CN115675530A - Driving assistance method and device for expressway driving scene - Google Patents
Driving assistance method and device for expressway driving scene Download PDFInfo
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Abstract
The application relates to the technical field of intelligent driving, in particular to a driving assistance method and a driving assistance device for a highway driving scene, wherein the method comprises the following steps: detecting the current scene of the vehicle; when the current scene is detected to be the highway driving scene, receiving driving information uploaded by a vehicle, and calculating the optimal driving assistance action according to the driving information and the navigation path; and generating a driving instruction according to the optimal driving assistance action, and sending the driving instruction to the vehicle. Therefore, the technical problems that hardware cost of the vehicle is increased due to the fact that hardware is excessively depended on in the related technology, the intelligentization level of the vehicle is low, the applicability of the vehicle is reduced, the vehicle using experience of a user is reduced, and the vehicle using requirement of the user cannot be met are solved.
Description
Technical Field
The application relates to the technical field of intelligent driving, in particular to a driving assistance method and device for a highway driving scene.
Background
In the related technology, information such as the distance between a user driving vehicle and a front vehicle and the vehicle speed is detected by a millimeter wave radar so as to keep the vehicle speed and the vehicle distance, a traffic line of a lane where the vehicle is located in the driving process is detected by an image system consisting of a plurality of cameras so as to keep the lane and the vehicle body stable and steering, and then constant speed/full speed self-adaptive cruise is realized by matching with an algorithm so as to realize the auxiliary driving of a vehicle scene for a highway.
However, the hardware cost of the vehicle is increased due to excessive dependence on hardware in the related art, the intelligentization level of the vehicle is low, the applicability of the vehicle is reduced, the vehicle using experience of a user is reduced, the vehicle using requirement of the user cannot be met, and a solution is urgently needed.
Disclosure of Invention
The application provides a driving assistance method and device for a highway driving scene, and aims to solve the technical problems that hardware cost of a vehicle is increased due to the fact that hardware is excessively depended in the related technology, the intelligentization level of the vehicle is low, the applicability of the vehicle is reduced, vehicle using experience of a user is reduced, and the vehicle using requirement of the user cannot be met.
An embodiment of a first aspect of the present application provides a driving assistance method for a driving scene on a highway, including the following steps: detecting the current scene of the vehicle; when the current scene is detected to be a highway driving scene, receiving driving information uploaded by the vehicle, and calculating an optimal driving assistance action according to the driving information and a navigation path; and generating a driving instruction according to the optimal driving assistance action, and sending the driving instruction to the vehicle.
Optionally, in an embodiment of the application, the calculating an optimal driving assistance action according to the driving information and the navigation path includes: and inputting the driving information and the navigation path into a pre-constructed model, and outputting the optimal driving assistance action.
Optionally, in an embodiment of the present application, before calculating the optimal driving assistance action, the method further includes: and based on the highway topological graph, taking every two highway exits on the line as the driving channels of the minimum unit, and generating basic data of the model.
Optionally, in an embodiment of the present application, inputting the driving information and the navigation path to a pre-constructed model includes: generating a driving route map of a fleet comprising at least one vehicle according to the basic data based on a dynamic planning method; and determining the optimal driving auxiliary action of each vehicle in the motorcade according to the driving route map of the motorcade.
Optionally, in an embodiment of the present application, after generating the travel roadmap for the fleet of vehicles including at least one vehicle, the method further includes: when detecting that any vehicle carries out a fleet switching action, carrying out next fleet planning before the any vehicle leaves a fleet, and adding a queue with the highest matching degree, wherein when the any vehicle is in a free state, the vehicle forms a queue independently, and the lane and the vehicle speed are kept until a new fleet is found.
An embodiment of a second aspect of the present application provides a driving assistance device for a highway driving scene, including: the detection module is used for detecting the current scene of the vehicle; the calculation module is used for receiving the driving information uploaded by the vehicle and calculating the optimal driving assistance action according to the driving information and the navigation path when the current scene is detected to be the highway driving scene; and the sending module is used for generating a driving instruction according to the optimal driving assistance action and sending the driving instruction to the vehicle.
Optionally, in an embodiment of the application, the calculation module is further configured to input the driving information and the navigation path to a pre-constructed model, and output the optimal driving assistance action.
Optionally, in an embodiment of the present application, the apparatus in the embodiment of the present application further includes: and the generating module is used for generating basic data of the model by taking every two expressway exits on the line as the driving channels of the minimum unit based on the expressway topological graph before calculating the optimal driving assistance action.
