Automatic driving control method and device applied to driving test scene

Abstract

The invention relates to the technical field of automatic driving, and discloses an automatic driving control method and device applied to a driving test scene, and the method comprises the steps: collecting the environment information of an environment where a driving test vehicle is located and the vehicle information of the driving test vehicle; determining an invigilation mode corresponding to the driving test vehicle according to the environment information and the vehicle information; when it is detected that the driving test vehicle has a vehicle returning demand, determining a driving control mode of the driving test vehicle according to the invigilation mode; the driving control mode comprises an automatic driving mode or a manual taking-over driving mode; wherein the automatic driving mode comprises a full-automatic driving mode or an auxiliary automatic driving mode; and according to the driving control mode, controlling the driving test vehicle to drive to a return destination corresponding to the vehicle return demand. Therefore, the driving test vehicle can be intelligently returned in different driving test scenes, so that the returning efficiency and the returning safety of the driving test vehicle are improved, and the driving test efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and in particular to an autonomous driving control method and device applied to a driving test scenario. Background Art

[0002] In the existing driving test process, when the driving test is over, the driving test vehicle used by the student needs to be returned. In the existing driving test scenario, the staff usually drives the driving test vehicle back to the return point, or controls the driving test vehicle to return to the return point through fully automatic driving technology. However, it takes a long time to wait for the staff to return the driving test vehicle, which can easily lead to low driving test efficiency; and returning the driving test vehicle through fully automatic driving technology is difficult to cope with different driving risks in the complex road conditions of the driving test scenario, which can easily lead to safety accidents.

[0003] Therefore, it is particularly important to propose a technical solution that can realize intelligent return of driving test vehicles, thereby improving the return efficiency and return safety of driving test vehicles and improving the efficiency of driving tests. Summary of the invention

[0004] The present invention provides an automatic driving control method and device applied to a driving test scenario, which can realize the intelligent return of the driving test vehicle, thereby improving the return efficiency and return safety of the driving test vehicle, which is conducive to improving the efficiency of the driving test.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses an automatic driving control method applied to a driving test scenario, the method comprising:

[0006] Collecting environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle;

[0007] Determine a proctoring mode corresponding to the driving test vehicle according to the environmental information and the vehicle information;

[0008] When it is detected that the driving test vehicle has a vehicle return demand, determining the driving control mode of the driving test vehicle according to the proctoring mode; the driving control mode includes an automatic driving mode or a manual takeover driving mode; wherein the automatic driving mode includes a fully automatic driving mode or an assisted automatic driving mode;

[0009] According to the driving control mode, the driving test vehicle is controlled to drive to a return destination corresponding to the vehicle return demand.

[0010] As an optional implementation manner, in the first aspect of the present invention, determining the proctoring mode corresponding to the driving test vehicle according to the environmental information and the vehicle information includes:

[0011] Determine driving test scenario information corresponding to the driving test vehicle according to the environmental information and the vehicle information; the driving test scenario information includes the driving test scenario type corresponding to the driving test vehicle and / or the environmental complexity of the environment in which the driving test vehicle is located;

[0012] Determining vehicle status information of the driving test vehicle according to the vehicle information;

[0013] According to the driving test scenario information and the vehicle status information, determining whether the driving test vehicle meets the preset AI proctoring conditions;

[0014] When it is determined that the driving test vehicle meets the AI ​​proctoring condition, determining that the proctoring mode corresponding to the driving test vehicle is the AI ​​proctoring mode; the AI ​​proctoring mode is a proctoring mode for proctoring the driving test vehicle based on artificial intelligence technology;

[0015] When it is determined that the driving test vehicle does not meet the AI ​​supervision conditions, the supervision mode corresponding to the driving test vehicle is determined to be a safety officer supervision mode; the safety officer supervision mode is a supervision mode in which a safety officer remotely supervises the driving test vehicle.

[0016] As an optional implementation, in the first aspect of the present invention, judging whether the driving test vehicle meets the preset AI proctoring conditions according to the driving test scenario information and the vehicle status information includes:

[0017] Determine whether the driving test scenario type belongs to a preset scenario type and whether the environment complexity is lower than or equal to the preset complexity and whether the vehicle status information meets the preset AI operation status condition;

[0018] When it is determined that the driving test scenario type does not belong to the preset scenario type or the environment complexity is higher than the preset complexity or the vehicle state information does not meet the AI ​​operating state condition, it is determined that the driving test vehicle does not meet the preset AI proctoring condition;

[0019] When it is determined that the driving test scenario type belongs to the preset scenario type and the environmental complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​operating status condition, it is determined that the driving test vehicle meets the preset AI proctoring conditions.

[0020] As an optional implementation, in the first aspect of the present invention, after determining that the driving test scenario type belongs to the preset scenario type and the environment complexity is lower than or equal to the preset complexity and the vehicle state information satisfies the AI ​​operating state condition, the method further includes:

[0021] Detecting whether there is a remote proctoring request corresponding to the driving test vehicle;

[0022] When detecting that there is a remote proctoring request corresponding to the driving test vehicle, determining that the driving test vehicle does not meet the preset AI proctoring conditions;

[0023] When it is detected that there is no remote proctoring request corresponding to the driving test vehicle, the operation of determining whether the driving test vehicle meets the preset AI proctoring conditions is triggered.

[0024] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0025] Determine whether the student corresponding to the driving test vehicle has completed the driving test process or whether the driving test score corresponding to the student is determined to be unqualified;

[0026] When it is determined that the student corresponding to the driving test vehicle has completed the driving test process or the driving test score corresponding to the student is determined to be unqualified, it is determined that there is a vehicle return demand for the driving test vehicle, and the demand information corresponding to the vehicle return demand is determined; the demand information at least includes the return destination.

[0027] As an optional implementation manner, in the first aspect of the present invention, determining the driving control mode of the driving test vehicle according to the proctoring mode includes:

[0028] When the proctoring mode is the AI ​​proctoring mode, determining that the driving control mode of the driving test vehicle is the fully automatic driving mode;

[0029] When the invigilation mode is a safety officer invigilation mode, obtaining qualification information of the safety officer corresponding to the driving test vehicle in the safety officer invigilation mode; the qualification information includes one or more combinations of qualification certificates, invigilation experience and invigilation records;

[0030] Determining whether the safety officer meets a preset driving intervention condition based on the qualification information;

[0031] When it is determined that the safety officer meets the driving intervention condition, determining the driving control mode of the driving test vehicle to be the assisted automatic driving mode;

[0032] When it is determined that the safety officer does not meet the driving intervention condition, the driving control mode of the driving test vehicle is determined to be the manual takeover driving mode.

[0033] As an optional implementation manner, in the first aspect of the present invention, controlling the driving test vehicle to drive to a return destination corresponding to the vehicle return demand according to the driving control mode includes:

[0034] Based on a preset path planning algorithm, determining a driving path corresponding to the driving test vehicle according to the return destination, the environmental information and the vehicle information;

[0035] When the driving control mode is the fully automatic driving mode, generating a first control instruction corresponding to the driving test vehicle based on a first driving control algorithm corresponding to the fully automatic driving mode and the driving path;

[0036] When the driving control mode is the assisted automatic driving mode, receiving the intervention control signal sent by the safety officer, and generating a second control instruction corresponding to the driving test vehicle based on a second driving control algorithm corresponding to the assisted automatic driving mode, the intervention control signal and the driving path;

[0037] According to the vehicle control instruction corresponding to the driving test vehicle, the driving test vehicle is controlled to drive to the return destination corresponding to the vehicle return demand; the vehicle control instruction includes the first control instruction or the second control instruction.

[0038] A second aspect of the present invention discloses an automatic driving control device applied to a driving test scenario, the device comprising:

[0039] A collection module, used to collect environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle;

[0040] A determination module, used to determine the proctoring mode corresponding to the driving test vehicle according to the environmental information and the vehicle information;

[0041] The determination module is further configured to determine a driving control mode of the driving test vehicle according to the proctoring mode when it is detected that the driving test vehicle has a vehicle return demand; the driving control mode includes an automatic driving mode or a manual takeover driving mode; wherein the automatic driving mode includes a fully automatic driving mode or an assisted automatic driving mode;

[0042] The control module is used to control the driving test vehicle to drive to the return destination corresponding to the vehicle return demand according to the driving control mode.

