An intelligent driving function adaptive recommendation method, system and medium

Abstract

The application discloses a kind of intelligent driving function self-adapting recommendation method, system and medium, belong to the field of automatic driving, the method includes: obtaining the road type of the position where the automatic driving vehicle is located;Confirm the map type for navigation that the automatic driving vehicle itself is equipped with;According to road type and map type, the corresponding automatic driving function is recommended for the automatic driving vehicle, wherein road type includes public road and internal road, and map type includes high-precision map and non-high-precision map.The driving function self-adapting recommendation method of the application, by the perception of the driving environment of the automatic driving vehicle and the judgment of the road type of the driving position, provides the most suitable automatic driving function under the current driving ring for the automatic driving vehicle, guarantees the safety of automatic driving process, completely automatically carries out the recommendation of driving function, improves the driving experience of driver.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving, in particular to a method and system for adaptive recommendation of intelligent driving functions and a medium. BACKGROUND

[0002] In the process of automatic driving of a vehicle, the automatic driving system of the vehicle will provide corresponding automatic driving functions for the automatic driving vehicle according to the road conditions of the vehicle driving, and provide driving instructions for the driving of the vehicle. In the process of automatic driving of the vehicle, multiple different automatic driving driving functions are set according to different conditions, so as to ensure that the automatic driving vehicle can drive safely in different environments. However, in the driving process of the automatic driving vehicle, how to accurately allocate different automatic driving functions to the automatic driving vehicle to ensure that the automatic driving vehicle can drive safely according to accurate driving instructions in different environments is a problem to be solved. In addition, in the process of automatic driving, the driver can manually select the corresponding automatic driving function according to the driving environment of the vehicle to control the automatic driving vehicle. Because the vehicle driving environment changes frequently, the driver needs to manually adjust frequently, which greatly affects the driving experience of the driver. SUMMARY

[0003] In view of the problem in the prior art that how to allocate the automatic driving function most suitable for the current driving road to the automatic driving vehicle in the process of automatic driving of the automatic driving vehicle, the present application provides a method and system for adaptive recommendation of intelligent driving functions and a medium.

[0004] In a first aspect, the present application provides a method for adaptive recommendation of intelligent driving functions, comprising: acquiring a road type of a position where an automatic driving vehicle is located; confirming a map type used for navigation by the automatic driving vehicle itself; and recommending a corresponding automatic driving function for the automatic driving vehicle according to the road type and the map type, wherein the road type includes a public road and an internal road, and the map type includes a high-precision map and a non-high-precision map.

[0005] Optionally, acquiring the road type of the position where the automatic driving vehicle is located comprises: determining the position where the automatic driving vehicle is located by a positioning unit carried by the automatic driving vehicle; and determining the road type according to environmental information obtained by a perception unit carried by the automatic driving vehicle.

[0006] Optionally, the automatic driving function is recommended to the automatic driving vehicle according to the road type and the map type, including: under the condition that the road type is a public road and the map type is a high-precision map, if the automatic driving vehicle is in a highway in the public road, a high-speed navigation assisted driving function is recommended to the automatic driving vehicle; if the automatic driving vehicle is in an urban road in the public road, a city road navigation assisted driving function is recommended to the automatic driving vehicle; if the automatic driving vehicle is in a parking road in the public road, an automatic parking assisted function is recommended to the automatic driving vehicle; and if the automatic driving vehicle is in other road in the public road, under the condition that a lane line is identified, a lane centering control function is recommended to the automatic driving vehicle, and under the condition that no lane line is identified, an adaptive cruise control function is recommended to the automatic driving vehicle.

[0007] Optionally, if the automatic driving vehicle is in a parking road in the public road, an automatic parking assisted function is recommended to the automatic driving vehicle, including: under the condition that the automatic driving vehicle monitors a parking road, the speed of the vehicle is less than a preset threshold, a parking space is identified, and the automatic driving vehicle has been slowed down, it is determined that the automatic driving vehicle is in a driving environment of the parking road.

