, and the size is 200m, which is set by the user autonomously.

In some embodiments, according to the positioning information, the road construction situation in which the positioning information from the target vehicle is obtained within a preset distance may be that the image is captured by a visual sensor, and then the image is transmitted to the processing unit, through digital processing, according to Pixel distribution, brightness, color and other information to discriminate the size, shape and color, and according to the discrimination results, to calculate the characteristic quantities of road construction signs (such as area, center of gravity, length, position, etc.), according to the characteristics of road construction signs to obtain the road construction situation within a preset distance from the positioning information of the target vehicle. Among them, road construction includes construction sections and non-construction sections.

In some embodiments, according to the positioning information, obtaining the clearness of the lane line within the preset distance from the positioning information of the target vehicle may be, capturing the image through a visual sensor, and then transmitting the image to the processing unit, and through digital processing, According to the pixel distribution, brightness, color and other information, the size, shape and color are judged, and according to the judgment result, the characteristic quantities of the road lane line (such as area, center of gravity, length, position, etc.) are calculated. The feature quantity is used to obtain the clarity of the lane line within the preset distance from the positioning information of the target vehicle.

The clarity of the lane line refers to the clarity of each detail shadow pattern and its boundary on the image of the lane line of the road within a preset distance from the positioning information of the target vehicle. Exemplarily, through the visual sensor, the resolution of the lane line within the preset distance obtained from the positioning information of the target vehicle is 4K resolution.

In this embodiment of the present application, the number of vehicles whose distance to the target vehicle is within a preset range and in an automatic driving state may be obtained by the target vehicle using a vehicle networking technology, such as a communication device (such as a VBOX (virtual machine) installed on the vehicle) , TBOX (Internet of Vehicles), etc.), to achieve vehicle-to-vehicle communication through communication protocols (such as LTE-V protocol, IP protocol, TCP protocol, etc.); it can also be the target vehicle through wireless communication technologies (such as WiFi, Bluetooth, zigbee, etc. technology) from the associated cloud or electronic device to obtain the number of vehicles that are within a preset range from the target vehicle and are in an autonomous driving state.

The preset range can be pre-stored in the storage unit of the target vehicle, or obtained from the associated cloud or electronic device through wireless communication technology (such as WiFi, Bluetooth, zigbee, etc.), or through a serial communication interface (such as , SPI) is obtained from the associated electronic device; the size of the preset range can be set by the user or obtained through third-party experimental data, such as 2Km, 2.5Km, 3Km, etc. Exemplarily, the preset range is pre-stored in the storage unit of the target vehicle, and the size is 2Km, which is set by the user autonomously.

It should be noted that the target vehicle and the vehicle whose obtained distance from the target vehicle is within a preset range and in an autonomous driving state can use the V2X (Vehicle to everything, vehicle-to-everything information exchange) module to transfer its own work The status is sent to the associated cloud or electronic device, from which the target vehicle obtains the number of vehicles that are within a preset distance from the target vehicle and are in an autonomous driving state.

It should be understood that through V2X technology, an autonomous vehicle can dynamically send the current driving behavior and expected driving behavior to other vehicles; if other vehicles also turn on the automatic driving function, the driving behavior and expected driving behavior of nearby vehicles can be obtained between vehicles. Realize the vehicle-to-vehicle interconnection; at the same time, the vehicle adjusts its own driving behavior by analyzing the driving conditions of other vehicles, ensuring the orderly driving of vehicles on the road, which is conducive to creating a better and orderly road driving environment.

Step S130: Obtain driving intention information for the target vehicle according to the historical driving data of the target vehicle.

In this embodiment of the present application, the historical driving data may include historical time, historical road sections, and historical driving environment information when the target vehicle starts automatic driving.

Among them, the historical time when the target vehicle starts automatic driving refers to the time when the driving mode of the target vehicle is the automatic driving mode before the current moment; the historical time when the target vehicle starts automatic driving may be multiple different time periods, or multiple identical The time period may also be a plurality of time periods with overlapping time periods.