[0043] As an optional implementation, in the second aspect of the present invention, the specific manner in which the determination module determines the proctoring mode corresponding to the driving test vehicle according to the environmental information and the vehicle information includes:

[0044] Determine driving test scenario information corresponding to the driving test vehicle according to the environmental information and the vehicle information; the driving test scenario information includes the driving test scenario type corresponding to the driving test vehicle and / or the environmental complexity of the environment in which the driving test vehicle is located;

[0045] Determining vehicle status information of the driving test vehicle according to the vehicle information;

[0046] According to the driving test scenario information and the vehicle status information, determining whether the driving test vehicle meets the preset AI proctoring conditions;

[0047] When it is determined that the driving test vehicle meets the AI ​​proctoring condition, determining that the proctoring mode corresponding to the driving test vehicle is the AI ​​proctoring mode; the AI ​​proctoring mode is a proctoring mode for proctoring the driving test vehicle based on artificial intelligence technology;

[0048] When it is determined that the driving test vehicle does not meet the AI ​​supervision conditions, the supervision mode corresponding to the driving test vehicle is determined to be a safety officer supervision mode; the safety officer supervision mode is a supervision mode in which a safety officer remotely supervises the driving test vehicle.

[0049] As an optional implementation, in the second aspect of the present invention, the specific manner in which the determination module determines whether the driving test vehicle meets the preset AI proctoring conditions according to the driving test scenario information and the vehicle status information includes:

[0050] Determine whether the driving test scenario type belongs to a preset scenario type and whether the environment complexity is lower than or equal to the preset complexity and whether the vehicle status information meets the preset AI operation status condition;

[0051] When it is determined that the driving test scenario type does not belong to the preset scenario type or the environment complexity is higher than the preset complexity or the vehicle state information does not meet the AI ​​operating state condition, it is determined that the driving test vehicle does not meet the preset AI proctoring condition;

[0052] When it is determined that the driving test scenario type belongs to the preset scenario type and the environmental complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​operating status condition, it is determined that the driving test vehicle meets the preset AI proctoring conditions.

[0053] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0054] A detection module, configured to detect whether there is a remote proctoring request corresponding to the driving test vehicle after the determination module determines that the driving test scenario type belongs to the preset scenario type and the environment complexity is lower than or equal to the preset complexity and the vehicle status information satisfies the AI ​​operating status condition;

[0055] The determination module is also used to determine that the driving test vehicle does not meet the preset AI proctoring conditions when it is detected that there is a remote proctoring request corresponding to the driving test vehicle; and to determine that the driving test vehicle meets the preset AI proctoring conditions when it is detected that there is no remote proctoring request corresponding to the driving test vehicle.

[0056] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0057] A judgment module, used to judge whether the student corresponding to the driving test vehicle has completed the driving test process or whether the driving test result corresponding to the student is judged to be unqualified;

[0058] The determination module is also used to determine that there is a vehicle return demand for the driving test vehicle and determine the demand information corresponding to the vehicle return demand when the judgment module determines that the student corresponding to the driving test vehicle has completed the driving test process or the driving test score corresponding to the student is judged to be unqualified; the demand information at least includes the return destination.

[0059] As an optional implementation, in the second aspect of the present invention, the specific manner in which the determination module determines the driving control mode of the driving test vehicle according to the proctoring mode includes:

[0060] When the proctoring mode is the AI ​​proctoring mode, determining that the driving control mode of the driving test vehicle is the fully automatic driving mode;

[0061] When the invigilation mode is a safety officer invigilation mode, obtaining qualification information of the safety officer corresponding to the driving test vehicle in the safety officer invigilation mode; the qualification information includes one or more combinations of qualification certificates, invigilation experience and invigilation records;

[0062] Determining whether the safety officer meets a preset driving intervention condition based on the qualification information;

[0063] When it is determined that the safety officer meets the driving intervention condition, determining the driving control mode of the driving test vehicle to be the assisted automatic driving mode;

[0064] When it is determined that the safety officer does not meet the driving intervention condition, the driving control mode of the driving test vehicle is determined to be the manual takeover driving mode.

[0065] As an optional implementation, in the second aspect of the present invention, the specific manner in which the control module controls the driving test vehicle to drive to the return destination corresponding to the vehicle return demand according to the driving control mode includes:

[0066] Based on a preset path planning algorithm, determining a driving path corresponding to the driving test vehicle according to the return destination, the environmental information and the vehicle information;

[0067] When the driving control mode is the fully automatic driving mode, generating a first control instruction corresponding to the driving test vehicle based on a first driving control algorithm corresponding to the fully automatic driving mode and the driving path;

[0068] When the driving control mode is the assisted automatic driving mode, receiving the intervention control signal sent by the safety officer, and generating a second control instruction corresponding to the driving test vehicle based on a second driving control algorithm corresponding to the assisted automatic driving mode, the intervention control signal and the driving path;

[0069] According to the vehicle control instruction corresponding to the driving test vehicle, the driving test vehicle is controlled to drive to the return destination corresponding to the vehicle return demand; the vehicle control instruction includes the first control instruction or the second control instruction.

[0070] The third aspect of the present invention discloses another automatic driving control device applied to a driving test scenario, the device comprising:

[0071] A memory storing executable program code;

[0072] a processor coupled to the memory;

[0073] The processor calls the executable program code stored in the memory to execute part or all of the steps of the automatic driving control method applied to the driving test scenario disclosed in the first aspect of the present invention.

[0074] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute part or all of the steps of the automatic driving control method applied to the driving test scenario disclosed in the first aspect of the present invention.

[0075] Compared with the prior art, the present invention has the following beneficial effects:

[0076] In the present invention, environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle are collected; the supervision mode corresponding to the driving test vehicle is determined based on the environmental information and the vehicle information; when it is detected that the driving test vehicle has a vehicle return demand, the driving control mode of the driving test vehicle is determined based on the supervision mode; the driving control mode includes an automatic driving mode or a manually taken over driving mode; wherein the automatic driving mode includes a fully automatic driving mode or an assisted automatic driving mode; according to the driving control mode, the driving test vehicle is controlled to drive to a return destination corresponding to the vehicle return demand. It can be seen that the implementation of the present invention can determine the corresponding supervision mode of the driving test vehicle according to the collected environmental information of the driving test vehicle's environment and the vehicle information of the driving test vehicle, and when it is detected that the driving test vehicle has a vehicle return demand, the corresponding driving control mode is determined according to the supervision mode, and then according to the driving control mode, the driving test vehicle is controlled to return to the return destination, and the driving test vehicle can be intelligently returned in different driving test scenarios by intelligently analyzing the scene in which the driving test vehicle is located and intelligently selecting the corresponding supervision mode of the driving test vehicle, so as to improve the flexibility and accuracy of determining the driving control mode of the driving test vehicle while improving the supervision flexibility, supervision reliability and intelligence of the driving test vehicle, and then the driving test vehicle can be driven back to the return point through the driving control mode adapted to the current scene, so as to improve the return efficiency and return safety of the driving test vehicle, which is beneficial to improving the utilization rate and use safety of the driving test vehicle, and further beneficial to improving the efficiency of the driving test. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0078] Figure 1 It is a flowchart of an automatic driving control method applied to a driving test scenario disclosed in an embodiment of the present invention;

[0079] Figure 2 It is a flow chart of another automatic driving control method applied to a driving test scenario disclosed in an embodiment of the present invention;

[0080] Figure 3 is a schematic diagram of a system architecture of an automatic driving control system disclosed in an embodiment of the present invention;

[0081] Figure 4 is a schematic diagram of the architecture of an automatic driving control device disclosed in an embodiment of the present invention;

[0082] Figure 5It is a flowchart diagram of another automatic driving control method applied to a driving test scenario disclosed in an embodiment of the present invention;

[0083] Figure 6 It is a structural schematic diagram of an automatic driving control device applied to a driving test scenario disclosed in an embodiment of the present invention;

[0084] Figure 7 is a structural schematic diagram of another automatic driving control device applied to a driving test scenario disclosed in an embodiment of the present invention;

[0085] Figure 8 It is a structural schematic diagram of another automatic driving control device applied to a driving test scenario disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0086] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0087] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0088] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0089] The present invention discloses an automatic driving control method and device applied to a driving test scene, which can determine the corresponding proctoring mode of the driving test vehicle according to the collected environmental information of the driving test vehicle and the vehicle information of the driving test vehicle, and when it is detected that the driving test vehicle has a vehicle return demand, the corresponding driving control mode is determined according to the proctoring mode, and then the driving test vehicle is controlled to return to the return destination according to the driving control mode, and the driving test vehicle can be intelligently returned to the driving test vehicle in different driving test scenes by intelligently analyzing the scene situation of the driving test vehicle and intelligently selecting the corresponding proctoring mode of the driving test vehicle, so as to improve the flexibility and accuracy of determining the driving control mode of the driving test vehicle while improving the proctoring flexibility, proctoring reliability and intelligence of the driving test vehicle, and then the driving test vehicle can be driven back to the return point by the driving control mode adapted to the current scene, so as to improve the return efficiency and return safety of the driving test vehicle, which is conducive to improving the utilization rate and use safety of the driving test vehicle, and thus is conducive to improving the efficiency of the driving test. The following are described in detail.

