CN115880890A

CN115880890A - Map validity detection method and related product

Info

Publication number: CN115880890A
Application number: CN202111128366.3A
Authority: CN
Inventors: 宿建烽; 赵凌; 李明超
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-09-26
Filing date: 2021-09-26
Publication date: 2023-03-31
Also published as: WO2023046125A1

Abstract

The embodiment of the application discloses a map validity detection method and a related product, wherein the method comprises the following steps: acquiring the running condition of a traffic flow on a map to be detected; and carrying out validity detection on the map to be detected according to the running condition of the traffic flow on the map to be detected. In the embodiment of the application, according to the running condition of the traffic flow on the map to be detected, the map to be detected is subjected to validity detection; the method can accurately and efficiently detect various explicit and implicit problems of all passable paths in the map to be detected. In addition, according to the running condition of the traffic flow on the map to be detected, carrying out validity detection on the map to be detected; the potential hazards of the map to be detected in the subsequent use process can be effectively detected.

Description

Map validity detection method and related product

Technical Field

The application relates to the field of map detection, in particular to a map validity detection method and a related product.

Background

High-precision maps are an important component of automated driving technology. High-precision maps have information with a higher precision (e.g., a precision level on the order of 10-30 centimeters or higher) than conventional maps. Such information may be lane shape, grade, curvature, grade, ground markings, traffic signs, etc., which are typically the basis of data required to implement autonomous driving. High-precision maps can provide detailed information about the driving environment to ensure the safety of the autonomous vehicle.

The effectiveness of an autopilot high-precision map, in contrast to conventional maps, does not depend solely on the consistency with real roads. The connection topological relation, the reference line fitting parameters and the like of the high-precision map can influence the control of the rule control algorithm on the vehicle. Therefore, there is a strong need for validity detection of high-precision maps. Therefore, there is a need to develop a scheme for accurately and efficiently detecting the validity of a high-precision map.

Disclosure of Invention

The embodiment of the application discloses a map validity detection method and related products, which can accurately and efficiently detect the validity of an electronic map.

In a first aspect, an embodiment of the present application provides a map validity detection method, where the method includes: acquiring the running condition of a traffic flow on a map to be detected; and carrying out validity detection on the map to be detected according to the running condition of the traffic flow on the map to be detected.

For example, the traffic flow may be formed by automatically driving a plurality of vehicles on the map to be detected according to the configured automatic driving manner according to traffic signal lights, speed limit signs, lane lines, road shapes, road connection relations and the like. Alternatively, the communication site includes a plurality of vehicles traveling on the map to be detected. According to the running condition of the traffic flow on the map to be detected, the validity detection of the map to be detected can be as follows: according to road abnormity (for example) encountered by one or more vehicles in the driving process on the map to be detected, whether the map to be detected has detection items related to the validity of the map to be detected, such as traffic signal lamp abnormity, speed limit sign abnormity, lane line abnormity, road shape abnormity (for example, abnormal folds at the curve, unreasonable U-shaped road parameters), road connection abnormity and the like, is determined, and then a quality inspection report for representing the validity of the map to be detected is generated. In the embodiment of the application, according to the running condition of the traffic flow on the map to be detected, the map to be detected is subjected to validity detection; the method can accurately and efficiently detect various explicit and implicit problems of all passable paths in the map to be detected. In addition, according to the running condition of the traffic flow on the map to be detected, carrying out validity detection on the map to be detected; the potential hazards of the map to be detected in the subsequent use process can be effectively detected.

In one possible implementation, the map to be detected is an electronic map, such as a high-precision map.

In a possible implementation manner, the acquiring the operation condition of the traffic flow on the map to be detected includes: taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow; randomly taking any driving behavior by the one or more vehicles on the map to be detected; the detecting the effectiveness of the map to be detected according to the running condition of the traffic flow on the map to be detected comprises the following steps: and performing effectiveness detection on the map to be detected according to the running conditions of the one or more vehicles on the map to be detected.

In the implementation mode, the running condition of one or more vehicles on the map to be detected is used as the running condition of the traffic flow; according to the running condition of the one or more vehicles on the map to be detected, carrying out effectiveness detection on the map to be detected; the potential hazards of the map to be detected in the subsequent use process can be effectively detected, and the reliability is high.

In a possible implementation manner, the performing validity detection on the map to be detected according to the driving condition of the one or more vehicles on the map to be detected includes: and outputting a quality inspection report according to the road abnormity encountered in the process of driving the one or more vehicles on the map to be detected. The quality check report may include information characterizing road anomalies encountered by the one or more vehicles while traveling on the map to be detected.

In this implementation, a quality inspection report is output based on road anomalies encountered during travel of one or more vehicles on the map to be inspected. The quality inspection report is obtained according to the road abnormity encountered in the process that one or more vehicles run on the map to be detected, so that the quality inspection report can accurately reflect the road abnormity condition in the map to be detected.

In one possible implementation, the one or more vehicles include a first vehicle; the outputting of the quality inspection report according to the road abnormality encountered in the process of driving the one or more vehicles on the map to be detected comprises: obtaining first abnormal information representing the first road abnormity according to the first road abnormity encountered in the process of driving of the first vehicle on the map to be detected; summarizing and processing a plurality of items of abnormal information, and outputting the quality inspection report; the plurality of items of exception information include the first exception information, and the quality inspection report includes the first exception information. Alternatively, the quality inspection report includes information characterizing the first road anomaly. Or the quality inspection report comprises information obtained by summarizing the first abnormal information and other abnormal information. The summary processing of the plurality of items of abnormal information may be to merge two or more items of abnormal information in the plurality of items of abnormal information into one item of abnormal information, so that repeated abnormal information may be removed or two or more items of road abnormal information may be merged into one item of road abnormal.

In the implementation mode, multiple items of abnormal information are summarized, and a quality inspection report is output. Because the multiple items of abnormal information are subjected to summarizing processing, repeated abnormal information can be removed, or two or more items of road abnormal information can be combined into one item of road abnormal information, the quality inspection report can more accurately and simply reflect the road abnormality in the map to be detected, so that a user can quickly check the road abnormality.

In one possible implementation, the method further includes: removing the first vehicle from the traffic flow after encountering the first road anomaly while the first vehicle is traveling on the map to be detected. In the present application, traffic flow is understood to be the traffic flow in a simulated scene simulating the operation of one or more vehicles on a map to be detected. Removing the first vehicle from the traffic flow is understood to be moving the first vehicle out of a simulation scenario.

In this implementation, a first vehicle is removed from the traffic flow after encountering a first road anomaly, which may avoid causing anomalies in other vehicles due to the road anomaly encountered by the first vehicle.

In one possible implementation manner, the plurality of items of exception information include second exception information; the second abnormal information represents second road abnormality irrelevant to drawing factors in the map to be detected, and the quality inspection report does not include the second abnormal information. Alternatively, the quality inspection report does not include information characterizing the second road anomaly.

In this implementation, the quality check report does not include the second anomaly information. That is to say, the quality inspection report does not contain the road abnormality irrelevant to the drawing factor, and the validity of the map to be detected can be better reflected.

In one possible implementation, the method further includes: labeling the second road abnormity in the map to be detected; the second road abnormity belongs to road abnormity caused by the boundary of the map to be detected or road abnormity caused by an un-mapped area in the map to be detected.

In this implementation, the second road anomaly in the map to be detected is labeled, so that the labeled second road anomaly is not subsequently taken as a road anomaly related to the drawing factor.

In a possible implementation manner, the aggregating the multiple items of abnormal information and outputting the quality inspection report includes: removing the second road abnormity in the plurality of abnormal information to obtain a plurality of initially selected abnormal information; and summarizing the plurality of items of initially selected abnormal information, and outputting the quality inspection report.

In the implementation mode, a plurality of items of initially selected abnormal information are summarized to obtain a quality inspection report. Therefore, the quality inspection report is only obtained by the abnormal information representing the road abnormity related to the drawing factors, and the effectiveness of the map to be detected can be better reflected.

In a possible implementation manner, before obtaining first anomaly information representing a first road anomaly according to the first road anomaly encountered by the first vehicle in the process of driving on the map to be detected, the method further includes: configuring a check item of the map to be detected; and detecting road abnormity encountered in the process of driving of the first vehicle on the map to be detected according to the check item to obtain the first road abnormity.

In the implementation mode, the road abnormity encountered in the process of driving of the first vehicle on the map to be detected is detected according to the check item, and the road abnormity beyond the check item does not need to be detected, so that the detection efficiency can be improved, and the workload can be reduced.

In one possible implementation, before configuring the check item of the map to be detected, the method further includes: receiving an inspection item configuration instruction, wherein the configuration of the inspection item of the map to be detected comprises the following steps: and configuring the inspection item of the map to be inspected according to the inspection item configuration instruction.

In the implementation mode, a user can conveniently configure the required detection check by sending or inputting the check item configuration instruction, thereby meeting the requirements of different application scenes and reducing the workload.

In one possible implementation, the method further includes: configuring an automatic driving regulation and control mode for the one or more vehicles; the automatic driving regulation mode is a default regulation mode or a user-defined regulation mode, and one or more vehicles randomly take any driving behaviors on the map to be detected according to the configured automatic driving regulation mode.

In the implementation mode, an automatic driving regulation mode is configured for one or more vehicles, and the quality requirements of the map to be detected in different use scenes can be adapted.

In one possible implementation, before configuring the autonomous driving regulation scheme for the one or more vehicles, the method further comprises: receiving a rule control mode configuration instruction; the configuring an autopilot schedule for the one or more vehicles comprises: and configuring the automatic driving regulation and control mode for the one or more vehicles according to the regulation and control mode configuration instruction.

In the implementation mode, a user can conveniently configure the required driving regulation mode by sending or inputting the regulation mode configuration instruction, so that the requirements of different application scenes are met.

In one possible implementation, before regarding the operation condition of one or more vehicles on the map to be detected as the operation condition of the traffic flow, the method further includes: determining a region to be detected in the map to be detected; the taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow comprises the following steps: taking the running condition of one or more vehicles on the area to be detected as the running condition of the traffic flow; the detecting the effectiveness of the map to be detected according to the running condition of the traffic flow on the map to be detected comprises the following steps: and performing validity detection on the area to be detected according to the running condition of the traffic flow in the area to be detected.