The historical road section refers to the road section where the driving mode of the target vehicle is the automatic driving mode before the current time; the historical road section can be a highway section, a first-class highway section, a second-class highway section, a third-class highway section, a fourth-class highway section, etc. limited.

The historical driving environment information refers to the driving environment information when the driving mode of the target vehicle is the automatic driving mode before the current time. Specifically, the historical driving environment information may include the historical atmospheric transparency when the target vehicle is driving automatically before the current moment, and the historical road construction conditions and historical lane line clarity within a preset distance from the target vehicle; the weather corresponding to the historical atmospheric transparency may include strong Rain, heavy fog, heavy snow and other weather; historical road construction can include construction sections and non-construction sections; historical lane line definition can include 4K resolution, 8K resolution, etc.

Optionally, obtaining the driving intention information for the target vehicle according to the historical driving data of the target vehicle may be, according to the positioning information, obtaining the current driving section and current driving environment information of the target vehicle; calculating the current driving time and historical time of the target vehicle. The first matching rate, the second matching rate between the current driving road section and the historical road section, and the third matching rate between the current driving environment information and the historical driving environment information; according to the first matching rate, the second matching rate and the third matching rate, obtain Driving intent information.

Specifically, according to the first matching ratio, the second matching ratio and the third matching ratio, the driving intention information may be obtained by, if the first matching ratio is greater than the first preset matching value and the second matching ratio is greater than the second preset matching value and the third matching rate is greater than the third preset matching value, and obtaining the driving intention is the intention to enable automatic driving.

As an embodiment, the calculation of the first matching ratio between the current travel time of the target vehicle and the historical time may be to calculate the coincidence degree between the current travel time of the target vehicle and the historical time. Exemplarily, the historical time includes: 7:00-8:30, 7:10-8:30, 7:11-8:00, 7:08-8:20, 7:09-8:15; target vehicle The current travel time of the target vehicle is 7:06, and the coincidence between the current travel time of the target vehicle and the historical time is 20%.

As another embodiment, calculating the first matching ratio between the current travel time of the target vehicle and the historical time may be: judging whether the historical time covers the current travel time of the target vehicle, and if so, determining that the first matching ratio is greater than the first preset Matching value; if not covered, determine that the first matching rate is not greater than the first preset matching value.

As an embodiment, calculating the second matching ratio between the current driving section and the historical section may be: judging whether the historical driving section covers the current driving section of the target vehicle, and if it does, determining that the second matching ratio is greater than the second preset matching value; If not covered, it is determined that the second matching rate is not greater than the second preset matching value.

As another implementation manner, calculating the second matching ratio between the current driving section and the historical road section may be calculating the degree of coincidence between the current driving section and the historical road section. Exemplarily, the historical road section includes a highway section and a first-class highway section; the current driving section of the target vehicle is a highway section, and the calculated coincidence between the current driving section of the target vehicle and the historical road section is 50%.

As an embodiment, the driving environment information includes the atmospheric transparency under the positioning information, the road construction situation and lane line clarity within a preset distance from the positioning information of the target vehicle, and the first driving environment information of the current driving environment information and the historical driving environment information is calculated. The three matching ratios may be, calculating the matching ratio between the specific value of the atmospheric transparency under the positioning information and the specific value of the historical atmospheric transparency, the construction matching ratio between the road construction situation and the historical road construction situation within the preset distance from the positioning information, and Distance positioning information within the preset distance between the lane line clarity and the clarity of the historical lane line clarity matching rate, can be the weather matching rate, construction matching rate, clarity matching rate average, mode, arithmetic average or Median, etc., to get a third match rate.

