CN105225508A - Road condition advisory method and device - Google Patents
Road condition advisory method and device Download PDFInfo
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- CN105225508A CN105225508A CN201510633818.1A CN201510633818A CN105225508A CN 105225508 A CN105225508 A CN 105225508A CN 201510633818 A CN201510633818 A CN 201510633818A CN 105225508 A CN105225508 A CN 105225508A
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Abstract
The disclosure discloses a kind of road condition advisory method and device, belongs to field of traffic safety.Described method comprises: the rideability parameter obtaining the vehicle bound with described unmanned aerial vehicle; Obtain the traffic information in described vehicle front preset distance; According to described rideability parameter and described traffic information, for described vehicle carries out road condition advisory.By obtaining the rideability parameter of vehicle, and obtaining the traffic information of this vehicle front, thinking that vehicle carries out road condition advisory; To solve in correlation technique because driver cannot accurately judge front road conditions, cause in motion emergency situations occurring, the problem that security cannot be protected; Reach the road conditions accurately can knowing vehicle front section, effectively avoid emergency situations when travelling, the effect of security when improve traveling.
Description
Technical Field
The disclosure relates to the field of traffic safety, and in particular to a road condition prompting method and device.
Background
With the increasing traffic congestion caused by the increase of private cars, more and more users choose to walk on a light vehicle, such as an electric scooter, a bicycle, a monocycle and the like.
Since the portable vehicle is more susceptible to the influence of the uneven road condition, when the user uses the portable vehicle for traveling, the user needs to observe the road condition ahead all the time. However, when some sections unsuitable for driving, such as a sharp turning section or an uphill section, the user often cannot accurately determine the road condition ahead, and thus an emergency situation occurs during driving, and safety cannot be guaranteed.
Disclosure of Invention
The disclosure provides a road condition prompting method and a road condition prompting device. The technical scheme is as follows:
according to a first aspect of the embodiments of the present disclosure, a road condition prompting method is provided, which is applied to an unmanned aerial vehicle, and the method includes:
acquiring the running performance parameters of the vehicle bound with the unmanned aircraft;
acquiring road condition information in a preset distance in front of the vehicle;
and prompting the road condition of the vehicle according to the driving performance parameters and the road condition information.
Optionally, the acquiring the driving performance parameter of the vehicle bound to the unmanned aerial vehicle includes:
establishing connection with the vehicle, acquiring the model of the vehicle sent by the vehicle, and acquiring the driving performance parameters corresponding to the model from a cloud server; or,
establishing connection with the vehicle, and acquiring the driving performance parameters sent by the vehicle; or,
sending a parameter acquisition request for acquiring the running performance parameters of the vehicle to an intelligent device bound with the unmanned aerial vehicle, wherein the parameter acquisition request is used for triggering the intelligent device to feed back the running performance parameters of the vehicle and receiving the running performance parameters of the vehicle sent by the intelligent device;
wherein the running performance parameter includes at least one of a maximum gradient on which the vehicle can run, a maximum speed on which the vehicle can run, a degree of flatness of a road surface on which the vehicle can safely run, and a parameter indicating whether the vehicle can run on an uneven road surface.
Optionally, the acquiring the road condition information within the predetermined distance in front of the vehicle includes:
acquiring positioning data of the vehicle;
acquiring road condition images in a preset distance in front of the vehicle according to the positioning data;
and carrying out image recognition on the road condition image to obtain the road condition information.
Optionally, the prompting the road condition of the vehicle according to the driving performance parameter and the road condition information includes:
when the road condition information indicates that the front road section meets the condition of no passing, the vehicle is reminded to drive around the road,
the communication prohibition condition is that the front road section is a non-motor lane, the road surface of the front road section is uneven, or the maximum gradient of the front road section is larger than the maximum gradient of the vehicle.
Optionally, the reminding the vehicle of detouring, including:
and sending alarm information to the vehicle, or sending alarm information to intelligent equipment bound with the unmanned aerial vehicle, wherein the alarm information is used for reminding the front road section of the unmanned aerial vehicle of not utilizing to run.