In this implementation, a region to be detected in a map to be detected is determined; according to the running condition of the traffic flow in the area to be detected, carrying out validity detection on the area to be detected; the validity detection can be carried out on the region to be detected in a more targeted manner, and the workload is reduced.

In one possible implementation, before determining the region to be detected in the map to be detected, the method further includes: receiving a detection area selection instruction; determining the area to be detected in the map to be detected comprises: and determining the area to be detected in the map to be detected according to the detection area selection instruction.

In the implementation mode, the area to be detected in the map to be detected is determined according to the received detection area selection instruction; the area to be detected can be conveniently determined, and the operation is simple.

In a possible implementation manner, the map to be detected is a high-precision map, for example, an electronic map used by an automatic driving device for realizing automatic driving. High-precision maps reach a precision level of around 10-30 centimeters or more. The validity detection of the map to be detected comprises the following steps: and detecting the consistency of the map to be detected and the real road and information related to vehicle running in the map to be detected, such as the connection relation of the road, reference line fitting parameters, topological parameters, sections, signals and the like.

In a possible implementation manner, before acquiring the running condition of the traffic flow on the map to be detected, the method further includes: receiving the map to be detected from the terminal equipment; the outputting of the quality inspection report according to the road abnormality encountered in the process of driving the one or more vehicles on the map to be detected comprises: and outputting the quality inspection report to the terminal equipment according to the road abnormity encountered in the process of driving the one or more vehicles on the map to be detected.

In the implementation mode, validity detection is carried out on the map to be detected from the terminal equipment, and a quality inspection report is sent to the terminal equipment; the map validity detection method and the map validity detection device can provide a service for detecting the validity of the map for the terminal device, and are high in detection efficiency and reliability.

In a second aspect, an embodiment of the present application provides another map validity detection method, where the method includes: determining a to-be-detected area in a to-be-detected map; acquiring the running condition of the traffic flow on the area to be detected; and performing validity detection on the area to be detected according to the running condition of the traffic flow on the area to be detected.

In the embodiment of the application, according to the running condition of the traffic flow on the area to be detected, the validity of the area to be detected is detected; various explicit and implicit problems of all passable paths in the area to be detected can be accurately and efficiently detected. In addition, according to the running condition of the traffic flow on the area to be detected, carrying out effectiveness detection on the area to be detected; the potential hazards of the to-be-detected area in the subsequent use process can be effectively detected.

In one possible implementation manner, before determining the area to be detected in the map to be detected, the method further includes: receiving a detection area selection instruction; determining the area to be detected in the map to be detected comprises: and determining the area to be detected in the map to be detected according to the detection area selection instruction.

In a possible implementation manner, the acquiring the running condition of the traffic flow on the area to be detected includes: taking the running condition of one or more vehicles on the area to be detected as the running condition of the traffic flow; randomly taking any driving behavior by the one or more vehicles on the area to be detected; the detecting the effectiveness of the area to be detected according to the operation condition of the traffic flow on the area to be detected comprises the following steps: and carrying out effectiveness detection on the area to be detected according to the running condition of the one or more vehicles on the area to be detected.

In the implementation mode, the running condition of one or more vehicles in the area to be detected is used as the running condition of the traffic flow; according to the running condition of the one or more vehicles on the area to be detected, carrying out effectiveness detection on the area to be detected; the potential hazards possibly existing in the subsequent use process of the area to be detected can be effectively detected, and the reliability is high.

In a possible implementation manner, the performing validity detection on the area to be detected according to the driving condition of the one or more vehicles on the area to be detected includes: and outputting a quality inspection report according to the road abnormity encountered in the process of driving the one or more vehicles on the area to be detected. The quality inspection report may include information indicative of road anomalies encountered by the one or more vehicles during travel over the area to be inspected.

In this implementation, a quality inspection report is output based on road anomalies encountered during travel of one or more vehicles over the area to be inspected. The quality inspection report is obtained according to the road abnormity encountered in the process of driving one or more vehicles on the area to be detected, so the quality inspection report can accurately reflect the road abnormity condition in the area to be detected.

In one possible implementation, the one or more vehicles include a first vehicle; the outputting of the quality inspection report according to the road abnormality encountered in the process of driving the one or more vehicles on the area to be detected comprises: obtaining first abnormal information representing the first road abnormity according to the first road abnormity encountered in the process of driving of the first vehicle on the area to be detected; summarizing and processing a plurality of items of abnormal information, and outputting the quality inspection report; the plurality of items of exception information include the first exception information, and the quality inspection report includes the first exception information. Alternatively, the quality inspection report includes information characterizing the first road anomaly. Or the quality inspection report comprises information obtained by summarizing the first abnormal information and other abnormal information. The summarizing process of the plurality of items of abnormal information may be to merge two or more items of abnormal information in the plurality of items of abnormal information into one item of abnormal information, so that repeated abnormal information may be removed or two or more items of road abnormal information may be merged into one item of road abnormal.

In the implementation mode, multiple items of abnormal information are summarized, and a quality inspection report is output. Because repeated abnormal information can be removed or two or more road abnormalities can be combined into one road abnormality by summarizing the abnormal information, the quality inspection report can more accurately and simply reflect the road abnormalities in the area to be detected, so that a user can quickly check the road abnormalities.

In one possible implementation, the plurality of items of exception information include second exception information; the second abnormal information represents a second road abnormality irrelevant to drawing factors in the area to be detected, and the quality inspection report does not include the second abnormal information. Alternatively, the quality inspection report does not include information characterizing the second road anomaly.

In this implementation, the quality check report does not include the second anomaly information. That is to say, the quality inspection report does not contain the road abnormality irrelevant to the drawing factor, and the validity of the region to be detected can be better reflected.

In one possible implementation, the method further includes: labeling the second road abnormity in the area to be detected; the second road abnormity belongs to road abnormity caused by the boundary of the area to be detected or road abnormity caused by an un-mapped area in the area to be detected.

In this implementation, the second road anomaly in the area to be detected is labeled, so that the labeled second road anomaly is not subsequently taken as a road anomaly related to the mapping factor.

In a possible implementation manner, the aggregating multiple items of abnormal information and outputting the quality inspection report includes: removing the second road abnormity in the plurality of abnormal information to obtain a plurality of initially selected abnormal information; and summarizing the plurality of items of initially selected abnormal information to obtain the quality inspection report.

In the implementation mode, a plurality of items of initially selected abnormal information are summarized to obtain a quality inspection report. Therefore, the quality inspection report is only obtained by the abnormal information representing the road abnormity related to the drawing factors, and the effectiveness of the area to be detected can be better reflected.

In a possible implementation manner, before obtaining first anomaly information representing a first road anomaly according to the first road anomaly encountered by the first vehicle in the process of traveling on the area to be detected, the method further includes: configuring the inspection items of the area to be detected; and detecting road abnormity encountered in the process of driving of the first vehicle on the area to be detected according to the check item to obtain the first road abnormity.

In the implementation mode, the road abnormity encountered in the process of driving of the first vehicle on the area to be detected is detected according to the check items, and the road abnormity beyond the check items does not need to be detected, so that the detection efficiency can be improved, and the workload can be reduced.

In a possible implementation manner, before configuring the check item of the region to be detected, the method further includes: receiving a checking item configuration instruction; the configuring the inspection items of the area to be detected comprises: and configuring the inspection item of the area to be inspected according to the inspection item configuration instruction.

In one possible implementation, the method further includes: configuring an automatic driving regulation and control mode for the one or more vehicles; the automatic driving regulation mode is a default regulation mode or a user-defined regulation mode, and one or more vehicles randomly take any driving behaviors on the area to be detected according to the configured automatic driving regulation mode.

In the implementation mode, an automatic driving regulation and control mode is configured for one or more vehicles, and the quality requirements of different use scenes on the area to be detected can be adapted.

In one possible implementation, before configuring the one or more vehicles with an automated driving regulation approach, the method further comprises: receiving a rule control mode configuration instruction; the configuring an autopilot schedule for the one or more vehicles comprises: and configuring the automatic driving regulation and control mode for the one or more vehicles according to the regulation and control mode configuration instruction.

In a possible implementation manner, the map to be detected is a high-precision map.

In a possible implementation manner, before acquiring the running condition of the traffic flow on the area to be detected, the method further includes: receiving the map to be detected from the terminal equipment; the outputting of the quality inspection report according to the road abnormality encountered in the process of driving the one or more vehicles on the area to be detected comprises: and outputting the quality inspection report to the terminal equipment according to the road abnormity encountered in the process of driving the one or more vehicles on the area to be detected.

In the implementation mode, validity detection is carried out on the area to be detected from the terminal equipment, and a quality inspection report is sent to the terminal equipment; the map validity detection method and the map validity detection device can provide a service for detecting the validity of the map for the terminal device, and are high in detection efficiency and reliability.

In a third aspect, an embodiment of the present application provides another map validity detection method, where the method includes: receiving a regulation mode configuration instruction; configuring an automatic driving regulation and control mode for one or more vehicles according to the regulation and control mode configuration instruction; and carrying out effectiveness detection on the map to be detected according to the running condition of the one or more vehicles on the map to be detected in the automatic driving regulation and control mode.

In the embodiment of the application, an automatic driving regulation mode is configured for one or more vehicles according to the received regulation mode configuration instruction, and the required driving regulation mode can be conveniently configured, so that the quality requirements of the map to be detected in different use scenes are met.

In one possible implementation, the receiving the rule-based configuration instruction includes: receiving a regulatory mode configuration file (or information) from a terminal device; the configuring an automatic driving regulation and control mode for one or more vehicles according to the regulation and control mode configuration instruction comprises the following steps: and configuring an automatic driving regulation and control mode for the one or more vehicles according to the regulation and control mode configuration file (or information). The regulatory mode profile may be used to configure an autonomous driving regulatory mode (or regulatory algorithm) of the one or more vehicles. The one or more vehicles may be automatically driven on the map to be detected using the regulatory mode profile. The one or more vehicles can randomly take any driving behaviors on the map to be detected according to a configured automatic driving regulation mode (or a regulation algorithm).

In the implementation mode, according to the received configuration file of the regulation mode, an automatic driving regulation mode is configured for one or more vehicles, and the required driving regulation mode can be conveniently configured, so that the quality requirements of the map to be detected in different use scenes are met.

In a possible implementation manner, the performing validity detection on the map to be detected according to the driving condition of the one or more vehicles on the map to be detected according to the automatic driving regulation and control manner includes: and outputting a quality inspection report according to the road abnormity encountered in the process that the one or more vehicles run on the map to be detected according to the automatic driving regulation and control mode.

