Human-machine co-driving control method, device, equipment and computer-readable storage medium

Abstract

The present invention discloses a human-machine co-driving control method, device, equipment and computer-readable storage medium. The method comprises: dividing the planned route to be driven into M driving sections, wherein M is a positive integer; when the distance of the vehicle from entering any driving section is less than a first preset distance, outputting prompt information of the type of any driving section; when the vehicle is in any driving section, detecting whether the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function operation conditions; if the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function operation conditions, controlling the vehicle to run the target function, and outputting prompt information that the target function is running. Through the present invention, the prompt of the function state node can be effectively, reasonably and timely performed.

Description

Technical Field

[0001] The present application relates to the field of vehicle assisted driving, and specifically to a human-machine co-driving control method, device, equipment and computer-readable storage medium. Background Art

[0002] When the car enters the intelligent cruise mode, the driver and the driving system (i.e., human and machine) are in a state of mutual cooperation, task handover, and alternating driving operations. This is also the normalization stage of intelligent driving for a period of time, that is, human-machine co-driving. Different from the conventional lane-level longitudinal and lateral intelligent cruise functions, such as Adaptive Cruise Control (ACC), Lane Centering Control (LCC), Intelligent Cruise Assist (ICA), the driver can start assisted driving after setting the navigation route and entering the available road section of NOA. In the process of going from point A to point B, multiple functions such as automatic on- and off-ramp, self-overtaking, self-lane changing, and adaptive cruise can be realized. In comparison, the NOA function appears to be more intelligent. In actual application, the above-mentioned major functions have certain differences in the functional operation domain, operating conditions, human-computer interaction, and the display and prompt strategies of the user interface.

[0003] Therefore, how to effectively, reasonably and timely provide prompts for functional status nodes, and at the same time ensure driving safety while increasing the driver's understanding, control and experience of the functions is a technical problem that urgently needs to be solved. Summary of the invention

[0004] The present application provides a human-machine co-driving control method, device, equipment and computer-readable storage medium, which can solve the technical problem existing in the prior art that functional status nodes cannot be prompted effectively, reasonably and timely.

[0005] In a first aspect, an embodiment of the present application provides a human-machine co-driving control method, the human-machine co-driving control method comprising:

[0006] Divide the planned route to be driven into M driving sections, where M is a positive integer;

[0007] When the distance from the vehicle to any driving section is less than a first preset distance, outputting prompt information of the type of any driving section;

[0008] When the vehicle is in any of the driving sections, detecting whether the target function state and the road conditions within a second preset distance range in front of the vehicle meet the target function operation conditions;

[0009] If the target function state and the road condition within a second preset distance range in front of the vehicle meet the target function operation conditions, the vehicle is controlled to operate the target function, and a prompt message indicating that the target function is operating is output.

[0010] In combination with the first aspect, in one implementation, before the step of dividing the planned route to be traveled into M travel sections, the method further includes:

[0011] According to the starting point and end point parameters, N planned routes are obtained, where N is a positive integer;

[0012] For each planned route, calculate the length ratio of all target road sections included in the planned route, where the target road sections are in the area covered by the high-precision map;

[0013] The planned route with the largest length ratio is selected from all planned routes, and the planned route with the largest length ratio is determined as the planned route to be driven.

[0014] In combination with the first aspect, in one implementation, after the step of calculating, for each planned route, the length ratio of all target road sections included in the planned route, wherein the target road section is in the high-precision map coverage area, the method further includes:

[0015] Select the planned route with the largest length ratio from all planned routes;

[0016] Check whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index;

[0017] If the congestion index of the planned route with the largest length ratio is less than the preset congestion index, the planned route with the largest length ratio is determined as the planned route to be driven;

[0018] If the congestion index of the planned route with the largest length ratio is not less than the preset congestion index, the planned route with the largest length ratio among the remaining planned routes is used as the planned route with the largest length ratio, and the step of detecting whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index is returned.

[0019] In combination with the first aspect, in one implementation, the step of dividing the planned route to be traveled into M travel sections includes:

[0020] Based on the target section, the planned route to be driven is divided into M driving sections, where a target section is a first-category driving section, a non-target section is a second-category driving section, and M is a positive integer. The non-target section is not in the high-precision map coverage area.

[0021] In combination with the first aspect, in one implementation, when any driving section is a first-category driving section, the target function operation condition is:

[0022] The status of the automatic assisted navigation driving function is normal, the lane line clarity within the second preset distance range in front of the vehicle is greater than the preset clarity, and the congestion index within the second preset distance range in front of the vehicle is less than the preset congestion index.

[0023] In combination with the first aspect, in one implementation, when any driving section is a second-category driving section, the target function operation condition is:

[0024] The adaptive cruise control function state is in a normal state, and the driving characteristic data of other vehicles within a second preset distance range in front of the vehicle are preset driving characteristics.