As another embodiment, calculating the third matching ratio between the current driving environment information and the historical driving environment information may be: judging whether the historical driving environment information covers the current driving environment information of the target vehicle, if the specific values of the historical atmospheric transparency include The specific value of the atmospheric transparency under the current positioning information, the historical road construction situation covers the road construction situation within the preset distance from the distance positioning information, and the historical lane line clarity covers the lane line clarity within the preset distance from the distance positioning information, It is determined that the third matching ratio is greater than the third preset matching value.

Wherein, the first preset matching value, the second preset matching value, and the third preset matching value may be stored in the storage unit of the target vehicle in advance, respectively, or may be through wireless communication technology (eg, WiFi, Bluetooth, zigbee and other technologies) Obtained from the associated cloud or electronic device, and can also be obtained from the associated electronic device through a serial communication interface (eg, SPI); the size of the first preset matching value, the size of the second preset matching value, and the third preset matching value. The size of the matching value can be set independently by the user or obtained through third-party experimental data, such as 50%, 80%, and 90%. It should be understood that the manner of obtaining/storing the first preset matching value, the second preset matching value and the third preset matching value may be the same or different, the sizes may be the same or different, and the size setting methods may be the same or different.

It should be understood that recommending the driving mode of the vehicle based on the historical driving data is more suitable for the user's living habits and improves the user's experience of driving the vehicle.

Step S140: Generate recommendation information of a driving mode according to the working state of the navigation device, the driving environment information, the number of vehicles, and the driving intention information.

In some embodiments, the recommendation information may include recommendation information for automatic driving and navigation path information for automatic driving, and may also include recommendation information for manual driving and navigation path information for manual driving.

Further, according to the working state of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the recommendation information of the driving mode is generated, which may be: if the driving environment information satisfies the preset environmental conditions, the working state of the navigation device is ON, and When the number of vehicles is greater than the first preset calibration value, or the driving environment information satisfies the preset environmental conditions, the working state of the navigation device is ON, and the driving intention information is when automatic driving is intended to be enabled, or the driving environment information satisfies the preset environmental conditions, When the number of vehicles is greater than the first preset calibration value, and the driving intention information is that automatic driving is intended to be enabled, automatic driving recommendation information is generated.

Further, according to the working state of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the recommendation information of the driving mode is generated, and it may also be: if the working state of the navigation device is off or the driving environment information does not meet the preset environmental conditions When , the recommendation information for manual driving is generated.

Wherein, the first preset calibration value may be pre-stored in the storage unit of the target vehicle, may also be obtained from an associated electronic device in the cloud through a wireless communication technology, or may be obtained from an associated electronic device through a serial communication interface; The size of the first preset calibration value may be independently set by the user, or may be obtained through third-party experimental data.

As an implementation manner, the size of the first preset calibration value is a fixed value, for example, the size of the first preset calibration value is 6, 10, and 11, which is not limited herein.

As another embodiment, the size of the first preset calibration value is related to the vehicle density within a preset range of the distance to the target vehicle. For example, the size of the first preset calibration value is the distance to the target vehicle within the preset range 30%, 20%, 50% of the vehicle density within the range, which is not limited here.

Exemplarily, the preset range is 2Km, and the size of the first preset calibration value is 30% of the vehicle density with the distance from the target vehicle within the preset range. If the number of vehicles is greater than the first preset calibration value (that is, the number of vehicles) >30% of the vehicle density with a distance to the target vehicle within 2Km); if the number of vehicles is less than or equal to the first preset calibration value (that is, the number of vehicles ≤ 30% of the vehicle density within 2Km of the target vehicle) ).