In this implementation, a quality inspection report is output based on road anomalies encountered by one or more vehicles in the process of traveling on a map to be inspected. The quality inspection report is obtained according to the road abnormity encountered in the process that one or more vehicles run on the map to be detected, so that the quality inspection report can accurately reflect the road abnormity condition in the map to be detected.

In one possible implementation, the one or more vehicles include a first vehicle; the outputting of the quality inspection report according to the road abnormality encountered in the process that the one or more vehicles run on the map to be detected in the automatic driving regulation and control mode comprises: obtaining first abnormal information representing the first road abnormity according to the first road abnormity encountered by the first vehicle in the process of driving on the map to be detected in the automatic driving regulation and control mode; summarizing and processing multiple items of abnormal information, and outputting the quality inspection report; the plurality of items of exception information include the first exception information, and the quality inspection report includes the first exception information.

In the implementation mode, multiple items of abnormal information are summarized, and a quality inspection report is output. Because the multiple items of abnormal information are subjected to summarizing processing, repeated abnormal information can be removed, or two or more road abnormalities are combined into one road abnormality, the quality inspection report can reflect the road abnormalities in the map to be detected more accurately and simply, so that a user can check the road abnormalities quickly.

In one possible implementation, the plurality of items of exception information include second exception information; the second abnormal information represents second road abnormality irrelevant to drawing factors in the map to be detected, and the quality inspection report does not include the second abnormal information. Alternatively, the quality inspection report does not include information characterizing the second road anomaly.

In one possible implementation, the method further includes: marking the second road abnormity in the map to be detected; the second road abnormity belongs to road abnormity caused by the boundary of the map to be detected or road abnormity caused by an un-mapped area in the map to be detected.

In this implementation, the second road anomaly in the map to be detected is marked so that the marked second road anomaly is not subsequently considered as a road anomaly associated with a cartographic factor.

In a possible implementation manner, the aggregating the multiple items of abnormal information and outputting the quality inspection report includes: removing the second road abnormity in the plurality of abnormal information to obtain a plurality of initially selected abnormal information; and summarizing the plurality of items of initially selected abnormal information to obtain the quality inspection report.

In a possible implementation manner, before performing validity detection on the map to be detected according to the driving condition of the one or more vehicles on the map to be detected according to the automatic driving regulation manner, the method further includes: determining a to-be-detected area in the to-be-detected map; the step of performing validity detection on the map to be detected according to the running condition of the one or more vehicles on the map to be detected in the automatic driving regulation and control mode comprises the following steps: and carrying out effectiveness detection on the map to be detected according to the running condition of the one or more vehicles on the area to be detected in the automatic driving regulation and control mode.

In this implementation, a region to be detected in a map to be detected is determined; according to the running condition of one or more vehicles in the area to be detected in an automatic driving regulation and control mode, carrying out effectiveness detection on the area to be detected; the validity detection can be carried out on the region to be detected in a more targeted manner, and the workload is reduced.

In a fourth aspect, an embodiment of the present application provides another map validity detection method, where the method includes: receiving a checking item configuration instruction; according to the inspection item configuration instruction, configuring an inspection item of the map to be detected; acquiring the running condition of the traffic flow on the map to be detected; detecting road abnormity encountered in the running process of the traffic flow on the map to be detected according to the inspection item; and carrying out validity detection on the map to be detected according to the detected road abnormity encountered in the running process of the traffic flow on the map to be detected.

In the embodiment of the application, the road abnormity encountered in the running process of the traffic flow on the map to be detected is detected according to the check item, and the road abnormity beyond the check item is not required to be detected, so that the detection efficiency can be improved, and the workload can be reduced.

In one possible implementation manner, the receiving the check item configuration instruction includes: receiving a check item configuration file; the step of configuring the inspection items of the map to be detected according to the inspection item configuration instruction comprises the following steps: and configuring the inspection items of the map to be inspected according to the inspection item configuration file.

In the implementation mode, the checking items of the map to be detected are configured according to the received checking item configuration file; the check items of the map to be detected can be quickly configured in detail.

In a possible implementation manner, the acquiring the operation condition of the traffic flow on the map to be detected includes: taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow; randomly taking any driving behavior by the one or more vehicles on the map to be detected; the detecting the road abnormity encountered by the traffic flow in the running process on the map to be detected according to the check item comprises the following steps: detecting road anomalies encountered by the one or more vehicles in the process of running on the map to be detected according to the check items; the detecting the effectiveness of the map to be detected according to the detected road abnormity encountered in the running process of the traffic flow on the map to be detected comprises the following steps: and performing effectiveness detection on the map to be detected according to the detected road abnormity encountered in the process of driving the one or more vehicles on the map to be detected.

In the implementation mode, the running condition of one or more vehicles on the map to be detected is used as the running condition of the traffic flow; carrying out validity detection on the map to be detected according to road abnormity encountered in the process of driving of the one or more vehicles on the map to be detected; the hidden danger that the map to be detected may exist in the subsequent use process can be effectively detected, and the reliability is high.

In a possible implementation manner, the performing, according to the detected road abnormality encountered during the driving process of the one or more vehicles on the map to be detected, validity detection on the map to be detected includes: and outputting a quality inspection report according to the road abnormity encountered in the process of driving the one or more vehicles on the map to be detected.

In this implementation, a quality inspection report is output based on road anomalies encountered by one or more vehicles in the process of traveling on a map to be inspected. The quality inspection report is obtained according to the road abnormity encountered in the process of driving one or more vehicles on the map to be inspected, so the quality inspection report can accurately reflect the road abnormity condition in the map to be inspected.

In one possible implementation, the one or more vehicles include a first vehicle; the outputting a quality inspection report according to the road abnormality encountered in the process of driving the one or more vehicles on the map to be detected comprises: obtaining first abnormal information representing the first road abnormity according to the first road abnormity encountered in the process of driving of the first vehicle on the map to be detected; summarizing and processing a plurality of items of abnormal information, and outputting the quality inspection report; the plurality of items of exception information include the first exception information, and the quality inspection report includes the first exception information.

In the implementation mode, a plurality of items of abnormal information are summarized, and a quality inspection report is output; the quality inspection report can reflect the road abnormity in the map to be detected more accurately and concisely, so that a user can check the road abnormity quickly.

In one possible implementation manner, before acquiring the running condition of the traffic flow on the map to be detected, the method further comprises the following steps: determining a region to be detected in the map to be detected; the acquiring the running condition of the traffic flow on the map to be detected comprises the following steps: acquiring the running condition of the traffic flow on the area to be detected; the detecting the road abnormity encountered by the traffic flow in the running process on the map to be detected according to the check item comprises the following steps: detecting road abnormity encountered in the running process of the traffic flow on the area to be detected according to the inspection item; the detecting the effectiveness of the map to be detected according to the detected road abnormity encountered in the running process of the traffic flow on the map to be detected comprises the following steps: and carrying out effectiveness detection on the area to be detected according to the detected road abnormity encountered in the running process of the traffic flow on the area to be detected.

In this implementation, a region to be detected in a map to be detected is determined; according to the detected road abnormity encountered in the running process of the traffic flow on the area to be detected, carrying out effectiveness detection on the area to be detected; the validity detection can be carried out on the region to be detected in a more targeted manner, and the workload is reduced.

In a fifth aspect, an embodiment of the present application provides a data processing apparatus, where the data processing apparatus has a function of implementing the behavior in the method embodiment of the first aspect. The functions can be realized by hardware, and the functions can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the above-described functions. In one possible implementation, the method includes an obtaining unit and a processing unit, wherein:

the acquisition unit is used for acquiring the running condition of the traffic flow on the map to be detected;

and the processing unit is used for carrying out validity detection on the map to be detected according to the running condition of the traffic flow on the map to be detected.

With regard to the technical effects brought about by the fifth aspect or various possible embodiments of the fifth aspect, reference may be made to the introduction of the technical effects of the first aspect or various possible embodiments of the first aspect.

In a sixth aspect, this application provides another data processing apparatus having functionality to implement the behavior in the method embodiment of the second aspect described above. The functions can be realized by hardware, and the functions can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the functions described above. In one possible implementation, the method includes a processing unit and an obtaining unit, wherein:

the processing unit is used for determining a to-be-detected area in a to-be-detected map;

the acquisition unit is used for acquiring the running condition of the traffic flow on the area to be detected;

and the processing unit is also used for carrying out effectiveness detection on the area to be detected according to the running condition of the traffic flow on the area to be detected.

With regard to the technical effects brought about by the sixth aspect or the various possible embodiments of the sixth aspect, reference may be made to the introduction to the second aspect or the various possible embodiments of the second aspect.

In a seventh aspect, this application provides another data processing apparatus, where the data processing apparatus has a function of implementing the behavior in the method embodiment of the third aspect. The functions can be realized by hardware, and the functions can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the above-described functions. In one possible implementation, the system includes a transceiver unit and a processing unit, wherein:

the receiving and sending unit is used for receiving a configuration instruction of a regulation and control mode;

the processing unit is used for configuring an automatic driving regulation and control mode for one or more vehicles according to the regulation and control mode configuration instruction; and performing effectiveness detection on the map to be detected according to the running condition of the one or more vehicles on the map to be detected in the automatic driving regulation and control mode.

With regard to the technical effects brought about by the seventh aspect or the various possible embodiments of the seventh aspect, reference may be made to the introduction of the technical effects of the third aspect or the various possible embodiments of the third aspect.

In an eighth aspect, embodiments of the present application provide another data processing apparatus, which has a function of implementing the behaviors in the method embodiment of the fourth aspect. The functions can be realized by hardware, and the functions can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the functions described above. In one possible implementation manner, the apparatus includes a transceiver unit, a processing unit, and an obtaining unit, where:

the receiving and sending unit is used for receiving a check item configuration instruction;

the processing unit is used for configuring the inspection item of the map to be detected according to the inspection item configuration instruction;

the processing unit is further used for detecting road abnormity encountered by the traffic flow in the running process on the map to be detected according to the check item; and carrying out validity detection on the map to be detected according to the detected road abnormity encountered in the running process of the traffic flow on the map to be detected.

With regard to the technical effects brought about by the eighth aspect or the various possible embodiments of the eighth aspect, reference may be made to the introduction to the technical effects of the fourth aspect or the various possible embodiments of the fourth aspect.