[0090] Embodiment 1

[0091] See also Figure 1 , Figure 1 : is a flow chart of an automatic driving control method applied to a driving test scenario disclosed in an embodiment of the present invention. Figure 1 The described automatic driving control method applied to the driving test scenario can be applied to an automatic driving control device, which may include an automatic driving control device, an automatic driving control terminal, an automatic driving control system and a server, wherein the server may include a local server or a cloud server, which is not limited in the embodiments of the present invention; wherein, exemplarily, the system architecture of the automatic driving control system may be as follows Figure 3 As shown, Figure 3 Schematic diagram of the system architecture of an automatic driving control system disclosed in an embodiment of the present invention; the method can also be applied to a driving teaching and testing system, and further, the driving teaching and testing system can be used to monitor, dispatch and control driving test vehicles, which is not limited in the embodiment of the present invention. Figure 1 As shown, the automatic driving control method applied to the driving test scenario may include the following operations:

[0092] 101. Collect environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle.

[0093] In an embodiment of the present invention, optionally, the environmental information of the environment in which the driving test vehicle is located may include one or more combinations of surrounding object information of the driving test vehicle, weather information of the driving test vehicle and traffic condition information of the driving test vehicle, which is not limited in the embodiment of the present invention; wherein, optionally, the surrounding objects may include one or more combinations of surrounding vehicles, surrounding pedestrians, surrounding obstacles and surrounding facilities, which is not limited in the embodiment of the present invention; optionally, the weather information may include one or more combinations of weather type, rainfall / snow amount, visibility and light intensity, which is not limited in the embodiment of the present invention; wherein, optionally, the vehicle information of the driving test vehicle may include one or more combinations of vehicle positioning information, vehicle configuration information and vehicle driving information, which is not limited in the embodiment of the present invention; optionally, the vehicle configuration information may include vehicle type and / or intelligent system configuration information (for example: whether an intelligent device / intelligent system related to an AI (Artificial Intelligence) proctoring mode / safety officer proctoring mode is configured), which is not limited in the embodiment of the present invention; optionally, the vehicle driving information may include one or more combinations of vehicle speed, vehicle steering, vehicle posture information and vehicle mileage, which is not limited in the embodiment of the present invention.

[0094] 102. Determine the corresponding supervision mode of the driving test vehicle based on the environmental information and vehicle information.

[0095] In an embodiment of the present invention, the supervision mode corresponding to the driving test vehicle may be an AI supervision mode or a safety officer supervision mode, which is not limited in the embodiment of the present invention.

[0096] 103. When it is detected that the driving test vehicle needs to be returned, the driving control mode of the driving test vehicle is determined according to the supervision mode.

[0097] In an embodiment of the present invention, the driving control mode includes an automatic driving mode or a manual takeover driving mode; wherein the automatic driving mode includes a fully automatic driving mode or an assisted automatic driving mode.

[0098] In the embodiment of the present invention, when the driving control mode is the manual takeover driving mode, the driver waits for the relevant driving test staff to take over the driving test vehicle and drive the driving test vehicle to the return destination corresponding to the vehicle return demand.

[0099] 104. According to the driving control mode, control the driving test vehicle to drive to the return destination corresponding to the vehicle return demand.

[0100] It can be seen that the method described in the embodiment of the present invention can determine the corresponding supervision mode of the driving test vehicle according to the collected environmental information of the driving test vehicle and the vehicle information of the driving test vehicle, and when it is detected that the driving test vehicle has a vehicle return demand, the corresponding driving control mode is determined according to the supervision mode, and then the driving test vehicle is controlled to return to the return destination according to the driving control mode. It can realize the intelligent return of the driving test vehicle in different driving test scenarios by intelligently analyzing the scene situation of the driving test vehicle and intelligently selecting the corresponding supervision mode of the driving test vehicle, so as to improve the flexibility and accuracy of determining the driving control mode of the driving test vehicle while improving the supervision flexibility, supervision reliability and intelligence of the driving test vehicle, and then the driving test vehicle can be driven back to the return point through the driving control mode adapted to the current scene, so as to improve the return efficiency and return safety of the driving test vehicle, which is beneficial to improving the utilization rate and use safety of the driving test vehicle, and thus is beneficial to improving the efficiency of the driving test test.

[0101] In an optional embodiment, collecting environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle may include the following operations:

[0102] Based on the environment perception module, collect environmental sensing parameters of the environment in which the driving test vehicle is located; obtain weather broadcast information and road condition broadcast information of the area where the driving test vehicle is located; wherein the weather broadcast information includes weather forecast information and / or real-time weather information; determine the environmental information of the environment in which the driving test vehicle is located according to the environmental sensing parameters, weather broadcast information and road condition broadcast information;

[0103] Based on at least two navigation and positioning systems in the positioning and navigation module, the vehicle positioning data of the driving test vehicle is collected, and based on the CAN (Controller Area Network) channel, the real-time driving data of the driving test vehicle is collected; based on the multi-sensor fusion algorithm, all vehicle positioning data and real-time driving data are fused to obtain the vehicle information of the driving test vehicle.

[0104] The environment perception module may include at least one sensor device. For example, the environment perception module may include a radar sensor, a camera, a laser rangefinder, and other sensor devices, which are not limited in the embodiments of the present invention. Figure 3 The environmental perception module in the autonomous driving control system shown is not limited in the embodiment of the present invention.

[0105] The positioning and navigation module may include at least two of GPS (Global Positioning System), GNSS-RTK (Global Navigation Satellite System Real-Time Kinematic), inertial navigation system and feature matching self-positioning system, which is not limited in the embodiment of the present invention. Exemplarily, the positioning and navigation module may be as follows: Figure 3 The positioning and navigation system in the autonomous driving control system shown is not limited in the embodiments of the present invention.

[0106] Among them, the multi-sensor fusion algorithm includes operations such as preprocessing, data registration and fusion processing.

[0107] It can be seen that this optional embodiment can determine the environmental information of the environment in which the driving test vehicle is located based on the collected environmental sensor parameters of the environment in which the driving test vehicle is located and the acquired weather broadcast information and road condition broadcast information. It can improve the accuracy of collecting environmental sensor parameters and acquiring broadcast information while improving the accuracy of determining environmental information, which is beneficial to improving the accuracy of determining the invigilation mode; and it can also collect vehicle positioning data based on at least two navigation and positioning systems, and collect real-time driving data of the driving test vehicle, and then fuse the above data based on a multi-sensor fusion algorithm to obtain vehicle information, which can improve the flexibility and accuracy of collecting vehicle positioning data and the accuracy of collecting vehicle driving data, thereby improving data fusion accuracy, and then improving the accuracy of vehicle information, which is beneficial to improving the accuracy of determining the invigilation mode.

[0108] In another optional embodiment, determining the proctoring mode corresponding to the driving test vehicle according to the environment information and the vehicle information may include the following operations:

[0109] Determine driving test scenario information corresponding to the driving test vehicle according to the environment information and the vehicle information; the driving test scenario information includes the driving test scenario type corresponding to the driving test vehicle and / or the environmental complexity of the environment in which the driving test vehicle is located;

[0110] Determine the vehicle status information of the driving test vehicle according to the vehicle information;

[0111] According to the driving test scenario information and vehicle status information, determine whether the driving test vehicle meets the pre-set AI proctoring conditions;

[0112] When it is determined that the driving test vehicle meets the AI ​​supervision conditions, the supervision mode corresponding to the driving test vehicle is determined to be the AI ​​supervision mode; the AI ​​supervision mode is a supervision mode for supervising the driving test vehicle based on artificial intelligence technology;

[0113] When it is determined that the driving test vehicle does not meet the AI ​​supervision conditions, the supervision mode corresponding to the driving test vehicle is determined to be the safety officer supervision mode; the safety officer supervision mode is a supervision mode in which the driving test vehicle is remotely supervised by a safety officer.

[0114] Among them, the higher the environmental complexity, the worse the weather conditions in the driving test vehicle's environment (for example, heavy rain, typhoon, haze and other weather conditions) and / or the more complex the traffic conditions on the road where the driving test vehicle is located (for example, road congestion, traffic accidents on surrounding roads, too many surrounding pedestrians or vehicles, surrounding vehicles driving too fast, etc.), that is, the easier it is for the driving test vehicle to have a safety accident during driving.