Referring to FIG. 3, in some embodiments, according to the working state of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the specific process of generating the recommended information may be: if the driving mode of the current target vehicle is manual driving, when When the driving environment information does not meet the preset environmental conditions, the recommendation information for manual driving is generated, and the target vehicle maintains the current manual driving mode; when the driving environment information meets the preset environmental conditions, the condition 1 is performed (the working state of the navigation device is ON) and condition 2 (the number of vehicles is greater than the first preset calibration value); if condition 1 is met (the working state of the navigation device is on), and condition 2 (the number of vehicles is greater than the first preset value) is met, an automatic driving Recommendation information; if condition 1 or condition 2 is satisfied, further judge the driving intention information of the target vehicle; if the driving intention information of the target vehicle is intended for automatic driving, and condition 1 is satisfied, generate recommendation information for automatic driving ; If the driving intent information is intended for automatic driving and condition 2 is satisfied, the recommendation information for automatic driving and the navigation path information for automatic driving are generated; if the driving intention information is for manual driving, the recommendation information for manual driving is generated, and the target vehicle keeps the current manual driving. the way you drive.

The preset environmental conditions may be pre-stored in the storage unit of the target vehicle, or obtained from the associated cloud or electronic device through wireless communication technologies (such as WiFi, Bluetooth, zigbee, etc.), or through serial communication The interface (eg, SPI) is obtained from the associated electronic device; the content of the preset environmental conditions may be set by the user, or may be set by third-party experimental data.

Optionally, the driving environment information may include atmospheric transparency under the positioning information, and road construction conditions and lane line clarity within a preset distance from the positioning information. The driving environment information satisfies the preset environmental conditions may be: obtaining the forward visibility of the positioning information according to the transparency of the atmosphere; if the forward visibility is greater than the preset visibility, the road construction is a non-construction road section, and the lane line clarity is greater than the preset clarity, and the driving is determined. The environmental information satisfies the preset environmental conditions.

The preset visibility may be pre-stored in the storage unit of the target vehicle, or obtained from the associated cloud or electronic device through wireless communication technologies (such as WiFi, Bluetooth, zigbee, etc.), or through a serial communication interface (eg, SPI) obtained from a related electronic device; the preset visibility size can be set by the user, or set by third-party experimental data, such as 3m, 3.5m, 4m, etc., which is not limited here.

Similarly, the preset definition can be pre-stored in the storage unit of the target vehicle, or obtained from the associated cloud or electronic device through wireless communication technologies (such as WiFi, Bluetooth, zigbee, etc.), or through the serial communication interface (eg, SPI) is obtained from a related electronic device; the size of the preset resolution can be set by the user, or can be set by third-party experimental data, such as 4K resolution, 8K resolution, etc., which are not limited here.

It should be understood that if the driving environment information meets the preset environmental conditions, it can be determined that the front visibility of the target vehicle is high, the road is not under construction, the road lane lines are clear enough, and the target vehicle drives automatically in this environment with higher safety.

Optionally, the recommended information may be voice information, interface display information, and indicator light indication information, which is not limited herein. Exemplarily, the recommended information is the voice information of "recommended to enable automatic driving" and the voice information of "prompt the driver to take over".

In some embodiments, when the number of vehicles is not greater than the first preset calibration value, if the target vehicle is in an automatic driving state, the target vehicle may generate prompt information for paying attention to road conditions. The prompt information may be voice information, interface display information, indicator light information, etc., which is not limited herein. Exemplarily, the voice information of "prompting the driver to pay attention to the road conditions" is generated to inform the driver to pay attention to the road conditions.

It should be understood that the driver drives the target vehicle based on the recommended information, taking into account the surrounding environment, the status of the target vehicle’s navigation equipment, and the historical driving data of the target vehicle, and the recommended driving mode of the vehicle is safer and more reasonable, which can improve the driver’s confidence in driving the vehicle. , which improves the user experience of autonomous driving.

The technical solutions provided by the embodiments of the present application obtain the positioning information of the target vehicle, historical driving data and the working status of the navigation device; according to the positioning information, the driving environment information of the target vehicle is obtained, and the distance to the target vehicle is within a preset range. According to the historical driving data of the target vehicle, the driving intention information of the target vehicle is obtained; according to the working status of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the recommendation of the driving mode is generated information. Therefore, the above method of the present application is used to obtain the number of vehicles driving automatically around the target vehicle in the case of vehicle-to-vehicle interconnection, and combine the working status, driving environment information and driving intention information of the navigation device of the target vehicle to generate a driving pattern of the target vehicle. The recommendation information enables users to drive in a safer and more reasonable way based on the recommendation information, which improves the user's sense of experience.