In a ninth aspect, the present application provides a data processing apparatus comprising a processor operable to execute computer executable instructions stored by a memory to cause a method as shown in the first aspect or any possible implementation of the first aspect to be performed, or to cause a method as shown in the second aspect or any possible implementation of the second aspect to be performed, or to cause a method as shown in the third aspect or any possible implementation of the third aspect to be performed, or to cause a method as shown in the fourth aspect or any possible implementation of the fourth aspect to be performed.

In the embodiment of the present application, in the process of executing the method, the process related to sending information in the method may be understood as a process of outputting information based on an instruction of a processor. In outputting the information, the processor outputs the information to the transceiver for transmission by the transceiver. This information, after being output by the processor, may also need to be further processed before reaching the transceiver. Similarly, when the processor receives incoming information, the transceiver receives the information and inputs it to the processor. Further, after the transceiver receives the information, the information may need to be further processed before being input to the processor.

The operations involving the processor, such as transmission and/or reception, may be generally understood as processor-based instruction output if not specifically stated or if not contradicted by actual role or inherent logic in the associated description.

In implementation, the processor may be a processor dedicated to performing the methods, or may be a processor executing computer instructions in a memory to perform the methods, such as a general-purpose processor. For example, the processor may also be adapted to execute a program stored in the memory, which when executed, causes the data processing apparatus to perform a method as illustrated in the first aspect above or any possible implementation of the first aspect.

In a possible implementation, the memory is located outside the data processing device.

In one possible implementation, the memory is located within the data processing apparatus described above.

In the embodiments of the present application, the processor and the memory may also be integrated into one device, that is, the processor and the memory may also be integrated together.

In a possible implementation manner, the data processing apparatus further includes a transceiver, and the transceiver is configured to receive a message or send a message, and the like.

In a tenth aspect, the present application provides a data processing apparatus comprising processing circuitry and interface circuitry for acquiring data or outputting data; the processing circuitry is configured to perform a respective method as illustrated in the first aspect or any possible implementation of the first aspect as such, or the processing circuitry is configured to perform a respective method as illustrated in the second aspect or any possible implementation of the second aspect as such, or the processing circuitry is configured to perform a respective method as illustrated in the third aspect or any possible implementation of the third aspect as such, or the processing circuitry is configured to perform a respective method as illustrated in the fourth aspect or any possible implementation of the fourth aspect as such.

In an eleventh aspect, the present application provides a computer-readable storage medium for storing a computer program which, when run on a computer, causes the method shown in the first aspect or any possible implementation of the first aspect described above to be performed, or causes the method shown in the second aspect or any possible implementation of the second aspect described above to be performed, or causes the method shown in the third aspect or any possible implementation of the third aspect described above to be performed, or causes the method shown in the fourth aspect or any possible implementation of the fourth aspect described above to be performed.

In a twelfth aspect, the present application provides a computer program product comprising a computer program or computer code which, when run on a computer, causes the method as shown in the first aspect or any possible implementation of the first aspect described above to be performed, or causes the method as shown in the second aspect or any possible implementation of the second aspect described above to be performed, or causes the method as shown in the third aspect or any possible implementation of the third aspect described above to be performed, or causes the method as shown in the fourth aspect or any possible implementation of the fourth aspect described above to be performed.

In a thirteenth aspect, the present application provides a map validity detection system, which includes a server and a terminal device, where the terminal device sends a map to be detected to the server; the server performs validity detection on the map to be detected by the method shown in the first aspect or any possible implementation manner of the first aspect, or performs validity detection on the map to be detected by the method shown in the second aspect or any possible implementation manner of the second aspect, or performs validity detection on the map to be detected by the method shown in the third aspect or any possible implementation manner of the third aspect, or performs validity detection on the map to be detected by the method shown in the fourth aspect or any possible implementation manner of the fourth aspect; and the server sends a quality inspection report which represents the effectiveness of the map to be detected and is obtained by detecting the effectiveness of the map to be detected to the terminal equipment.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments or the background art of the present application, the drawings required to be used in the embodiments or the background art of the present application will be described below.

Fig. 1 is a schematic diagram illustrating steps involved in a flow of a map validity detection method according to an embodiment of the present application;

fig. 2 is a flowchart of a map validity detection method according to an embodiment of the present application;

3A, 3B, 3C and 3D are examples of road anomalies encountered by a vehicle traveling on a map to be detected according to an embodiment of the present application;

fig. 4 is a flowchart of another map validity detection method according to an embodiment of the present application;

fig. 5 is a flowchart of another map validity detection method according to an embodiment of the present application;

fig. 6 is a flowchart of another map validity detection method according to an embodiment of the present application;

FIG. 7 is an example of a configuration of a test item provided in an embodiment of the present application;

fig. 8 is a flowchart of another map validity detection method according to an embodiment of the present application;

fig. 9A is an example of a traffic signal light scene at an intersection according to an embodiment of the present disclosure;

fig. 9B is an example of a roundabout import-export scenario provided in an embodiment of the present application;

fig. 9C is an example of an automatic driving scenario of a main road according to an embodiment of the present application;

fig. 10 is a flowchart of another map validity detection method according to an embodiment of the present application;

fig. 11 is a flowchart of another map validity detection method according to an embodiment of the present application;

fig. 12 is an interactive flowchart of another map validity detection method according to an embodiment of the present application;

FIG. 13 illustrates an example of a map management interface;

fig. 14 is an example of a visualization result of a quality inspection report provided by an embodiment of the present application;

fig. 15 is an interactive flowchart of another map validity detection method according to an embodiment of the present application;

FIG. 16 is an example of a custom configuration interface provided by an embodiment of the present application;

fig. 17 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;

fig. 18 is a schematic structural diagram of another data processing apparatus according to an embodiment of the present application;

fig. 19 is a schematic structural diagram of another data processing apparatus according to an embodiment of the present application;

fig. 20 is a schematic structural diagram of another data processing apparatus according to an embodiment of the present application;

fig. 21 is a schematic structural diagram of a terminal device according to an embodiment of the present application;

fig. 22 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

The terms "first" and "second," and the like in the description, the claims, and the drawings of the embodiments of the present application are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. Such as a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The terminology used in the following embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in the specification of the present application and the appended claims, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the listed items. For example, "a and/or B" may represent: only A, only B and both A and B are present, wherein A and B may be singular or plural. The term "plurality" as used in this application refers to two or more.

As described in the background, today there is a strong demand for validity detection of high-precision maps. Therefore, there is a need to develop a scheme for accurately and efficiently detecting the validity of a high-precision map. Therefore, the scheme capable of accurately and efficiently detecting the effectiveness of the high-precision map is provided. By adopting the map validity detection method provided by the embodiment of the application, various explicit and implicit problems of all passable paths in the map to be detected can be accurately and efficiently detected, and potential hazards possibly existing in the subsequent use process of the map to be detected can be effectively detected. Further, the map validity detection method provided by the embodiment of the application can also adapt to the quality requirements of different use scenes on high-precision maps.

The map validity detection scene to which the map validity detection method provided in the embodiment of the present application is applicable is briefly introduced below.

Map validity detection scenario 1: inputting a map to be detected into a data processing device by a user (or a detector) for validity detection; the data processing device adopts the map validity detection method provided by the application to carry out validity detection on the map to be detected and outputs a quality inspection report containing the validity detection result of the map to be detected. The data processing device can be a terminal device with a data processing function, such as a desktop computer, a notebook computer, a mobile phone, a tablet computer and the like. In some embodiments, before the user (or the detection person) performs validity detection on the map to be detected through the data processing device, any configuration operation can be performed as follows: the method comprises the steps of configuring inspection items of a map to be detected, configuring an automatic driving regulation and control mode of a vehicle, configuring validity detection aiming at an area to be detected in the map to be detected, and the like.

Map validity detection scenario 2: a user uploads a map to be detected to a cloud server through terminal equipment; the cloud server performs validity detection on the map to be detected by adopting the map validity detection method provided by the embodiment of the application, and sends a quality inspection report containing the validity detection result of the map to be detected to the terminal equipment. In some embodiments, the user may further send an instruction to the cloud server through the terminal device to implement the following configuration: the method comprises the steps of configuring inspection items of a map to be detected, configuring an automatic driving regulation and control mode of a vehicle, configuring validity detection aiming at a region to be detected in the map to be detected and the like. For example, the user configures the automatic driving regulation mode of the vehicle by sending a regulation mode configuration file to the cloud server through the terminal device. For another example, the user transmits the check item configuration file to the cloud server through the terminal device to configure the check items of the map to be detected.

In the map validity detection scene, the map validity detection method provided by the embodiment of the application can be used for accurately and efficiently detecting the validity of a high-precision map.

The following first introduces the steps involved in the map validity detection method flow with reference to the drawings.

Fig. 1 is a schematic diagram of steps involved in a process of a map validity detection method according to an embodiment of the present application. As shown in fig. 1, the steps involved in the map validity detection method flow include: 101. acquiring a map to be detected; 102. carrying out validity detection on the map to be detected; 103. outputting a quality inspection report containing the validity detection result of the map to be detected; 104. releasing the map to be detected; 105. and modifying the map to be detected. In practical applications, after the map to be detected passes the validity detection, the map to be detected may be published, for example, the map to be detected is used for real vehicle testing, algorithm training, simulation, data playback, and the like. Modifying the map to be detected under the condition that the map to be detected does not pass the validity detection; and then, carrying out validity detection on the modified map to be detected, so as to ensure that the map passing the validity detection is published.

The map validity detection method provided by the present application is described below with reference to the accompanying drawings. Fig. 2 is a flowchart of a map validity detection method according to an embodiment of the present application. As shown in fig. 2, the method includes:

201. and the data processing device acquires the running condition of the traffic flow on the map to be detected.

The data processing device may be a terminal device having a data processing function, such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a scene structure and simulation conversion device, a simulator, or the like, or may be a cloud server, a network server, an application server, or the like. The map to be detected may be a high-precision map, for example, an electronic map used for automatic driving by an automatic driving device.