[0008] Optionally, the automatic driving function is recommended to the automatic driving vehicle according to the road type and the map type, including: under the condition that the road type is a public road and the map type is a non-precision map, if the driving environment of the automatic driving vehicle is a parking road, an automatic parking assisted function is recommended to the automatic driving vehicle; and if the driving environment of the automatic driving vehicle is other road, under the condition that a lane line is identified, a lane centering control function is recommended to the automatic driving vehicle, and under the condition that no lane line is identified, an adaptive cruise control function is recommended to the automatic driving vehicle.

[0009] Optionally, the automatic driving function is recommended to the automatic driving vehicle according to the road type and the map type, including: under the condition that the road type is a ground road in an internal road and the map type is an LPNP map, a memory parking navigation assisted driving function is recommended to the automatic driving vehicle; under the condition that the road type is a ground road in an internal road and the map type is a non-LPNP map, if a parking space is identified, an automatic parking assisted function is recommended to the automatic driving vehicle; if no parking space is identified but a lane line is identified, a lane centering control function is recommended to the automatic driving vehicle; and if no parking space is identified and no lane line is identified, an adaptive cruise control function is recommended to the automatic driving vehicle.

[0010] Optionally, according to the road type and the map type, a corresponding automatic driving function is recommended for the automatic driving vehicle, including: under the condition that the road type is a parking building road in an internal road, if the map type is a PNP map, a parking pilot assisted driving function is recommended for the automatic driving vehicle; if the map type is only an LPNP map, a memory parking pilot assisted driving function is recommended for the automatic driving vehicle; if the map type is no map, under the condition that a parking space is identified, an automatic parking assistance function is recommended for the automatic driving vehicle, and under the condition that no parking space is identified, learning of the LPNP is performed.

[0011] Optionally, according to the road type and the map type, a corresponding automatic driving function is recommended for the automatic driving vehicle, including: under the condition that the road type is an underground road in an internal road, if the map type is a PNP map, a parking pilot assisted driving function is recommended for the automatic driving vehicle; if the map type is only an LPNP map, a memory parking pilot assisted driving function is recommended for the automatic driving vehicle; if the map type is no map, under the condition that a parking space is identified, an automatic parking assistance function is recommended for the automatic driving vehicle, and under the condition that no parking space is identified, learning of the LPNP is performed.

[0012] In a second aspect, the present application provides an intelligent driving function adaptive recommendation system, comprising: a perception module that acquires a road type of a position where an automatic driving vehicle is located; a map confirmation module that confirms a map type of a navigation map carried by the automatic driving vehicle itself; and a function recommendation module that recommends a corresponding automatic driving function for the automatic driving vehicle according to the road type and the map type, wherein the road type includes a public road and an internal road, and the map type includes a high-precision map and a non-high-precision map.

[0013] In a third aspect, the present application provides a computer readable storage medium storing a computer program, wherein the computer program is operated to execute the intelligent driving function adaptive recommendation method in the first aspect.

[0014] The intelligent driving function adaptive recommendation method of the present application provides the most suitable automatic driving function for the automatic driving vehicle under the current driving environment through perception of the driving environment of the automatic driving vehicle and judgment of the road type of the driving position, ensures safety of the automatic driving process, and completely automatically performs recommendation of the driving function, thereby improving driving experience of the driver. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description exemplarily show some embodiments of the present application.

[0016] Figure 1A schematic diagram of one embodiment of the intelligent driving function adaptive recommendation method of this application is shown;

[0017] Figure 2 A schematic diagram of one embodiment of the intelligent driving function adaptive recommendation system of this application is shown.

[0018] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0019] The preferred embodiments of this application will now be described in detail with reference to the accompanying drawings, so that the advantages and features of this application can be more easily understood by those skilled in the art, thereby providing a clearer and more definite definition of the scope of protection of this application.

[0020] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0021] During autonomous driving, the vehicle's autonomous driving system provides corresponding autonomous driving functions and driving instructions based on different road conditions and driving environments. Multiple different autonomous driving functions are set up to ensure safe driving in various environments. However, accurately allocating different autonomous driving functions to the vehicle to ensure safe driving under accurate guidance in different conditions is a problem that urgently needs to be solved. Furthermore, during autonomous driving, the driver manually selects appropriate autonomous driving functions to control the vehicle based on the current driving environment. Because the driving environment changes, the driver needs to make frequent manual adjustments, which significantly impacts the driving experience.