According to a second aspect of the embodiments of the present disclosure, a road condition prompting device is provided, which is applied to an unmanned aerial vehicle, the device includes:
a parameter acquisition module configured to acquire a driving performance parameter of a vehicle bound with the unmanned aerial vehicle;
the road condition acquisition module is configured to acquire road condition information within a preset distance in front of the vehicle;
and the navigation module is configured to prompt the road condition of the vehicle according to the driving performance parameters acquired by the parameter acquisition module and the road condition information acquired by the road condition acquisition module.
Optionally, the parameter obtaining module includes:
the first obtaining sub-module is configured to establish connection with the vehicle, obtain the model of the vehicle sent by the vehicle, and obtain the driving performance parameter corresponding to the model from a cloud server; or,
the second obtaining submodule is configured to establish connection with the vehicle and obtain the driving performance parameters sent by the vehicle; or,
the system comprises a sending submodule and a receiving submodule, wherein the sending submodule is configured to send a parameter obtaining request for obtaining the running performance parameters of the vehicle to an intelligent device bound with the unmanned aerial vehicle, the parameter obtaining request is used for triggering the intelligent device to feed back the running performance parameters of the vehicle, and the receiving submodule is configured to receive the running performance parameters of the vehicle sent by the intelligent device;
wherein the running performance parameter includes at least one of a maximum gradient on which the vehicle can run, a maximum speed on which the vehicle can run, a degree of flatness of a road surface on which the vehicle can safely run, and a parameter indicating whether the vehicle can run on an uneven road surface.
Optionally, the road condition obtaining module includes:
a third acquisition sub-module configured to acquire positioning data of the vehicle;
the image acquisition sub-module is configured to acquire a road condition image in front of the vehicle within a preset distance according to the positioning data acquired by the third acquisition sub-module;
and the image recognition submodule is configured to perform image recognition on the road condition image acquired by the image acquisition submodule to obtain the road condition information.
Optionally, the navigation module is further configured to:
when the road condition information indicates that the front road section meets the condition of no passing, the vehicle is reminded to drive around the road,
the communication prohibition condition is that the front road section is a non-motor lane, the road surface of the front road section is uneven, or the maximum gradient of the front road section is larger than the maximum gradient of the vehicle.
Optionally, the navigation module is further configured to:
and sending alarm information to the vehicle, or sending alarm information to intelligent equipment bound with the unmanned aerial vehicle, wherein the alarm information is used for reminding the front road section of the unmanned aerial vehicle of not utilizing to run.
According to a third aspect of the embodiments of the present disclosure, there is provided a road condition prompting device applied to an unmanned aerial vehicle, the device including:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to:
acquiring the running performance parameters of the vehicle bound with the unmanned aircraft;
acquiring road condition information in a preset distance in front of the vehicle;
and prompting the road condition of the vehicle according to the driving performance parameters and the road condition information.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
the method comprises the steps of obtaining driving performance parameters of a vehicle and obtaining road condition information in front of the vehicle to prompt the vehicle about the road condition; the driving performance parameters of the vehicle and the road condition information in front of the vehicle are combined, so that whether the vehicle can continue to drive can be accurately judged, and the problems that in the related technology, the road condition in front cannot be accurately judged by a driver, so that an emergency occurs during driving, and the safety cannot be guaranteed are solved; the road condition of the road section in front of the vehicle can be accurately known, the emergency situation during driving is effectively avoided, and the safety during driving is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a schematic diagram of an implementation environment related to a road condition prompting method according to a part of an exemplary embodiment;
fig. 2 is a flowchart illustrating a road condition prompting method according to an exemplary embodiment;
fig. 3A is a flowchart illustrating a road condition prompting method according to another exemplary embodiment;
FIG. 3B is a flow chart illustrating a method of obtaining a vehicle's driving performance parameters according to one exemplary embodiment;
fig. 3C is a schematic diagram of a road condition prompt according to an exemplary embodiment;
fig. 4 is a block diagram of a road condition prompting device according to an exemplary embodiment;
fig. 5 is a block diagram illustrating a road condition prompting device according to another exemplary embodiment;
fig. 6 is a block diagram illustrating a road condition prompting device according to yet another exemplary embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Fig. 1 is a schematic diagram of an implementation environment related to a road condition prompting method according to a part of exemplary embodiments, and as shown in fig. 1, the implementation environment may include an unmanned aerial vehicle 110, a vehicle 120, and an intelligent device 130.