Optionally, in an embodiment of the present application, inputting the driving information and the navigation path into a pre-constructed model includes: and based on a dynamic planning method, generating a driving route map of a fleet of vehicles comprising at least one vehicle according to the basic data, and determining the optimal driving auxiliary action of each vehicle in the fleet according to the driving route map of the fleet.
Optionally, in an embodiment of the present application, the apparatus of the embodiment of the present application further includes: and the control module is used for planning the next vehicle team before any vehicle leaves the fleet and adding the queue with the highest matching degree when detecting that any vehicle performs a vehicle team switching action after generating the driving route map of the vehicle team comprising at least one vehicle, wherein when any vehicle is in a free state, the vehicle is independently formed into a queue, and the lane and the vehicle speed are kept until a new vehicle team is found.
An embodiment of a third aspect of the present application provides a server, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the driving assistance method for the highway driving scenario as described in the above embodiments.
An embodiment of a fourth aspect of the present application provides a computer-readable storage medium storing a computer program, which when executed by a processor, implements the driving assistance method for a highway driving scenario as above.
According to the embodiment of the application, when the current scene of the vehicle is detected to be the highway driving scene, the driving information uploaded by the vehicle is received, the optimal driving assistance action is calculated according to the driving information and the navigation path, the driving instruction is generated according to the optimal driving assistance action, and the driving instruction is sent to the vehicle, so that the intelligent level of the vehicle is improved, the applicability of the vehicle is improved, and the vehicle using requirements of users are met. Therefore, the technical problems that hardware cost of the vehicle is increased due to the fact that hardware is excessively depended on in the related technology, the intelligentization level of the vehicle is low, the applicability of the vehicle is reduced, the vehicle using experience of a user is reduced, and the vehicle using requirement of the user cannot be met are solved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a driving assistance method for an expressway driving scene according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of driving assistance for a highway driving scenario in accordance with an embodiment of the present application;
FIG. 3 is a timing diagram illustrating driving assistance during a highway driving scenario in accordance with an exemplary embodiment of the present application;
fig. 4 is a schematic structural diagram of a driving assistance device for a highway driving scene according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a server according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The following describes a driving assistance method and apparatus for a highway driving scene according to an embodiment of the present application with reference to the drawings. In the method, when the current scene of the vehicle is detected to be the highway driving scene, the driving information uploaded by the vehicle can be received, the optimal driving assistance action is calculated according to the driving information and the navigation path, the driving instruction is generated according to the optimal driving assistance action, and the driving instruction is sent to the vehicle, so that the intelligent level of the vehicle is improved, the applicability of the vehicle is improved, and the vehicle demand of the user is met. Therefore, the technical problems that hardware cost of a vehicle is increased due to the fact that hardware is excessively depended in the related technology, the intelligentization level of the vehicle is low, the applicability of the vehicle is reduced, the vehicle using experience of a user is reduced, and the vehicle using requirement of the user cannot be met are solved.
Specifically, fig. 1 is a schematic flow chart of a driving assistance method for an expressway driving scene according to an embodiment of the present application.
As shown in fig. 1, the driving assistance method for the highway driving scene includes the following steps:
in step S101, the current scene of the vehicle is detected.
It can be understood that the present scene of the vehicle can be detected in the embodiment of the present application, for example, whether the present scene is an expressway driving scene in the following steps can be detected by the vehicle body camera in the embodiment of the present application, so that the performability of driving assistance in the expressway driving scene is improved, and the intelligence level of the vehicle is improved.
In step S102, when it is detected that the current scene is the highway driving scene, the driving information uploaded by the vehicle is received, and the optimal driving assistance action is calculated according to the driving information and the navigation path.
It can be understood that, when it is detected that the current scene is the highway driving scene, the embodiment of the application can receive the driving information uploaded by the vehicle through the server, for example, detect whether obstacles are near around the vehicle body through the millimeter wave radar, identify a road traffic line through the vehicle body camera, and calculate the optimal driving assistance action according to the driving information and the navigation path in the following steps, thereby effectively improving the automation degree of the vehicle and improving the driving experience of a user.
Optionally, in an embodiment of the present application, before calculating the optimal driving assistance action, the method further includes: and based on the highway topological graph, taking every two highway exits on the line as the driving channel of the minimum unit to generate basic data of the model.