[0022] Therefore, the application monitors the road type, map type and other information during the driving process of the autonomous vehicle, automatically recommends a suitable autonomous driving function for the autonomous vehicle through the autonomous driving system, and ensures the operation of the autonomous vehicle. At the same time, the process of frequently changing the autonomous driving function by the driver is omitted, and one-key driving of the autonomous vehicle can be realized.

[0023] To solve the above problems, the application provides an intelligent driving function adaptive recommendation method, system and medium. The method comprises: acquiring a road type of a position where the autonomous vehicle is located; confirming a map type for navigation carried by the autonomous vehicle itself; and recommending a corresponding autonomous driving function for the autonomous vehicle according to the road type and the map type, wherein the road type comprises a public road and an internal road, and the public road comprises a highway and an urban road, and the map type comprises a high-precision map and a non-high-precision map.

[0024] The application monitors the environmental information during the driving process of the autonomous vehicle, and allocates the most suitable autonomous driving function for the autonomous vehicle according to the road type, such as a public road and an internal road, the high-precision map or the non-high-precision map configured by the autonomous vehicle, and whether the autonomous vehicle is in a highway or an urban road. The autonomous driving function ODD (Operational Design Domain) design operating range comprises PNP (Parking Navigation Pilot) parking navigation pilot assisted driving, LPNP (Learned Parking Navigation Pilot) learned parking navigation pilot assisted driving, APA (Automatic Parking Assist) automatic parking assist, LCC (Lane Centering Control) lane centering control, ACC (Adaptive Cruise Control) adaptive cruise control, HNP (Highway Navigation Pilot) highway navigation pilot assisted driving, UNP (Urban Navigation Pilot) urban road navigation pilot assisted driving, and the like.

[0025] In the following, the technical solutions of the application and how the technical solutions solve the above technical problems will be described in detail with specific embodiments. The specific embodiments described below can be combined to form new embodiments. For the same or similar ideas or processes described in one embodiment, they can not be described again in other embodiments. The embodiments of the application will be described below with reference to the drawings.

[0026] Figure 1A schematic diagram of one embodiment of the adaptive recommendation method of intelligent driving functions is shown.

[0027] In Figure 1 In the embodiment shown, the adaptive recommendation method of intelligent driving functions includes process S101, obtaining the road type of the location where the autonomous vehicle is located.

[0028] In this embodiment, when assigning the autonomous driving function, first, the environment where the autonomous vehicle is located is determined, whether it is located on a highway or an urban road, and then the most suitable autonomous driving function is recommended.

[0029] Optionally, obtaining the road type of the location where the autonomous vehicle is located includes: determining the location of the autonomous vehicle through a positioning unit carried by the autonomous vehicle; and determining the road type according to the location and environmental information obtained by a perception unit carried by the autonomous vehicle.

[0030] In this optional embodiment, when recommending the corresponding autonomous driving function to the autonomous vehicle, first, the environment where the autonomous vehicle is located and the driving situation are determined. In this process, the position of the autonomous vehicle can be determined through a positioning unit carried by the vehicle itself, such as a GPS positioning unit. Through the position, it can be determined whether the autonomous vehicle is located on a public road for a plurality of vehicles to travel or on an internal road for only a part of vehicles to park. Then, through a perception unit carried by the autonomous vehicle, such as a radar sensor, a camera, etc., the specific road around the autonomous vehicle can be obtained, such as determining that the autonomous vehicle is located on a highway or an urban road, so as to recommend the appropriate autonomous driving function to the autonomous vehicle.

[0031] In Figure 1 In the embodiment shown, the adaptive recommendation method of intelligent driving functions includes process S102, confirming the type of the map carried by the autonomous vehicle for navigation.

[0032] In this embodiment, providing the vehicle with what kind of autonomous driving function is related to the navigation map carried by the autonomous vehicle. The navigation map carried by the autonomous vehicle includes a high-precision map and a non-high-precision map. Because there is a big gap in map accuracy between the high-precision map and the non-high-precision map, according to the different types of maps carried by the vehicle, the autonomous driving system recommends different autonomous driving functions for the vehicle, so as to ensure the safe driving of the autonomous vehicle and the driving experience of the driver.

