Automatic driving area identification method and device, storage medium and vehicle equipment

Abstract

The application relates to an automatic drivable area identification method and device, a storage medium and a vehicle equipment. The method comprises the following steps: acquiring a first road condition parameter, the first road condition parameter being a road condition parameter collected by a vehicle in a manual driving state during driving along a to-be-identified route in a to-be-identified area; judging whether the first road condition parameter meets a preset first automatic driving road condition; if the first automatic driving road condition is met, it is determined that the to-be-identified route is an automatic drivable route; under the condition that the to-be-identified route is determined to be the automatic drivable route, a second road condition parameter is acquired, the second road condition parameter being a road condition parameter collected by the vehicle in an automatic driving state during driving along the automatic drivable route; and judging whether the second road condition parameter meets a preset second automatic driving road condition; if the second automatic driving road condition is met, it is determined that the to-be-identified area is an automatic drivable area. The application improves the accuracy of automatic drivable area identification.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving, in particular to an automatic drivable area identification method and device, a storage medium and a vehicle equipment. BACKGROUND

[0002] With the continuous development of automatic driving technology, the application range of automatic driving system is also more extensive. However, the current application of automatic driving technology still faces many challenges, one of which is how to accurately and effectively identify and determine the area where automatic driving can be safely implemented.

[0003] In the traditional technology, the identification of the automatic drivable area mainly depends on the static map and the pre-labeled high-precision data. However, the identification method in the traditional technology has limitations in the actual environment, especially in the dynamic changing road conditions. The identification method only through the static map and the pre-labeled data has low accuracy and reliability, and is easy to cause safety hazards. SUMMARY

[0004] Therefore, it is necessary to provide an automatic drivable area identification method, device, storage medium and vehicle equipment capable of improving the identification accuracy and reliability in view of the above technical problems.

[0005] In a first aspect, the present application provides an automatic drivable area identification method. The method comprises:

[0006] obtaining a first road condition parameter, the first road condition parameter being a road condition parameter collected by a vehicle in a manual driving state during driving along a to-be-identified route in a to-be-identified area;

[0007] determining whether the first road condition parameter meets a preset first automatic driving road condition, and if the first automatic driving road condition is met, determining that the to-be-identified route is an automatic drivable route;

[0008] under the condition that the to-be-identified route is determined to be an automatic drivable route, obtaining a second road condition parameter, the second road condition parameter being a road condition parameter collected by the vehicle during driving along the automatic drivable route in an automatic driving state;

[0009] determining whether the second road condition parameter meets a preset second automatic driving road condition, and if the second automatic driving road condition is met, determining that the to-be-identified area is an automatic drivable area.

[0010] In one of the embodiments, the first road condition parameter comprises a plurality of first road condition sub-parameters, and the first automatic driving road condition comprises a plurality of first preset sub-conditions corresponding to the plurality of first road condition sub-parameters; the judging whether the first road condition parameter satisfies the preset first automatic driving road condition comprises:

[0011] judging whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition;

[0012] if all the first road condition sub-parameters satisfy the corresponding first preset sub-condition, judging that the first road condition parameter satisfies the preset first automatic driving road condition.

[0013] In one of the embodiments, the first road condition sub-parameter comprises a first network state parameter; the judging whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition comprises:

[0014] determining a network state detection result of each first network detection point based on the first network state parameter of the plurality of first network detection points and a first network state threshold value, wherein each two adjacent first network detection points are spaced apart by a first preset distance in the to-be-identified route;

[0015] determining a first network state qualification rate based on the network state detection results of all the first network detection points and the number of the first network detection points;

[0016] if the first network state qualification rate is greater than a first qualification rate threshold value, determining that the corresponding first preset sub-condition is satisfied.

[0017] In one of the embodiments, the first road condition sub-parameter comprises a road width; the judging whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition comprises:

[0018] judging whether the road width of each road width detection point is greater than a road width threshold value based on the road width of the plurality of road width detection points and the road width threshold value, wherein each two adjacent road width detection points are spaced apart by a second preset distance in the to-be-identified route;

[0019] if the road width of all the road width detection points is greater than the road width threshold value, determining that the corresponding first preset sub-condition is satisfied.

[0020] In one of the embodiments, the first road condition sub-parameter comprises an ambient light intensity; the judging whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition comprises:

[0021] The ambient light intensity of each light intensity detection point is determined based on the ambient light intensity of the plurality of light intensity detection points and a light intensity threshold value, wherein each two adjacent light intensity detection points are spaced apart by a third preset distance in the to-be-identified route.

[0022] If the ambient light intensity of all light intensity detection points is greater than the light intensity threshold value, it is determined that the corresponding first preset sub-condition is met.

[0023] In one embodiment, the first road condition sub-parameter includes a minimum turning radius and an intersection distance, the intersection distance including a distance between each two adjacent intersections in the to-be-identified route; and the determination of whether the first road condition sub-parameter meets the corresponding first preset sub-condition includes:

[0024] determining whether the minimum turning radius of each intersection in the to-be-identified route is greater than a radius threshold value, and determining whether the intersection distance is greater than an intersection distance threshold value;

[0025] If the minimum turning radius of all intersections is greater than the radius threshold value and the intersection distance is greater than the intersection distance threshold value, it is determined that the corresponding first preset sub-condition is met.

[0026] In one embodiment, the second road condition parameter includes a plurality of second road condition sub-parameters, and the second automatic driving road condition includes a plurality of second preset sub-conditions corresponding to the plurality of second road condition sub-parameters; and the determination of whether the second road condition parameter meets the preset second automatic driving road condition includes:

[0027] determining whether the second road condition sub-parameter meets the corresponding second preset sub-condition;

[0028] If all second road condition sub-parameters meet the corresponding second preset sub-condition, it is determined that the second road condition parameter meets the preset second automatic driving road condition.

[0029] In one embodiment, the second road condition sub-parameter includes an automatic driving test number and an automatic driving completion number in the automatically drivable route; and the determination of whether the second road condition sub-parameter meets the corresponding second preset sub-condition includes:

[0030] determining whether the automatic driving test number is greater than a preset test number, and determining whether the automatic driving completion number is greater than a preset completion number, the preset test number being greater than or equal to the preset completion number;

[0031] If the automatic driving test number is greater than the preset test number and the automatic driving completion number is greater than the preset completion number, it is determined that the corresponding second preset sub-condition is met.

[0032] In one of the embodiments, the second road condition sub-parameter comprises a number of passing vehicles in a meeting vehicle, the number of passing vehicles in the meeting vehicle comprising a number of vehicles passing during a single meeting vehicle waiting period in the automatically drivable route; the determining whether the second road condition sub-parameter satisfies a corresponding second preset sub-condition comprises:

[0033] determining whether the number of passing vehicles in the meeting vehicle is less than a preset number of passing vehicles threshold;

[0034] if the number of passing vehicles in the meeting vehicle is less than the preset number of passing vehicles threshold, it is determined that the corresponding second preset sub-condition is satisfied.

[0035] In one of the embodiments, the second road condition sub-parameter comprises a number of passing vehicles at an intersection, the number of passing vehicles at the intersection comprising a number of vehicles passing in the same direction and a number of vehicles passing in the opposite direction at each intersection in the automatically drivable route; the determining whether the second road condition sub-parameter satisfies a corresponding second preset sub-condition comprises:

[0036] determining whether the number of vehicles passing in the same direction is less than a preset number of vehicles passing in the same direction threshold, and determining whether the number of vehicles passing in the opposite direction is less than a preset number of vehicles passing in the opposite direction threshold;

[0037] if the number of vehicles passing in the same direction is less than the preset number of vehicles passing in the same direction threshold and the number of vehicles passing in the opposite direction is less than the preset number of vehicles passing in the opposite direction threshold, it is determined that the corresponding second preset sub-condition is satisfied.