One possible implementation of step 201 is as follows: taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow; and randomly adopting any driving behaviors on the map to be detected by the one or more vehicles. The operating conditions of one or more vehicles on the map to be detected as the operating conditions of the traffic flow can be understood as follows: the data processing device simulates or simulates the running of one or more vehicles on the map to be detected to obtain the traffic flow. Or, the data processing device takes the operation state of one or more simulated vehicles on the map to be detected as the operation condition of the traffic flow. In the embodiment of the application, the traffic flow can be understood as the traffic flow in a simulation scene in which the data processing device simulates the running of one or more vehicles on the map to be detected. Alternatively, the traffic flow in the present application refers to a traffic flow in a communication scene (i.e., a simulation scene simulating the operation of one or more vehicles on a map to be detected) simulated or simulated by a data processing device.

202. And the data processing device performs validity detection on the map to be detected according to the running condition of the traffic flow on the map to be detected.

In some embodiments, the running condition of the traffic flow on the map to be detected is the running condition of one or more vehicles on the map to be detected; one possible implementation of step 202 is as follows: and performing validity detection on the map to be detected according to the running condition of the one or more vehicles on the map to be detected. According to the running condition of one or more vehicles on the map to be detected, the validity detection of the map to be detected can be as follows: and outputting a quality inspection report according to the road abnormity encountered in the process of driving the one or more vehicles on the map to be detected.

Fig. 3A to 3D are diagrams illustrating examples of road anomalies encountered by a vehicle traveling on a map to be detected according to an embodiment of the present disclosure. In fig. 3A, the left rectangular box shows a road section caused by drawing process non-specification (i.e., drawing-related factors), and the right rectangular box shows road overlap caused by drawing process non-specification. In fig. 3B, the left rectangular box shows a road section caused by the drawing process irregularity, and the right rectangular box shows a road overlap caused by the drawing process irregularity. In fig. 3C, the rectangular frame shows the abnormal wrinkles at the curve caused by the irregular drawing process. In fig. 3D, the unreasonable parameters (too small curvature and insufficient width) of the U-shaped road caused by the irregular drawing process are shown in a rectangular frame. The invisible problems of road sections, road overlapping, abnormal folds at curves, unreasonable U-shaped road parameters (too small curvature and insufficient width) and the like caused by the irregular drawing process can be detected by the data processing device.

An example of outputting a quality inspection report based on road anomalies encountered by one or more vehicles during their travel over a map to be inspected is as follows: according to first road abnormity encountered in the process of driving of a first vehicle on a map to be detected, obtaining first abnormity information representing the first road abnormity; summarizing and processing a plurality of items of abnormal information, and outputting the quality inspection report; the plurality of items of abnormality information include the first abnormality information. The first vehicle is any one of the one or more vehicles. It should be understood that the data processing device may obtain anomaly information characterizing each road anomaly encountered by each of the one or more vehicles during the driving process on the map to be detected. In some embodiments, the data processing device generates different anomaly information in the event that the data processing device detects that the vehicle encounters different road anomalies during operation of the traffic flow scenario simulated or simulated by the data processing device. For example, the exception information may be a message info generated by a regulatory algorithm run by the data processing apparatus, or may be a Transmission Control Protocol (TCP) message generated by the data processing apparatus (e.g., a platform); it may also be a scp message generated by a simulator operated by the data processing apparatus (e.g. a Virtual Test Drive (VTD)). In some embodiments, the data processing device may employ a preconfigured checkterm algorithm to detect road anomalies and generate corresponding anomaly information. In some embodiments, the data processing apparatus may package these messages as pluggable checkitem algorithms, configured as an option; the user can also develop and use the self-owned check item algorithm according to the interface provided by the cloud server (corresponding to the platform). That is, the user may configure the data processing apparatus to detect which road anomalies. Still further, the user may also configure the data processing apparatus to detect road anomalies using a custom check-term algorithm and generate corresponding anomaly information.

Each of the plurality of items of anomaly information characterizes one or more road anomalies encountered by one of the one or more vehicles during travel over the map to be detected. The process of collecting multiple items of abnormal information may be: repeated abnormal information in the abnormal information is removed or two or more road abnormal information in the abnormal information is combined into one road abnormal information, so that the quality inspection report can reflect the road abnormality in the map to be detected more accurately and simply, and a user can check the road abnormality quickly. For example, a plurality of items of abnormality information characterizing the same road abnormality (e.g., road overlap) of the same road section are combined into one item of abnormality information. In some embodiments, the plurality of items of abnormality information include second abnormality information; the second anomaly information represents a second road anomaly in the map to be detected, which is irrelevant to drawing factors, and the quality inspection report does not include the second anomaly information. In these embodiments, before the data processing device performs the summary processing on the multiple items of abnormal information, the data processing device may remove the second abnormal information from the multiple items of abnormal information to obtain multiple items of initially selected abnormal information; and summarizing the plurality of items of initially selected abnormal information to obtain the quality inspection report. For example, the data processing device may remove all road anomalies that are not related to the drawing factor in the plurality of items of anomaly information before performing the summary processing on the plurality of items of anomaly information. And summarizing the plurality of items of initially selected abnormal information to obtain a quality inspection report. Therefore, the quality inspection report is only obtained by the abnormal information representing the road abnormity related to the drawing factors, and the effectiveness of the map to be detected can be better reflected.

In some embodiments, the data processing device outputs a quality inspection result and outputs a visualization result; the user can more intuitively see the road abnormity in the map to be detected.

In the embodiment of the application, according to the running condition of the traffic flow on the map to be detected, the map to be detected is subjected to validity detection; the method can accurately and efficiently detect various explicit and implicit problems of all passable paths in the map to be detected. In addition, according to the running condition of the traffic flow on the map to be detected, carrying out validity detection on the map to be detected; the potential hazards of the map to be detected in the subsequent use process can be effectively detected.

Fig. 4 is a flowchart of another map validity detection method according to an embodiment of the present application. The method flow in fig. 4 is one possible implementation of the method flow in fig. 2. As shown in fig. 4, the method includes:

401. the data processing device acquires a map to be detected.

In some embodiments, the data processing apparatus is a terminal device with a data processing function, such as a desktop computer, a notebook computer, a mobile phone, a tablet computer, a scene construction and simulation conversion device, and a simulator; the step 401 can be realized by acquiring a map to be detected transmitted by a mobile disk through a communication interface; or receiving the map to be detected from other terminal equipment through a communication interface; the map to be detected can also be acquired from a cloud server through a network. In some embodiments, the data processing apparatus is a cloud server; the implementation manner of step 401 may be to receive the map to be detected uploaded by the terminal device through the communication interface; or obtaining the map to be detected from other servers through the network. The method for acquiring the map to be detected by the data processing device is not limited.

402. And the data processing device preprocesses the map to be detected.

The high-precision map is usually a regional map, and only covers part of roads in a selected range according to actual use requirements, so that reasonable map anomalies such as map external boundaries, uncovered areas in the map and the like are inevitable. The data processing device for preprocessing the map to be detected comprises the following steps: marking a second road abnormity in the map to be detected; the second road abnormality belongs to a road abnormality caused by a boundary of the map to be detected or a road abnormality caused by an un-mapped area in the map to be detected. Or the second road anomaly belongs to a road anomaly in the map to be detected, which is unrelated to the drawing factor. In some embodiments, the data processing device may mark all road anomalies in the map to be detected that are not related to the drawing factors, such as road anomalies caused by boundaries of the map to be detected, road anomalies caused by un-mapped areas in the map to be detected, and the like. Step 402 may also be understood as identifying and labeling the boundaries of the map to be detected. In the map preprocessing process, the data processing device can mark reasonable boundary conditions of the map to be detected in a visual or data level by adopting a manual marking or automatic marking mode so as to facilitate subsequent processing. And for reasonable problems of broken roads of the boundary part of the map, un-mapped areas in the city, dead peers in the real world and the like, marking by using an automatic marking algorithm or a manual marking mode in a preprocessing stage.

403. And acquiring the running condition of the traffic flow on the map to be detected.

One possible implementation of step 403 is: the data processing device simulates or simulates the running of one or more vehicles on the map to be detected to obtain the running condition of the traffic flow on the map to be detected. One or more vehicles run on the map to be detected by adopting any legal and reasonable driving behaviors according to a configured automatic driving regulation mode (or regulation algorithm) to form a traffic flow. Since the driving behavior of each of the one or more vehicles on the map to be inspected is random, the traffic flow formed by the operation of the one or more vehicles on the map to be inspected is also random. It will be appreciated that the operation of the data processing means to simulate or simulate the operation of one or more vehicles on the map to be inspected may be considered to be the operation to generate a random traffic flow.

In some embodiments, the data processing apparatus may perform the following operations before performing step 403: receiving a rule control mode configuration instruction; and configuring an automatic driving regulation mode (or a regulation algorithm) for one or more vehicles according to the regulation mode configuration instruction. Another possible implementation of step 403 is: the data processing device simulates or simulates one or more vehicles to run on the map to be detected according to the configured automatic driving regulation and control mode, and the running condition of the traffic flow on the map to be detected is obtained. The configuration command according to the above rule control method may be: a regulatory mode profile (or information) is received from a terminal device. In these embodiments, the user may configure the automatic driving schedule for one or more vehicles based on their own needs. That is, the regulation and control manner (or regulation and control algorithm) used by the data processing device to generate the traffic flow (i.e. simulating or simulating the driving of one or more vehicles on the map to be detected to form the traffic flow) can be configured, and the user can select the default algorithm provided by the data processing device or use the own algorithm (or self-defined algorithm) according to the actual requirement. In the present application, the control algorithm and the control method have the same meaning.

An example of step 403 is as follows: the data processing device dynamically and randomly places vehicles in the map to be detected, and the vehicles randomly adopt driving behaviors such as straight movement, lane changing, left-right turning, turning around and the like in the map to be detected according to the configured regulation algorithm (or regulation control mode). After running for a period of time, the random traffic flow will cover all the selectable paths of all the roads in the map to be detected. In this example, the program run by the data processing apparatus may detect that the vehicle encounters a road abnormality while traveling, and generate corresponding abnormality information. That is, each vehicle corresponds to a program for detecting a road abnormality encountered by the vehicle, and the detection of a road abnormality encountered by a certain vehicle by the program may be regarded as the detection of a road abnormality encountered by the vehicle during travel. The program run by the data processing device generates the abnormality information in such a manner that the vehicle will send corresponding abnormality information (message) to the data processing device.

404. And the data processing device performs validity detection on the map to be detected according to the running condition of the traffic flow on the map to be detected.