[0033] In Figure 1In the illustrated embodiment, the intelligent driving function adaptive recommendation method of the present application includes a process S103 of recommending a corresponding automatic driving function for an autonomous vehicle according to a road type and a map type.

[0034] In this embodiment, after the road type in which the current autonomous vehicle is located and the navigation map carried by the vehicle itself are determined, a suitable automatic driving function is recommended for the autonomous vehicle according to the corresponding results. The ODD (Operational Design Domain) design operating range of the autonomous driving function includes PNP (Parking Navigation Pilot) parking navigation pilot assisted driving, LPNP (Learned Parking Navigation Pilot) learned parking navigation pilot assisted driving, APA (Automatic Parking Assist) automatic parking assist, LCC (Lane Centering Control) lane centering control, ACC (Adaptive Cruise Control) adaptive cruise control, HNP (Highway Navigation Pilot) highway navigation pilot assisted driving, UNP (Urban Navigation Pilot) urban road navigation pilot assisted driving, and the like. It can be seen that different scenarios have their own corresponding autonomous driving functions, and therefore the accuracy of the autonomous driving function recommendation needs to be ensured.

[0035] The LPNP map refers to a high-precision map generated by learned parking, and mainly includes a positioning layer, a navigation layer, a rendering layer, and the like.

[0036] Optionally, the corresponding autonomous driving function is recommended for the autonomous vehicle according to the road type and the map type, including: under the condition that the road type is a public road and the map type is a high-precision map, if the autonomous vehicle is located on a highway in the public road, a highway navigation pilot assisted driving function is recommended for the autonomous vehicle; if the autonomous vehicle is located on an urban road in the public road, an urban road navigation pilot assisted driving function is recommended for the autonomous vehicle; if the autonomous vehicle is located on a parking road in the public road, an automatic parking assist function is recommended for the autonomous vehicle; and if the autonomous vehicle is located on other roads in the public road, under the condition that lane lines exist, a lane centering control function is recommended for the autonomous vehicle, and under the condition that no lane lines exist, an adaptive cruise control function is recommended for the autonomous vehicle.

[0037] In this embodiment, when recommending the automatic driving function, firstly determine the current automatic driving vehicle road type and map type, and then determine the accuracy of the navigation map carried by the automatic driving vehicle itself. If the road type is public road and the map type is high-precision map, if the automatic driving vehicle is in the highway in the public road, recommend the automatic driving vehicle with the highway navigation auxiliary driving function, so that the vehicle is more suitable for driving on the highway. If the automatic driving vehicle is in the urban road in the public road, recommend the automatic driving vehicle with the urban road navigation auxiliary driving function; if the automatic driving vehicle is in other roads in the public road, recommend the automatic driving vehicle with the lane centering control function under the condition of identifying the existence of lane line, and recommend the automatic driving vehicle with the adaptive cruise control function under the condition of non-existence of lane line.

[0038] Optionally, if the automatic driving vehicle is in the parking road in the public road, recommend the automatic driving vehicle with the automatic parking auxiliary function, including: under the condition that the automatic driving vehicle monitors the parking road, the speed of the vehicle is less than the preset threshold, and the existence of the parking space and the automatic driving vehicle has been slowed down, determine that the automatic driving vehicle is in the driving environment of the parking road.

[0039] In this optional embodiment, in the driving environment of the parking road, because when parking, there is a corresponding parking road with a free parking space, in addition, the speed of the vehicle is decelerating, and the speed of the automatic driving vehicle is less than the preset threshold, indicating that the vehicle is driving at low speed at this time, ensuring the safety and stability of the vehicle when parking.

[0040] Specifically, when determining that the automatic driving vehicle performs the automatic parking auxiliary function, in order to ensure the safety when parking, the driver's step on the brake pedal can be monitored to further determine the safety of parking. The preset threshold of the vehicle speed can be selected as 20KM / H. This value can be reasonably adjusted according to the actual driving scene or requirements, and the present application does not make specific limitation.