Please refer to FIG. 4. FIG. 4 is a schematic flowchart of a method for recommending a driving mode of a vehicle according to another embodiment of the present application. The method can be executed by a terminal with a navigation function and an automatic driving system, such as a vehicle, a robot, an intelligent Wearable devices and the like are not specifically limited here. Referring to FIG. 4 , the method includes at least steps S210 to S260.

Step S210: Acquire the positioning information of the target vehicle, historical driving data and the working state of the navigation device.

Step S220: According to the positioning information, obtain the driving environment information of the target vehicle, and obtain the number of vehicles whose distance from the target vehicle is within a preset range and in an automatic driving state.

Step S230: Obtain driving intention information for the target vehicle according to the historical driving data of the target vehicle.

Step S240: Generate recommendation information of a driving mode according to the working state of the navigation device, the driving environment information, the number of vehicles, and the driving intention information.

For the specific execution process of step S210 to step S240, please refer to the specific description of step S110 to step S140 above, which will not be repeated here.

Step S250: Receive a control instruction fed back based on the recommendation information.

Optionally, receiving the control instruction based on the recommendation information feedback may be that the target vehicle receives the control instruction that is fed back by the user based on the recommendation information within a preset feedback period. The control instructions include automatic driving control instructions or manual driving control instructions.

Specifically, the preset feedback duration can be pre-stored in the storage unit of the target vehicle, or obtained from an associated cloud or electronic device through wireless communication technology, or obtained from an associated electronic device through a serial communication interface; preset feedback The size of the duration can be set by the user, or obtained through third-party experimental data, such as 2min, 3min, 4min, etc., which is not limited here.

It should be understood that, if the target vehicle does not receive a control command within the preset feedback time period, the target vehicle maintains the current driving mode to drive the target vehicle.

In this embodiment of the present application, a control instruction from the user based on the recommendation information feedback may be received during the driving of the vehicle, wherein the control instruction input by the driver of the current target vehicle through the on-board computer may be received, or the control instruction input by the driver of the current target vehicle may be received. A control command sent to at least one vehicle through a third-party electronic device, for example, by receiving the driver's click operation on buttons such as "automatic driving" and "manual driving" on the display unit of the in-vehicle computer, to determine to receive a control command, or to receive a driving A control instruction sent by a user through an electronic device such as a mobile phone, a tablet computer, or a notebook computer, and the manner of receiving the user feedback control instruction based on the recommendation information is not limited in the embodiments of the present application.

Step S260: If the control command is an automatic driving control command, control the target vehicle to drive automatically.

After the target vehicle acquires the control instruction, the driving manner of the target vehicle can be controlled in response to the control instruction. Wherein, if the control command is an automatic driving control command, the target vehicle can control the driving direction of the target vehicle by controlling the steering wheel angle, gear position, engine power output, and driving state of the target vehicle through the automatic driving system control in response to the automatic driving control command. , distance, speed, etc. for automatic driving. Optionally, the current steering wheel angle information of the target vehicle can be obtained through the EPS (Electric Power Steering, electric power steering) of the vehicle, and the steering wheel can be controlled to turn to the target angle; the TCU (Transmission Control Unit, automatic transmission control unit) of the target vehicle can be used. Obtain the current gear information of the target vehicle, and control the switch to the target gear; obtain the current power output of the engine through the ECM (Engine Control Module, engine control module) of the target vehicle, and control the engine to switch to the target power output; The vehicle's ESP (Electronic Stability Program, body electronic stability system) obtains the current driving status of the target vehicle, such as target vehicle driving distance information, wheel speed pulse information, etc., and controls the braking force of each wheel to adjust the target vehicle's driving status. The cooperation of various components controls the automatic driving of the target vehicle. Those skilled in the art can also control and cooperate with each component of the vehicle through other control units, modules or systems, which are not specifically limited in this embodiment of the present application.