[0038] In one of the embodiments, the second road condition sub-parameter comprises a second network state parameter; the determining whether the second road condition sub-parameter satisfies a corresponding second preset sub-condition comprises:

[0039] determining a network state detection result of each second network detection point based on a second network state parameter of a plurality of second network detection points and a second network state threshold, wherein every two adjacent second network detection points are spaced apart by a fourth preset distance in the to-be-identified route;

[0040] determining a second network state qualification rate based on the network state detection result of all second network detection points and the number of second network detection points;

[0041] if the second network state qualification rate is greater than a second qualification rate threshold, it is determined that the corresponding second preset sub-condition is satisfied.

[0042] In one of the embodiments, the second road condition sub-parameter comprises a number of recognized pedestrians, the number of recognized pedestrians comprising a number of pedestrians recognized per fifth preset distance in the automatically drivable route; the determining whether the second road condition sub-parameter satisfies a corresponding second preset sub-condition comprises:

[0043] determining whether the number of pedestrians identified is less than a preset number threshold of pedestrians;

[0044] If the number of pedestrians identified is less than the preset number threshold of pedestrians, it is determined that the corresponding second preset sub-condition is met.

[0045] In one embodiment, the second road condition sub-parameter includes at least one pedestrian identification duration, the pedestrian identification duration including the duration of each time a pedestrian is identified in the automatically drivable route; and the determining whether the second road condition sub-parameter meets the corresponding second preset sub-condition includes:

[0046] determining, based on the at least one pedestrian identification duration, a cumulative pedestrian identification duration in the automatically drivable route;

[0047] determining whether the cumulative pedestrian identification duration is less than a preset duration threshold, and if it is less than the preset duration threshold, it is determined that the corresponding second preset sub-condition is met.

[0048] In a second aspect, the present application further provides an automatically drivable area identification device. The device includes:

[0049] a first road condition parameter acquisition module, configured to acquire a first road condition parameter, the first road condition parameter being a road condition parameter collected by a vehicle in a manual driving state while driving along a to-be-identified route in a to-be-identified area;

[0050] an automatically drivable route determination module, configured to determine whether the first road condition parameter meets a preset first automatic driving road condition, and if the first automatic driving road condition is met, it is determined that the to-be-identified route is an automatically drivable route;

[0051] a second road condition parameter acquisition module, configured to acquire a second road condition parameter in the case that it is determined that the to-be-identified route is an automatically drivable route, the second road condition parameter being a road condition parameter collected by the vehicle in an automatic driving state while driving along the automatically drivable route;

[0052] an automatically drivable area determination module, configured to determine whether the second road condition parameter meets a preset second automatic driving road condition, and if the second automatic driving road condition is met, it is determined that the to-be-identified area is an automatically drivable area.

[0053] In a third aspect, the present application further provides a computer readable storage medium. The computer readable storage medium has a computer program stored thereon, and the computer program, when executed by a processor, implements the steps of any of the automatically drivable area identification methods of the first aspect.

[0054] In a fourth aspect, the present application provides a vehicle device. The vehicle device comprises a memory and a processor, the memory stores a computer program, and the processor implements the steps of any of the automatic drivable area identification methods in the first aspect when executing the computer program.

[0055] The automatic drivable area identification method, device, storage medium and vehicle device described above first manually drive in the to-be-identified route and obtain first road condition parameters, determine whether the preset first automatic driving road condition condition is met, if the preset first automatic driving road condition condition is met, automatically drive along the automatic drivable route, and obtain second road condition parameters, and further determine whether the second road condition sub-parameters meet the preset second automatic driving road condition condition. The present application makes multiple judgments by obtaining the first road condition parameters and the second road condition parameters, fully considers the dynamically changing road condition, compared with the traditional technology, overcomes the limitation of the dependence on the static map in the traditional technology, and improves the flexibility, reliability and accuracy of the automatic drivable area identification.

[0056] The details of one or more embodiments of the present application are presented in the following drawings and description to make other features, objects and advantages of the present application more apparent. BRIEF DESCRIPTION OF DRAWINGS

[0057] The drawings described herein are intended to provide a further understanding of the present application, form a part of the present application, and explain the present application together with the description. The illustrative embodiments of the present application and their description serve to explain the present application without limiting the present application. In the drawings:

[0058] Figure 1 It is an application environment diagram of the automatic drivable area identification method in one embodiment;

[0059] Figure 2 It is a flowchart of the automatic drivable area identification method in one embodiment;

[0060] Figure 3 It is a flowchart of the automatic drivable area identification method in one embodiment;

[0061] Figure 4 It is a structural block diagram of the automatic drivable area identification device in one embodiment;

[0062] Figure 5 It is an internal structure diagram of the vehicle device in one embodiment. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical scheme and advantages of the present application more apparent, the present application is further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0064] The terms “module”, “unit”, etc., used below refer to a combination of software and / or hardware that can perform a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in hardware, implementation in software, or a combination of software and hardware, is also possible and contemplated.

[0065] The autonomous driving area identification method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, vehicle 102 is equipped with data acquisition device 104 and vehicle equipment 106. Figure 1 (Not shown in the image) Data acquisition device 104 may include camera equipment, lidar, etc., and vehicle equipment 106 includes a memory and a processor. Data acquisition device 104 acquires first road condition parameters and sends them to vehicle equipment 106. The first road condition parameters are road condition parameters collected by vehicle 102 while driving in manual mode along the route to be identified in the area to be identified. Vehicle equipment 106 determines whether the first road condition parameters meet preset first autonomous driving road condition conditions. If the first autonomous driving road condition conditions are met, the route to be identified is determined to be an autonomous driving route. If the route to be identified is determined to be an autonomous driving route, data acquisition device 104 acquires second road condition parameters and sends them to vehicle equipment 106. The second road condition parameters are road condition parameters collected by vehicle 102 while driving in autonomous mode along the autonomous driving route. Vehicle equipment 106 determines whether the second road condition parameters meet preset second autonomous driving road condition conditions. If the second autonomous driving road condition conditions are met, the area to be identified is determined to be an autonomous driving area. In other embodiments, the vehicle equipment may also connect to a cloud server network to send the first road condition parameters and the second road condition parameters to the cloud server, and the cloud server shall determine whether the first road condition parameters meet the preset first autonomous driving road condition conditions and whether the second road condition parameters meet the preset second autonomous driving road condition conditions.

[0066] In one embodiment, such as Figure 2 As shown, a method for identifying autonomous driving areas is provided, including the following steps:

[0067] S201: Obtain first road condition parameters, which are road condition parameters collected when the vehicle is driving in manual driving mode along the route to be identified in the area to be identified.

[0068] In the embodiments of the present application, the to-be-identified area can include a driving area and / or a parking area. The driving area can include a road for motor vehicles to travel on, and can also include a road for non-motor vehicles to travel on, a pedestrian road, and the like. The parking area can include a parking lot, a temporary parking area, and the like. The parking lot can include a road parking lot, an underground parking lot, or other parking areas where vehicles can be parked.

[0069] The to-be-identified route includes a vehicle travel route in the to-be-identified area, and whether the vehicle travel route is automatically drivable has not been determined. In some embodiments, a travel starting point and a travel ending point are determined in the to-be-identified area, and the to-be-identified route can be a travel route of the vehicle traveling from the travel starting point to the travel ending point. In other embodiments, if the to-be-identified area is a parking area, such as an underground parking lot, the to-be-identified route can be a travel route of the vehicle traveling from an entrance of the underground parking lot to a target parking space.

[0070] In the process of the vehicle traveling along the to-be-identified route in the to-be-identified area in the manual driving state, the first road condition parameter can be acquired. The first road condition parameter can include road condition information collected by the vehicle in the process of traveling along the to-be-identified route. In some embodiments, the first road condition parameter can include a plurality of first road condition sub-parameters, which can be a first network state parameter, a road width, an ambient light intensity, a minimum turning radius, an intersection spacing, and the like. The first road condition parameter can be used to determine whether the to-be-identified route meets the automatic driving condition.

[0071] In some embodiments, the first road condition parameter can be acquired by a data acquisition device arranged on the vehicle. Specifically, the road width, the minimum turning radius, the intersection spacing, and the like can be acquired by a vehicle-mounted radar, and the ambient light intensity and the like can be acquired by a light sensor. The present application does not limit the specific manner of acquiring the first road condition parameter.