[0115] Among them, the driving test scene type can be one of the urban road type, highway type, parking lot type, subject two type, and subject three type, which is not limited in the embodiment of the present invention.

[0116] Among them, the vehicle status information can be used to indicate whether the operating status of the driving test vehicle is normal and / or whether the driving test vehicle is in a safe driving state and / or whether the driving test vehicle is equipped with an intelligent system that can support the AI ​​supervision mode and / or whether the intelligent system equipped in the driving test vehicle can operate normally, which is not limited in the embodiments of the present invention.

[0117] It can be seen that this optional embodiment can determine the driving test scenario type and / or the environmental complexity of the environment corresponding to the driving test vehicle based on the environmental information and vehicle information, and determine the vehicle status information of the driving test vehicle based on the vehicle information, and then combine the driving test scenario information and the vehicle status information to determine whether the driving test vehicle meets the pre-set AI invigilation conditions. If the judgment result is yes, the invigilation mode corresponding to the driving test vehicle is determined to be the AI ​​invigilation mode, otherwise the invigilation mode corresponding to the driving test vehicle is determined to be the safety officer invigilation mode, which can improve the analysis accuracy and comprehensiveness of the environmental information and vehicle information, thereby improving the accuracy of the judgment of whether the driving test vehicle meets the AI ​​invigilation conditions, and then improve the accuracy of determining the invigilation mode based on the accurate judgment result, which is conducive to improving the invigilation flexibility, invigilation reliability and intelligence of the driving test vehicle.

[0118] In this optional embodiment, optionally, judging whether the driving test vehicle meets the preset AI proctoring conditions according to the driving test scenario information and the vehicle status information may include the following operations:

[0119] Determine whether the driving test scenario type belongs to the preset scenario type and whether the environmental complexity is lower than or equal to the preset complexity and whether the vehicle status information meets the preset AI operating status conditions;

[0120] When it is determined that the driving test scenario type does not belong to the preset scenario type or the environment complexity is higher than the preset complexity or the vehicle status information does not meet the AI ​​operating status condition, it is determined that the driving test vehicle does not meet the preset AI proctoring condition;

[0121] When it is determined that the driving test scenario type belongs to the preset scenario type and the environment complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​operating status conditions, it is determined that the driving test vehicle meets the pre-set AI proctoring conditions.

[0122] Among them, illustratively, the preset scene type may include subject three scene type and / or subject two scene type, which is not limited in the embodiment of the present invention.

[0123] Among them, optionally, when the vehicle status information is used to indicate that the operating status of the driving test vehicle is abnormal / the driving test vehicle is not in a safe driving state / the driving test vehicle is not equipped with the above-mentioned intelligent system / the intelligent system equipped with the driving test vehicle cannot operate normally, it is determined that the vehicle status information does not meet the AI ​​operating status conditions.

[0124] It can be seen that this optional embodiment can also determine that the driving test vehicle does not meet the preset AI supervision conditions when it is judged that the driving test scene type does not belong to the preset scene type or the environmental complexity is higher than the preset complexity or the vehicle status information does not meet the AI ​​operating state conditions, and determine that the driving test vehicle meets the preset AI supervision conditions when it is judged that the driving test scene type belongs to the preset scene type and the environmental complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​operating state conditions, that is, it can determine that the driving test vehicle does not meet the AI ​​supervision conditions when it is judged that the scene type does not meet the requirements or the driving environment is relatively complex and accidents are prone to occur or the driving test vehicle does not support AI supervision, which can improve the judgment accuracy and judgment flexibility of whether the driving test vehicle meets the AI ​​supervision conditions, thereby facilitating the determination accuracy of the supervision mode of the driving test vehicle, and then facilitating the determination accuracy of the subsequent driving control mode of the driving test vehicle, so as to avoid the driving test vehicle using the fully automatic driving mode in a complex driving environment, so as to reduce the possibility of traffic accidents when the driving test vehicle uses the fully automatic driving mode in a complex driving environment, thereby improving the automatic driving safety of the driving test vehicle, so as to improve the return safety of the driving test vehicle.

[0125] In this optional embodiment, optionally, after determining that the driving test scenario type belongs to a preset scenario type and the environment complexity is lower than or equal to the preset complexity and the vehicle state information meets the AI ​​operation state condition, the method may further include the following operations:

[0126] Detect whether there is a remote proctoring request corresponding to the driving test vehicle;

[0127] When a remote proctoring request corresponding to the driving test vehicle is detected, it is determined that the driving test vehicle does not meet the pre-set AI proctoring conditions;

[0128] When it is detected that there is no remote proctoring request corresponding to the driving test vehicle, an operation is triggered to determine whether the driving test vehicle meets the pre-set AI proctoring conditions.

[0129] Among them, the remote supervision request can be issued by the student corresponding to the driving test vehicle, and can also be issued by the invigilator corresponding to the driving test vehicle, which is not limited in the embodiment of the present invention.

[0130] It can be seen that this optional embodiment can also determine that the driving test vehicle does not meet the AI ​​supervision conditions after determining that the driving test scene type belongs to the preset scene type and the environmental complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​operating status conditions. If a remote supervision request corresponding to the driving test vehicle is detected, it is determined that the driving test vehicle does not meet the AI ​​supervision conditions, so that the supervision mode of the driving test vehicle is determined to be the safety officer supervision mode, and can respond to the supervision mode selection request of the driving test vehicle, thereby further improving the matching degree of the supervision mode with actual needs, and further improving the determination accuracy of the supervision mode.

[0131] In yet another optional embodiment, when the invigilation mode is a safety officer invigilation mode, the method may further include the following operations:

[0132] During the driving test process, check whether the safety officer of the driving test vehicle has violated the regulations or made operational errors;

[0133] When it is detected that the safety officer corresponding to the driving test vehicle has violated the regulations or made an operational error, the safety officer corresponding to the driving test vehicle will be changed, or the supervision mode corresponding to the driving test vehicle will be changed to manual supervision mode or AI supervision mode.

[0134] It can be seen that this optional embodiment can change and adjust the invigilation configuration if it is detected that the safety officer corresponding to the driving test vehicle has violated regulations or made operational errors during the driving test process. This can improve the reliability of monitoring the safety officer's invigilation situation, thereby improving the safety and reliability of the invigilation process, as well as improving the adjustment flexibility of the invigilation configuration, thereby improving the standardization and safety of the driving test process.

[0135] Embodiment 2

[0136] See also Figure 2 , Figure 2 : is a flow chart of an automatic driving control method applied to a driving test scenario disclosed in an embodiment of the present invention. Figure 2The described automatic driving control method applied to the driving test scenario can be applied to an automatic driving control device, which may include an automatic driving control device, an automatic driving control terminal, an automatic driving control system and a server, wherein the server may include a local server or a cloud server, which is not limited in the embodiments of the present invention; wherein, exemplarily, the system architecture of the automatic driving control system may be as follows Figure 3 As shown, Figure 3 Schematic diagram of the system architecture of an automatic driving control system disclosed in an embodiment of the present invention; the method can also be applied to a driving teaching and testing system, and further, the driving teaching and testing system can be used to monitor, dispatch and control driving test vehicles, which is not limited in the embodiment of the present invention. Figure 2 As shown, the automatic driving control method applied to the driving test scenario may include the following operations:

[0137] 201. Collect environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle.

[0138] 202. Determine the invigilation mode corresponding to the driving test vehicle based on the environmental information and vehicle information.

[0139] In the embodiment of the present invention, when it is detected that the driving test vehicle has a vehicle return demand, the operation of step 203 or the operations of steps 204 to 207 are performed.

[0140] 203. When the invigilation mode is the AI ​​invigilation mode, the driving control mode of the driving test vehicle is determined to be the fully automatic driving mode.

[0141] 204. When the invigilation mode is the safety officer invigilation mode, obtain the qualification information of the safety officer corresponding to the driving test vehicle in the safety officer invigilation mode.

[0142] In an embodiment of the present invention, the qualification information may include a combination of one or more of the qualification certificate, invigilation experience and invigilation records, which is not limited by the embodiment of the present invention; optionally, the invigilation experience may include a combination of one or more of the number of invigilation times, the total invigilation time, and the number of years of invigilation; the invigilation records may include a combination of one or more of the safety officer's vehicle control records, emergency handling records, and vehicle return records during each invigilation process, which is not limited by the embodiment of the present invention.

[0143] 205. Based on the qualification information, determine whether the safety officer meets the pre-set driving intervention conditions.

[0144] In an embodiment of the present invention, when the safety officer meets the pre-set driving intervention conditions, it means that the safety officer has the ability to remotely control the driving test vehicle and / or the ability to deal with emergencies during driving, which is not limited in this embodiment of the present invention.