The drone 110 may be used to capture images. Drone 110 may also be bound to vehicle 120 and may be wirelessly connected to vehicle 120. The Wireless mode may be Wi-Fi (Wireless-Fidelity, Chinese full name: Wireless Fidelity), or Bluetooth.
The vehicle 120 may be a large truck, a private car, a two-wheeled vehicle (including a bicycle, an electric vehicle, etc.), a unicycle, etc., and the type of the vehicle 120 is not limited in this embodiment.
The smart device 130 may be bound and connected to the drone 110, the vehicle 120. The smart device 130 may be a smart phone, an in-vehicle system, a tablet computer, a wearable device, etc., and the wearable device may be a device wearable on a user, such as a smart bracelet, a smart key ring, a smart watch, a smart tie clip, a smart ring, etc.
Optionally, the implementation environment may also include a server 140. Drone 110 may establish a connection with server 140 and may interact from server 140. The smart device 130 may interact with the server 140.
Fig. 2 is a flowchart illustrating a road condition prompting method according to an exemplary embodiment, and as shown in fig. 2, the road condition prompting method is applied to the unmanned aerial vehicle 110 in the implementation environment shown in fig. 1, and includes the following steps.
In step 201, driving performance parameters of a vehicle bound to an unmanned aerial vehicle are acquired.
The driving performance parameter is used to identify a parameter required for achieving a specified performance while the vehicle is driving.
In step 202, road condition information within a predetermined distance in front of the vehicle is obtained.
The traffic information is information describing the condition of the driving road.
In step 203, a road condition is prompted for the vehicle according to the driving performance parameter and the road condition information.
In summary, the road condition prompting method provided in the embodiment of the present disclosure prompts the vehicle for the road condition by acquiring the driving performance parameter of the vehicle and acquiring the road condition information in front of the vehicle; the driving performance parameters of the vehicle and the road condition information in front of the vehicle are combined, so that whether the vehicle can continue to drive can be accurately judged, and the problems that in the related technology, the road condition in front cannot be accurately judged by a driver, so that an emergency occurs during driving, and the safety cannot be guaranteed are solved; the road condition of the road section in front of the vehicle can be accurately known, the emergency situation during driving is effectively avoided, and the safety during driving is improved.
Fig. 3A is a flowchart illustrating a road condition prompting method according to another exemplary embodiment, and as shown in fig. 3A, the road condition prompting method is applied to the unmanned aerial vehicle 110 in the implementation environment shown in fig. 1, and includes the following steps.
In step 301, driving performance parameters of a vehicle bound to the drone are obtained.
The running performance parameter of the vehicle referred to herein includes at least one of a maximum gradient on which the vehicle can run, a maximum speed at which the vehicle can run, a degree of flatness of a road surface on which the vehicle can safely run, and a parameter indicating whether the vehicle can run on an uneven road surface.
In practical applications, please refer to fig. 3B, which is a flowchart illustrating a method for obtaining a driving performance parameter of a vehicle according to an exemplary embodiment, in fig. 3B, the obtaining of the driving performance parameter of the vehicle bound to the drone may include at least the following three ways:
in the first method 301a, a connection is established with the vehicle, the model of the vehicle sent by the vehicle is obtained, and the driving performance parameter corresponding to the model is obtained from the cloud server.
The drone may first establish a connection with the vehicle.
Optionally, the unmanned aerial vehicle may establish a connection with the vehicle through a wireless network connection manner such as WiFi or bluetooth.
After the unmanned aerial vehicle and the vehicle are connected in advance, the unmanned aerial vehicle can send a first obtaining request for requesting to obtain the model of the vehicle to the vehicle, the first obtaining request is used for triggering the vehicle to feed back the model of the vehicle, and the unmanned aerial vehicle receives the model of the vehicle fed back by the vehicle.