[0025] In combination with the first aspect, in one implementation, when any driving section is a second-category driving section, the target function operation condition is:

[0026] The smart cruise assist function status and the adaptive cruise control function status are both in normal status, the lane line clarity within the second preset distance range in front of the vehicle is greater than the preset clarity, and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are the preset driving characteristics.

[0027] In a second aspect, an embodiment of the present application provides a human-machine co-driving control device, the human-machine co-driving control device comprising:

[0028] A division module, used to divide the planned route to be driven into M driving sections, where M is a positive integer;

[0029] An output module, configured to output prompt information of the type of any driving section when the distance of the vehicle from entering any driving section is less than a first preset distance;

[0030] a detection module, used for detecting whether the target function state and the road condition within a second preset distance range in front of the vehicle meet the target function operation conditions when the vehicle is in any of the driving sections;

[0031] The output module is also used to control the vehicle to run the target function if the target function state and the road conditions within a second preset distance range in front of the vehicle meet the target function operation conditions, and output a prompt message that the target function is running.

[0032] In a third aspect, an embodiment of the present application provides a human-machine co-driving control device, which includes a processor, a memory, and a human-machine co-driving control program stored in the memory and executable by the processor, wherein when the human-machine co-driving control program is executed by the processor, the steps of the human-machine co-driving control method described above are implemented.

[0033] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a human-machine co-driving control program is stored. When the human-machine co-driving control program is executed by a processor, the steps of the human-machine co-driving control method as described above are implemented.

[0034] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0035] By dividing the planned route to be driven into M driving sections, where M is a positive integer, it is convenient for the vehicle controller to match the optimal intelligent driving function for the vehicle for any driving section, which brings great convenience to the user's travel; when the distance between the vehicle and entering any driving section is less than a first preset distance, the prompt information of the type of any driving section is output; when the vehicle is still a certain distance away from entering any driving section, the user is reminded in advance of the type of the driving section that the vehicle is about to enter, so as to let the user understand the current environmental conditions and increase the sense of trust; when the vehicle is in any driving section, the target function state and the road conditions within the second preset distance range in front of the vehicle are detected to see whether they meet the target function operation conditions; when the vehicle is in any driving section, the target function state and the vehicle are always detected. The target function will be run only if the road conditions within the second preset distance range in front of the vehicle meet the target function running conditions, which effectively ensures the user's driving safety and avoids traffic accidents; if the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function running conditions, the vehicle controller will control the vehicle to run the target function and output prompt information that the target function is running. If the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function running conditions, the vehicle controller will control the vehicle to run the target function and always output prompt information that can represent that the target function is running, so that the user can always know that the target function is running. At the same time, if the target function exits due to an emergency, the user can also find it in time, thereby avoiding major traffic accidents. It solves the technical problems in related technologies that the function status nodes cannot be effectively, reasonably and timely prompted, and the technical problems of ensuring driving safety while increasing the driver's understanding, control and experience of the function. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flowchart of a human-machine co-driving control method for the present application;

[0037] Figure 2 A detailed flow chart of determining target sections and non-target sections for the human-machine co-driving control method of this application;

[0038] Figure 3 For this application Figure 1 A detailed flow chart of determining the planned route to be driven;

[0039] Figure 4 This is a functional module diagram of the human-machine co-driving control device of the present application;

[0040] Figure 5 This is a schematic diagram of the hardware structure of the human-machine co-driving control device involved in the embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0042] First, some technical terms in the present application are explained to facilitate those skilled in the art to understand the present application.

[0043] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0044] In a first aspect, an embodiment of the present application provides a human-machine co-driving control method.

[0045] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of the human-machine co-driving control method applied for.

[0046] like Figure 1 As shown, the human-machine co-driving control method includes:

[0047] Step S10, dividing the planned route to be traveled into M travel sections, where M is a positive integer;

[0048] In this embodiment, before the vehicle sets off, the vehicle controller obtains the user's planned route to be driven from the on-board navigation software, and divides the planned route to be driven into M driving sections, where M is a positive integer. In this way, it is beneficial for the vehicle controller to match the vehicle with the optimal intelligent driving function according to the actual situation of any driving section, which brings great convenience to the user's travel. For example: M is 3, and the planned route to be driven is divided into 3 driving sections. It should be noted that the numerical values ​​listed in this embodiment, such as "3", are only used to illustrate the content of this embodiment and are not specific limiting values.