As a possible implementation manner, the embodiment of the present application may be based on a highway topological graph, for example, national highways may be regarded as one network, each highway exit may be regarded as a point on the highway network or a point where two lines meet, the highway network is simplified into a graph, the road planning topological graph is used as basic data, a distance between two points in the topological graph is used as a channel, that is, a vehicle travels at a high speed, and then, the embodiment of the present application may perform channel division, the national highway topological graph may use every two highway exits on one line as a minimum unit travel channel, and the channel may be used as basic data, thereby improving an intelligent level of driving assistance.
In one embodiment of the present application, calculating an optimal driving assistance action according to the travel information and the navigation path includes: and inputting the driving information and the navigation path into a pre-constructed model, and outputting the optimal driving assistance action.
In the actual execution process, the vehicle can upload the running information to the server in real time in the running process, and the server can input the running information reported by the vehicle in real time and the navigation path provided by the vehicle-mounted map in the following steps into a pre-constructed model and output the optimal driving assistance action, so that the running instruction can be issued to the vehicle in real time, and the vehicle can be guaranteed to run normally to realize the driving assistance.
In one embodiment of the present application, inputting the driving information and the navigation path into a pre-constructed model includes: generating a driving route map of a fleet comprising at least one vehicle according to the basic data based on a dynamic planning method; an optimal driving assistance action for each vehicle in the platoon is determined from a driving roadmap of the platoon.
In some embodiments, the embodiment of the present application may generate a driving route map of a fleet including at least one vehicle according to basic data based on a dynamic planning method, for example, a server may collect all vehicles with high-speed driving requirements, merge the driving routes into a national high-speed network topology map, so that a driving scene of the vehicle on an expressway may be converted into a conversion process of turning from one channel to another channel, and all vehicles in the channel may form a fleet.
For example, in the embodiment of the present application, a server may use a high-speed driving plan that a first vehicle accesses the vehicle as a driving channel, where the driving channel may include multiple channel units in a topological graph, and after a second vehicle accesses the second vehicle, overlapping portions may still be regarded as a single channel, and respective unique portions may be regarded as other channels, and so on, where 10 vehicles are accessed as an upper limit, at this time, a driving route map of a fleet is completely formed, and the vehicles are sequentially queued, leave the fleet switching channel in sequence, and join another fleet.
In other words, the dynamic planning algorithm can be used for dividing the fleet, all fleets can be seen as numerous straight lines from the starting point to the end point, the vehicles are points on the straight lines, switching is performed among the numerous straight lines according to the planned paths of the vehicles, and positions in the fleets after switching are connected with the vehicles behind by the vehicles never to be vacant, so that the vehicles can be switched to the end point in one channel and one fleet, the intelligence of the vehicles is improved, and the driving experience of users is improved.
In one embodiment of the present application, after generating a driving roadmap including at least one vehicle fleet, the method further includes: when detecting that any vehicle carries out the switching action of the fleet, the next fleet is planned before any vehicle leaves the fleet, and a queue with the highest matching degree is added, wherein when any vehicle is in a free state, the vehicle forms a queue independently, and the lane and the vehicle speed are kept until a new fleet is found.
In some embodiments, when detecting that any vehicle performs a fleet switching action, for example, the vehicle has a state of departing during switching fleet but during driving, when the vehicle starts a fleet searching mode as a free state crossing two channels, the server may perform next fleet planning before the vehicle departs, join in a queue forming the highest matching degree, wherein the vehicle forms a queue independently in the free state, and keep the lane and the vehicle speed until a new fleet is found, thereby improving the safety and reliability of vehicle driving assistance.
In addition, the embodiment of the application can carry out vehicle-leading election, the vehicle-leading can be used as the core of the stable operation of the whole vehicle, the vehicle-leading can be a driving base line similar to a sea level line when the altitude is calculated, the vehicle speed and the channel information of the vehicle-leading can be used as a standard of free vehicles, the free vehicles control the vehicle speed through an instruction issued by the server and seek to join the motorcade, and after the free vehicles join the motorcade, the vehicle-leading is used as the standard to keep the vehicle distance to drive.
In step S103, a travel command is generated in accordance with the optimal driving assistance operation, and the travel command is transmitted to the vehicle.
It can be understood that, the server in the embodiment of the present application may generate the driving instruction according to the optimal driving assistance action in the above steps, and send the driving instruction to the vehicle, thereby improving the intelligence level of the vehicle, improving the applicability of the vehicle, and satisfying the vehicle use demand of the user.