In the embodiment of the application, the data processing device performs validity detection on the map to be detected according to the running condition of the traffic flow on the map to be detected; all roads and all passable paths of a map to be detected (such as a high-precision map) can be detected within preset time, so that various explicit and implicit problems can be detected. For example, the preset time may be in the order of minutes, seconds, or milliseconds. Therefore, the data processing device can accurately and efficiently detect the validity of the map to be detected by adopting the method flow in fig. 4.

The accuracy requirements of high-precision maps may be different for different usage scenarios. For example, the automatic driving real vehicle test requires that the road connection relation of the high-precision map is accurate and the topological shape is consistent with the real road. As another example, the global path planning test need only ensure the connectivity of high-precision maps. Therefore, before the map to be detected is subjected to validity detection, the user can configure the regulation algorithm used for generating the traffic flow, for example, select the default algorithm provided by the data processing device, or use the own algorithm according to the actual requirement. The map validity detection scheme is introduced below, in which a rule control algorithm used for generating a traffic flow is configured before validity detection is performed on a map to be detected.

Fig. 5 is a flowchart of another map validity detection method according to an embodiment of the present application. As shown in fig. 5, the method includes:

501. the data processing device receives a rule-controlled configuration instruction.

In some embodiments, the data processing apparatus is a terminal device with a data processing function, such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, or the like; the implementation of step 501 may be: user input of the prescribed-mode configuration instructions is received via an input device (e.g., keyboard, touch screen, mouse, etc.). In some embodiments, the data processing apparatus is a cloud server, and the implementation manner of step 501 may be: the data processing device receives a regulation mode configuration instruction from the terminal equipment. That is, the user may send the rule-wise configuration instruction to the cloud server through a terminal device (e.g., an in-vehicle device).

502. And the data processing device configures an automatic driving regulation and control mode for one or more vehicles according to the regulation and control mode configuration instruction.

In some embodiments, one possible implementation of step 501 may be to receive a regulatory mode profile (or information) from the terminal device; one possible implementation of step 502 may be to configure an automatic driving regulation method (or regulation algorithm) for the one or more vehicles according to the regulation method configuration file (or information). The regulatory mode profile may be used to configure an autonomous driving regulatory mode (or regulatory algorithm) for the one or more vehicles. The one or more vehicles can be automatically driven on the map to be detected by using the rule control mode configuration file. And the one or more vehicles can randomly take any driving behaviors on the map to be detected according to a configured automatic driving regulation mode (or a regulation algorithm).

In some embodiments, step 501 may be replaced with: the data processing device receives a rule control algorithm configuration instruction; step 502 may be replaced by: and the data processing device configures an automatic driving regulation and control algorithm for one or more vehicles according to the regulation and control algorithm configuration instruction. And the one or more vehicles can randomly take any driving behaviors on the map to be detected according to the configured automatic driving regulation algorithm to form a random traffic flow. For example, the user-configured data processing device generates a random traffic flow using a user-defined regulatory algorithm.

503. And the data processing device performs effectiveness detection on the map to be detected according to the running condition of one or more vehicles on the map to be detected in a configured automatic driving regulation and control mode.

One possible implementation of step 503 may be: and the data processing device outputs a quality inspection report according to the road abnormity encountered in the process that the one or more vehicles run on the map to be detected in the configured automatic driving regulation mode. For example, the data processing device obtains a plurality of items of abnormal information representing road abnormalities according to the road abnormalities encountered in the process that each vehicle runs on the map to be detected in the configured automatic driving regulation and control mode; summarizing and processing a plurality of items of abnormal information, and outputting the quality inspection report; the plurality of items of abnormality information include first abnormality information, and the quality inspection report includes the first abnormality information. The first anomaly information represents first road anomalies encountered by a first vehicle in the process of driving on the map to be detected according to the configured automatic driving regulation and control mode. The first road abnormality can be any item which fails to pass the validity detection, such as a road section, a speed limit sign, a road front, a road rear, a curve curvature, a lane line, a stop line, a signal lamp, a continuous access, a road overlap and the like, and can also be an abnormality aiming at a certain section of road. In this implementation, a quality inspection report is output based on road anomalies encountered during travel of one or more vehicles on the map to be inspected. The quality inspection report is obtained according to the road abnormity encountered in the process of driving one or more vehicles on the map to be inspected, so the quality inspection report can accurately reflect the road abnormity condition in the map to be inspected.

The accuracy requirements of high-precision maps may be different for different usage scenarios. For example, the automatic driving real vehicle test requires accurate road connection relation of a high-precision map and consistent topological shape with a real road; while the global path planning test only needs to ensure map connectivity. That is to say, for the map to be detected under different usage scenarios, the required detection items can be configured according to actual requirements, that is, which types of road anomalies are detected. In some embodiments, the data processing apparatus may be configured with a check term for detecting road anomalies. For example, the data processing device may maintain a library of inspection item algorithms for a set of pluggable high-precision maps, and the user may dynamically configure which inspection item algorithms the data processing device employs to detect road anomalies according to actual needs. In this example, the user may also upload and use an owned algorithm for checking item configurations. The map validity detection scheme is described below in which check items used for validity detection of a map to be detected are configured before validity detection of the map to be detected.

Fig. 6 is a flowchart of another map validity detection method according to an embodiment of the present application. As shown in fig. 6, the method includes:

601. the data processing apparatus receives a check item configuration instruction.

In some embodiments, the data processing apparatus is a terminal device with a data processing function, such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, or the like; the implementation of step 601 may be: the check item configuration instruction input by the user is received through an input device (such as a keyboard, a touch screen, a mouse and the like). In some embodiments, the data processing apparatus is a cloud server, and the implementation manner of step 601 may be: the data processing device receives the check item configuration instruction from the terminal equipment. That is, the user may transmit the check item configuration instruction to the cloud server through the terminal device (e.g., the in-vehicle device).

602. And the data processing device configures the check items of the map to be detected according to the check item configuration instruction.

In some embodiments, one possible implementation of step 601 may be to receive a configuration file (or information) from a receiving inspection item; one possible implementation of step 602 may be to configure the inspection item of the map to be detected according to the inspection item configuration file (or information). Configuring the check items of the map to be detected can be understood as configuring which kinds of road anomalies the data processing device detects. Fig. 7 is an example of a configuration of a detection item provided in an embodiment of the present application. As shown in fig. 7, the check items are divided into three categories, i.e., signals, connection relationships, and topology parameters, and each category includes a plurality of check items. For example, the data processing device configures the inspection items of the map to be inspected as each inspection item under the connection relationship and the road shape and the lane line under the topology parameter according to the inspection item configuration instruction.

603. And the data processing device acquires the running condition of the traffic flow on the map to be detected.

Step 603 may refer to step 201.

604. And the data processing device detects road abnormity encountered in the running process of the traffic flow on the map to be detected according to the check item.

In some embodiments, the check items of the map to be detected configured by the data processing apparatus include a plurality of items; the data processing device respectively adopts the checking item algorithm corresponding to each checking item to detect the road abnormity corresponding to the checking item. For example, the check items of the map to be detected, which are configured in advance by the data processing device, share F types, and the user configures the check items of the map to be detected as K types of the F types of check items through the check item configuration instruction according to the actual demand; the data processing device adopts K detection item algorithms corresponding to the K detection items to respectively detect the road abnormity corresponding to each detection item. F and K are both integers greater than 0.

605. And the data processing device performs validity detection on the map to be detected according to the detected road abnormity encountered in the running process of the traffic flow on the map to be detected.

In some embodiments, one possible implementation of step 603 is as follows: taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow; one possible implementation of step 604 is as follows: detecting road anomalies encountered by the one or more vehicles in the process of running on the map to be detected according to the check items; one possible implementation of step 605 is as follows: and carrying out validity detection on the map to be detected according to the detected road abnormity encountered in the process that one or more vehicles run on the map to be detected.

In the embodiment of the application, the road abnormity met by the traffic flow in the running process on the map to be detected is detected according to the check item, and the road abnormity beyond the check item does not need to be detected, so that the detection efficiency can be improved, and the workload can be reduced.

Fig. 8 is a flowchart of another map validity detection method according to an embodiment of the present application. The method flow in fig. 8 is one possible implementation of the method flow in fig. 5 or fig. 6. As shown in fig. 8, the method includes:

801. the data processing device receives a rule-controlled configuration instruction.

Step 801 may be referred to as step 501.

802. And the data processing device configures an automatic driving regulation and control mode for one or more vehicles according to the regulation and control mode configuration instruction.

Step 802 may be referred to as step 502.

803. The data processing apparatus receives a check item configuration instruction.

Step 803 may be referred to as step 601.

804. And the data processing device configures the check items of the map to be detected according to the check item configuration instruction.

Step 803 may be seen with reference to step 602.

805. And the data processing device takes the running condition of one or more vehicles on the map to be detected according to the configured automatic driving regulation and control mode as the running condition of the traffic flow.

In some embodiments, the data processing device simulates or simulates one or more vehicles to travel on the map to be detected according to the configured automatic driving regulation mode to obtain the traffic flow.

806. And the data processing device detects road abnormity encountered in the running process of the traffic flow on the map to be detected according to the check item.

Step 806 may be referred to as step 604.

807. And the data processing device performs validity detection on the map to be detected according to the detected road abnormity encountered in the running process of the traffic flow on the map to be detected.

Step 807 may be referred to as step 605.

In the embodiment of the application, on one hand, an automatic driving regulation mode is configured for one or more vehicles according to the received regulation mode configuration instruction, and the required driving regulation mode can be conveniently configured, so that the quality requirements of the map to be detected in different use scenes are met. On the other hand, road abnormity encountered in the running process of the traffic flow on the map to be detected is detected according to the check item, and the road abnormity beyond the check item is not required to be detected, so that the detection efficiency can be improved, and the workload can be reduced.

In practical application, a user usually needs to perform validity detection on a part of a region or some scenes in a map to be detected, namely a scene test requirement. In the application, the validity detection of a partial area or some scenes in a map to be detected can be called scene testing.

Aiming at the scene test requirement, a part of area (namely the area to be detected) in the high-precision map can be selected, and the part of area in the high-precision map can be detected in a refined mode. Fig. 9A is an example of a traffic signal lamp scene at an intersection according to an embodiment of the present application. Fig. 9B is an example of a roundabout import-export scenario provided in an embodiment of the present application. Fig. 9C is an example of an automatic driving scenario of a trunk road according to an embodiment of the present application.