[0049] Furthermore, in one embodiment, before the step of dividing the planned route to be traveled into M travel sections, the method further includes:

[0050] According to the starting point and end point parameters, N planned routes are obtained, where N is a positive integer; for each planned route, the length ratio of all target sections included in the planned route is calculated, where the target section is in the high-precision map coverage area;

[0051] In this embodiment, before the vehicle departs, the user can manually or by voice input and determine the starting point and end point parameters of the trip on the in-vehicle navigation software, and obtain N planned routes based on the input starting point and end point parameters in combination with the map data information on the in-vehicle navigation software, where N is a positive integer; for each planned route, the high-precision map data is matched with the traditional map data to obtain the target road sections in the planned route that are in the high-precision map coverage area and the non-target road sections in the planned route that are not in the high-precision map coverage area, and further calculate the length ratio of all target road sections included in the planned route. For example: refer to Figure 2 , Figure 2 A detailed flow chart of determining target sections and non-target sections for the human-machine co-driving control method of this application. Figure 2 As shown, A and E represent the starting point and the end point respectively, section BC and section DE represent the sections in the high-precision map coverage area, and then section AB and section CD represent the sections not in the high-precision map coverage area. Then, sections BC and DE are taken as target sections, and sections AB and section CD are taken as non-target sections. The length proportion of all target sections (i.e., section BC + section DE) contained in the planned route in the planned route (i.e., section AE) is calculated.

[0052] The planned route with the largest length ratio is selected from all planned routes, and the planned route with the largest length ratio is determined as the planned route to be driven.

[0053] In this embodiment, the automatic assisted navigation driving function meets the driving needs of users in multiple scenarios such as highways, urban elevated ring roads, and urban expressways, and reduces the long-term driving burden of users to a certain extent, relieves driving fatigue, improves the driving experience of users, makes driving safer, more efficient, and more comfortable, and improves driving safety. Therefore, during the user's travel, most people will choose the automatic assisted navigation driving function to drive. However, the automatic assisted navigation driving function needs to be combined with high-precision map data to operate, and the target road section is in the high-precision map coverage area. Therefore, it is necessary to select the planned route with the largest length of all target road sections included in the planned route from all the planned routes, and determine the planned route with the largest length as the planned route to be driven. For example: there are 3 planned routes, the length of the first planned route accounts for 50%, the length of the second planned route accounts for 40%, and the length of the third planned route accounts for 30%. The first planned route with a length of 50% of the three planned routes is determined as the planned route to be driven. It should be noted that the values ​​listed in this embodiment, such as "3", "50%", "40%", and "30%", are only used to illustrate the content of this embodiment, and are not specific limiting values.

[0054] In this embodiment, N planned routes are obtained according to the starting point and end point parameters, where N is a positive integer; for each planned route, the length ratio of all target sections included in the planned route is calculated, where the target section is in the high-precision map coverage area; the planned route with the largest length ratio is selected from all planned routes, and the planned route with the largest length ratio is determined as the planned route to be driven. The technical problem of how to select a better planned route to be driven for users in the related art to provide users with a better driving experience is solved.

[0055] Further, in one embodiment, referring to Figure 3 , Figure 3 For this application Figure 1 A detailed flow chart of determining the planned route to be driven. Figure 3 As shown, after the step of calculating the length ratio of all target sections included in the planned route in the planned route for each planned route, wherein the target section is in the high-precision map coverage area, the method further includes:

[0056] Step S01, selecting a planned route with the largest length ratio from all planned routes;

[0057] Step S02, detecting whether the congestion index of the planned route with the largest length ratio is less than a preset congestion index;

[0058] In this embodiment, determining the planned route to be driven not only needs to consider the length ratio of all target road sections included in the planned route in the planned route, but also needs to consider the congestion index of the planned route. Therefore, after selecting the planned route with the largest length ratio from all the planned routes, it is also necessary to detect whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index. When the congestion index of the planned route with the largest length ratio is less than the preset congestion index, it means that there is no congestion on the road of the planned route with the largest length ratio, and thus it meets the user's travel requirements, and the planned route with the largest length ratio is determined as the planned route to be driven; when the congestion index of the planned route with the largest length ratio is not less than the preset congestion index, it means that there is congestion on the road of the planned route with the largest length ratio, and thus it does not meet the user's travel requirements, and it is necessary to reselect a planned route as the planned route to be driven.

[0059] Step S03, if the congestion index of the planned route with the largest length ratio is less than the preset congestion index, the planned route with the largest length ratio is determined as the planned route to be driven;

[0060] In this embodiment, if the congestion index of the planned route with the largest length ratio is less than the preset congestion index, it means that there is no congestion on the road of the planned route with the largest length ratio, and thus it meets the user's travel requirements, and the planned route with the largest length ratio is determined as the planned route to be driven. For example: the congestion index value range of the map software and the traffic control is mostly 0~>10, which is divided into five levels: among them, 0~2, 2~4, 4~6, 6~8, 8~>10 correspond to the five levels of "smooth", "basic smooth", "mild congestion", "moderate congestion", and "severe congestion", respectively. The higher the congestion index value, the more serious the traffic congestion. The preset congestion index is 3, and the congestion index of the planned route with the largest length ratio is 0. At this time, the congestion index of the planned route with the largest length ratio is less than the preset congestion index, which means that the planned route with the largest length ratio is currently "smooth", which meets the user's travel requirements. Therefore, the planned route with the largest length ratio is determined as the planned route to be driven. It should be noted that the numerical values ​​listed in this embodiment, such as "0~>10", "0~2", "2~4", "4~6", "6~8", "8~>10", "3" and "0", are only used to illustrate the content of this embodiment and are not specific limiting values.