Then, the drone may send, to the server, a second acquisition request for requesting acquisition of the driving performance parameter corresponding to the model, where the second acquisition request is used to trigger the server to query and feed back the driving performance parameter corresponding to the model, and correspondingly, the drone may receive the driving performance parameter of the model fed back by the server.
Optionally, after the drone is connected to the vehicle, the vehicle may continuously broadcast a message, where the message at least includes the model of the vehicle, and the drone sends, according to the model broadcast by the vehicle, a second acquisition request for requesting to acquire the driving performance parameter corresponding to the model to the server.
In the second method 301b, a connection is established with the vehicle, and the driving performance parameters transmitted by the vehicle are acquired.
In practical implementation, the driving performance parameters of the vehicle may be stored in a memory chip of the vehicle in advance, after the vehicle is connected with the drone, the vehicle may directly send the driving performance parameters in the memory chip to the drone, and correspondingly, the drone may directly receive the driving performance parameters sent by the vehicle.
Optionally, after the unmanned aerial vehicle establishes a connection with the vehicle, the unmanned aerial vehicle may further send a third acquisition request for requesting to acquire the driving performance parameter of the vehicle to the vehicle, where the third acquisition request is used to trigger the vehicle to feed back the driving performance parameter of the vehicle, and correspondingly, the unmanned aerial vehicle may receive the driving performance parameter sent by the vehicle.
Optionally, the vehicle may further continuously broadcast a message, where the message at least includes the driving performance parameter of the vehicle, and the drone receives the message broadcast by the vehicle and obtains the driving performance parameter of the vehicle from the message.
In the third mode 301c, a parameter obtaining request for obtaining the driving performance parameter of the vehicle is sent to the smart device bound to the unmanned aerial vehicle, where the parameter obtaining request is used to trigger the smart device to feed back the driving performance parameter of the vehicle, and receive the driving performance parameter of the vehicle sent by the smart device.
The unmanned aerial vehicle can be bound with the intelligent device, and a parameter acquisition request for requesting to acquire the driving performance parameters of the vehicle is sent to the intelligent device bound with the unmanned aerial vehicle. After receiving the parameter acquisition request, the intelligent device can acquire the driving performance parameters of the vehicle and feed the acquired driving performance parameters back to the unmanned aerial vehicle.
Optionally, when the intelligent device obtains the running performance parameters of the vehicle, the intelligent device may retrieve a vehicle identifier broadcast by a surrounding vehicle, bind the vehicle identifier with the intelligent device or a user account logged in on the intelligent device, and send an inquiry request carrying the vehicle identifier to the server, where the inquiry request is used to trigger the server to feed back the model of the vehicle and the running performance parameters of the vehicle. The intelligent device can store the model of the vehicle and the driving performance parameters of the vehicle, which are acquired from the server, or store the model of the vehicle and the driving performance parameters of the vehicle and the user account in a binding manner.
In order to estimate the road condition of the road section ahead for the vehicle, the embodiment may refer to the following description of step 302 to step 304.
In step 302, positioning data for the vehicle is acquired.
When the unmanned aircraft acquires the positioning data of the vehicle, the following modes can be adopted: unmanned vehicles and vehicle interconnect, and vehicle-mounted system or positioning system in the vehicle can fix a position the position of vehicle in real time, obtain the location data of vehicle to real-time with locating data transmission to unmanned vehicles, unmanned vehicles can real-time acquisition this moment the location data of this vehicle.
Optionally, the unmanned aerial vehicle may further send a positioning acquisition request for requesting to acquire positioning data to the vehicle at predetermined time intervals, and after receiving the positioning acquisition request, the vehicle may send the positioning data acquired by the vehicle-mounted system or the positioning system to the unmanned aerial vehicle.
In step 303, an image of the road condition in a predetermined distance in front of the vehicle is collected according to the positioning data.
The predetermined distance may be set according to actual conditions, for example, according to the current speed per hour of the vehicle, for example, the predetermined distance may be positively correlated with the current speed per hour of the vehicle, i.e., the faster the current speed per hour of the vehicle, the larger the predetermined distance, the slower the current speed per hour of the vehicle, and the smaller the predetermined distance.