Taking fig. 9A and 9B as an example, the scenario test may be to perform validity detection on a traffic light scene at a crossroad and a roundabout influx-efflux scene. The validity detection of the high-precision map can configure checking items related to stop lines, signal lamps, intersection connectivity, merging-in and merging-out roads and the like aiming at an area corresponding to an intersection traffic signal lamp scene or an area corresponding to a roundabout merging-out scene. Therefore, the detection efficiency is improved, and meanwhile, the fine detection of the local area can be ensured.

Taking fig. 9C as an example, the scenario test may be validity detection for an automatic driving scenario of a main road. The validity detection of the high-precision map can configure checking items related to road connectivity, topology, road types, lane line detection and the like aiming at the area corresponding to the automatic driving scene of the main road, and ensure that the area of the high-precision map related to the scene is accurate and valid.

Fig. 10 is a flowchart of another map validity detection method according to an embodiment of the present application. The data processing apparatus may implement the scenarized test by executing the method flow in fig. 10. As shown in fig. 10, the method includes:

1001. the data processing device determines a region to be detected in a map to be detected.

The area to be detected may be any area in the map to be detected. For example, the area to be detected is an area corresponding to one or more intersection traffic signal lamp scenes in the map to be detected. For example, the area to be detected is an area corresponding to one or more roundabout inflows into and out of the scene in the map to be detected.

In some embodiments, the data processing apparatus may receive a detection region selection instruction before performing step 1001; one possible implementation of step 1001 is as follows: and determining the area to be detected in the map to be detected according to the detection area selection instruction. In some embodiments, the data processing apparatus is a terminal device with a data processing function, such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, or the like; the data processing device receiving the detection area selection instruction may be: a detection area selection instruction input by a user is received through an input device (e.g., a keyboard, a touch screen, a mouse, etc.). For example, a user marks a circular frame or a rectangular frame in a map to be detected through a mouse, and the area corresponding to the circular frame or the rectangular frame is the area to be detected. For another example, the user marks a plurality of roads in the map to be detected by using a mouse, and the areas corresponding to the roads are the areas to be detected. In some embodiments, the data processing apparatus is a cloud server, and the receiving, by the data processing apparatus, the detection area selection instruction may be: the data processing device receives a detection area selection instruction from the terminal equipment. That is, the user may transmit the detection area selection instruction to the cloud server through a terminal device (e.g., an in-vehicle device). For example, a user marks a circular frame or a rectangular frame in a map to be detected through a mouse associated with the terminal device, and an area corresponding to the circular frame or the rectangular frame is an area to be detected; the terminal equipment generates a detection area selection instruction corresponding to the area to be detected and sends the detection area selection instruction to the data processing device.

1002. And the data processing device acquires the running condition of the traffic flow on the area to be detected.

Step 1002 may refer to step 201.

1003. And the data processing device performs validity detection on the area to be detected according to the running condition of the traffic flow on the area to be detected.

In the embodiment of the application, according to the running condition of the traffic flow on the area to be detected, the effectiveness detection is carried out on the area to be detected; various explicit and implicit problems of all passable paths in the area to be detected can be accurately and efficiently detected. In addition, according to the running condition of the traffic flow on the area to be detected, carrying out effectiveness detection on the area to be detected; the hidden danger of the to-be-detected area in the subsequent use process can be effectively detected.

Fig. 11 is a flowchart of another map validity detection method according to an embodiment of the present application. The method flow in fig. 11 is one possible implementation of the method flow in fig. 10. As shown in fig. 11, the method includes:

1101. the data processing device determines a region to be detected in a map to be detected.

Step 1101 may be referred to as step 1001.

1102. And the data processing device is used for preprocessing the area to be detected.

One possible implementation of step 1102 is as follows: and marking the road abnormity irrelevant to the drawing factors in the area to be detected. In the process of preprocessing the area to be detected, the data processing device can adopt a manual marking or automatic marking mode to mark road abnormity irrelevant to drawing factors in the area to be detected in a visual or data layer.

1103. The data processing apparatus receives the check item configuration instruction.

Step 1103 may refer to step 601.

1104. And the data processing device configures the inspection item of the area to be inspected according to the inspection item configuration instruction.

Step 1104 may be referred to as step 602.

1105. And the data processing device acquires the running condition of the traffic flow on the area to be detected.

Step 1105 may refer to step 201.

In some embodiments, the data processing apparatus may further perform the following operations: receiving a rule control algorithm configuration instruction; and configuring an automatic driving regulation and control algorithm for one or more vehicles according to the regulation and control algorithm configuration instruction. One possible implementation of step 1105 is as follows: and the data processing device takes the running condition of one or more vehicles which randomly adopt any driving behaviors on the area to be detected according to the configured automatic driving regulation algorithm as the running condition of the traffic flow on the area to be detected. That is, the data processing device may generate a corresponding traffic flow according to the configured regulatory algorithm.

1106. And the data processing device detects road abnormity encountered in the running process of the traffic flow on the area to be detected according to the check items and generates a plurality of items of abnormal information.

Each item of abnormal information in the plurality of items of abnormal information represents one or more road abnormalities encountered in the process of driving of one vehicle in the traffic flow on the area to be detected. Step 1106 may be referred to as step 604.

1107. The data processing device collects and processes the plurality of items of abnormal information and outputs a quality inspection report.

In some embodiments, before the data processing device performs summary processing on a plurality of items of abnormal information, the data processing device may remove abnormal information representing marked road abnormality from the plurality of items of abnormal information to obtain a plurality of items of initially selected abnormal information; and summarizing the plurality of items of initially selected abnormal information to obtain the quality inspection report. For example, the data processing apparatus may remove all road anomalies unrelated to the mapping factor, i.e. road anomalies marked in the preprocessing stage, from the plurality of items of anomaly information before performing the aggregate processing on the plurality of items of anomaly information.

In the embodiment of the application, validity detection is carried out on the to-be-detected area in the to-be-detected map, and a check item of the to-be-detected area is configured; the method can perform targeted detection on the area to be detected and improve the detection efficiency.

The map validity detection method provided by the application can be applied to an automatic driving cloud platform (corresponding to a cloud server). The cloud server can provide a map quality inspection function for the client by using the high-precision map management module. The cloud server can provide a set of automatic driving regulation and control algorithm as a default algorithm for high-precision map quality inspection (namely, validity inspection); meanwhile, a control interface of the rule control algorithm is opened, so that a client is allowed to upload according to the standard and use the self-owned algorithm for map validity detection. That is, the cloud server may generate a traffic flow using a default autopilot regulatory algorithm, or may generate a traffic flow using a custom regulatory algorithm uploaded by the user. In addition, the cloud server can also maintain a set of high-precision map inspection item algorithm library and can be dynamically configured according to actual requirements; while opening an exception message (error message) interface standard that allows clients to upload and use proprietary algorithms for checking item configurations in accordance with the standard. The following describes a scheme in which the cloud server provides a map quality inspection function for a user with reference to the accompanying drawings.

Fig. 12 is an interaction flowchart of another map validity detection method according to an embodiment of the present application. As shown in fig. 12, the method includes:

1201. and the terminal equipment sends the map to be detected to the data processing device.

The data processing device may be a cloud server, i.e. a server in an autonomous cloud platform. The terminal equipment can be vehicle-mounted equipment, a mobile phone, a tablet computer, a notebook computer, a desktop computer and other terminal equipment with a data processing function. FIG. 13 illustrates an example of a map management interface. As shown in fig. 13, the map management interface includes: an upload map package option and a detail option, an update option, a delete option, and a quality check option for each map package uploaded to the cloud server. In fig. 13, each row shows the ID, name, status, creation time, update time of an uploaded map package, and details option, update option, deletion option, and quality inspection option for the map package. The user selects (e.g., clicks, touches) a details option for a certain map package and the map management interface may present the details of the map package. A map package may be updated after a user selects (e.g., clicks, touches) an update option for the map package. The user selects (e.g., clicks, touches) a delete option for a map package and can delete the information for that map package in the map management interface. The user selects (for example, clicks and touches) a quality inspection option for a certain map package, and the cloud server performs validity inspection on the map package. After a user selects (for example, clicks) an option of uploading a map packet, an open window can pop up in a map management interface displayed by the terminal device, and the user can select the map packet stored by the terminal device under any path through the open window and upload the map packet to the cloud server.

1202. And the terminal equipment sends an effectiveness detection instruction aiming at the map to be detected to the data processing device.

In some embodiments, after detecting that the user selects (e.g., clicks, touches) the quality inspection option for the map to be detected, the terminal device sends a validity detection instruction for the map to be detected to the data processing apparatus.

1203. And the data processing device detects the effectiveness of the map to be detected and sends a quality inspection report to the terminal equipment.

The data processing device can adopt the method flow in fig. 2 and fig. 4 to detect the validity of the map to be detected. The data processing device may perform validity detection on the map to be detected, and may be: and responding to the validity detection instruction aiming at the map to be detected, and performing validity detection on the map to be detected by the data processing device.

1204. And displaying the quality inspection report by the terminal equipment.

The quality inspection report can show which inspection items of the map to be detected pass the validity detection and which inspection items do not pass the validity detection. Fig. 13 is an example of a quality inspection report provided in an embodiment of the present application. As shown in fig. 13, the three items of inspection items, i.e., the curvature of a curve, the section of a road, and the overlap of roads, of the map to be detected fail to pass the validity detection, and other items of inspection (e.g., connectivity, signal lights, speed limit signs, road successors, etc.) all pass the validity detection.

1205. And the terminal equipment responds to the received quality inspection report visualization instruction and displays the visualization result of the quality inspection report.

Fig. 14 is an example of a visualization result of a quality inspection report provided in an embodiment of the present application. As shown in fig. 14, one road anomaly is shown in each circle. In some embodiments, the quality inspection report displayed by the terminal device includes a visualization option, and the terminal device detects that an operation of selecting the visualization option by the user is that a quality inspection report visualization instruction is received. Step 1203 is optional, not necessary.

In the embodiment of the application, the terminal equipment can conveniently and quickly detect the effectiveness of any map by utilizing the map quality inspection function provided by the data processing device.

Fig. 15 is an interaction flowchart of another map validity detection method according to an embodiment of the present application. The method flow in fig. 15 is one possible implementation of the method flow in fig. 12. As shown in fig. 15, the method includes:

1501. and the terminal equipment sends the map to be detected to the data processing device.

Step 1501 may be seen as step 1201.