In some embodiments, the target vehicle, in response to the automatic driving control instruction, acquires the navigation path information of the automatic driving, and controls the automatic driving of the target vehicle based on the navigation path information.

The navigation path information may be the navigation path information generated by the navigation device of the target vehicle according to the destination set when the user feeds back the control information, or the target vehicle based on the current positioning information of the target vehicle and the location information of the target vehicle. For the most frequently set destination in the historical driving data, the navigation device of the target vehicle generates navigation route information according to the most frequently set destination; it may also be the navigation route information currently navigated by the navigation device of the target vehicle.

It should be noted that, according to the working status of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the recommendation information of the driving mode is generated, and the user selects the method of driving the target vehicle based on the recommendation information, which optimizes the interaction of the vehicle's automatic driving function. , reducing the driver's frequent takeover of the target vehicle for driving, which is conducive to creating a more orderly driving environment and reducing driving congestion.

5, the target vehicle F00 includes a positioning and navigation module F02, an automatic driving calculation module F04, an automatic driving control module F06, an automatic driving perception module F08, a V2X module F10, and a vehicle-machine control module F12.

The positioning and navigation module F02 may include GPS, which is used to obtain the positioning information of the target vehicle, current positioning road information, and historical driving data, determine whether the working status of the navigation device of the current target vehicle is turned on, and generate the navigation and positioning information of the target vehicle.

The automatic driving calculation module F04 is composed of hardware and program codes. The hardware may include cameras, radars, etc., and is used to obtain driving intention information according to the historical driving data of the target vehicle.

The automatic driving perception module F06 may include a visual sensor, a camera, a radar, etc., for obtaining the driving environment information of the target vehicle according to the positioning information.

The V2X (Vehicle-to-External Information Exchange) module F08 is used to obtain the number of vehicles whose distance to the target vehicle is within a preset range and in an automatic driving state according to the positioning information of the target vehicle.

The automatic driving control module F10 may include a plurality of program codes, a display screen, a sound pickup device, etc., which are used to generate recommended information for automatic driving or recommended manual driving according to the working status of the navigation device, driving environment information, number of vehicles, and driving intention information. Recommended information for driving.

The vehicle-machine control module F12 may include TCU (Transmission Control Unit, automatic transmission control unit), ECM (Engine Control Module, engine control module), ESP (Electronic Stability Program, body electronic stability system), etc., and is used for receiving recommendation-based information. Feedback control command; if the control command is an automatic driving control command, control the target vehicle to drive automatically.

The technical solutions provided by the embodiments of the present application obtain the positioning information of the target vehicle, historical driving data and the working status of the navigation device; according to the positioning information, the driving environment information of the target vehicle is obtained, and the distance to the target vehicle is within a preset range. The number of vehicles in the automatic driving state; according to the historical driving data of the target vehicle, the driving intention information of the target vehicle is obtained; according to the working status of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the driving mode is generated. Recommendation information; receive control instructions based on the recommendation information feedback; if the control instructions are automatic driving control instructions, control the target vehicle to drive automatically. Therefore, the above method of the present application is adopted, combined with the driving environment information of the vehicle, the historical driving data and the working status of the navigation device, to generate the recommended information of the driving mode of the vehicle, so that the user can feedback the control instruction based on the recommended information, and control the target vehicle to be safer and more reasonable. The driving mode of the target vehicle is more suitable for the driver's behavior, and the user's experience is improved.