Optionally, the predetermined distance may also be set according to a farthest distance that the camera on the drone can shoot, for example, the predetermined distance may be in forward correlation with the farthest distance that the camera on the drone can shoot, that is, the longer the farthest distance that the camera can shoot, the larger the predetermined distance, the shorter the farthest distance that the camera can shoot, and the smaller the predetermined distance.
Alternatively, the predetermined distance may be set according to the current speed per hour of the vehicle and the farthest distance that the unmanned aerial vehicle camera can photograph.
For example, the predetermined distance may be 100m, 500m, or 1km, and the predetermined distance is not limited in the embodiment.
Because the sight distance of the driver of the vehicle is limited, in order to ensure that the driver can know the road condition of the front road section in advance, the unmanned aerial vehicle can determine the current position of the vehicle according to the positioning data of the vehicle and then acquire the road condition image in the preset distance in front of the vehicle.
Optionally, when the unmanned aerial vehicle needs to shoot road condition images in the preset distance in front of the vehicle, the viewing angle of the camera in the unmanned aerial vehicle can be adjusted according to the height of the unmanned aerial vehicle, the preset distance, the distance between the unmanned aerial vehicle and the vehicle, the relative angle and the like, so that the camera can acquire the road condition images in the preset distance in front of the vehicle.
It should be noted that the distance between the unmanned aerial vehicle and the vehicle may be fixed, that is, preset, or may be dynamically changed, and at this time, the unmanned aerial vehicle may determine the distance and the relative angle between the unmanned aerial vehicle and the vehicle according to the positioning data of the vehicle and the positioning data obtained by positioning the unmanned aerial vehicle itself.
Optionally, the unmanned aerial vehicle may synchronize with the speed per hour of the vehicle, that is, the speed per hour of the vehicle may be transmitted to the unmanned aerial vehicle in real time, and the unmanned aerial vehicle adjusts the speed per hour of its own flight according to the speed per hour.
Optionally, the vehicle-mounted system of the vehicle may send the current speed of the vehicle to the drone in real time, and the drone adjusts the flight speed of the drone in the horizontal direction according to the received current speed of the vehicle. In this way, the drone only needs to calculate the distance and relative angle to the vehicle once or at predetermined time intervals.
In step 304, the image of the road condition is recognized to obtain the road condition information.
When the image of the road condition is identified, the road condition information of the road condition can be obtained according to the existing image identification technology. The technology of identifying the road condition of the road condition image can be realized by a person skilled in the art, and is not described herein again.
In step 305, a road condition is presented for the vehicle according to the driving performance parameter and the road condition information.
The unmanned aerial vehicle can determine whether to remind the vehicle of prompting the road condition according to the road condition information and the driving performance parameters of the vehicle.
For example, when the road condition information indicates that the front road section meets the traffic prohibition condition, the vehicle is reminded to drive around the road, where the traffic prohibition condition is that the front road section is a non-motor vehicle lane, the road surface of the front road section is uneven, or the maximum gradient of the front road section is greater than the maximum gradient that the vehicle can drive.
For another example, when the road condition information indicates that the front road section meets the passing condition, the vehicle is reminded to normally run.
When reminding the vehicle to drive around the road, the unmanned aerial vehicle can send alarm information to the vehicle, or can send alarm information to the intelligent device bound with the unmanned aerial vehicle, and the alarm information is used for reminding the front road section not to be driven.
Referring to fig. 3C, which is a schematic diagram of a road condition prompt according to an exemplary embodiment, in fig. 3C, when determining that the maximum gradient of the road section ahead is greater than the maximum gradient that the vehicle can run according to the collected road condition image of the road section ahead of the vehicle 120, the drone 110 sends an alarm message to the vehicle, where the alarm message indicates that "the road section ahead has a high slope and please drive around the road".