[0072] S203: Determine whether the first road condition parameter meets a preset first automatic driving road condition. If the first road condition parameter meets the first automatic driving road condition, it is determined that the to-be-identified route is an automatically drivable route.

[0073] In the embodiments of the present application, by setting the preset first automatic driving road condition and determining whether the first road condition parameter meets the preset first automatic driving road condition, it can be determined whether the to-be-identified route is an automatically drivable route.

[0074] In some embodiments, if the first road condition parameter includes a plurality of first road condition sub-parameters, a first preset sub-condition can be set for each road condition sub-parameter respectively. If all the first road condition sub-parameters satisfy the first preset sub-condition, or a first preset number of first road condition sub-parameters satisfy the first preset sub-condition, it is determined that the to-be-identified route is an automatic driving route, otherwise it is determined that the to-be-identified route is not an automatic driving route. In other embodiments, a machine learning model or a deep learning model can also be used to determine whether the to-be-identified route is an automatic driving route. The model is trained by historical data. After inputting the first road condition parameter, the model can determine whether the first road condition parameter satisfies the preset first automatic driving road condition, and output the result that the to-be-identified route is an automatic driving route or not.

[0075] In some embodiments, the first road condition parameter includes a plurality of first road condition sub-parameters, and the first automatic driving road condition includes a plurality of first preset sub-conditions corresponding to the plurality of first road condition sub-parameters. The determination of whether the first road condition parameter satisfies the preset first automatic driving road condition includes:

[0076] S301: Determine whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition.

[0077] S303: If all the first road condition sub-parameters satisfy the corresponding first preset sub-condition, it is determined that the first road condition parameter satisfies the preset first automatic driving road condition.

[0078] In the embodiments of the present application, the first road condition parameter can include a plurality of first road condition sub-parameters, and a corresponding first preset sub-condition is set for each first road condition sub-parameter. It is determined whether each first road condition sub-parameter satisfies the corresponding first preset sub-condition. If all the first road condition sub-parameters satisfy the corresponding first preset sub-condition, it is determined that the first road condition parameter satisfies the preset first automatic driving road condition. If there is at least one first road condition sub-parameter that does not satisfy the corresponding first preset sub-condition, it is determined that the first road condition parameter does not satisfy the preset first automatic driving road condition.

[0079] S205: In the case where it is determined that the to-be-identified route is an automatic driving route, a second road condition parameter is obtained, which is a road condition parameter collected by the vehicle in an automatic driving state along the automatic driving route.

[0080] In the embodiments of the present application, in the case where it is determined that the to-be-identified route is an automatic driving route, it is further determined whether the to-be-identified area is an automatic driving area after testing along the automatic driving route in an automatic driving state.

[0081] The vehicle can obtain a second road condition parameter in the process of driving along the automatic driving route in the automatic driving state. The second road condition parameter can include road condition information collected by the vehicle in the process of driving along the automatic driving route. In some embodiments, the second road condition parameter can include a plurality of second road condition sub-parameters, and the second road condition sub-parameters can be the number of automatic driving tests and the number of automatic driving completions in the automatic driving route, the number of passing vehicles at the intersection, the number of passing vehicles at the intersection, the second network state parameter, the number of pedestrian identifications, the identification time of at least one pedestrian, and the like. The second road condition parameter can be used to further determine whether the to-be-identified region meets the automatic driving condition.

[0082] In some embodiments, the second road condition parameter can be obtained by a data collection device arranged on the vehicle. Specifically, the number of pedestrian identifications can be obtained by a vehicle-mounted camera, and the second network state parameter can be obtained by a vehicle-mounted network test device. The specific method of obtaining the second road condition parameter is not limited in the present application.

[0083] S207: Determine whether the second road condition parameter meets a preset second automatic driving road condition. If the second automatic driving road condition is met, the to-be-identified region is determined to be an automatic driving region.

[0084] In the embodiments of the present application, by setting a preset second automatic driving road condition and determining whether the second road condition parameter meets the preset second automatic driving road condition, it can be further determined whether the to-be-identified region is an automatic driving region.

[0085] In some embodiments, if the second road condition parameter includes a plurality of second road condition sub-parameters, a second preset sub-condition can be set for each second road condition sub-parameter. If all second road condition sub-parameters meet the second preset sub-condition, or a second preset number of second road condition sub-parameters meet the second preset sub-condition, the to-be-identified region is determined to be an automatic driving region, otherwise the to-be-identified region is determined to be a non-automatic driving region. In some other embodiments, a machine learning model or a deep learning model can be used to determine whether the to-be-identified region is an automatic driving region. The model is trained by historical data. After inputting the second road condition parameter, the model can determine whether the second road condition parameter meets the preset second automatic driving road condition and output the output result of the to-be-identified region being an automatic driving region or a non-automatic driving region.

[0086] In some embodiments, the second road condition parameter includes a plurality of second road condition sub-parameters, and the second automatic driving road condition includes a plurality of second preset sub-conditions corresponding to the plurality of second road condition sub-parameters. The determination of whether the second road condition parameter meets the preset second automatic driving road condition includes:

[0087] S401: Determine whether the second road condition sub-parameters meet the corresponding second preset sub-conditions.

[0088] S403: If all the second road condition sub-parameters meet the corresponding second preset sub-conditions, determine that the second road condition parameter meets the preset second automatic driving road condition.

[0089] In the embodiments of the present application, the second road condition parameter can include a plurality of second road condition sub-parameters, and a corresponding second preset sub-condition is set for each second road condition sub-parameter. It is determined whether each second road condition sub-parameter meets the corresponding second preset sub-condition. If all the second road condition sub-parameters meet the corresponding second preset sub-conditions, it is determined that the second road condition parameter meets the preset second automatic driving road condition. If there is at least one second road condition sub-parameter that does not meet the corresponding second preset sub-condition, it is determined that the second road condition parameter does not meet the preset second automatic driving road condition.

[0090] The automatic driving area identification method provided by the embodiments of the present application first manually drives in the to-be-identified route and obtains a first road condition parameter to determine whether the preset first automatic driving road condition is met. If the preset first automatic driving road condition is met, automatic driving is performed along the automatic driving route, and a second road condition parameter is obtained to further determine whether the second road condition sub-parameters meet the preset second automatic driving road condition. The present application makes multiple judgments on the road conditions of the to-be-identified area by obtaining the first road condition parameter and the second road condition parameter, fully considers the dynamically changing road conditions, and compared with the traditional technology, overcomes the limitations of the traditional technology on the static map, and improves the flexibility, reliability and accuracy of the automatic driving area identification.

[0091] The following describes an implementation manner of determining whether the first road condition sub-parameters meet the corresponding first preset sub-conditions through the embodiments of the present application.

[0092] In some embodiments, the first road condition sub-parameters include a first network state parameter; and the determination of whether the first road condition sub-parameters meet the corresponding first preset sub-conditions includes:

[0093] S501: Determine the network state detection result of each first network detection point based on the first network state parameters of the plurality of first network detection points and the first network state threshold value, wherein each two adjacent first network detection points are spaced apart by a first preset distance in the to-be-identified route.

[0094] S503: Determine the first network state qualification rate based on the network state detection results of all the first network detection points and the number of the first network detection points.

[0095] S505: If the first network state qualified rate is greater than a first qualified rate threshold, it is determined that the corresponding first preset sub-condition is met.

[0096] In the embodiments of the present application, whether the automatic driving condition is met can be determined by the network state on the to-be-identified route. The first road condition sub-parameter includes a first network state parameter, which can be a network signal strength value or a network uplink / downlink data second average transmission value, etc.

[0097] A plurality of first network detection points are set in the to-be-identified route, and the interval between every two adjacent first network detection points is a first preset distance. The first preset distance can also include a plurality of first preset sub-distances, each of which can be the same or different. That is, the interval between every two adjacent first network detection points can be the same or different. In some specific embodiments, the first preset distance can be 10 meters, that is, a first network detection point is set every 10 meters in the to-be-identified route.