[0061] Step S04, if the congestion index of the planned route with the largest length ratio is not less than the preset congestion index, the planned route with the largest length ratio among the remaining planned routes is used as the planned route with the largest length ratio, and the process returns to the step of detecting whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index.

[0062] In this embodiment, if the congestion index of the planned route with the largest length ratio is not less than the preset congestion index, for example: the preset congestion index is 3, and the congestion index of the planned route with the largest length ratio is 8, then the congestion index of the planned route with the largest length ratio is greater than the preset congestion index, indicating that the road of the planned route with the largest length ratio is congested, and therefore does not meet the user's travel requirements, and it is necessary to reselect a planned route as the planned route to be driven. Therefore, it is necessary to select another planned route with the largest length ratio from the remaining planned routes for detection, and the planned route with the largest length ratio in the remaining planned routes is used as the planned route with the largest length ratio, and return to the step of executing the detection of whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index. It should be noted that the numerical values ​​listed in this embodiment, such as "3" and "8", are only used to illustrate the content of this embodiment and are not specific limiting values.

[0063] In this embodiment, the planned route with the largest length ratio is selected from all planned routes; the congestion index of the planned route with the largest length ratio is detected to be less than the preset congestion index; if the congestion index of the planned route with the largest length ratio is less than the preset congestion index, the planned route with the largest length ratio is determined as the planned route to be driven; if the congestion index of the planned route with the largest length ratio is not less than the preset congestion index, the planned route with the largest length ratio among the remaining planned routes is used as the planned route with the largest length ratio, and the step of detecting whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index is returned to execute. The technical problem of how to select a better planned route to be driven for the user in the related art to provide the user with a better driving experience is solved.

[0064] Furthermore, in one embodiment, the step of dividing the planned route to be traveled into M travel sections includes:

[0065] Based on the target section, the planned route to be driven is divided into M driving sections, where a target section is a first-class driving section, a non-target section is a second-class driving section, and M is a positive integer. The non-target route is not in the high-precision map coverage area.

[0066] In this embodiment, the planned route to be driven is divided into M driving sections based on the target section, where a target section is a first-class driving section, a non-target section is a second-class driving section, and M is a positive integer. The non-target route is not in the high-precision map coverage area. For example: Please continue to refer to Figure 2 ,like Figure 2As shown, A and E represent the starting point and the end point respectively, and sections BC and DE are target sections and are in the area covered by the high-precision map; and sections AB and CD are non-target sections and are not in the area covered by the high-precision map. Therefore, based on the target sections, the planned route to be driven is divided into four driving sections, and a target section is taken as a first-class driving section (i.e., section BC or section DE is both a target section and a first-class driving section of the planned route to be driven), and a non-target section is taken as a second-class driving section (i.e., section AB or section CD is both a non-target section and a second-class driving section of the planned route to be driven). It should be noted that the numerical values ​​listed in this embodiment, such as "4", are only used to illustrate the content of this embodiment and are not specific limiting values.

[0067] In this embodiment, the planned route to be driven is divided into M driving sections based on the target section, wherein one target section is a first-class driving section, one non-target section is a second-class driving section, and M is a positive integer, and the non-target route is not in the high-precision map coverage area. This solves the technical problem of how to divide the driving planned route into driving sections in the related art.

[0068] Step S20, when the distance from the vehicle to any driving section is less than a first preset distance, outputting prompt information of the type of any driving section;

[0069] In this embodiment, when the distance of the vehicle from entering any driving section is less than the first preset distance, it is necessary to promptly output prompt information of the type of any driving section to the driver to remind the user of the type of driving section the vehicle is about to enter, so as to let the user understand the current environmental conditions and increase the sense of trust. For example: Please continue to refer to Figure 2 ,like Figure 2 As shown, A and E represent the starting point and the end point respectively, sections BC and DE are target sections, sections AB and CD are non-target sections, and the first preset distance is 100 meters. When the distance between the vehicle and section BC is less than 100 meters, the user needs to be prompted by voice or text, such as "You will enter a high-precision map section 100 meters ahead, please pay attention!", in order to let the user understand the current environmental conditions and increase their sense of trust.