In summary, the road condition prompting method provided in the embodiment of the present disclosure prompts the vehicle for the road condition by acquiring the driving performance parameter of the vehicle and acquiring the road condition information in front of the vehicle; the driving performance parameters of the vehicle and the road condition information in front of the vehicle are combined, so that whether the vehicle can continue to drive can be accurately judged, and the problems that in the related technology, the road condition in front cannot be accurately judged by a driver, so that an emergency occurs during driving, and the safety cannot be guaranteed are solved; the road condition of the road section in front of the vehicle can be accurately known, the emergency situation during driving is effectively avoided, and the safety during driving is improved.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods. For details not disclosed in the embodiments of the apparatus of the present disclosure, refer to the embodiments of the method of the present disclosure.
Fig. 4 is a block diagram of a traffic condition prompting device according to an exemplary embodiment, and as shown in fig. 4, the traffic condition prompting device is applied to the unmanned aerial vehicle 110 in the implementation environment shown in fig. 1, and the traffic condition prompting device includes but is not limited to: a parameter obtaining module 410, a road condition obtaining module 420 and a navigation module 430.
A parameter acquisition module 410 configured to acquire a driving performance parameter of a vehicle bound with the unmanned aerial vehicle;
a traffic information acquiring module 420 configured to acquire traffic information within a predetermined distance in front of the vehicle;
the navigation module 430 is configured to prompt the vehicle for a road condition according to the driving performance parameter obtained by the parameter obtaining module 410 and the road condition information obtained by the road condition obtaining module 420.
In summary, the road condition prompting device provided in the embodiment of the present disclosure prompts the vehicle for the road condition by acquiring the driving performance parameter of the vehicle and acquiring the road condition information in front of the vehicle; the driving performance parameters of the vehicle and the road condition information in front of the vehicle are combined, so that whether the vehicle can continue to drive can be accurately judged, and the problems that in the related technology, the road condition in front cannot be accurately judged by a driver, so that an emergency occurs during driving, and the safety cannot be guaranteed are solved; the road condition of the road section in front of the vehicle can be accurately known, the emergency situation during driving is effectively avoided, and the safety during driving is improved.
Fig. 5 is a block diagram of a traffic condition prompting device according to another exemplary embodiment, as shown in fig. 6, the traffic condition prompting device is applied to the unmanned aerial vehicle 110 in the implementation environment shown in fig. 1, and the traffic condition prompting device includes but is not limited to: a parameter obtaining module 510, a road condition obtaining module 520 and a navigation module 530.
A parameter obtaining module 510 configured to obtain a driving performance parameter of a vehicle bound with the unmanned aerial vehicle;
a traffic information acquiring module 520 configured to acquire traffic information within a predetermined distance in front of the vehicle;
a navigation module 530 configured to prompt the vehicle for a road condition according to the driving performance parameter obtained by the parameter obtaining module 510 and the road condition information obtained by the road condition obtaining module 520.
Optionally, the parameter obtaining module 510 includes: the first obtaining submodule 511, the second obtaining submodule 512, or the sending submodule 513 and the receiving submodule 514.
The first obtaining sub-module 511 is configured to establish connection with the vehicle, obtain the model of the vehicle sent by the vehicle, and obtain the driving performance parameter corresponding to the model from the cloud server; or,
a second obtaining submodule 512, configured to establish a connection with the vehicle, and obtain the driving performance parameter sent by the vehicle; or,
a sending submodule 513 configured to send a parameter obtaining request for obtaining a driving performance parameter of the vehicle to an intelligent device bound to the unmanned aerial vehicle, where the parameter obtaining request is used to trigger the intelligent device to feed back the driving performance parameter of the vehicle, and a receiving submodule 514 configured to receive the driving performance parameter of the vehicle sent by the intelligent device;
wherein the running performance parameter includes at least one of a maximum gradient at which the vehicle can run, a maximum speed at which the vehicle can run, a degree of flatness of a road surface on which the vehicle can safely run, and a parameter indicating whether the vehicle can run on an uneven road surface.
Optionally, the road condition obtaining module 520 includes: a third acquisition submodule 521, an image acquisition submodule 522 and an image identification submodule 523.