[0098] The first network state parameter is obtained at each first network detection point, and the network state parameter of each first network detection point is compared with a first network state threshold to determine the network state detection result of each first network detection point. The network state detection result can include network state detection qualified or network state detection unqualified. In some specific embodiments, if the first network state parameter is a network signal strength value, for example, a signal strength value determined by a vehicle-mounted network module through network connection test with the cloud, when the network signal strength value is greater than a preset first network strength threshold, it is determined that the network state detection result of the network detection point is qualified, otherwise the network state detection result is unqualified.

[0099] Based on the network state detection results of all first network detection points and the number of first network detection points, a first network state qualified rate is determined. In some specific embodiments, the first network state qualified rate can be determined by dividing the number of first network detection points with qualified network state detection results by the number of first network detection points.

[0100] If the first network state qualified rate is greater than a first qualified rate threshold, it is determined that the corresponding first preset sub-condition is met. Specifically, if there are 100 network detection points in total, and the detection results of 96 network detection points are qualified, the first network state qualified rate is 96 / 100=96%. If the first qualified rate threshold is set to 95%, the first network state qualified rate is greater than the first qualified rate threshold, and it is determined that the corresponding first preset sub-condition is met.

[0101] The application sets network detection points and a first qualified rate threshold in the to-be-identified route, judges the overall network connection state on the to-be-identified route, determines that the first road condition sub-parameter meets the corresponding first preset sub-condition in the case that the network connection state is good, that is, meets the judgment requirement of automatic driving, can fully consider the network connection state in the actual road condition, and thus improves the reliability and accuracy of the automatic driving area identification.

[0102] In some embodiments, the first road condition sub-parameter comprises a road width; and the determining whether the first road condition sub-parameter meets the corresponding first preset sub-condition comprises:

[0103] S601: Determine whether the road width of each road width detection point is greater than the road width threshold based on the road width of the plurality of road width detection points and the road width threshold, wherein every two adjacent road width detection points are spaced apart by a second preset distance in the to-be-identified route.

[0104] S603: If the road width of all road width detection points is greater than the road width threshold, it is determined that the corresponding first preset sub-condition is met.

[0105] In the embodiments of the application, whether the automatic driving condition is met can be determined by the road width on the to-be-identified route. The first road condition sub-parameter comprises a road width. It can be understood that the wider the road width, the higher the safety of vehicle automatic driving.

[0106] A plurality of road width detection points are set in the to-be-identified route, and every two adjacent road width detection points are spaced apart by a second preset distance. The second preset distance can comprise a plurality of second preset sub-distances, and each second preset sub-distance can be the same or different. That is, the interval between every two adjacent road width detection points can be the same or different. In some specific embodiments, the second preset distance can be 10 meters, that is, a road width detection point is set every 10 meters in the to-be-identified route.

[0107] The road width of each road width detection point is obtained, and the road width of each road width detection point is compared with the road width threshold to determine whether the road width of each road width detection point is greater than the road width threshold. If the road width of all road width detection points is greater than the road width threshold, it is determined that the corresponding first preset sub-condition is met. In some specific embodiments, the road condition threshold can be set to 6 meters.

[0108] The application sets road width detection points and a road width threshold in the to-be-identified route, judges the overall road width condition on the to-be-identified route, determines that the first road condition sub-parameter meets the corresponding first preset sub-condition when the road width meets the condition, that is, meets the judgment requirement of automatic driving, can fully consider the road width in the actual road condition, and thus improves the reliability and accuracy of the automatic driving area identification.

[0109] In some embodiments, the first road condition sub-parameter comprises an ambient light intensity; and the determining whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition comprises:

[0110] S701: Based on the ambient light intensity of the plurality of light intensity detection points and the light intensity threshold, respectively determine whether the ambient light intensity of each light intensity detection point is greater than the light intensity threshold, wherein every two adjacent light intensity detection points are spaced apart by a third preset distance in the to-be-identified route.

[0111] S703: If the ambient light intensity of all light intensity detection points is greater than the light intensity threshold, it is determined that the corresponding first preset sub-condition is satisfied.

[0112] In the embodiments of the present application, it can be determined whether the automatic driving condition is satisfied by the ambient light intensity on the to-be-identified route. The first road condition sub-parameter comprises the ambient light intensity. It can be understood that the ambient light intensity needs to satisfy the light condition of the vehicle data acquisition device, and thus the automatic driving of the vehicle is realized.

[0113] A plurality of light intensity detection points are set in the to-be-identified route, and every two adjacent light intensity detection points are spaced apart by a third preset distance. The third preset distance can also comprise a plurality of third preset sub-distances, and each third preset sub-distance can be the same or different. That is, the interval between every two adjacent light intensity detection points can be the same or different. In some specific embodiments, the third preset distance can be 10 meters, that is, a light intensity detection point is set every 10 meters in the to-be-identified route.

[0114] The ambient light intensity of each light intensity detection point is obtained, and the ambient light intensity of each light intensity detection point is compared with the light intensity threshold to respectively determine whether the ambient light intensity of each light intensity detection point is greater than the light intensity threshold. If the ambient light intensity of all light intensity detection points is greater than the light intensity threshold, it is determined that the corresponding first preset sub-condition is satisfied. In some specific embodiments, the light intensity threshold can be set to 80 LUX.

[0115] The present application sets the light intensity detection points and the light intensity threshold in the to-be-identified route to determine the overall ambient light intensity on the to-be-identified route. When the ambient light intensity satisfies the condition, it is determined that the first road condition sub-parameter satisfies the corresponding first preset sub-condition, that is, it meets the judgment requirement of automatic driving. The ambient light intensity in the actual road condition can be fully considered, and thus the reliability and accuracy of the automatic driving area recognition are improved.

[0116] In some embodiments, the first road condition sub-parameter includes a minimum turning radius and an intersection distance, the intersection distance including a distance between each two adjacent intersections in the to-be-identified route; the determining whether the first road condition sub-parameter satisfies a corresponding first preset sub-condition includes:

[0117] S801: determining whether a minimum turning radius of each intersection in the to-be-identified route is greater than a radius threshold value, and determining whether the intersection distance is greater than an intersection distance threshold value.

[0118] S803: if the minimum turning radius of all intersections is greater than the radius threshold value and the intersection distance is greater than the intersection distance threshold value, it is determined that a corresponding first preset sub-condition is satisfied.

[0119] In the embodiments of the present application, whether the automatic driving condition is satisfied can be determined by the minimum turning radius and the intersection distance on the to-be-identified route. The first road condition sub-parameter includes the minimum turning radius and the intersection distance. It can be understood that the greater the minimum turning radius and the intersection distance, the higher the safety of automatic driving of the vehicle.

[0120] The minimum turning radius of each intersection in the to-be-identified route is determined whether it is greater than a radius threshold value, and the intersection distance is determined whether it is greater than an intersection distance threshold value. The intersection can include a corner intersection, a T-shaped intersection, a cross intersection, etc. in the to-be-identified route. The intersection distance includes a distance between each two adjacent intersections in the to-be-identified route.

[0121] If the minimum turning radius of all intersections is greater than the radius threshold value and the intersection distance is greater than the intersection distance threshold value, it is determined that a corresponding first preset sub-condition is satisfied. In some specific embodiments, the radius threshold value can be 6 meters, and the intersection distance threshold value can be 100 meters.

[0122] The present application determines that the first road condition sub-parameter satisfies the corresponding first preset sub-condition when the intersection distance and the intersection density on the to-be-identified route both meet the requirements, that is, it meets the judgment requirements of automatic driving. The difficulty of automatic driving through the intersection in the actual road condition is fully considered, and the reliability and accuracy of the automatic driving area recognition are improved.

[0123] The following describes an implementation manner of determining whether a second road condition sub-parameter satisfies a corresponding second preset sub-condition in a case where the to-be-identified route is determined to be an automatic driving route.