[0145] In the embodiment of the present invention, optionally, step 205 may include the following operations:

[0146] Based on the qualification information, determine whether the safety officer has the preset qualification certificate and whether the invigilation experience meets the preset experience requirements and whether the invigilation records include successful handling of emergencies / dealing with severe weather;

[0147] When it is determined that the safety officer does not have the preset qualification certificate or the invigilation experience does not meet the preset experience conditions or the invigilation record does not record the successful handling of emergencies / coping with bad weather, it is determined that the safety officer does not meet the preset driving intervention conditions;

[0148] When it is determined that the safety officer has the preset qualification certificate and the invigilation experience meets the preset experience conditions and the invigilation record records successful handling of emergencies / coping with severe weather, it is determined that the safety officer meets the pre-set driving intervention conditions.

[0149] Further optionally, when the number of invigilation times is greater than or equal to a preset number of times or the total invigilation time is greater than or equal to a preset time or the number of invigilation years is greater than or equal to a preset number of years, it is determined that the invigilation experience meets the preset experience condition, which is not limited in the embodiment of the present invention.

[0150] In the embodiment of the present invention, when the judgment result of step 205 is yes, the operation of step 206 is executed; when the judgment result of step 205 is no, the operation of step 207 is executed.

[0151] 206. Determine that the driving control mode of the driving test vehicle is the assisted automatic driving mode.

[0152] 207. Determine that the driving control mode of the driving test vehicle is the manual takeover driving mode.

[0153] 208. According to the driving control mode, control the driving test vehicle to drive to the return destination corresponding to the vehicle return demand.

[0154] In the embodiment of the present invention, for other detailed descriptions of step 201-step 202 and step 204, please refer to the detailed description of step 101-step 102 and step 104 in the first embodiment, and the embodiment of the present invention will not be repeated here.

[0155] It can be seen that the method described in the embodiment of the present invention can determine the corresponding supervision mode of the driving test vehicle according to the collected environmental information of the driving test vehicle and the vehicle information of the driving test vehicle, and when it is detected that the driving test vehicle has a vehicle return demand, the corresponding driving control mode is determined according to the supervision mode, and then the driving test vehicle is controlled to return to the return destination according to the driving control mode. It can realize the intelligent return of the driving test vehicle in different driving test scenarios by intelligently analyzing the scene situation of the driving test vehicle and intelligently selecting the corresponding supervision mode of the driving test vehicle, so as to improve the flexibility and accuracy of determining the driving control mode of the driving test vehicle while improving the supervision flexibility, supervision reliability and intelligence of the driving test vehicle, and then the driving test vehicle can be driven back to the return point through the driving control mode adapted to the current scene, so as to improve the return efficiency and return safety of the driving test vehicle, which is beneficial to improving the utilization rate and use safety of the driving test vehicle, and thus is beneficial to improving the efficiency of the driving test test. In addition, when it is detected that there is a need to return the driving test vehicle, when the monitoring mode is the AI ​​monitoring mode, the driving control mode of the driving test vehicle is determined to be the fully automatic driving mode, and when the monitoring mode is the safety officer monitoring mode, it is necessary to first obtain the qualification information of the safety officer corresponding to the driving test vehicle in the safety officer monitoring mode, and then judge whether the safety officer meets the pre-set driving intervention conditions based on the qualification information. If the judgment result is yes, the driving control mode of the driving test vehicle is determined to be the assisted automatic driving mode, otherwise the driving control mode of the driving test vehicle is determined to be the manual takeover driving mode, which can improve the flexibility and accuracy of determining the driving control mode, and in the safety officer monitoring mode, improve the accuracy of testing the safety officer's qualifications, thereby facilitating further improving the accuracy of determining the driving control mode and improving the safety of the driving control process of the driving test vehicle, and further facilitating further improving the return efficiency and return safety of the driving test vehicle.

[0156] In an optional embodiment, the method may further include the following operations:

[0157] Determine whether the student corresponding to the driving test vehicle has completed the driving test process or whether the student's corresponding driving test score is judged to be unqualified;

[0158] When it is determined that the student corresponding to the driving test vehicle has completed the driving test process or the student's corresponding driving test score is judged to be unqualified, it is determined that there is a vehicle return demand for the driving test vehicle, and the demand information corresponding to the vehicle return demand is determined; the demand information at least includes the return destination.

[0159] The demand information corresponding to the vehicle return demand may also include the type of vehicle to be returned and / or the reason for returning the vehicle, which is not limited in the embodiment of the present invention.

[0160] It can be seen that this optional embodiment can determine that there is a need to return the driving test vehicle and determine the demand information corresponding to the vehicle return demand when it is determined that the student corresponding to the driving test vehicle has completed the driving test process or the student's corresponding driving test score is judged to be unqualified. This can improve the timeliness and flexibility of the judgment on the need to return the driving test vehicle, thereby helping to improve the timeliness of the return of the driving test vehicle.

[0161] In another optional embodiment, according to the driving control mode, controlling the driving test vehicle to drive to the return destination corresponding to the vehicle return demand may include the following operations:

[0162] Based on the pre-set path planning algorithm, determine the driving path corresponding to the driving test vehicle according to the return destination, environmental information and vehicle information;

[0163] When the driving control mode is the fully automatic driving mode, generating a first control instruction corresponding to the driving test vehicle based on a first driving control algorithm and a driving path corresponding to the fully automatic driving mode;

[0164] When the driving control mode is the assisted automatic driving mode, receiving the intervention control signal sent by the safety officer, and generating a second control instruction corresponding to the driving test vehicle based on the second driving control algorithm corresponding to the assisted automatic driving mode, the intervention control signal and the driving path;

[0165] According to the vehicle control instructions corresponding to the driving test vehicle, the driving test vehicle is controlled to drive to the return destination corresponding to the vehicle return demand; the vehicle control instructions include the first control instructions or the second control instructions.

[0166] Optionally, the first driving control algorithm and the second driving test control algorithm may be the same driving control algorithm or different driving control algorithms, which is not limited in the embodiment of the present invention. The driving control algorithm is used to generate vehicle control instructions.

[0167] Optionally, the driving path corresponding to the driving test vehicle can be determined based on the path planning algorithm pre-set in the path planning module according to the return destination, environmental information and vehicle information, which is not limited in the embodiment of the present invention. Figure 3 The path planning system in the autonomous driving control system shown is not limited in the embodiments of the present invention.

[0168] Optionally, an intervention control signal sent by a safety officer may be received based on a CAN channel, which is not limited in the embodiment of the present invention.

[0169] Among them, the vehicle control instruction can be used to adjust the throttle, brake, steering, gear shifting, speed and other vehicle motion control parameters, which is not limited in the embodiment of the present invention.

[0170] Optionally, the above-mentioned vehicle control instruction generation operation may be performed based on a motion control module, which is not limited in the embodiment of the present invention. Figure 3 The motion control system in the autonomous driving control system shown is not limited in the embodiment of the present invention.

[0171] It can be seen that this optional embodiment can plan the driving path corresponding to the driving test vehicle based on the preset path planning algorithm, according to the return destination, environmental information and vehicle information. If the driving control mode is the fully automatic driving mode, then based on the first driving control algorithm and driving path corresponding to the fully automatic driving mode, a first control instruction corresponding to the driving test vehicle is generated. If the driving control mode is the assisted automatic driving mode, the intervention control signal sent by the safety officer is received, and based on the second driving control algorithm, intervention control signal and driving path corresponding to the assisted automatic driving mode, a second control instruction corresponding to the driving test vehicle is generated. Then, according to the vehicle control instruction corresponding to the driving test vehicle, the driving test vehicle is controlled to drive to the return destination corresponding to the vehicle return demand. This can improve the accuracy of the driving path planning of the automatic driving while improving the flexibility and accuracy of generating the control instructions of the driving test vehicle, thereby improving the driving control accuracy of the driving test vehicle, which is beneficial to improving the return reliability and return safety of the driving test vehicle.

[0172] In this optional embodiment, optionally, when the driving control module is in the fully automatic driving mode, in the process of controlling the driving test vehicle to drive to the return destination corresponding to the vehicle return demand, the method may further include the following operations:

[0173] Detect real-time environmental information and real-time traffic conditions during the process of returning the driving test vehicle;

[0174] Determine the real-time driving risk factor corresponding to the driving test vehicle based on real-time environmental information and real-time traffic condition information;

[0175] Determine whether the real-time driving risk factor is greater than or equal to the preset risk factor;

[0176] When it is determined that the real-time driving risk factor is greater than or equal to the preset risk factor, the driving control mode corresponding to the driving test vehicle is changed to an assisted automatic driving mode or a manual takeover driving mode;

[0177] When the driving control mode is changed to the assisted automatic driving mode, the operation of receiving the intervention control signal sent by the safety officer is triggered;

[0178] When the driving control mode is changed to manual takeover driving mode, control the driving test vehicle to drive to the safe area closest to the current position and wait for relevant driving test staff to take over the driving test vehicle.