[0041] Optionally, according to the road type and the map type, the corresponding automatic driving function is recommended for the automatic driving vehicle, including: under the condition that the road type is public road and the map type is non-precision map, if the automatic driving vehicle is in the parking road in the public road, recommend the automatic driving vehicle with the automatic parking auxiliary function; if the automatic driving vehicle is in other roads in the public road, recommend the automatic driving vehicle with the lane centering control function under the condition of identifying the existence of lane line, and recommend the automatic driving vehicle with the adaptive cruise control function under the condition of non-existence of lane line.

[0042] In the optional embodiment, after the vehicle enters the parking road, the automatic parking assistance function is recommended for the autonomous vehicle; when the autonomous vehicle is located on other roads except the expressway, the urban road and the parking road, the lane centering control function and the adaptive cruise control function are respectively recommended for the autonomous vehicle according to whether there is lane line.

[0043] Optionally, according to the road type and the map type, the corresponding autonomous driving function is recommended for the autonomous vehicle, including: under the condition that the road type is the ground road in the internal road and the map type is the LPNP map, the memory parking pilot assisted driving function is recommended for the autonomous vehicle; under the condition that the road type is the ground road in the internal road and the map type is the non-LPNP map, if the parking space is recognized, the automatic parking assistance function is recommended for the autonomous vehicle; if the parking space is not recognized but the lane line is recognized, the lane centering control function is recommended for the autonomous vehicle; if the parking space is not recognized and the lane line is not recognized, the adaptive cruise control function is recommended for the autonomous vehicle.

[0044] In the optional embodiment, under the condition that the road type is the ground road in the internal road, for example, the ground parking lot road, if the autonomous vehicle is equipped with the LPNP map, the memory parking pilot assisted driving function is recommended for the autonomous vehicle; if the vehicle is not equipped with the LPNP map, but the autonomous vehicle recognizes the parking space at this time, the automatic parking assistance function is recommended for the autonomous vehicle; if the vehicle does not recognize the parking space at this time, but recognizes the lane line, the lane centering control function is recommended for the autonomous vehicle, and the free parking space is searched during the driving of the vehicle; if the vehicle does not recognize the parking space at this time, and does not recognize the lane line, the adaptive cruise control function is recommended for the autonomous vehicle, and the free parking space is searched during the driving of the vehicle.

[0045] Optionally, according to the road type and the map type, the corresponding autonomous driving function is recommended for the autonomous vehicle, including: under the condition that the road type is the parking building road in the internal road, if the map type is the PNP map, the parking pilot assisted driving function is recommended for the autonomous vehicle; if the map type is the LPNP map, the memory parking pilot assisted driving function is recommended for the autonomous vehicle; if the map type is the non-map, under the condition that the parking space is recognized, the automatic parking assistance function is recommended for the autonomous vehicle, and under the condition that the parking space is not recognized, the LPNP learning is performed.

[0046] In the optional embodiment, for the parking building road whose road type is internal road, if the autonomous vehicle is only equipped with the PNP map, the autonomous vehicle is recommended with the parking pilot assisted driving function, in which the autonomous parking assistance function of the autonomous vehicle is used to park in a random parking space. If the autonomous vehicle is equipped with both the PNP map and the LPNP map, the autonomous vehicle is recommended with the parking pilot assisted driving function, in which the parking space information in the LPNP map is mapped to the PNP map, and the autonomous parking assistance function of the autonomous vehicle is used to park in a random parking space. If the autonomous vehicle is only equipped with the LPNP map, the autonomous vehicle is recommended with the memory parking pilot assisted driving function, and the autonomous parking assistance function of the autonomous vehicle is used to park in a random parking space. If the autonomous vehicle is not equipped with the parking building map, if a parking space is successfully identified, the autonomous vehicle is recommended with the autonomous parking assistance function; if no parking space is identified, the LPNP learning is performed.

[0047] Optionally, according to the road type and the map type, the corresponding autonomous driving function is recommended for the autonomous vehicle, including: under the condition that the road type is an underground road in an internal road, if the map type is that there is a PNP map, the autonomous vehicle is recommended with the parking pilot assisted driving function; if the map type is that there is only a LPNP map, the autonomous vehicle is recommended with the memory parking pilot assisted driving function; if the map type is that there is no map, under the condition that a parking space is identified, the autonomous vehicle is recommended with the autonomous parking assistance function, and under the condition that no parking space is identified, the LPNP learning is performed.