In addition, the embodiment of the application does not need to limit the brand of the vehicle when the vehicle is accessed, improves the applicability of the vehicle, reduces the hardware cost of the vehicle, and improves the convenience and intelligence of vehicle-assisted driving upgrading.
The operation of one embodiment of the present application will be described in detail with reference to fig. 2 and 3.
As shown in fig. 2, a schematic structural diagram of driving assistance for a highway driving scene according to an embodiment of the present invention is shown, and fig. 3 is a schematic timing diagram of driving assistance for a highway driving scene according to an embodiment of the present invention, where the present invention combines hardware and software, where the hardware may be a millimeter wave radar and an image system, the hardware may be a vehicle body safety radar installed on a front left side, a rear left side, a front right side, and a rear right side of a vehicle body, and may detect obstacles around the vehicle body to ensure safety of the vehicle body, and the millimeter wave radar is used in front of the vehicle body to detect a distance between the vehicle and a vehicle ahead and a driving speed of the vehicle ahead, and this part of functions is basically configured in an entry level vehicle type of the vehicle, and may be reused, and the left, right, and front three cameras constitute a vehicle body image system, and the image system may identify a road traffic line to maintain a road, thereby ensuring normal driving of the vehicle.
And then, the vehicle performs data interaction with the server in the driving process, so as to upload vehicle driving information in real time, the server can utilize data reported by the vehicle in real time, and perform model calculation by combining a navigation line, and issue a driving instruction to the vehicle in real time to ensure that the vehicle normally drives to realize auxiliary driving, so that the hardware configuration is reduced, the convenience of vehicle system upgrading is improved, the applicability of the vehicle is improved, and the vehicle using requirements of users are met.
According to the driving assistance method for the highway driving scene, when the current scene of the vehicle is detected to be the highway driving scene, the driving information uploaded by the vehicle can be received, the optimal driving assistance action is calculated according to the driving information and the navigation path, the driving instruction is generated according to the optimal driving assistance action, and the driving instruction is sent to the vehicle, so that the intelligent level of the vehicle is improved, the applicability of the vehicle is improved, and the vehicle using requirements of users are met. Therefore, the technical problems that hardware cost of the vehicle is increased due to the fact that hardware is excessively depended on in the related technology, the intelligentization level of the vehicle is low, the applicability of the vehicle is reduced, the vehicle using experience of a user is reduced, and the vehicle using requirement of the user cannot be met are solved.
Next, a driving assistance device for a highway driving scene proposed according to an embodiment of the present application is described with reference to the drawings.
Fig. 4 is a block diagram schematically illustrating a driving assistance apparatus for a highway driving scene according to an embodiment of the present application.
As shown in fig. 4, the driving assistance device 10 for the highway driving scenario includes: a detection module 100, a calculation module 200 and a sending module 300.
Specifically, the detecting module 100 is configured to detect a current scene of the vehicle.
And the calculating module 200 is configured to receive driving information uploaded by a vehicle when it is detected that the current scene is an expressway driving scene, and calculate an optimal driving assistance action according to the driving information and the navigation path.
The sending module 300 is configured to generate a driving instruction according to the optimal driving assistance action, and send the driving instruction to the vehicle.
Optionally, in an embodiment of the present application, the calculation module 200 is further configured to input the driving information and the navigation path to a pre-constructed model, and output the optimal driving assistance action.
Optionally, in an embodiment of the present application, the apparatus 10 of the embodiment of the present application further includes: and generating a module.
The generating module is used for generating basic data of the model by taking every two expressway exits on the line as the driving channels of the minimum unit based on the expressway topological graph before calculating the optimal driving assistance action.
Optionally, in an embodiment of the present application, inputting the driving information and the navigation path to a pre-constructed model includes: and based on a dynamic planning method, generating a driving route map of a fleet of vehicles comprising at least one vehicle according to the basic data, and determining the optimal driving assistance action of each vehicle in the fleet of vehicles according to the driving route map of the fleet of vehicles.
Optionally, in an embodiment of the present application, the apparatus 10 of the embodiment of the present application further includes: and a control module.
The control module is used for planning the next vehicle fleet before any vehicle departs from the fleet and adding a queue with the highest matching degree when detecting that any vehicle performs a vehicle fleet switching action after generating a driving route map of the vehicle fleet comprising at least one vehicle, wherein when any vehicle is in a free state, the vehicle trains independently and keeps a lane and a vehicle speed until a new vehicle fleet is found.
It should be noted that the foregoing explanation of the embodiment of the driving assistance method for the highway driving scene is also applicable to the driving assistance device for the highway driving scene in this embodiment, and is not repeated here.