[0179] Among them, optionally, the above-mentioned safe area can be one of a roadside area where vehicles can be parked, a parking lot, and an area where the environmental complexity is lower than a preset complexity, which is not limited in the embodiment of the present invention.

[0180] It can be seen that this optional embodiment can also detect real-time environmental information and real-time traffic conditions information during the process of returning the driving test vehicle, and determine the real-time driving risk coefficient corresponding to the driving test vehicle based on the above real-time information. If it is judged that the real-time driving risk coefficient is greater than or equal to the preset risk coefficient, the driving control mode corresponding to the driving test vehicle is changed to an assisted automatic driving mode or a manual takeover driving mode. Further, when the driving control mode is changed to the assisted automatic driving mode, the operation of receiving the intervention control signal sent by the safety officer is triggered. When the driving control mode is changed to the manual takeover driving mode, the driving test vehicle is controlled to drive to the safe area closest to the current position, and wait for the relevant driving test staff to take over the driving test vehicle. This can improve the timeliness and accuracy of the analysis of real-time driving conditions during the automatic driving process, thereby improving the adjustment accuracy and timeliness of the driving control mode, and then improving the flexibility of coping with changes in the driving environment during the vehicle return process, which is beneficial to improving the safety of the return of the driving test vehicle.

[0181] In the embodiment of the present invention, for example, the automatic driving control method applied to the driving test scenario can be applied to the following Figure 3 The automatic driving control system shown in FIG. Figure 4 In the automatic driving control device, Figure 4 A schematic diagram of the architecture of an automatic driving control device disclosed in an embodiment of the present invention.

[0182] Among them, Figure 3 As shown, the automatic driving control system may include an environmental perception system, a positioning and navigation system, a path planning system, a motion control system and an assisted driving system. Specifically: the environmental perception module may be used to collect real-time data of the surrounding environment, such as obstacles, road conditions, etc., to provide a basis for decision-making for the vehicle; the positioning and navigation module may be used to accurately determine the vehicle position, plan the optimal path, and ensure that the vehicle arrives at the destination accurately; the path planning module may be used to formulate a safe and efficient driving route based on environmental perception and positioning and navigation information; the motion control module may be used to convert the planning results into actual driving operations, such as steering, acceleration and deceleration, etc., to ensure stable driving of the vehicle; the assisted driving system may be used to provide functions such as automatic parking and lane keeping, to improve driving comfort and safety.

[0183] Among them, Figure 4As shown, the automatic driving control device may include an environment perception module, a path planning module, a control execution module, a proctoring mode determination module, a safety officer evaluation module, a sending module and a receiving module. Specifically: the environment perception module may be used to perceive the environment around the vehicle, including identifying obstacles, road conditions, etc., to help the automatic driving system make appropriate decisions; the positioning and navigation module may be used to determine the current position of the vehicle, monitor traffic conditions and road conditions in real time, and provide accurate navigation guidance to help the vehicle accurately reach the destination; the path planning module may be used to plan the vehicle's driving path based on the information provided by the environment perception module and the positioning and navigation module to ensure that the vehicle reaches the destination safely and efficiently; the control execution module may be used to control the steering, acceleration and deceleration of the vehicle according to the output of the path planning module to realize the automatic driving function; the proctoring mode determination module may be used to determine the automatic driving algorithm corresponding to the automatic driving strategy; the automatic driving algorithm is used to drive the vehicle where the automatic driving device is located to the destination; the safety officer evaluation module may be used to evaluate the safety performance of the system, monitor the operation of the system, ensure that the system can operate safely under various circumstances, and promptly discover and deal with potential safety issues. At the same time, the qualifications of the safety officer are evaluated; the sending module may be used to send data or instructions to other devices or systems to realize information exchange and control instruction transmission. For example, it sends a guidance request to the remote safety officer to transmit vehicle status information; the receiving module can be used to receive data or instructions from other devices or systems so that the autonomous driving system can make corresponding responses and decisions. For example, it receives driving guidance information from the safety officer of the autonomous driving, which contains driving guidance strategies.

[0184] In an embodiment of the present invention, illustratively, the process of the automatic driving control method applied to the driving test scenario can be as follows Figure 5 As shown, Figure 5 This is a flow chart of another automatic driving control method applied to a driving test scenario disclosed in an embodiment of the present invention. Specifically, the method may include the following specific operations:

[0185] Based on the environmental information and vehicle information collected by the sensor, determine whether the AI ​​proctoring mode is supported; if the AI ​​proctoring mode is supported, select the automatic driving algorithm to control the vehicle to the destination; if the AI ​​proctoring mode is not supported, determine whether the safety officer proctoring mode is supported. If the safety officer proctoring mode is supported, the safety officer will issue a control instruction and send a control signal through the CAN channel to control the vehicle to the destination; if neither the AI ​​proctoring mode nor the safety officer proctoring mode is supported, the vehicle will stop and wait for the examination room staff to take over the vehicle and return it manually, and the test data will be saved when the vehicle has been returned, which is not limited in the embodiments of the present invention.

[0186] Embodiment 3

[0187] See also Figure 6 , Figure 6 1 is a schematic diagram of the structure of an automatic driving control device applied to a driving test scenario disclosed in an embodiment of the present invention. Figure 6 The described automatic driving control device applied to the driving test scenario may include an automatic driving control device, an automatic driving control terminal, an automatic driving control system and a server, wherein the server may include a local server or a cloud server, which is not limited in the embodiments of the present invention; the device may be applied to a driving teaching and testing system, and further, the driving teaching and testing system may be used to monitor, dispatch and control driving test vehicles, which is not limited in the embodiments of the present invention. Figure 6 As shown, the automatic driving control device applied to the driving test scenario may include:

[0188] The collection module 301 is used to collect environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle;

[0189] A determination module 302, for determining a proctoring mode corresponding to the driving test vehicle according to the environment information and the vehicle information;

[0190] The determination module 302 is further configured to determine the driving control mode of the driving test vehicle according to the proctoring mode when it is detected that the driving test vehicle has a vehicle return demand; the driving control mode includes an automatic driving mode or a manual takeover driving mode; wherein the automatic driving mode includes a fully automatic driving mode or an assisted automatic driving mode;

[0191] The control module 303 is used to control the driving test vehicle to drive to the return destination corresponding to the vehicle return demand according to the driving control mode.

[0192] It can be seen that the device described in the embodiment of the present invention can determine the corresponding supervision mode of the driving test vehicle according to the collected environmental information of the driving test vehicle and the vehicle information of the driving test vehicle, and when it is detected that the driving test vehicle has a vehicle return demand, the corresponding driving control mode is determined according to the supervision mode, and then the driving test vehicle is controlled to return to the return destination according to the driving control mode. It can realize the intelligent return of the driving test vehicle in different driving test scenarios by intelligently analyzing the scene situation of the driving test vehicle and intelligently selecting the corresponding supervision mode of the driving test vehicle, so as to improve the flexibility and accuracy of determining the driving control mode of the driving test vehicle while improving the supervision flexibility, supervision reliability and intelligence of the driving test vehicle, and then the driving test vehicle can be driven back to the return point through the driving control mode adapted to the current scene, so as to improve the return efficiency and return safety of the driving test vehicle, which is beneficial to improving the utilization rate and use safety of the driving test vehicle, and thus is beneficial to improving the efficiency of the driving test test.

[0193] In an optional embodiment, the specific manner in which the determination module 302 determines the proctoring mode corresponding to the driving test vehicle according to the environment information and the vehicle information may include:

[0194] Determine driving test scenario information corresponding to the driving test vehicle according to the environment information and the vehicle information; the driving test scenario information includes the driving test scenario type corresponding to the driving test vehicle and / or the environmental complexity of the environment in which the driving test vehicle is located;

[0195] Determine the vehicle status information of the driving test vehicle according to the vehicle information;

[0196] According to the driving test scenario information and vehicle status information, determine whether the driving test vehicle meets the pre-set AI proctoring conditions;

[0197] When it is determined that the driving test vehicle meets the AI ​​supervision conditions, the supervision mode corresponding to the driving test vehicle is determined to be the AI ​​supervision mode; the AI ​​supervision mode is a supervision mode for supervising the driving test vehicle based on artificial intelligence technology;

[0198] When it is determined that the driving test vehicle does not meet the AI ​​supervision conditions, the supervision mode corresponding to the driving test vehicle is determined to be the safety officer supervision mode; the safety officer supervision mode is a supervision mode in which the driving test vehicle is remotely supervised by a safety officer.