[0070] Step S30, when the vehicle is in any of the driving sections, detecting whether the target function state and the road condition within a second preset distance range in front of the vehicle meet the target function operation conditions;

[0071] In this embodiment, when the vehicle is in any driving section, it is necessary to detect whether the target state and the road conditions within the second preset distance range in front of the vehicle meet the target function operation conditions. The target function state and the road conditions within the second preset distance range in front of the vehicle are constantly monitored, so as to determine in advance whether the vehicle can run the target function, so as to ensure the driving safety of the user and avoid traffic accidents. If the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function operation conditions, it means that the vehicle can run the target function within the second preset distance range in front; if the target function state and the road conditions within the second preset distance range in front of the vehicle do not meet the target function operation conditions, it means that the vehicle cannot run the target function within the second preset distance range in front. Among them, any driving section includes driving sections in the high-precision map coverage area and driving sections not in the high-precision map coverage area, and the target functions include automatic assisted navigation driving function, adaptive cruise control function state, and intelligent cruise assist function + adaptive cruise control function.

[0072] Furthermore, in one embodiment, when any driving section is a first-category driving section, the target function operation condition is:

[0073] The status of the automatic assisted navigation driving function is normal, the lane line clarity within the second preset distance range in front of the vehicle is greater than the preset clarity, and the congestion index within the second preset distance range in front of the vehicle is less than the preset congestion index.

[0074] In this embodiment, when any driving section is a first-class driving section, the operating conditions of the automatic assisted navigation driving function are obtained from the local database (Note: the first-class driving section is in the high-precision map coverage area, and the automatic assisted navigation driving function is implemented based on high-precision map data, so it can only be operated in the high-precision map coverage area). Among them, the operating conditions of the automatic assisted navigation driving function are that the state of the automatic assisted navigation driving function is normal (Note: the normal state is when the associated systems and components of the automatic assisted navigation driving function are normal and fault-free, otherwise it is an abnormal state), the clarity of the lane line within the second preset distance range in front of the vehicle is greater than the preset clarity, and the congestion index within the second preset distance range in front of the vehicle is less than the preset congestion index. In this way, by constantly monitoring the state of the vehicle's automatic assisted navigation driving function and the road conditions within the second preset distance range in front of the vehicle, it is possible to determine in advance whether the vehicle can run the automatic assisted navigation driving function, while ensuring the user's driving safety and avoiding traffic accidents. For example: Please continue to refer to Figure 2 ,like Figure 2As shown, A and E represent the starting point and the end point respectively, section BC and section DE are target sections, section AB and section CD are non-target sections, any driving section is a first-class driving section, and when a first-class driving section is section BC, at this time, the vehicle is in section BC, the state of the vehicle's automatic assisted navigation driving function is normal, the clarity of the lane line within 50m in front of the vehicle is 100%, which is greater than the preset clarity of 95%, and the congestion index within 50m in front of the vehicle is 0, which is less than the preset congestion index 3. Therefore, it is determined that the operating conditions of the automatic assisted navigation driving function are met. It should be noted that the values ​​listed in this embodiment, such as "section BC", "50m", "100%", "95%", "0" and "3", are only used to illustrate the content of this embodiment and are not specific limiting values.

[0075] Furthermore, in one embodiment, when any driving section is a second-category driving section, the target function operation condition is:

[0076] The adaptive cruise control function state is in a normal state, and the driving characteristic data of other vehicles within a second preset distance range in front of the vehicle are preset driving characteristics.

[0077] In this embodiment, when any driving section is a second-category driving section, the operating conditions of the adaptive cruise control function are obtained from the local database (Note: the second-category driving section is not in the high-precision map coverage area, and the adaptive cruise control function does not need to be combined with high-precision map data to operate). Among them, the operating conditions of the adaptive cruise control function are that the state of the adaptive cruise control function is in a normal state (Note: the associated systems and components of the adaptive cruise control function are normal and fault-free, which is a normal state, otherwise, a fault is an abnormal state), and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are preset driving characteristics. In this way, the state of the vehicle's adaptive cruise control function and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are monitored at all times as preset driving characteristics, which can determine in advance whether the vehicle can run the adaptive cruise control function, while ensuring the user's driving safety and avoiding traffic accidents. Among them, the preset driving characteristics include the vehicle speed being within the preset speed range, the vehicle distance being greater than the preset vehicle distance, and the driving trajectory not being a driving trajectory for cutting in. For example: Please continue to refer to Figure 2 ,like Figure 2As shown, A and E represent the starting point and the end point respectively, the road section BC and the road section DE are the target road sections, the road section AB and the road section CD are the non-target road sections, any driving road section is a second-class driving road section, and when a second-class driving road section is the road section CD, at this time, the vehicle is in the road section CD, the state of the adaptive cruise control function is normal, and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are the preset driving characteristics (that is, the speeds of other vehicles within 50m in front of the vehicle are all between 60km / h and 80km / h, the distances between other vehicles are all greater than 20m, and the driving trajectories of other vehicles do not have the driving trajectories of cutting in). Therefore, it is determined that the operating conditions of the adaptive cruise control function are met. It should be noted that the values ​​listed in this embodiment, such as "road section CD", "50m", "60km / h-80km / h" and "20m", are only used to illustrate the content of this embodiment and are not specific limiting values.