[0124] In some embodiments, the second road condition sub-parameter includes an automatic driving test number and an automatic driving completion number in the automatic driving route; the determining whether the second road condition sub-parameter satisfies a corresponding second preset sub-condition includes:

[0125] S901: Determine whether the number of automatic driving tests is greater than a preset number of tests, and determine whether the number of automatic driving completions is greater than a preset number of completions, the preset number of tests being greater than or equal to the preset number of completions.

[0126] S903: If the number of automatic driving tests is greater than the preset number of tests and the number of automatic driving completions is greater than the preset number of completions, it is determined that the corresponding second preset sub-condition is met.

[0127] In the embodiments of the present application, in the case of determining that the to-be-identified route is an automatically drivable route, the vehicle needs to be controlled to drive along the automatically drivable route multiple times in an automatic driving state and obtain a second road condition parameter, so as to further determine whether the to-be-identified area meets the condition of automatic driving.

[0128] The second road condition sub-parameter includes the number of automatic driving tests and the number of automatic driving completions in the automatically drivable route. The number of automatic driving tests can be the number of attempts to drive along the automatically drivable route. If the automatic driving function is terminated before reaching the end of the automatically drivable route, or successfully drives to the end of the automatically drivable route, the number of automatic driving tests is increased by 1. The number of automatic driving completions is the number of times of driving along the automatically drivable route from the start of the automatically drivable route to the end of the automatically drivable route.

[0129] If the number of automatic driving tests is greater than the preset number of tests and the number of automatic driving completions is greater than the preset number of completions, it is determined that the corresponding second preset sub-condition is met. In some specific embodiments, the preset number of tests is 5 and the preset number of completions is 3, that is, 3 times of completion in 5 times of automatic driving test are considered to meet the corresponding second preset sub-condition.

[0130] In the embodiments of the present application, by performing automatic driving test multiple times on the automatically drivable route in the to-be-identified area, it is further determined whether the actual road condition meets the automatic driving condition through the number of automatic driving tests and the number of automatic driving completions, which effectively improves the reliability and accuracy of the identification of the automatically drivable area.

[0131] In some embodiments, the second road condition sub-parameter includes the number of passing vehicles, which includes the number of vehicles passing during a single passing waiting period in the automatically drivable route; and the determination of whether the second road condition sub-parameter meets the corresponding second preset sub-condition includes:

[0132] S1001: Determine whether the number of passing vehicles is less than a preset passing vehicle number threshold.

[0133] S1003: If the number of passing vehicles in the meeting vehicle is less than the preset passing vehicle number threshold, it is determined that the corresponding second preset sub-condition is met.

[0134] In the embodiments of the present application, whether the automatic driving condition is met can be determined by the number of passing vehicles in the meeting vehicle in the to-be-identified region. The second road condition sub-parameter includes the number of passing vehicles in the meeting vehicle, which includes the number of vehicles passing during a single meeting vehicle waiting period on the automatic driving route. Specifically, the number of passing vehicles in the meeting vehicle can be the sum of the number of passing vehicles and the number of counter vehicles detected when the vehicle is in a single meeting vehicle deceleration or stop state.

[0135] Whether the number of passing vehicles in the meeting vehicle is less than the preset passing vehicle number threshold is determined, and if the number of passing vehicles in the meeting vehicle is less than the preset passing vehicle number threshold, it is determined that the corresponding second preset sub-condition is met. In some specific embodiments, the vehicle number threshold can be 3.

[0136] By obtaining the number of passing vehicles in the meeting vehicle, the embodiments of the present application can determine the size of the traffic flow in the actual road condition of the to-be-identified region, further determine whether the actual road condition meets the automatic driving condition, and effectively improve the reliability and accuracy of the automatic driving region identification.

[0137] In some embodiments, the second road condition sub-parameter includes the number of passing vehicles at the intersection, the number of passing vehicles at the intersection includes the number of same-direction vehicles and the number of counter vehicles at each intersection on the automatic driving route; and the determination of whether the second road condition sub-parameter meets the corresponding second preset sub-condition includes:

[0138] S1101: Determine whether the number of same-direction vehicles is less than a preset same-direction vehicle number threshold, and determine whether the number of counter vehicles is less than a preset counter vehicle number threshold.

[0139] S1103: If the number of same-direction vehicles is less than the preset same-direction vehicle number threshold and the number of counter vehicles is less than the preset counter vehicle number threshold, it is determined that the corresponding second preset sub-condition is met.

[0140] In the embodiments of the present application, whether the automatic driving condition is met can be determined by the number of passing vehicles in the meeting vehicle in the to-be-identified region. The second road condition sub-parameter includes the number of passing vehicles in the meeting vehicle, which includes the number of vehicles passing during a single meeting vehicle waiting period on the automatic driving route. Specifically, the number of passing vehicles in the meeting vehicle can be the sum of the number of passing vehicles and the number of counter vehicles detected when the vehicle is in a single meeting vehicle deceleration or stop state.

[0141] determining whether the number of the same-direction vehicles is less than a preset same-direction vehicle number threshold and determining whether the number of the opposite-direction vehicles is less than a preset opposite-direction vehicle number threshold. If the number of the same-direction vehicles is less than the preset same-direction vehicle number threshold and the number of the opposite-direction vehicles is less than the preset opposite-direction vehicle number threshold, it is determined that the corresponding second preset sub-condition is met. In some embodiments, the same-direction vehicle number threshold can be 3 and the opposite-direction vehicle number threshold can be 3.

[0142] By obtaining the number of vehicles passing through the intersection, the embodiments of the present application can determine the size of the traffic flow of the intersection in the actual road condition of the to-be-identified region, further determine whether the actual road condition meets the automatic driving condition, and effectively improve the reliability and accuracy of the automatic driving region identification.

[0143] In some embodiments, the second road condition sub-parameter includes a second network state parameter; and the determining whether the second road condition sub-parameter meets the corresponding second preset sub-condition includes:

[0144] S1201: determining a network state detection result of each second network detection point based on the second network state parameters of the plurality of second network detection points and the second network state threshold, wherein every two adjacent second network detection points are spaced apart by a fourth preset distance in the to-be-identified route.

[0145] S1203: determining a second network state qualification rate based on the network state detection results of all the second network detection points and the number of the second network detection points.

[0146] S1205: if the second network state qualification rate is greater than a second qualification rate threshold, it is determined that the corresponding second preset sub-condition is met.

[0147] In the embodiments of the present application, the network state on the automatic driving route can be used to further determine whether the automatic driving condition is met. The second road condition sub-parameter includes a second network state parameter, which can be a network signal strength value or a network uplink / downlink data second average transmission value.

[0148] A plurality of second network detection points are arranged in the to-be-identified route, and every two adjacent second network detection points are spaced apart by a fourth preset distance. The fourth preset distance can include a plurality of fourth preset sub-distances, and each fourth preset sub-distance can be the same or different. That is, the interval between every two adjacent second network detection points can be the same or different. In some embodiments, the fourth preset distance can be 10 meters, that is, a second network detection point is arranged every 10 meters in the to-be-identified route.

[0149] At each second network detection point, a second network state parameter is acquired, and the network state parameter of each second network detection point is compared with a second network state threshold value to determine a network state detection result of each second network detection point. The network state detection result can include a network state detection qualified result or a network state detection unqualified result. In some embodiments, if the second network state parameter is a network signal strength value, for example, a signal strength value determined by a vehicle-mounted network module through network connection test with the cloud, when the network signal strength value is greater than a preset second network strength threshold value, it is determined that the network state detection result of the network detection point is qualified, otherwise, it is determined that the network state detection result is unqualified.

[0150] Based on the network state detection results of all second network detection points and the number of second network detection points, a second network state qualified rate is determined. In some embodiments, the second network state qualified rate can be determined by dividing the number of second network detection points with qualified network state detection results by the number of second network detection points.