[0048] In the optional embodiment, for the parking building road whose road type is internal road, if the autonomous vehicle is only equipped with the PNP map, the autonomous vehicle is recommended with the parking pilot assisted driving function, in which the autonomous parking assistance function of the autonomous vehicle is used to park in a random parking space. If the autonomous vehicle is equipped with both the PNP map and the LPNP map, the autonomous vehicle is recommended with the parking pilot assisted driving function, in which the parking space information in the LPNP map is mapped to the PNP map, and the autonomous parking assistance function of the autonomous vehicle is used to park in a random parking space. If the autonomous vehicle is only equipped with the LPNP map, the autonomous vehicle is recommended with the memory parking pilot assisted driving function, and the autonomous parking assistance function of the autonomous vehicle is used to park in a random parking space. If the autonomous vehicle is not equipped with the parking building map, if a parking space is successfully identified, the autonomous vehicle is recommended with the autonomous parking assistance function; if no parking space is identified, the LPNP learning is performed.

[0049] The adaptive recommendation method for autonomous driving functions in this application provides the most suitable autonomous driving functions for the autonomous vehicle under the current driving environment by perceiving the driving environment and judging the road type of the driving position, ensuring the safety of the autonomous driving process, recommending driving functions in a fully automatic manner, and improving the driver's driving experience.

[0050] Figure 2 A schematic diagram of one embodiment of the intelligent driving function adaptive recommendation system of this application is shown.

[0051] exist Figure 2 In the implementation of this application, the intelligent driving function adaptive recommendation system includes: a perception module 201, which acquires the road type and driving environment of the location of the autonomous vehicle; a map confirmation module 202, which confirms the map type used for navigation on the autonomous vehicle itself; and a function recommendation module 203, which recommends corresponding autonomous driving functions for the autonomous vehicle based on the road type, driving environment, and map type, wherein the road type includes public roads and internal roads, the driving environment includes highways and urban roads, and the map type includes high-precision maps and non-high-precision maps.

[0052] Optionally, in the perception module 201, the location of the autonomous vehicle is determined by the positioning unit carried by the autonomous vehicle; based on the location and the environmental information obtained by the perception unit carried by the autonomous vehicle, the road type and driving environment are determined.

[0053] Optionally, in the function recommendation module 203, under the conditions that the road type is a public road and the map type is a high-precision map, if the autonomous vehicle is on a highway within a public road, then the highway navigation assistance function is recommended for the autonomous vehicle; if the autonomous vehicle is on an urban road within a public road, then the urban road navigation assistance function is recommended for the autonomous vehicle; if the autonomous vehicle is on a parking road within a public road, then the automatic parking assistance function is recommended for the autonomous vehicle; if the autonomous vehicle is on other roads within a public road, then if lane lines are identified, the lane centering control function is recommended for the autonomous vehicle, and if lane lines are not identified, the adaptive cruise control function is recommended for the autonomous vehicle.

[0054] Optionally, in the function recommendation module 203, when the autonomous vehicle detects a parking space road, its own speed is less than a preset threshold, it recognizes the existence of a parking space, and the autonomous vehicle has slowed down, it determines that the autonomous vehicle is in the driving environment of the parking road.

[0055] Optionally, in the function recommendation module 203, under the condition that the road type is a public road and the map type is a non-precision map, if the autonomous vehicle is in a parking road in the public road, the autonomous vehicle is recommended an automatic parking assistance function; if the autonomous vehicle is in other road in the public road, under the condition that a lane line is identified, the autonomous vehicle is recommended a lane centering control function, and under the condition that no lane line is identified, the autonomous vehicle is recommended an adaptive cruise control function.

[0056] Optionally, in the function recommendation module 203, under the condition that the road type is a ground road in an internal road and the map type is an LPNP map, the autonomous vehicle is recommended a memory parking pilot assisted driving function; under the condition that the road type is a ground road in an internal road and the map type is a non-LPNP map, if a parking space is identified, the autonomous vehicle is recommended an automatic parking assistance function; if no parking space is identified but a lane line is identified, the autonomous vehicle is recommended a lane centering control function; if no parking space is identified and no lane line is identified, the autonomous vehicle is recommended an adaptive cruise control function.