[0078] Furthermore, in one embodiment, when any driving section is a second-category driving section, the target function operation condition is:

[0079] The smart cruise assist function status and the adaptive cruise control function status are both in normal status, the lane line clarity within the second preset distance range in front of the vehicle is greater than the preset clarity, and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are the preset driving characteristics.

[0080] In this embodiment, when any driving section is a second-class driving section, the operating conditions of the smart cruise assist function and the adaptive cruise control function are obtained from the local database (Note: the second-class driving section is not in the high-precision map coverage area, and the smart cruise assist function and the adaptive cruise control function do not need to be combined with high-precision map data to operate). Among them, the operating conditions of the smart cruise assist function and the adaptive cruise control function are that the state of the smart cruise assist function and the state of the adaptive cruise control function are both in a normal state (Note: the associated systems and components of the smart cruise assist function and the adaptive cruise control function are normal and fault-free, which is a normal state, otherwise, a fault is an abnormal state), the clarity of the lane line within the second preset distance range in front of the vehicle is greater than the preset clarity, and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are preset driving characteristics. In this way, the state of the smart cruise assist function, the state of the adaptive cruise control function, the clarity of the lane line within the second preset distance range in front of the vehicle is greater than the preset clarity, and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are preset driving characteristics. It is possible to judge in advance whether the vehicle can run the smart cruise assist function and the adaptive cruise control function, while ensuring the driving safety of the user and avoiding traffic accidents. The preset driving characteristics include the vehicle speed being within the preset speed range, the vehicle distance being greater than the preset vehicle distance, and the driving trajectory not being a lane-cutting trajectory. Figure 2 ,like Figure 2 As shown, A and E represent the starting point and the end point respectively, sections BC and DE are target sections, sections AB and CD are non-target sections, any driving section is a second-class driving section, and a second-class driving section is section CD, at this time, the vehicle is in section CD, the smart cruise assist function state and the adaptive cruise control function state are normal, the lane line clarity within 50m in front of the vehicle is 100% greater than the preset clarity 95%, and the driving characteristic data of other vehicles are preset driving characteristics (that is, the speed of other vehicles within 50m in front of the vehicle is 60km / h-80km / h, the distance between other vehicles is greater than 20m, and the driving trajectories of other vehicles do not have the driving trajectory of cutting in). Therefore, it is determined that the operating conditions of the smart cruise assist function and the adaptive cruise control function are met. It should be noted that the values ​​listed in this embodiment, such as "road section CD", "50m", "100%", "95%", "60km / h-80km / h" and "20m", are only used to illustrate the content of this embodiment and are not specific limiting values.

[0081] Step S40: If the target function state and the road condition within a second preset distance range in front of the vehicle meet the target function operation conditions, the vehicle is controlled to operate the target function, and a prompt message indicating that the target function is operating is output.

[0082] In this embodiment, if the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function operation conditions, it means that the vehicle can run the target function within the second preset distance range in front and there is no driving safety hazard, then the vehicle is controlled to run the target function, and a prompt message that the target function is running is output. For example: if the automatic assisted navigation driving function state and the road conditions within the second preset distance range in front of the vehicle meet the automatic assisted navigation driving operation conditions, then the vehicle is controlled to run the automatic assisted navigation driving function, and the automatic assisted navigation driving function is prompted to complete the function activation through voice, pop-up windows, dynamic effects, buttons and other multi-dimensional methods. At the same time, the automatic assisted navigation driving function icon changes from gray to highlighted, a blue path guide line appears in front of the current lane where the vehicle is located, and the lane rendering of the actual driving environment (including lane line type, number of lanes, route name, road edge, etc.) jointly characterizes the operating state of the automatic assisted navigation driving function.

[0083] In this embodiment, by dividing the planned route to be driven into M driving sections, where M is a positive integer, it is convenient for the vehicle controller to match the optimal intelligent driving function for the vehicle for any driving section, which brings great convenience to the user's travel; when the distance between the vehicle and entering any driving section is less than the first preset distance, the prompt information of the type of any driving section is output; when the vehicle is still some distance away from entering any driving section, the user is reminded in advance of the type of the driving section the vehicle is about to enter, so as to let the user understand the current environmental conditions and increase the sense of trust; when the vehicle is in any driving section, the target function state and the road conditions within the second preset distance range in front of the vehicle are detected to see whether they meet the target function operation conditions; when the vehicle is in any driving section, the target function state is detected at all times If the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function operation conditions, the target function will be operated only if the target function operation conditions are met, which effectively ensures the user's driving safety and avoids traffic accidents; if the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function operation conditions, the vehicle controller will control the vehicle to operate the target function and output a prompt message that the target function is running. If the target function state and the road conditions within the second preset distance range in front of the vehicle meet the target function operation conditions, the vehicle controller will control the vehicle to operate the target function and always output a prompt message that can represent that the target function is running, so that the user can always know that the target function is running. At the same time, if the target function exits due to an emergency, the user can also find it in time, thereby avoiding major traffic accidents. This embodiment solves the technical problems in the related technology that the function state node cannot be effectively, reasonably and timely prompted, and the driver's understanding, control and experience of the function can be increased while ensuring driving safety.