[0151] If the second network state qualified rate is greater than a second qualified rate threshold value, it is determined that the corresponding second preset sub-condition is met. Specifically, if there are 100 network detection points in total and the detection results of 98 network detection points are qualified, the second network state qualified rate is 98 / 100 = 98%. If the second qualified rate threshold value is set to 95%, the second network state qualified rate is greater than the second qualified rate threshold value, and it is determined that the corresponding second preset sub-condition is met.

[0152] The present application further judges the overall network connection state on the automatic driving route by setting second network detection points and a second qualified rate threshold value on the automatic driving route, determines that the second road condition sub-parameter meets the corresponding second preset sub-condition in the case of good network connection state, that is, meets the judgment requirements of automatic driving, can further verify the network connection state in the actual road condition, and thus improves the reliability and accuracy of automatic driving area recognition.

[0153] In some embodiments, the second road condition sub-parameter includes a pedestrian recognition number, the pedestrian recognition number includes a number of pedestrians recognized every fifth preset distance of driving on the automatic driving route, and the judgment of whether the second road condition sub-parameter meets the corresponding second preset sub-condition includes:

[0154] S1301: judging whether the pedestrian recognition number is less than a preset pedestrian number threshold value.

[0155] S1303: if the pedestrian recognition number is less than the preset pedestrian number threshold value, it is determined that the corresponding second preset sub-condition is met.

[0156] In the embodiments of the present application, whether the automatic driving condition is met can be determined by the number of pedestrians identified in the to-be-identified area. The second road condition sub-parameter includes the number of pedestrians identified, and the number of pedestrians identified includes the number of pedestrians identified every fifth preset distance in the automatic driving route.

[0157] Whether the number of pedestrians identified is less than a preset number of pedestrians threshold is determined, and if the number of pedestrians identified is less than the preset number of pedestrians threshold, it is determined that the corresponding second preset sub-condition is met. In some specific embodiments, the fifth preset distance can be 20 meters, and the number of pedestrians threshold can be 3. If the number of pedestrians identified every 20 meters in the automatic driving route is less than 3, it is determined that the corresponding second preset sub-condition is met.

[0158] In the embodiments of the present application, by obtaining the number of pedestrians identified, the size of the human flow in the actual road condition of the to-be-identified area can be determined, and whether the actual road condition meets the automatic driving condition is further determined, thereby effectively improving the reliability and accuracy of the automatic driving area identification.

[0159] In some embodiments, the second road condition sub-parameter includes at least one pedestrian identification time length, and the pedestrian identification time length includes the duration of each time a pedestrian is identified in the automatic driving route; and the determination of whether the second road condition sub-parameter meets the corresponding second preset sub-condition includes:

[0160] S1401: determining the cumulative pedestrian identification time length in the automatic driving route based on the at least one pedestrian identification time length.

[0161] S1403: determining whether the cumulative pedestrian identification time length is less than a preset time length threshold, and if it is less than the preset time length threshold, it is determined that the corresponding second preset sub-condition is met.

[0162] In the embodiments of the present application, whether the automatic driving condition is met can be determined by the pedestrian identification time length in the to-be-identified area. The second road condition sub-parameter includes at least one pedestrian identification time length, and the pedestrian identification time length includes the duration of each time a pedestrian is identified in the automatic driving route. Specifically, the vehicle travels along the automatic driving route in the automatic driving state, and each time a pedestrian is detected, the timing start point is determined, and the timing end point is determined until there is no pedestrian in the detection range, and the pedestrian identification time length is the duration from the timing start point to the timing end point.

[0163] The cumulative pedestrian identification time length in the automatic driving route is determined based on the at least one pedestrian identification time length, and specifically, all pedestrian identification time lengths are added to determine the cumulative pedestrian identification time length. Whether the cumulative pedestrian identification time length is less than a preset time length threshold is determined, and if it is less than the preset time length threshold, it is determined that the corresponding second preset sub-condition is met. In some specific embodiments, the preset time length threshold can be 3 minutes.

[0164] The following specific embodiments illustrate the implementation of the autonomous driving area identification method.

[0165] like Figure 3 As shown, after creating the route to be identified in the area to be identified, the network status is acquired every 10m during vehicle travel and its compliance is determined. The road width and ambient light intensity are also acquired every 10m. The minimum turning radius of each intersection on the route to be identified and the number of intersections passed every 100m are also acquired, and judgments are made based on the aforementioned first road condition parameters. If the network status compliance rate of the route to be identified is greater than 95%, all road widths are greater than or equal to 6m, all ambient light intensities are greater than or equal to 80LUX, the minimum turning radius of all intersections is greater than or equal to 6m, and the number of intersections passed every 100m is less than or equal to 1, then the route to be identified is determined to be a route suitable for autonomous driving. If at least one of the above judgment conditions is not met, then the route to be identified is determined to be a route unsuitable for autonomous driving.

[0166] Furthermore, the autonomous driving route is verified to determine whether the area to be identified is an autonomous driving area. The vehicle is controlled to drive continuously on the autonomous driving route 5 times in autonomous driving mode, and the number of successful journeys to the destination is determined to be greater than 3 times. The vehicle is controlled to drive continuously on the autonomous driving route 3 times in autonomous driving mode, and the number of vehicles passing by in a single waiting time when meeting oncoming traffic is determined to be less than or equal to 4. When the vehicle is within 5 meters of an intersection, the total number of vehicles traveling in the same direction and in the opposite direction when the vehicle stops at each intersection is determined to be less than or equal to 3. The number of different pedestrians identified within every 20 meters of travel is determined to be less than or equal to 3. The cumulative duration of continuous pedestrian identification is determined to be less than or equal to 3 minutes. The network status is acquired every 10 meters and its compliance is determined, and the network status compliance rate is determined to be greater than 95%. If all the above conditions are met, the area to be identified is determined to be an autonomous driving area; if at least one of the above conditions is not met, the area to be identified is determined to be a non-autonomous driving area.

[0167] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0168] Based on the same inventive concept, the embodiments of the present application also provide an automatic drivable area identification device 1900 for implementing the automatic drivable area identification method described above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more automatic drivable area identification device 1900 embodiments provided below can refer to the limitations of the automatic drivable area identification method described above, which will not be repeated here.

[0169] In one embodiment, as shown in FIG. 19, an automatic drivable area identification device 1900 is provided, comprising: Figure 4

[0170] A first road condition parameter acquisition module 1901 is configured to acquire a first road condition parameter, wherein the first road condition parameter is a road condition parameter collected by a vehicle in a manual driving state while driving along a to-be-identified route in a to-be-identified area.

[0171] An automatic drivable route judgment module 1902 is configured to judge whether the first road condition parameter meets a preset first automatic driving road condition, and if the first automatic driving road condition is met, determine that the to-be-identified route is an automatic drivable route.

[0172] A second road condition parameter acquisition module 1903 is configured to acquire a second road condition parameter under the condition that the to-be-identified route is determined to be an automatic drivable route, wherein the second road condition parameter is a road condition parameter collected by the vehicle while driving along the automatic drivable route in an automatic driving state.

[0173] An automatic drivable area judgment module 1904 is configured to judge whether the second road condition parameter meets a preset second automatic driving road condition, and if the second automatic driving road condition is met, determine that the to-be-identified area is an automatic drivable area.

[0174] In some embodiments, the first road condition parameter comprises a plurality of first road condition sub-parameters, and the first automatic driving road condition comprises a plurality of first preset sub-conditions corresponding to the plurality of first road condition sub-parameters; the automatic drivable route judgment module 1902 is further configured to judge whether the first road condition sub-parameters meet the corresponding first preset sub-conditions; and if all first road condition sub-parameters meet the corresponding first preset sub-conditions, it is judged that the first road condition parameter meets the preset first automatic driving road condition.

[0175] ​In some embodiments, the first road condition sub-parameter comprises a first network state parameter; the automatic drivable route determining module 1902 is further configured to determine a network state detection result of each first network detection point based on the first network state parameter of the first network detection point and a first network state threshold, wherein every two adjacent first network detection points are spaced apart by a first preset distance in the to-be-identified route; determine a first network state qualification rate based on the network state detection results of all first network detection points and the number of first network detection points; and determine that the corresponding first preset sub-condition is met if the first network state qualification rate is greater than a first qualification rate threshold.