A third obtaining submodule 521 configured to obtain positioning data of the vehicle;
an image acquisition submodule 522 configured to acquire an image of the road condition in a predetermined distance in front of the vehicle according to the positioning data acquired by the third acquisition submodule 521;
an image recognition sub-module 523 configured to perform image recognition on the road condition image collected by the image collection sub-module 522 to obtain the road condition information.
Optionally, the navigation module 530 is further configured to:
when the road condition information indicates that the front road section meets the condition of no passing, the vehicle is reminded to drive around the road,
the communication prohibition condition is that the front road section is a non-motor lane, the road surface of the front road section is uneven, or the maximum gradient of the front road section is larger than the maximum gradient capable of being driven by the vehicle.
Optionally, the navigation module 530 is further configured to:
and sending alarm information to the vehicle, or sending alarm information to intelligent equipment bound with the unmanned aerial vehicle, wherein the alarm information is used for reminding that the front road section is not used for driving.
In summary, the road condition prompting device provided in the embodiment of the present disclosure prompts the vehicle for the road condition by acquiring the driving performance parameter of the vehicle and acquiring the road condition information in front of the vehicle; the driving performance parameters of the vehicle and the road condition information in front of the vehicle are combined, so that whether the vehicle can continue to drive can be accurately judged, and the problems that in the related technology, the road condition in front cannot be accurately judged by a driver, so that an emergency occurs during driving, and the safety cannot be guaranteed are solved; the road condition of the road section in front of the vehicle can be accurately known, the emergency situation during driving is effectively avoided, and the safety during driving is improved.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
An exemplary embodiment of the present disclosure provides a traffic condition prompting device, which can implement the traffic condition prompting method provided by the present disclosure, and the traffic condition prompting device is applied to the unmanned aerial vehicle 110 in the implementation environment shown in fig. 1, and the traffic condition prompting device may include: a processor, a memory for storing processor-executable instructions;
wherein the processor is configured to:
acquiring running performance parameters of a vehicle bound with the unmanned aerial vehicle;
acquiring road condition information in a preset distance in front of the vehicle;
and prompting the road condition for the vehicle according to the driving performance parameters and the road condition information.
Fig. 6 is a block diagram illustrating a road condition prompting device according to yet another exemplary embodiment. For example, apparatus 600 may be provided as an unmanned aircraft. Referring to fig. 6, the apparatus 600 includes a processing component 602 that further includes one or more processors and memory resources, represented by memory 604, for storing instructions, such as an application, positioning system or positioning application, etc., that are executable by the processing component 602. The application programs stored in memory 604 may include one or more modules that each correspond to a set of instructions. The apparatus 600 may further include a camera 612, and the camera 612 may capture the road condition image. In addition, the processing component 602 is configured to execute the instructions to execute the road condition prompting method.
The apparatus 600 may also include a power component 606 configured to perform power management of the apparatus 600, a wired or wireless network interface 608 configured to connect the apparatus 600 to a network, and an input output (I/O) interface 610. The apparatus 600 may operate based on an operating system, such as Windows Server, MacOSXTM, UnixTM, LinuxTM, FreeBSDTM, or the like, stored in the memory 604.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (11)
1. A road condition prompting method is applied to an unmanned aerial vehicle, and the method comprises the following steps:
acquiring the running performance parameters of the vehicle bound with the unmanned aircraft;
acquiring road condition information in a preset distance in front of the vehicle;
and prompting the road condition of the vehicle according to the driving performance parameters and the road condition information.
2. The method of claim 1, wherein the obtaining of the driving performance parameters of the vehicle bound to the drone comprises:
establishing connection with the vehicle, acquiring the model of the vehicle sent by the vehicle, and acquiring the driving performance parameters corresponding to the model from a cloud server; or,
establishing connection with the vehicle, and acquiring the driving performance parameters sent by the vehicle; or,
sending a parameter acquisition request for acquiring the running performance parameters of the vehicle to an intelligent device bound with the unmanned aerial vehicle, wherein the parameter acquisition request is used for triggering the intelligent device to feed back the running performance parameters of the vehicle and receiving the running performance parameters of the vehicle sent by the intelligent device;
wherein the running performance parameter includes at least one of a maximum gradient on which the vehicle can run, a maximum speed on which the vehicle can run, a degree of flatness of a road surface on which the vehicle can safely run, and a parameter indicating whether the vehicle can run on an uneven road surface.