[0057] Optionally, further comprising: if no parking space is identified, learning LPNP of the autonomous vehicle is performed.

[0058] Optionally, in the function recommendation module 203, under the condition that the road type is a parking building road in an internal road, if the map type is an existing PNP map, the autonomous vehicle is recommended a parking pilot assisted driving function; if the map type is only an existing LPNP map, the autonomous vehicle is recommended a memory parking pilot assisted driving function; if the map type is a non-existing map, under the condition that a parking space is identified, the autonomous vehicle is recommended an automatic parking assistance function, and under the condition that no parking space is identified, learning of LPNP is performed.

[0059] Optionally, in the function recommendation module 203, under the condition that the road type is an underground road in an internal road, if the map type is an existing PNP map, the autonomous vehicle is recommended a parking pilot assisted driving function; if the map type is only an existing LPNP map, the autonomous vehicle is recommended a memory parking pilot assisted driving function; if the map type is a non-existing map, under the condition that a parking space is identified, the autonomous vehicle is recommended an automatic parking assistance function, and under the condition that no parking space is identified, learning of LPNP is performed.

[0060] In an embodiment of the present application, a computer readable storage medium stores computer instructions, wherein the computer instructions are operated to perform the deep learning based speech coding method described in any embodiment. Wherein the storage medium can be directly in hardware, in a software module executed by a processor, or in a combination of both.

[0061] The software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium.

[0062] The processor can be a central processing unit (CPU), a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The general purpose processor can be a microprocessor, but in the alternative, the processor can be any conventional processor, controller, microcontroller, or state machine. The processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. The storage medium can be embodied in a computer program product that can be traded from one user to another. The storage medium can be, for example, but is not limited to, one or more types of removable nonvolatile memory such as

[0063] In an embodiment of the present disclosure, a computer device includes a processor and a memory, and the memory stores computer instructions, and the processor operates the computer instructions to perform the deep learning based speech coding method described in any of the embodiments.

[0064] In the embodiments provided by the present disclosure, it should be understood that the disclosed apparatus can be implemented in other manners. For example, the described apparatus embodiments are merely illustrative. For example, the division of the units is only a logical function division. There can be another division manner for the actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the among different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0065] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e. may be located in one place, or may also be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0066] The above is only an embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structural transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied to other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. An adaptive recommendation method for intelligent driving functions, characterized in that, include: Obtain the road type where the autonomous vehicle is located; Confirm the type of map used for navigation that is installed on the autonomous vehicle itself; Based on the road type and the map type, recommend corresponding autonomous driving functions for the autonomous vehicle, wherein the road type includes public roads and internal roads, and the map type includes high-precision maps and non-high-precision maps; The step of recommending corresponding autonomous driving functions for the autonomous vehicle based on the road type and the map type includes: under the condition that the road type is a public road and the map type is a high-precision map, If the autonomous vehicle is on a highway in a public road, then the highway navigation assistance function is recommended for the autonomous vehicle. If the autonomous vehicle is on a city road within a public road, then the city road navigation assistance function is recommended for the autonomous vehicle. If the autonomous vehicle is in a parking lane on a public road, then an automatic parking assistance function is recommended for the autonomous vehicle. If the autonomous vehicle is on other roads in the public road, then if lane lines are identified, lane centering control function is recommended for the autonomous vehicle; if lane lines are not identified, adaptive cruise control function is recommended for the autonomous vehicle. If the road type is a parking garage road within an internal road, and the map type is a PNP map, then a parking navigation assistance function is recommended for the autonomous vehicle. If the map type is an LPNP map, then the memory parking navigation assist function is recommended for the autonomous vehicle. If the map type is non-existent, and a parking space is identified, an automatic parking assist function is recommended for the autonomous vehicle; if no parking space is identified, LPNP learning is performed.