[0199] It can be seen that the device described in the implementation of this optional embodiment can determine the driving test scene type and / or the environmental complexity of the environment corresponding to the driving test vehicle based on the environmental information and vehicle information, and determine the vehicle status information of the driving test vehicle based on the vehicle information, and then combine the driving test scene information and the vehicle status information to determine whether the driving test vehicle meets the pre-set AI supervision conditions. If the judgment result is yes, the supervision mode corresponding to the driving test vehicle is determined to be the AI ​​supervision mode, otherwise the supervision mode corresponding to the driving test vehicle is determined to be the safety officer supervision mode, which can improve the analysis accuracy and comprehensiveness of the environmental information and vehicle information, thereby improving the accuracy of the judgment of whether the driving test vehicle meets the AI ​​supervision conditions, and then improve the accuracy of the determination of the supervision mode based on the accurate judgment result, which is conducive to improving the supervision flexibility, supervision reliability and intelligence of the driving test vehicle.

[0200] In this optional embodiment, the specific manner in which the determination module 302 determines whether the driving test vehicle meets the preset AI proctoring conditions according to the driving test scenario information and the vehicle status information may include:

[0201] Determine whether the driving test scenario type belongs to the preset scenario type and whether the environmental complexity is lower than or equal to the preset complexity and whether the vehicle status information meets the preset AI operating status conditions;

[0202] When it is determined that the driving test scenario type does not belong to the preset scenario type or the environment complexity is higher than the preset complexity or the vehicle status information does not meet the AI ​​operating status condition, it is determined that the driving test vehicle does not meet the preset AI proctoring condition;

[0203] When it is determined that the driving test scenario type belongs to the preset scenario type and the environment complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​operating status conditions, it is determined that the driving test vehicle meets the pre-set AI proctoring conditions.

[0204] It can be seen that the device described in the implementation of this optional embodiment can also determine that the driving test vehicle does not meet the preset AI supervision conditions when it is judged that the driving test scene type does not belong to the preset scene type or the environmental complexity is higher than the preset complexity or the vehicle status information does not meet the AI ​​running state conditions, and determine that the driving test vehicle meets the preset AI supervision conditions when it is judged that the driving test scene type belongs to the preset scene type and the environmental complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​running state conditions, that is, it can determine that the driving test vehicle does not meet the AI ​​supervision conditions when it is judged that the scene type does not meet the requirements or the driving environment is relatively complex and accidents are prone to occur or the driving test vehicle does not support AI supervision, which can improve the judgment accuracy and judgment flexibility of whether the driving test vehicle meets the AI ​​supervision conditions, thereby facilitating the improvement of the accuracy of determining the supervision mode of the driving test vehicle, and further facilitating the improvement of the accuracy of determining the subsequent driving control mode of the driving test vehicle, so as to avoid the driving test vehicle using the fully automatic driving mode in a complex driving environment, so as to reduce the possibility of traffic accidents when the driving test vehicle uses the fully automatic driving mode in a complex driving environment, thereby improving the automatic driving safety of the driving test vehicle, so as to improve the safety of the return of the driving test vehicle.

[0205] In this optional embodiment, optionally, as Figure 7 As shown, the device may also include:

[0206] The detection module 304 is used to detect whether there is a remote proctoring request corresponding to the driving test vehicle after the determination module 302 determines that the driving test scenario type belongs to the preset scenario type and the environment complexity is lower than or equal to the preset complexity and the vehicle state information meets the AI ​​operation state condition;

[0207] The determination module 302 is also used to determine that the driving test vehicle does not meet the pre-set AI supervision conditions when it is detected that there is a remote supervision request corresponding to the driving test vehicle; when it is detected that there is no remote supervision request corresponding to the driving test vehicle, determine that the driving test vehicle meets the pre-set AI supervision conditions.

[0208] It can be seen that the device described in the implementation of this optional embodiment can also determine that the driving test vehicle does not meet the AI ​​supervision conditions after detecting a remote supervision request corresponding to the driving test vehicle after judging that the driving test scene type belongs to the preset scene type and the environmental complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​operating status conditions, so that the supervision mode of the driving test vehicle is determined to be the safety officer supervision mode, and can respond to the supervision mode selection request of the driving test vehicle, thereby further improving the matching degree of the supervision mode with actual needs, and further improving the accuracy of determining the supervision mode.

[0209] In another optional embodiment, Figure 7 As shown, the device may also include:

[0210] The judgment module 305 is used to judge whether the student corresponding to the driving test vehicle has completed the driving test process or whether the driving test result corresponding to the student is judged to be unqualified;

[0211] The determination module 302 is also used to determine whether there is a vehicle return demand for the driving test vehicle and determine the demand information corresponding to the vehicle return demand when the judgment module 305 determines that the student corresponding to the driving test vehicle has completed the driving test process or the student's corresponding driving test score is judged to be unqualified; the demand information at least includes the return destination.

[0212] It can be seen that the device described in the implementation of this optional embodiment can determine that there is a need to return the driving test vehicle and determine the demand information corresponding to the vehicle return demand when it is determined that the student corresponding to the driving test vehicle has completed the driving test process or the driving test score corresponding to the student is judged to be unqualified. This can improve the timeliness and flexibility of the judgment on the need to return the driving test vehicle, thereby helping to improve the timeliness of the return of the driving test vehicle.

[0213] In another optional embodiment, the specific manner in which the determination module 302 determines the driving control mode of the driving test vehicle according to the proctoring mode may include:

[0214] When the proctoring mode is AI proctoring mode, the driving control mode of the driving test vehicle is determined to be fully automatic driving mode;

[0215] When the invigilation mode is the safety officer invigilation mode, obtain the qualification information of the safety officer corresponding to the driving test vehicle in the safety officer invigilation mode; the qualification information includes one or more combinations of qualification certificates, invigilation experience and invigilation records;

[0216] Based on the qualification information, determine whether the safety officer meets the pre-set driving intervention conditions;

[0217] When it is determined that the safety officer meets the driving intervention conditions, the driving control mode of the driving test vehicle is determined to be the auxiliary automatic driving mode;

[0218] When it is determined that the safety officer does not meet the driving intervention conditions, the driving control mode of the driving test vehicle is determined to be the manual takeover driving mode.

[0219] It can be seen that the device described in the implementation of this optional embodiment can determine that the driving control mode of the driving test vehicle is a fully automatic driving mode when it detects that there is a need to return the driving test vehicle, when the proctoring mode is the AI ​​proctoring mode, and when the proctoring mode is the safety officer proctoring mode, it is necessary to first obtain the qualification information of the safety officer corresponding to the driving test vehicle in the safety officer proctoring mode, and then judge whether the safety officer meets the pre-set driving intervention conditions based on the qualification information. If the judgment result is yes, the driving control mode of the driving test vehicle is determined to be an assisted automatic driving mode, otherwise, the driving control mode of the driving test vehicle is determined to be a manual takeover driving mode, which can improve the flexibility and accuracy of determining the driving control mode, and in the safety officer proctoring mode, improve the accuracy of testing the safety officer's qualifications, thereby facilitating further improving the accuracy of determining the driving control mode and improving the safety of the driving control process of the driving test vehicle, and further facilitating further improving the return efficiency and return safety of the driving test vehicle.

[0220] In this optional embodiment, the specific manner in which the control module 303 controls the driving test vehicle to drive to the return destination corresponding to the vehicle return demand according to the driving control mode may include:

[0221] Based on the pre-set path planning algorithm, determine the driving path corresponding to the driving test vehicle according to the return destination, environmental information and vehicle information;

[0222] When the driving control mode is the fully automatic driving mode, generating a first control instruction corresponding to the driving test vehicle based on a first driving control algorithm and a driving path corresponding to the fully automatic driving mode;

[0223] When the driving control mode is the assisted automatic driving mode, receiving the intervention control signal sent by the safety officer, and generating a second control instruction corresponding to the driving test vehicle based on the second driving control algorithm corresponding to the assisted automatic driving mode, the intervention control signal and the driving path;

[0224] According to the vehicle control instructions corresponding to the driving test vehicle, the driving test vehicle is controlled to drive to the return destination corresponding to the vehicle return demand; the vehicle control instructions include the first control instructions or the second control instructions.