According to the driving assistance device for the highway driving scene, provided by the embodiment of the application, when the current scene of the vehicle is detected to be the highway driving scene, the driving information uploaded by the vehicle can be received, the optimal driving assistance action is calculated according to the driving information and the navigation path, the driving instruction is generated according to the optimal driving assistance action, and the driving instruction is sent to the vehicle, so that the intelligentization level of the vehicle is improved, the applicability of the vehicle is improved, and the vehicle using requirements of users are met. Therefore, the technical problems that hardware cost of a vehicle is increased due to the fact that hardware is excessively depended in the related technology, the intelligentization level of the vehicle is low, the applicability of the vehicle is reduced, the vehicle using experience of a user is reduced, and the vehicle using requirement of the user cannot be met are solved.
Fig. 5 is a schematic structural diagram of a server according to an embodiment of the present application. The server may include:
a memory 501, a processor 502, and a computer program stored on the memory 501 and executable on the processor 502.
The processor 502 implements the driving assistance method for the highway driving scenario provided in the above-described embodiment when executing the program.
Further, the server further comprises:
a communication interface 503 for communication between the memory 501 and the processor 502.
A memory 501 for storing computer programs that can be run on the processor 502.
The memory 501 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
Alternatively, in practical implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 may complete communication with each other through an internal interface.
The processor 502 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.
The present embodiment also provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the driving assistance method for the highway driving scenario as above.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A driving assistance method for a highway driving scene is applied to a server, wherein the method comprises the following steps:
detecting the current scene of the vehicle;
when the current scene is detected to be a highway driving scene, receiving driving information uploaded by the vehicle, and calculating an optimal driving assistance action according to the driving information and a navigation path; and
and generating a driving instruction according to the optimal driving assistance action, and sending the driving instruction to the vehicle.
2. The method according to claim 1, wherein the calculating an optimal driving assistance action according to the travel information and the navigation path comprises:
and inputting the driving information and the navigation path into a pre-constructed model, and outputting the optimal driving assistance action.
3. The method according to claim 2, further comprising, prior to calculating the optimal driving assistance action:
and based on the highway topological graph, taking every two highway exits on the line as the driving channels of the minimum unit, and generating basic data of the model.
4. The method of claim 3, wherein inputting the travel information and the navigation path to a pre-constructed model comprises:
generating a driving route map of a fleet comprising at least one vehicle according to the basic data based on a dynamic planning method;
and determining the optimal driving auxiliary action of each vehicle in the motorcade according to the driving route map of the motorcade.
5. The method of claim 4, further comprising, after generating the travel roadmap for the fleet of vehicles comprising at least one vehicle:
when detecting that any vehicle carries out a fleet switching action, carrying out next fleet planning before the any vehicle leaves a fleet, and adding a queue with the highest matching degree, wherein when the any vehicle is in a free state, the vehicle forms a queue independently, and the lane and the vehicle speed are kept until a new fleet is found.
6. A driving assistance apparatus for a highway driving scenario, applied to a server, wherein the apparatus comprises:
the detection module is used for detecting the current scene of the vehicle;
the calculation module is used for receiving the driving information uploaded by the vehicle when the current scene is detected to be a highway driving scene, and calculating the optimal driving auxiliary action according to the driving information and the navigation path; and
and the sending module is used for generating a driving instruction according to the optimal driving assistance action and sending the driving instruction to the vehicle.
7. The apparatus of claim 6, wherein the computing module is further configured to input the driving information and the navigation path to a pre-constructed model and output the optimal driving assistance action.
8. The apparatus of claim 7, further comprising:
and the generating module is used for generating basic data of the model by taking every two expressway exits on the line as the driving channels of the minimum unit based on the expressway topological graph before calculating the optimal driving assistance action.
9. A server, comprising: memory, processor and computer program stored on the memory and executable on the processor, the processor executing the program to implement the driving assistance method of a highway driving scenario according to any of claims 1-5.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing a driving assistance method for a highway driving scenario according to any one of claims 1-5.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202211433996.6A CN115675530A (en) | 2022-11-16 | 2022-11-16 | Driving assistance method and device for expressway driving scene |
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| CN202211433996.6A CN115675530A (en) | 2022-11-16 | 2022-11-16 | Driving assistance method and device for expressway driving scene |
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2022
- 2022-11-16 CN CN202211433996.6A patent/CN115675530A/en active Pending
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