[0084] In a second aspect, an embodiment of the present application also provides a human-machine co-driving control device.

[0085] In one embodiment, referring to Figure 4 , Figure 4 This is a functional module diagram of the human-machine co-driving control device in this application. Figure 4 As shown, the human-machine co-driving control device includes:

[0086] A division module 10 is used to divide the planned route to be traveled into M travel sections, where M is a positive integer;

[0087] The output module 20 is used to output prompt information of the type of any driving section when the distance of the vehicle from entering any driving section is less than a first preset distance;

[0088] The detection module 30 is used to detect whether the target function state and the road condition within a second preset distance range in front of the vehicle meet the target function operation conditions when the vehicle is in any of the driving sections;

[0089] The output module 20 is also used to control the vehicle to run the target function if the target function state and the road conditions within a second preset distance range in front of the vehicle meet the target function running conditions, and output a prompt message that the target function is running.

[0090] Furthermore, in one embodiment, the human-machine co-driving control device further includes a determination module, which is used to:

[0091] According to the starting point and end point parameters, N planned routes are obtained, where N is a positive integer;

[0092] For each planned route, calculate the length ratio of all target road sections included in the planned route, where the target road sections are in the area covered by the high-precision map;

[0093] The planned route with the largest length ratio is selected from all planned routes, and the planned route with the largest length ratio is determined as the planned route to be driven.

[0094] Furthermore, in one embodiment, the determining module is further configured to:

[0095] Select the planned route with the largest length ratio from all planned routes;

[0096] Check whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index;

[0097] If the congestion index of the planned route with the largest length ratio is less than the preset congestion index, the planned route with the largest length ratio is determined as the planned route to be driven;

[0098] If the congestion index of the planned route with the largest length ratio is not less than the preset congestion index, the planned route with the largest length ratio among the remaining planned routes is used as the planned route with the largest length ratio, and the step of detecting whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index is returned.

[0099] Furthermore, in one embodiment, the division module 10 is specifically used for:

[0100] Based on the target section, the planned route to be driven is divided into M driving sections, where a target section is a first-class driving section, a non-target section is a second-class driving section, and M is a positive integer. The non-target route is not in the high-precision map coverage area.

[0101] Furthermore, in one embodiment, the detection module 30 is specifically used for:

[0102] The status of the automatic assisted navigation driving function is normal, the lane line clarity within the second preset distance range in front of the vehicle is greater than the preset clarity, and the congestion index within the second preset distance range in front of the vehicle is less than the preset congestion index.

[0103] Furthermore, in one embodiment, the detection module 30 is further configured to:

[0104] The adaptive cruise control function state is in a normal state, and the driving characteristic data of other vehicles within a second preset distance range in front of the vehicle are preset driving characteristics.

[0105] Furthermore, in one embodiment, the detection module 30 is further configured to:

[0106] The smart cruise assist function status and the adaptive cruise control function status are both in normal status, the lane line clarity within the second preset distance range in front of the vehicle is greater than the preset clarity, and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are the preset driving characteristics.

[0107] Among them, the functional implementation of each module in the above-mentioned human-machine co-driving control device corresponds to the various steps in the above-mentioned human-machine co-driving control method embodiment, and its functions and implementation processes will not be repeated here one by one.

[0108] In a third aspect, an embodiment of the present application provides a human-machine co-driving control device, which may be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0109] Reference Figure 5 , Figure 5 Schematic diagram of the hardware structure of the human-machine co-driving control device involved in the embodiment of the present application. In the embodiment of the present application, the human-machine co-driving control device may include a processor, a memory, a communication interface and a communication bus.

[0110] The communication bus may be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0111] The communication interface includes input / output (I / O) interface, physical interface and logical interface, etc., which are used to realize the interconnection of devices inside the human-machine co-driving control device, and the interface used to realize the interconnection between the human-machine co-driving control device and other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display (Display), a keyboard (Keyboard), etc.

[0112] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0113] The processor may be a general-purpose processor, which may call the human-machine co-driving control program stored in the memory and execute the human-machine co-driving control method provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the human-machine co-driving control program is called may refer to the various embodiments of the human-machine co-driving control method of the present application, which will not be repeated here.