[0225] It can be seen that the device described in the implementation of this optional embodiment can also plan the driving path corresponding to the driving test vehicle based on the preset path planning algorithm, according to the return destination, environmental information and vehicle information. If the driving control mode is a fully automatic driving mode, then based on the first driving control algorithm and driving path corresponding to the fully automatic driving mode, a first control instruction corresponding to the driving test vehicle is generated; if the driving control mode is an assisted automatic driving mode, the intervention control signal sent by the safety officer is received, and based on the second driving control algorithm, intervention control signal and driving path corresponding to the assisted automatic driving mode, a second control instruction corresponding to the driving test vehicle is generated; then, according to the vehicle control instruction corresponding to the driving test vehicle, the driving test vehicle is controlled to drive to the return destination corresponding to the vehicle return demand, which can improve the generation flexibility and accuracy of the control instructions of the driving test vehicle while improving the accuracy of the driving path planning of the automatic driving, thereby improving the driving control accuracy of the driving test vehicle, which is beneficial to improving the return reliability and return safety of the driving test vehicle.

[0226] Embodiment 4

[0227] See also Figure 8 , Figure 8 FIG. 1 is a schematic diagram of the structure of another automatic driving control device for use in a driving test scenario disclosed in an embodiment of the present invention. Figure 8 As shown, the automatic driving control device applied to the driving test scenario may include:

[0228] A memory 401 storing executable program codes;

[0229] a processor 402 coupled to the memory 401;

[0230] The processor 402 calls the executable program code stored in the memory 401 to execute part or all of the steps in the automatic driving control method applied to the driving test scenario described in Embodiment 1 or Embodiment 2 of the present invention.

[0231] Embodiment 5

[0232] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute part or all of the steps in the automatic driving control method applied to the driving test scenario described in Embodiment 1 or Embodiment 2 of the present invention.

[0233] Embodiment 6

[0234] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute part or all of the steps in the automatic driving control method applied to the driving test scenario described in Example 1 or Example 2.

[0235] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0236] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0237] Finally, it should be noted that the automatic driving control method and device applied to the driving test scenario disclosed in the embodiment of the present invention only discloses the preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions recorded in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An automatic driving control method applied to a driving test scenario, characterized in that: The method comprises: Collecting environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle; Determine a proctoring mode corresponding to the driving test vehicle according to the environmental information and the vehicle information; When it is detected that the driving test vehicle has a vehicle return demand, determining the driving control mode of the driving test vehicle according to the proctoring mode; the driving control mode includes an automatic driving mode or a manual takeover driving mode; wherein the automatic driving mode includes a fully automatic driving mode or an assisted automatic driving mode; According to the driving control mode, the driving test vehicle is controlled to drive to a return destination corresponding to the vehicle return demand.

2. The automatic driving control method applied to the driving test scenario according to claim 1 is characterized in that: The determining, according to the environment information and the vehicle information, a proctoring mode corresponding to the driving test vehicle includes: Determine driving test scenario information corresponding to the driving test vehicle according to the environmental information and the vehicle information; the driving test scenario information includes the driving test scenario type corresponding to the driving test vehicle and / or the environmental complexity of the environment in which the driving test vehicle is located; Determining vehicle status information of the driving test vehicle according to the vehicle information; According to the driving test scenario information and the vehicle status information, determining whether the driving test vehicle meets the preset AI proctoring conditions; When it is determined that the driving test vehicle meets the AI ​​proctoring condition, determining that the proctoring mode corresponding to the driving test vehicle is the AI ​​proctoring mode; the AI ​​proctoring mode is a proctoring mode for proctoring the driving test vehicle based on artificial intelligence technology; When it is determined that the driving test vehicle does not meet the AI ​​supervision conditions, the supervision mode corresponding to the driving test vehicle is determined to be a safety officer supervision mode; the safety officer supervision mode is a supervision mode in which a safety officer remotely supervises the driving test vehicle.

3. The automatic driving control method applied to the driving test scenario according to claim 2 is characterized in that: The determining, based on the driving test scenario information and the vehicle status information, whether the driving test vehicle meets a preset AI proctoring condition includes: Determine whether the driving test scenario type belongs to a preset scenario type and whether the environment complexity is lower than or equal to the preset complexity and whether the vehicle status information meets the preset AI operation status condition; When it is determined that the driving test scenario type does not belong to the preset scenario type or the environment complexity is higher than the preset complexity or the vehicle state information does not meet the AI ​​operating state condition, it is determined that the driving test vehicle does not meet the preset AI proctoring condition; When it is determined that the driving test scenario type belongs to the preset scenario type and the environmental complexity is lower than or equal to the preset complexity and the vehicle status information meets the AI ​​operating status condition, it is determined that the driving test vehicle meets the preset AI proctoring conditions.

4. The automatic driving control method applied to the driving test scenario according to claim 3 is characterized in that: After determining that the driving test scenario type belongs to the preset scenario type and the environment complexity is lower than or equal to the preset complexity and the vehicle state information satisfies the AI ​​operating state condition, the method further includes: Detecting whether there is a remote proctoring request corresponding to the driving test vehicle; When detecting that there is a remote proctoring request corresponding to the driving test vehicle, determining that the driving test vehicle does not meet the preset AI proctoring conditions; When it is detected that there is no remote proctoring request corresponding to the driving test vehicle, the operation of determining whether the driving test vehicle meets the preset AI proctoring conditions is triggered.

5. The automatic driving control method applied to the driving test scenario according to claim 1 is characterized in that: The method further comprises: Determine whether the student corresponding to the driving test vehicle has completed the driving test process or whether the driving test score corresponding to the student is determined to be unqualified; When it is determined that the student corresponding to the driving test vehicle has completed the driving test process or the driving test score corresponding to the student is determined to be unqualified, it is determined that there is a vehicle return demand for the driving test vehicle, and the demand information corresponding to the vehicle return demand is determined; the demand information at least includes the return destination.

6. The automatic driving control method applied to the driving test scenario according to any one of claims 1 to 5, characterized in that: Determining the driving control mode of the driving test vehicle according to the proctoring mode includes: When the proctoring mode is the AI ​​proctoring mode, determining that the driving control mode of the driving test vehicle is the fully automatic driving mode; When the invigilation mode is a safety officer invigilation mode, obtaining qualification information of the safety officer corresponding to the driving test vehicle in the safety officer invigilation mode; the qualification information includes one or more combinations of qualification certificates, invigilation experience and invigilation records; Determining whether the safety officer meets a preset driving intervention condition based on the qualification information; When it is determined that the safety officer meets the driving intervention condition, determining the driving control mode of the driving test vehicle to be the assisted automatic driving mode; When it is determined that the safety officer does not meet the driving intervention condition, the driving control mode of the driving test vehicle is determined to be the manual takeover driving mode.

7. The automatic driving control method applied to the driving test scenario according to claim 6 is characterized in that: According to the driving control mode, controlling the driving test vehicle to drive to the return destination corresponding to the vehicle return demand includes: Based on a preset path planning algorithm, determining a driving path corresponding to the driving test vehicle according to the return destination, the environmental information and the vehicle information; When the driving control mode is the fully automatic driving mode, generating a first control instruction corresponding to the driving test vehicle based on a first driving control algorithm corresponding to the fully automatic driving mode and the driving path; When the driving control mode is the assisted automatic driving mode, receiving the intervention control signal sent by the safety officer, and generating a second control instruction corresponding to the driving test vehicle based on a second driving control algorithm corresponding to the assisted automatic driving mode, the intervention control signal and the driving path; According to the vehicle control instruction corresponding to the driving test vehicle, the driving test vehicle is controlled to drive to the return destination corresponding to the vehicle return demand; the vehicle control instruction includes the first control instruction or the second control instruction.

8. An automatic driving control device applied to a driving test scenario, characterized in that: The device comprises: A collection module, used to collect environmental information of the environment in which the driving test vehicle is located and vehicle information of the driving test vehicle; A determination module, used to determine the proctoring mode corresponding to the driving test vehicle according to the environmental information and the vehicle information; The determination module is further configured to determine a driving control mode of the driving test vehicle according to the proctoring mode when it is detected that the driving test vehicle has a vehicle return demand; the driving control mode includes an automatic driving mode or a manual takeover driving mode; wherein the automatic driving mode includes a fully automatic driving mode or an assisted automatic driving mode; The control module is used to control the driving test vehicle to drive to the return destination corresponding to the vehicle return demand according to the driving control mode.

9. An automatic driving control device applied to a driving test scenario, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the automatic driving control method applied to the driving test scenario as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, which, when called, are used to execute the automatic driving control method applied to the driving test scenario as described in any one of claims 1-7.

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