Please refer to FIG. 6 , which shows an apparatus for recommending a driving mode of a vehicle provided by an embodiment of the present application. The apparatus 300 includes: a positioning information acquisition unit 310 , an environment information acquisition unit 320 , an intention acquisition unit 330 , and recommendation information Generation unit 340 . Specifically, the positioning information obtaining unit 310 is used to obtain the positioning information of the target vehicle, historical driving data and the working status of the navigation device; the environment information obtaining unit 320 is used to obtain the driving environment information of the target vehicle according to the positioning information, and obtain The number of vehicles whose distance from the target vehicle is within the preset range and in an automatic driving state; the intent acquisition unit 330 is used to obtain the driving intent information for the target vehicle according to the historical driving data of the target vehicle; the recommendation information generation unit 340 is used for Based on the working state of the navigation device, the driving environment information, the number of vehicles and the driving intention information, the recommendation information of the driving mode is generated.

It should be noted that the various embodiments of this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments can be referred to each other. . As for the apparatus type embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for the relevant part, please refer to the partial description of the method embodiment. Any processing manners described in the method embodiments may be implemented by corresponding processing modules in the apparatus embodiments, and will not be repeated in the apparatus embodiments.

Referring to FIG. 6 , based on the above-mentioned method for recommending a driving mode of a vehicle, the present application further provides another electronic device 400 that includes the aforementioned method for recommending a driving mode of a vehicle, and the electronic device 400 further includes one or more a processor 410, a memory 420, and one or more application programs. The memory 420 stores a program that can execute the content in the foregoing embodiments, and the processor 410 can execute the program stored in the memory 420 . The electronic device 400 may be a smart wearable device, a vehicle, a smart robot, a tablet computer, a personal computer, or the like.

The processor 410 may include one or more cores for processing data and a message matrix unit. The processor 410 uses various interfaces and lines to connect various parts of the entire electronic device 400, and executes by running or executing the instructions, programs, code sets or instruction sets stored in the memory 420, and calling the data stored in the memory 420. Various functions of the electronic device 400 and processing data. Optionally, the processor 410 may employ at least one of digital signal processing (Digital Signal Processing, DSP), field-programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). implemented in hardware. The processor 410 may integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processor (Graphics Processing Unit, GPU), a modem, and the like. Among them, the CPU mainly handles the operating system, user interface and application programs, etc.; the GPU is used for rendering and drawing of the display content; the modem is used to handle wireless communication. It can be understood that, the above-mentioned modem may not be integrated into the processor 410, and is implemented by a communication chip alone.

The memory 420 may include random access memory (Random Access Memory, RAM), or may include read-only memory (Read-Only Memory). Memory 420 may be used to store instructions, programs, codes, sets of codes, or sets of instructions. The memory 420 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing the operating system, instructions for implementing at least one function (such as obtaining positioning information of the target vehicle, historical driving data, and navigation equipment). working state, etc.), instructions for implementing the following method embodiments, etc. The storage data area may also store data (such as driving environment information, driving intention information, historical driving data) created by the terminal during use.

In some embodiments, the electronic device 400 is a vehicle that includes an automated driving system.

Please refer to FIG. 8 , which shows a structural block diagram of a computer-readable storage medium 500 provided by an embodiment of the present application. The computer-readable storage medium 500 stores program codes 510, and the program codes 510 can be invoked by the processor to execute the methods described in the above method embodiments.

The computer-readable storage medium 500 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), EPROM, hard disk, or ROM. Optionally, the computer-readable storage medium 500 includes a non-transitory computer-readable storage medium. Computer readable storage medium 500 has storage space for program code 510 to perform any of the method steps in the above-described methods. These program codes 510 can be read from or written to one or more computer program products. The program code may, for example, be compressed in a suitable form.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or some technical features thereof are equivalently replaced; and these modifications or replacements do not drive the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims (10)

1. A method for recommending a driving style of a vehicle, the method comprising:

acquiring positioning information, historical driving data and a working state of navigation equipment of a target vehicle;

according to the positioning information, obtaining running environment information of the target vehicle, and obtaining the number of vehicles which are within a preset range and in an automatic driving state;

obtaining driving intention information for the target vehicle according to the historical driving data;

and generating recommendation information of a driving mode according to the working state of the navigation equipment, the running environment information, the number of vehicles and the driving intention information.