3. The method of claim 1, wherein the obtaining the traffic information within a predetermined distance in front of the vehicle comprises:
acquiring positioning data of the vehicle;
acquiring road condition images in a preset distance in front of the vehicle according to the positioning data;
and carrying out image recognition on the road condition image to obtain the road condition information.
4. The method according to any one of claims 1 to 3, wherein the prompting the vehicle of the road condition according to the driving performance parameter and the road condition information comprises:
when the road condition information indicates that the front road section meets the condition of no passing, the vehicle is reminded to drive around the road,
the communication prohibition condition is that the front road section is a non-motor lane, the road surface of the front road section is uneven, or the maximum gradient of the front road section is larger than the maximum gradient of the vehicle.
5. The method of claim 4, wherein the alerting the vehicle to drive around comprises:
and sending alarm information to the vehicle, or sending alarm information to intelligent equipment bound with the unmanned aerial vehicle, wherein the alarm information is used for reminding the front road section of the unmanned aerial vehicle of not utilizing to run.
6. The utility model provides a road conditions suggestion device which characterized in that, is applied to among the unmanned aerial vehicle, the device includes:
a parameter acquisition module configured to acquire a driving performance parameter of a vehicle bound with the unmanned aerial vehicle;
the road condition acquisition module is configured to acquire road condition information within a preset distance in front of the vehicle;
and the navigation module is configured to prompt the road condition of the vehicle according to the driving performance parameters acquired by the parameter acquisition module and the road condition information acquired by the road condition acquisition module.
7. The apparatus of claim 6, wherein the parameter obtaining module comprises:
the first obtaining sub-module is configured to establish connection with the vehicle, obtain the model of the vehicle sent by the vehicle, and obtain the driving performance parameter corresponding to the model from a cloud server; or,
the second obtaining submodule is configured to establish connection with the vehicle and obtain the driving performance parameters sent by the vehicle; or,
the system comprises a sending submodule and a receiving submodule, wherein the sending submodule is configured to send a parameter obtaining request for obtaining the running performance parameters of the vehicle to an intelligent device bound with the unmanned aerial vehicle, the parameter obtaining request is used for triggering the intelligent device to feed back the running performance parameters of the vehicle, and the receiving submodule is configured to receive the running performance parameters of the vehicle sent by the intelligent device;
wherein the running performance parameter includes at least one of a maximum gradient on which the vehicle can run, a maximum speed on which the vehicle can run, a degree of flatness of a road surface on which the vehicle can safely run, and a parameter indicating whether the vehicle can run on an uneven road surface.
8. The apparatus of claim 6, wherein the road condition obtaining module comprises:
a third acquisition sub-module configured to acquire positioning data of the vehicle;
the image acquisition sub-module is configured to acquire a road condition image in front of the vehicle within a preset distance according to the positioning data acquired by the third acquisition sub-module;
and the image recognition submodule is configured to perform image recognition on the road condition image acquired by the image acquisition submodule to obtain the road condition information.
9. The apparatus of any of claims 6 to 8, wherein the navigation module is further configured to:
when the road condition information indicates that the front road section meets the condition of no passing, the vehicle is reminded to drive around the road,
the communication prohibition condition is that the front road section is a non-motor lane, the road surface of the front road section is uneven, or the maximum gradient of the front road section is larger than the maximum gradient of the vehicle.
10. The apparatus of claim 9, wherein the navigation module is further configured to:
and sending alarm information to the vehicle, or sending alarm information to intelligent equipment bound with the unmanned aerial vehicle, wherein the alarm information is used for reminding the front road section of the unmanned aerial vehicle of not utilizing to run.
11. The utility model provides a road conditions suggestion device which characterized in that, is applied to among the unmanned aerial vehicle, the device includes:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to:
acquiring the running performance parameters of the vehicle bound with the unmanned aircraft;
acquiring road condition information in a preset distance in front of the vehicle;
and prompting the road condition of the vehicle according to the driving performance parameters and the road condition information.
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