2. The intelligent driving function adaptive recommendation method according to claim 1, characterized in that, The road types for obtaining the location of the autonomous vehicle include: The location of the autonomous vehicle is determined by the positioning unit carried by the autonomous vehicle. The road type is determined based on the location and the environmental information obtained by the perception unit on the autonomous vehicle.

3. The intelligent driving function adaptive recommendation method according to claim 1, characterized in that, If the autonomous vehicle is located on a parking lane in a public road, then an automatic parking assistance function is recommended for the autonomous vehicle, including: When the autonomous vehicle detects a parking space and its speed is less than a preset threshold, and the autonomous vehicle has already decelerated after recognizing the existence of a parking space, it is determined that the autonomous vehicle is in the driving environment of the parking road.

4. The intelligent driving function adaptive recommendation method according to claim 1, characterized in that, The step of recommending corresponding autonomous driving functions for the autonomous vehicle based on the road type and the map type includes: Given that the road type is a public road and the map type is a non-high-precision map, If the autonomous vehicle is in a parking lane on a public road, then an automatic parking assistance function is recommended for the autonomous vehicle. If the autonomous vehicle is on another road within a public road, lane centering control is recommended for the autonomous vehicle if lane lines are identified, and adaptive cruise control is recommended for the autonomous vehicle if lane lines are not identified.

5. The intelligent driving function adaptive recommendation method according to claim 1, characterized in that, The step of recommending corresponding autonomous driving functions for the autonomous vehicle based on the road type and the map type includes: Under the condition that the road type is a ground road within an internal road and the map type is an LPNP map, a memory parking navigation assistance function is recommended for the autonomous driving vehicle. If the road type is an internal road and the map type is a non-LPNP map, then if a parking space is identified, the automatic parking assistance function is recommended for the autonomous vehicle. If no parking space is detected, but lane lines are detected, then lane centering control function is recommended for the autonomous vehicle. If no parking space or lane line is detected, then adaptive cruise control is recommended for the autonomous vehicle.

6. The intelligent driving function adaptive recommendation method according to claim 1, characterized in that, The step of recommending corresponding autonomous driving functions for the autonomous vehicle based on the road type and the map type includes: If the road type is an underground road within an internal road, and the map type is a PNP map, then a parking navigation assistance function is recommended for the autonomous vehicle. If the map type is an LPNP map, then the memory parking navigation assist function is recommended for the autonomous vehicle. If the map type is non-existent, and a parking space is identified, an automatic parking assist function is recommended for the autonomous vehicle; if no parking space is identified, LPNP learning is performed.

7. An intelligent driving function adaptive recommendation system, characterized in that, include: The perception module obtains the road type at the location of the autonomous vehicle; The map confirmation module confirms the type of map used for navigation that is installed on the autonomous vehicle itself; The function recommendation module recommends corresponding autonomous driving functions for the autonomous vehicle based on the road type and the map type, wherein the road type includes public roads and internal roads, and the map type includes high-precision maps and non-high-precision maps; The step of recommending corresponding autonomous driving functions for the autonomous vehicle based on the road type and the map type includes: under the condition that the road type is a public road and the map type is a high-precision map, If the autonomous vehicle is on a highway in a public road, then the highway navigation assistance function is recommended for the autonomous vehicle. If the autonomous vehicle is on a city road within a public road, then the city road navigation assistance function is recommended for the autonomous vehicle. If the autonomous vehicle is in a parking lane on a public road, then an automatic parking assistance function is recommended for the autonomous vehicle. If the autonomous vehicle is on other roads in the public road, then if lane lines are identified, lane centering control function is recommended for the autonomous vehicle; if lane lines are not identified, adaptive cruise control function is recommended for the autonomous vehicle. If the road type is a parking garage road within an internal road, and the map type is a PNP map, then a parking navigation assistance function is recommended for the autonomous vehicle. If the map type is an LPNP map, then the memory parking navigation assist function is recommended for the autonomous vehicle. If the map type is non-existent, and a parking space is identified, an automatic parking assist function is recommended for the autonomous vehicle; if no parking space is identified, LPNP learning is performed.

8. A computer-readable storage medium storing a computer program, wherein the computer program is operated to perform the intelligent driving function adaptive recommendation method according to any one of claims 1-6.

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