2. The method according to claim 1, wherein the generating recommendation information of a driving pattern according to the operating state of the navigation apparatus, the running environment information, the number of vehicles, and the driving intention information comprises:

if the driving environment information meets the preset environment condition, the working state of the navigation equipment is started, and when the number of vehicles is greater than a first preset calibration value, or the driving environment information meets the preset environment condition, the working state of the navigation equipment is started, and the driving intention information is intention to start automatic driving, or the driving environment information meets the preset environment condition, the number of vehicles is greater than the first preset calibration value, and when the driving intention information is intention to start automatic driving, the recommendation information of automatic driving is generated.

3. The method according to claim 2, wherein the generating recommendation information of a driving pattern according to the operating state of the navigation apparatus, the running environment information, the number of vehicles, and the driving intention information includes:

and if the working state of the navigation equipment is closed or the running environment information does not meet the preset environment condition, generating recommendation information of manual driving.

4. The method of claim 2, wherein the driving environment information includes atmospheric transparency under the positioning information and road construction conditions and lane line definition within a preset distance from the positioning information, and the driving environment information satisfies preset environmental conditions, including:

obtaining a front visibility of the positioning information according to the atmospheric transparency;

if the front visibility is larger than the preset visibility, the road construction condition is a non-construction road section, the lane line definition is larger than the preset definition, and it is determined that the driving environment information meets the preset environment condition.

5. The method according to any one of claims 1 to 4, wherein the historical driving data includes historical time, historical road segment, and historical driving environment information at which the target vehicle is turned on for autonomous driving, and the obtaining the driving intention information for the target vehicle based on the historical driving data of the target vehicle includes:

acquiring the current running road section and the current running environment information of the target vehicle according to the positioning information;

calculating a first matching rate of the current driving time of the target vehicle and the historical time, a second matching rate of the current driving road section and the historical road section, and a third matching rate of the current driving environment information and the historical driving environment information;

and acquiring driving intention information of the target vehicle according to the first matching rate, the second matching rate and the third matching rate.

6. The method according to claim 5, wherein the obtaining driving intention information according to the first matching rate, the second matching rate and the third matching rate, obtaining driving intention information for the target vehicle comprises:

and if the first matching rate is greater than a first preset matching value, the second matching rate is greater than a second preset matching value and the third matching rate is greater than a third preset matching value, the driving intention of the target vehicle is obtained and automatic driving is started as the intention.

7. The method of claim 1, further comprising:

receiving a control instruction fed back based on the recommendation information;

and if the control instruction is an automatic driving control instruction, controlling the target vehicle to automatically drive.

8. An apparatus for recommending a driving style of a vehicle, the apparatus comprising:

the navigation device comprises a positioning information acquisition unit, a navigation information processing unit and a control unit, wherein the positioning information acquisition unit is used for acquiring the positioning information, historical driving data and the working state of the navigation device of a target vehicle;

the environment information acquisition unit is used for acquiring running environment information of the target vehicle according to the positioning information and acquiring the number of vehicles which are within a preset range and in an automatic driving state;

an intention acquisition unit for acquiring driving intention information for the target vehicle based on historical driving data of the target vehicle;

and the recommendation information generating unit is used for generating recommendation information of the driving mode according to the working state of the navigation equipment, the running environment information, the number of vehicles and the driving intention information.

9. An electronic device, comprising:

one or more processors;

a memory;

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of claims 1-7.

10. A computer-readable storage medium, characterized in that a program code is stored in the computer-readable storage medium, which program code can be called by a processor to execute the method according to any one of claims 1-7.

Images