[0176] In some embodiments, the first road condition sub-parameter comprises a road width; the automatic drivable route determining module 1902 is further configured to determine whether the road width of each road width detection point is greater than a road width threshold based on the road width of the road width detection point and the road width threshold, wherein every two adjacent road width detection points are spaced apart by a second preset distance in the to-be-identified route; and determine that the corresponding first preset sub-condition is met if the road width of all road width detection points is greater than the road width threshold.

[0177] In some embodiments, the first road condition sub-parameter comprises an ambient light intensity; the automatic drivable route determining module 1902 is further configured to determine whether the ambient light intensity of each light intensity detection point is greater than a light intensity threshold based on the ambient light intensity of the light intensity detection point and the light intensity threshold, wherein every two adjacent light intensity detection points are spaced apart by a third preset distance in the to-be-identified route; and determine that the corresponding first preset sub-condition is met if the ambient light intensity of all light intensity detection points is greater than the light intensity threshold.

[0178] In some embodiments, the first road condition sub-parameter comprises a minimum turning radius and an intersection distance, the intersection distance comprising a distance between every two adjacent intersections in the to-be-identified route; the automatic drivable route determining module 1902 is further configured to determine whether the minimum turning radius of each intersection in the to-be-identified route is greater than a radius threshold, and determine whether the intersection distance is greater than an intersection distance threshold; and determine that the corresponding first preset sub-condition is met if the minimum turning radius of all intersections is greater than the radius threshold and the intersection distance is greater than the intersection distance threshold.

[0179] In some embodiments, the second road condition parameter includes a plurality of second road condition sub-parameters, and the second automatic driving road condition includes a plurality of second preset sub-conditions corresponding to the plurality of second road condition sub-parameters; the automatic drivable area determining module 1904 is further configured to determine whether the second road condition sub-parameters satisfy corresponding second preset sub-conditions; if all the second road condition sub-parameters satisfy corresponding second preset sub-conditions, it is determined that the second road condition parameter satisfies the preset second automatic driving road condition.

[0180] In some embodiments, the second road condition sub-parameters include a number of automatic driving tests and a number of automatic driving completions on the automatic drivable route; the automatic drivable area determining module 1904 is further configured to determine whether the number of automatic driving tests is greater than a preset test number, and determine whether the number of automatic driving completions is greater than a preset completion number, wherein the preset test number is greater than or equal to the preset completion number; if the number of automatic driving tests is greater than the preset test number and the number of automatic driving completions is greater than the preset completion number, it is determined that the corresponding second preset sub-condition is satisfied.

[0181] In some embodiments, the second road condition sub-parameters include a number of meeting vehicles, which includes a number of vehicles passing during a single meeting waiting period on the automatic drivable route; the automatic drivable area determining module 1904 is further configured to determine whether the number of meeting vehicles is less than a preset passing vehicle number threshold; if the number of meeting vehicles is less than the preset passing vehicle number threshold, it is determined that the corresponding second preset sub-condition is satisfied.

[0182] In some embodiments, the second road condition sub-parameters include a number of intersection vehicles, which includes a number of vehicles passing in the same direction and a number of vehicles passing in the opposite direction at each intersection on the automatic drivable route; the automatic drivable area determining module 1904 is further configured to determine whether the number of vehicles passing in the same direction is less than a preset same direction vehicle number threshold, and determine whether the number of vehicles passing in the opposite direction is less than a preset opposite direction vehicle number threshold; if the number of vehicles passing in the same direction is less than the preset same direction vehicle number threshold and the number of vehicles passing in the opposite direction is less than the preset opposite direction vehicle number threshold, it is determined that the corresponding second preset sub-condition is satisfied.

[0183] In some embodiments, the second road condition sub-parameter comprises a second network state parameter; the automatic drivable area determining module 1904 is further configured to determine a network state detection result of each second network detection point based on the second network state parameter of the second network detection point and a second network state threshold, wherein each two adjacent second network detection points are spaced apart by a fourth preset distance in the to-be-identified route; determine a second network state qualified rate based on the network state detection results of all second network detection points and the number of second network detection points; and determine that the corresponding second preset sub-condition is met if the second network state qualified rate is greater than a second qualified rate threshold.

[0184] In some embodiments, the second road condition sub-parameter comprises a number of pedestrians identified, which comprises a number of pedestrians identified per fifth preset distance in the automatic drivable route; the automatic drivable area determining module 1904 is further configured to determine whether the number of pedestrians identified is less than a preset number of pedestrians threshold; and determine that the corresponding second preset sub-condition is met if the number of pedestrians identified is less than the preset number of pedestrians threshold.

[0185] In some embodiments, the second road condition sub-parameter comprises at least one pedestrian identification duration, which comprises a duration of each time a pedestrian is identified in the automatic drivable route; the automatic drivable area determining module 1904 is further configured to determine a cumulative pedestrian identification duration in the automatic drivable route based on the at least one pedestrian identification duration; determine whether the cumulative pedestrian identification duration is less than a preset duration threshold, and determine that the corresponding second preset sub-condition is met if the cumulative pedestrian identification duration is less than the preset duration threshold.

[0186] The above-mentioned various modules in the automatic drivable area identification apparatus 1900 can be all or part realized by software, hardware and combinations thereof. The above-mentioned various modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a memory in a computer device in software form, so as to be called and executed by a processor to perform the operations corresponding to the above-mentioned various modules.

[0187] In one embodiment, a vehicle device is provided, and an internal structure diagram of the vehicle device can be as shown in Figure 5The vehicle device includes a processor, a memory and a network interface connected through a system bus. The processor of the vehicle device is configured to provide computing and control capabilities. The memory of the vehicle device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The database of the vehicle device is configured to store data. The network interface of the vehicle device is configured to communicate with an external terminal through a network connection. The computer program, when executed by the processor, implements an automatic drivable area identification method.

[0188] Those skilled in the art can understand that, Figure 5 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the vehicle device to which the scheme of the present application is applied. The specific vehicle device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0189] In one embodiment, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. The computer program, when executed by a processor, implements the steps of any of the automatic drivable area identification methods in the first aspect.

[0190] In one embodiment, a computer program product is provided, and the computer program product includes a computer program. The computer program, when executed by a processor, implements the steps of any of the automatic drivable area identification methods in the first aspect.

[0191] Unless otherwise defined, technical terms and scientific terms used in the present application shall have the same meaning as those commonly understood by a person skilled in the art to which the present application belongs. In the present application, the terms "one", "a", "an", "the", "these", and similar words do not indicate a quantity restriction, and they can be singular or plural. In the present application, the terms "include", "contain", "have", and any variants thereof are intended to cover non-exclusive inclusion; for example, a process, method, and system, product or device containing a series of steps or modules (units) are not limited to the listed steps or modules (units), but can include steps or modules (units) not listed, or can include other steps or modules (units) inherent to the process, method, product or device. In the present application, the terms "connect", "connected", "coupled" and the like do not limit to physical or mechanical connection, but can include electrical connection, whether direct or indirect. In the present application, "multiple" means two or more. "And / or" describes the association between the associated objects, which means that there can be three relationships, for example, "A and / or B" can mean that A exists alone, A and B exist together, and B exists alone. Generally, the character " / " represents an "or" relationship between the associated objects. In the present application, the terms "first", "second", "third", and the like are only used to distinguish similar objects, and do not represent a specific order for the objects.

[0192] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties.

[0193] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0194] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist, it should be considered as the scope of the present application.

[0195] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for identifying autonomous driving areas, characterized in that, The method includes: Obtain the first road condition parameter, which is the road condition parameter collected when the vehicle is driving in manual driving mode along the route to be identified in the area to be identified. Determine whether the first road condition parameter meets the preset first autonomous driving road condition. If it meets the first autonomous driving road condition, then determine that the route to be identified is an autonomous driving route. If the route to be identified is determined to be an autonomous driving route, a second road condition parameter is obtained. The second road condition parameter is the road condition parameter collected by the vehicle while driving along the autonomous driving route in autonomous driving mode. Determine whether the second road condition parameter meets the preset second autonomous driving road condition conditions. If it meets the second autonomous driving road condition conditions, then determine that the area to be identified is an area where autonomous driving is possible.