[0114] Those skilled in the art will understand that Figure 5 The hardware structure shown in the figure does not constitute a limitation on the present application, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0115] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium.

[0116] The computer-readable storage medium of the present application stores a human-machine co-driving control program, wherein when the human-machine co-driving control program is executed by a processor, the steps of the human-machine co-driving control method as described above are implemented.

[0117] Among them, the method implemented when the human-machine co-driving control program is executed can refer to the various embodiments of the human-machine co-driving control method of this application, and will not be repeated here.

[0118] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0119] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0120] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0121] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0122] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0123] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0124] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A human-machine co-driving control method, characterized in that: The human-machine co-driving control method comprises: According to the starting point and end point parameters, N planned routes are obtained, where N is a positive integer; For each planned route, calculate the length ratio of all target sections included in the planned route, where the target section is in the area covered by the high-precision map; Select the planned route with the largest length ratio from all planned routes; Check whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index; If the congestion index of the planned route with the largest length ratio is less than the preset congestion index, the planned route with the largest length ratio is determined as the planned route to be driven; If the congestion index of the planned route with the largest length ratio is not less than the preset congestion index, the planned route with the largest length ratio among the remaining planned routes is used as the planned route with the largest length ratio, and the step of detecting whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index is returned to execute; Divide the planned route to be driven into M driving sections, where M is a positive integer; When the distance from the vehicle to any driving section is less than a first preset distance, outputting prompt information of the type of any driving section; When the vehicle is in any of the driving sections, detecting whether the target function state and the road conditions within a second preset distance range in front of the vehicle meet the target function operation conditions; If the target function state and the road condition within a second preset distance range in front of the vehicle meet the target function operation conditions, the vehicle is controlled to operate the target function, and a prompt message indicating that the target function is operating is output.

2. The human-machine co-driving control method according to claim 1, characterized in that: The step of dividing the planned route to be traveled into M travel sections comprises: Based on the target section, the planned route to be driven is divided into M driving sections, where a target section is a first-category driving section, a non-target section is a second-category driving section, and M is a positive integer. The non-target section is not in the high-precision map coverage area.

3. The human-machine co-driving control method according to claim 2, characterized in that: When any driving section is a first-class driving section, the target function operation conditions are: The status of the automatic assisted navigation driving function is normal, the lane line clarity within the second preset distance range in front of the vehicle is greater than the preset clarity, and the congestion index within the second preset distance range in front of the vehicle is less than the preset congestion index.

4. The human-machine co-driving control method according to claim 2, characterized in that: When any driving section is a second-category driving section, the target function operation conditions are: The adaptive cruise control function state is in a normal state, and the driving characteristic data of other vehicles within a second preset distance range in front of the vehicle are preset driving characteristics.

5. The human-machine co-driving control method according to claim 2, characterized in that: When any driving section is a second-category driving section, the target function operation conditions are: The smart cruise assist function status and the adaptive cruise control function status are both in normal status, the lane line clarity within the second preset distance range in front of the vehicle is greater than the preset clarity, and the driving characteristic data of other vehicles within the second preset distance range in front of the vehicle are the preset driving characteristics.

6. A human-machine co-driving control device, characterized in that: The human-machine co-driving control device comprises: A division module is used to obtain N planned routes according to the starting point and end point parameters, where N is a positive integer; for each planned route, calculate the length ratio of all target sections contained in the planned route in the planned route, where the target section is in the high-precision map coverage area; select the planned route with the largest length ratio from all planned routes; detect whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index; if the congestion index of the planned route with the largest length ratio is less than the preset congestion index, determine the planned route with the largest length ratio as the planned route to be driven; if the congestion index of the planned route with the largest length ratio is not less than the preset congestion index, determine the planned route with the largest length ratio in the remaining planned routes as the planned route with the largest length ratio, and return to execute the step of detecting whether the congestion index of the planned route with the largest length ratio is less than the preset congestion index; divide the planned route to be driven into M driving sections, where M is a positive integer; An output module, configured to output prompt information of the type of any driving section when the distance of the vehicle from entering any driving section is less than a first preset distance; a detection module, used for detecting whether the target function state and the road condition within a second preset distance range in front of the vehicle meet the target function operation conditions when the vehicle is in any of the driving sections; The output module is used to control the vehicle to run the target function if the target function state and the road conditions within a second preset distance range in front of the vehicle meet the target function operation conditions, and output a prompt message that the target function is running.

7. A human-machine co-driving control device, characterized in that: The human-machine co-driving control device includes a processor, a memory, and a human-machine co-driving control program stored in the memory and executable by the processor, wherein when the human-machine co-driving control program is executed by the processor, the steps of the human-machine co-driving control method as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a human-machine co-driving control program, wherein when the human-machine co-driving control program is executed by a processor, the steps of the human-machine co-driving control method as described in any one of claims 1 to 5 are implemented.

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