2. The method according to claim 1, characterized in that, The first road condition parameter includes multiple first road condition sub-parameters, and the first autonomous driving road condition includes multiple first preset sub-conditions corresponding to the multiple first road condition sub-parameters; determining whether the first road condition parameter meets the preset first autonomous driving road condition includes: Determine whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition; If all first road condition sub-parameters satisfy the corresponding first preset sub-conditions, then it is determined that the first road condition parameters satisfy the preset first autonomous driving road condition conditions.

3. The method according to claim 2, characterized in that, The first traffic condition sub-parameter includes a first network state parameter; determining whether the first traffic condition sub-parameter satisfies the corresponding first preset sub-condition includes: Based on the first network state parameters and the first network state threshold of multiple first network detection points, the network state detection result of each first network detection point is determined respectively, wherein every two adjacent first network detection points are separated by a first preset distance in the route to be identified; The first network status pass rate is determined based on the network status detection results of all first network detection points and the number of first network detection points. If the first network status pass rate is greater than the first pass rate threshold, then the corresponding first preset sub-condition is determined to be met.

4. The method according to claim 2, characterized in that, The first road condition sub-parameter includes road width; determining whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition includes: Based on the road width and road width threshold of multiple road width detection points, it is determined whether the road width of each road width detection point is greater than the road width threshold. In this case, every two adjacent road width detection points are separated by a second preset distance in the route to be identified. If the road width at all road width detection points is greater than the road width threshold, then the corresponding first preset sub-condition is determined to be satisfied.

5. The method according to claim 2, characterized in that, The first road condition sub-parameter includes ambient light intensity; determining whether the first road condition sub-parameter satisfies the corresponding first preset sub-condition includes: Based on the ambient light intensity and light intensity threshold of multiple light intensity detection points, it is determined whether the ambient light intensity of each light intensity detection point is greater than the light intensity threshold. In this case, every two adjacent light intensity detection points are spaced apart by a third preset distance in the route to be identified. If the ambient light intensity at all light intensity detection points is greater than the light intensity threshold, then the corresponding first preset sub-condition is determined to be met.

6. The method according to claim 2, characterized in that, The first traffic condition sub-parameters include the minimum turning radius and the intersection spacing, wherein the intersection spacing includes the distance between every two adjacent intersections in the route to be identified; the step of determining whether the first traffic condition sub-parameters meet the corresponding first preset sub-condition includes: Determine whether the minimum turning radius of each intersection in the route to be identified is greater than a radius threshold, and determine whether the intersection spacing is greater than an intersection spacing threshold; If the minimum turning radius of all intersections is greater than the radius threshold and the intersection spacing is greater than the intersection spacing threshold, then the corresponding first preset sub-condition is determined to be satisfied.

7. The method according to claim 1, characterized in that, The second road condition parameter includes multiple second road condition sub-parameters, and the second autonomous driving road condition includes multiple second preset sub-conditions corresponding to the multiple second road condition sub-parameters; determining whether the second road condition parameter meets the preset second autonomous driving road condition includes: Determine whether the second road condition sub-parameter satisfies the corresponding second preset sub-condition; If all second road condition sub-parameters satisfy the corresponding second preset sub-conditions, then it is determined that the second road condition parameters satisfy the preset second autonomous driving road condition conditions.

8. The method according to claim 7, characterized in that, The second road condition sub-parameter includes the number of autonomous driving tests and the number of autonomous driving completions on the autonomous driving route; determining whether the second road condition sub-parameter meets the corresponding second preset sub-condition includes: Determine whether the number of autonomous driving tests is greater than the preset number of tests, and determine whether the number of autonomous driving completions is greater than the preset number of completions, wherein the preset number of tests is greater than or equal to the preset number of completions; If the number of autonomous driving tests is greater than the preset number of tests and the number of autonomous driving completions is greater than the preset number of completions, then the corresponding second preset sub-condition is determined to be satisfied.

9. The method according to claim 7, characterized in that, The second road condition sub-parameter includes the number of oncoming vehicles passing through, which includes the number of vehicles passing through during a single oncoming vehicle waiting period on the automated driving route. The step of determining whether the second road condition sub-parameter satisfies the corresponding second preset sub-condition includes: Determine whether the number of vehicles passing each other is less than a preset threshold for the number of vehicles passing; If the number of vehicles passing each other is less than the preset threshold for the number of vehicles passing each other, then the corresponding second preset sub-condition is determined to be met.

10. The method according to claim 7, characterized in that, The second road condition sub-parameter includes the number of vehicles passing through the intersection, which includes the number of vehicles traveling in the same direction and the number of vehicles traveling in the opposite direction at each intersection in the automated driving route. The step of determining whether the second road condition sub-parameter satisfies the corresponding second preset sub-condition includes: Determine whether the number of vehicles traveling in the same direction is less than a preset threshold for the number of vehicles traveling in the same direction, and determine whether the number of vehicles traveling in the wrong direction is less than a preset threshold for the number of vehicles traveling in the wrong direction; If the number of vehicles traveling in the same direction is less than the preset threshold for the number of vehicles traveling in the same direction and the number of vehicles traveling in the wrong direction is less than the preset threshold for the number of vehicles traveling in the wrong direction, then the corresponding second preset sub-condition is determined to be satisfied.

11. The method according to claim 7, characterized in that, The second traffic condition sub-parameter includes a second network state parameter; determining whether the second traffic condition sub-parameter satisfies the corresponding second preset sub-condition includes: Based on the second network state parameters and second network state thresholds of multiple second network detection points, the network state detection result of each second network detection point is determined respectively, wherein every two adjacent second network detection points are spaced apart by a fourth preset distance in the route to be identified; Based on the network status detection results of all second network detection points and the number of second network detection points, the second network status pass rate is determined. If the second network status pass rate is greater than the second pass rate threshold, then the corresponding second preset sub-condition is determined to be met.

12. The method according to claim 7, characterized in that, The second road condition sub-parameter includes the number of pedestrians identified, which includes the number of pedestrians identified every fifth preset distance traveled on the automated driving route; The step of determining whether the second road condition sub-parameter satisfies the corresponding second preset sub-condition includes: Determine whether the number of pedestrians identified is less than a preset pedestrian number threshold; If the number of pedestrians identified is less than the preset pedestrian number threshold, then the corresponding second preset sub-condition is determined to be satisfied.

13. The method according to claim 7, characterized in that, The second road condition sub-parameter includes at least one pedestrian recognition duration, which includes the duration of each pedestrian recognition in the autonomous driving route; The step of determining whether the second road condition sub-parameter satisfies the corresponding second preset sub-condition includes: The cumulative pedestrian recognition time in the automated driving route is determined based on the at least one pedestrian recognition time. Determine whether the cumulative pedestrian recognition time is less than a preset time threshold. If it is less than the preset time threshold, then the corresponding second preset sub-condition is satisfied.

14. An automated driving area identification device, characterized in that, The device includes: The first road condition parameter acquisition module is used to acquire the first road condition parameter, which is the road condition parameter collected when the vehicle is driving in manual driving mode along the route to be identified in the area to be identified. An automated driving route determination module is used to determine whether the first road condition parameters meet the preset first automated driving road condition conditions. If the first automated driving road condition conditions are met, the route to be identified is determined to be an automated driving route. The second road condition parameter acquisition module is used to acquire second road condition parameters when the route to be identified is determined to be an autonomous driving route. The second road condition parameters are road condition parameters collected by the vehicle while driving along the autonomous driving route in autonomous driving mode. The autonomous driving area determination module is used to determine whether the second road condition parameter meets the preset second autonomous driving road condition. If the second autonomous driving road condition is met, the area to be identified is determined to be an autonomous driving area.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 13.

16. A vehicle device comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 13.

Images