1502. And the terminal equipment sends a checking item configuration instruction and/or a regulation mode configuration instruction to the data processing device.

Fig. 16 is an example of a custom configuration interface provided in an embodiment of the present application. As shown in FIG. 16, the custom configuration interface includes: using built-in algorithm options, simulation algorithm interfaces, algorithm version interfaces, using built-in configuration options, custom configuration options, and default configuration options. The built-in algorithm option is used for corresponding to two states, and if the built-in algorithm option is used in the state in the graph 16, the terminal device configuration is indicated to adopt a custom algorithm to carry out validity detection on the map to be detected; if the option using the built-in algorithm is not in the state shown in fig. 16, it indicates that the map to be detected is detected using the built-in algorithm for validity detection. If the option using the built-in algorithm is in the state shown in fig. 16, the user selects the simulation algorithm (i.e., the rule control algorithm) used for validity detection of the map to be detected through the simulation algorithm interface and selects the version of the simulation algorithm through the algorithm version interface. The built-in configuration options correspond to two states, and if the built-in configuration options are in the state in fig. 16, it indicates that the terminal device adopts built-in configuration (i.e., a default check item) to perform validity detection on the map to be detected; if the use of the built-in configuration option is not in the state shown in fig. 16, it indicates that the map to be detected is detected to be valid by using the custom configuration. In some embodiments, after the user selects the custom configuration option in the custom configuration interface, the terminal device displays the check item configuration interface, and the user can configure the check item of the map to be detected through the check item configuration interface. It should be understood that the operation of configuring the simulation algorithm and evaluating the item configuration (i.e. the test item configuration) through the user-defined configuration interface displayed by the terminal device is the operation of sending the test item configuration instruction and/or the rule mode configuration instruction to the data processing apparatus.

1503. And the terminal equipment sends an effectiveness detection instruction aiming at the map to be detected to the data processing device.

Step 1503 may be referred to as step 1202.

1504. And the data processing device performs validity detection on the map to be detected according to the inspection item configuration instruction and/or the regulation mode configuration instruction, and sends a quality inspection report to the terminal equipment.

One possible implementation of step 1504 is as follows: the data processing device configures the inspection item of the map to be detected according to the inspection item configuration instruction; configuring an automatic driving regulation and control mode for one or more vehicles according to a regulation and control mode configuration instruction; the data processing device takes the running condition of one or more vehicles on the map to be detected according to the configured automatic driving regulation and control mode as the running condition of the traffic flow; the data processing device detects road abnormity encountered in the running process of the traffic flow on the map to be detected according to the check item; and the data processing device performs validity detection on the map to be detected according to the road abnormity encountered in the running process of the detected traffic flow on the map to be detected, and sends a quality inspection report to the terminal equipment. An example of the data processing device performing validity detection on the map to be detected according to the detected road abnormality encountered in the running process of the traffic flow on the map to be detected is as follows: the data processing device detects road abnormity encountered in the running process of the traffic flow on the map to be detected according to the check items and generates a plurality of items of abnormal information; and summarizing the plurality of items of abnormal information to obtain a quality inspection report.

In some embodiments, step 1503 may be replaced with: the method comprises the steps that terminal equipment sends an effectiveness detection instruction for a to-be-detected area in a to-be-detected map to a data processing device; step 1504 may be replaced with: and the data processing device performs validity detection on the area to be detected according to the inspection item configuration instruction and/or the regulation mode configuration instruction, and sends a quality inspection report to the terminal equipment.

1505. And the terminal equipment displays the quality inspection report.

Step 1505 may be found in step 1204.

1506. And the terminal equipment responds to the received quality inspection report visualization instruction and displays the visualization result of the quality inspection report.

Step 1506 may refer to step 1205.

In the embodiment of the application, the terminal equipment can conveniently and quickly detect the effectiveness of any map by utilizing the map quality inspection function provided by the data processing device. The user can also send a check item configuration instruction and/or a rule control mode configuration instruction to the data processing device through the terminal equipment so as to adapt to the quality requirements of the map to be detected in different use scenes.

The map validity detection method provided by the application is introduced in the foregoing. A data processing apparatus for implementing the map validity detection method provided by the present application is described below.

Fig. 17 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application. As shown in fig. 17, the data processing apparatus includes:

an acquisition unit 1701 for acquiring the running status of the traffic flow on the map to be detected;

the processing unit 1702 is configured to perform validity check on the map to be checked according to the running status of the traffic flow on the map to be checked.

In a possible implementation manner, the obtaining unit 1701 is specifically configured to use an operation condition of one or more vehicles on the map to be detected as an operation condition of the traffic flow; randomly taking any driving behavior by the one or more vehicles on the map to be detected;

the processing unit 1702 is specifically configured to perform validity check on the map to be checked according to the driving condition of the one or more vehicles on the map to be checked.

In a possible implementation manner, the processing unit 1702 is specifically configured to output a quality inspection report according to a road anomaly encountered during the driving of the one or more vehicles on the map to be detected.

In one possible implementation, the one or more vehicles include a first vehicle;

a processing unit 1702, configured to obtain first anomaly information representing that the first road is anomalous according to a first road anomaly encountered during a process that the first vehicle travels on the map to be detected; summarizing and processing a plurality of items of abnormal information to obtain the quality inspection report; the above-mentioned device still includes:

an output unit 1703 configured to output the quality inspection report; the plurality of items of abnormality information include the first abnormality information, and the quality inspection report includes the first abnormality information.

In a possible implementation manner, the processing unit 1702 is further configured to remove the first vehicle from the traffic flow after the first vehicle encounters the first road abnormality during the driving on the map to be detected.

In a possible implementation manner, the plurality of items of exception information include second exception information; the second anomaly information represents a second road anomaly in the map to be detected, which is irrelevant to the drawing factor, and the quality inspection report does not include the second anomaly information.

In a possible implementation manner, the processing unit 1702 is further configured to mark the second road anomaly in the map to be detected; the second road abnormality belongs to a road abnormality caused by a boundary of the map to be detected or a road abnormality caused by an un-mapped area in the map to be detected.

In a possible implementation manner, the processing unit 1702 is specifically configured to remove the second road anomaly from the multiple items of anomaly information, so as to obtain multiple items of initially selected anomaly information; and summarizing the plurality of items of initially selected abnormal information and outputting the quality inspection report.

In a possible implementation manner, the processing unit 1702 is further configured to configure the check item of the map to be detected; and detecting road abnormity encountered by the first vehicle in the process of running on the map to be detected according to the check item to obtain the first road abnormity.

In a possible implementation manner, the apparatus further includes: a receiving unit 1704 for receiving a check item configuration instruction; the processing unit 1702 is further configured to configure the check item of the map to be detected according to the check item configuration instruction.

In a possible implementation, the processing unit 1702 is further configured to configure an automatic driving regulation mode for the one or more vehicles; the automatic driving regulation mode is a default regulation mode or a user-defined regulation mode, and the one or more vehicles randomly take any driving behaviors on the map to be detected according to the configured automatic driving regulation mode.

In a possible implementation manner, the receiving unit 1704 is further configured to receive a rule-based configuration instruction;

the processing unit 1702 is further configured to configure the automatic driving regulation method for the one or more vehicles according to the regulation method configuration command.

In a possible implementation manner, the processing unit 1702 is further configured to determine an area to be detected in the map to be detected;

an obtaining unit 1701, which is specifically configured to use an operation status of one or more vehicles on the to-be-detected area as an operation status of the traffic flow;

the processing unit 1702 is specifically configured to perform validity detection on the area to be detected according to the running status of the traffic flow in the area to be detected.

In a possible implementation manner, the receiving unit 1704 is further configured to receive a detection area selection instruction;

the processing unit 1702 is specifically configured to determine the to-be-detected area in the to-be-detected map according to the detection area selection instruction.

In a possible implementation manner, the receiving unit 1704 is further configured to receive the map to be detected from the terminal device; output section 1703 is specifically configured to output the quality inspection report to the terminal device.

Fig. 18 is a schematic structural diagram of another data processing apparatus according to an embodiment of the present application. As shown in fig. 18, the data processing apparatus includes:

a processing unit 1801, configured to determine a to-be-detected area in a to-be-detected map;

an obtaining unit 1802, configured to obtain an operation status of a traffic flow on the area to be detected;

the processing unit 1801 is further configured to perform validity detection on the area to be detected according to the running status of the traffic flow on the area to be detected.

In a possible implementation manner, the apparatus further includes: a receiving unit 1803, configured to receive a detection area selection instruction; the processing unit 1801 is specifically configured to determine the to-be-detected area in the to-be-detected map according to the detection area selection instruction.

In a possible implementation manner, the processing unit 1801 is specifically configured to use an operation status of one or more vehicles on the area to be detected as an operation status of the traffic flow; randomly taking any driving behavior by the one or more vehicles on the area to be detected; and performing effectiveness detection on the area to be detected according to the running condition of the one or more vehicles on the area to be detected.

In a possible implementation manner, the processing unit 1801 is specifically configured to obtain a quality inspection report according to a road anomaly encountered during a process that the one or more vehicles travel on the area to be detected; the above-mentioned device still includes: an output unit 1804 configured to output the quality inspection report.

In one possible implementation, the one or more vehicles include a first vehicle; a processing unit 1801, configured to obtain first anomaly information indicating that the first road is anomalous, according to a first road anomaly encountered during a process that the first vehicle travels on the area to be detected; summarizing and processing a plurality of items of abnormal information to obtain the quality inspection report; the plurality of items of abnormality information include the first abnormality information, and the quality inspection report includes the first abnormality information.

In a possible implementation manner, the processing unit 1801 is further configured to mark the second road anomaly in the area to be detected; the second road abnormality belongs to a road abnormality caused by a boundary of the area to be detected or a road abnormality caused by an area not mapped in the area to be detected.

In a possible implementation manner, the processing unit 1801 is specifically configured to remove the second road anomaly from the multiple items of anomaly information, so as to obtain multiple items of initially selected anomaly information; and summarizing the plurality of items of initially selected abnormal information to obtain the quality inspection report.

In a possible implementation manner, the processing unit 1801 is further configured to configure the inspection item of the to-be-detected region; and detecting road abnormity encountered in the process of driving of the first vehicle on the area to be detected according to the inspection item to obtain the first road abnormity.

In a possible implementation manner, the apparatus further includes: a receiving unit 1803, configured to receive a check item configuration instruction; the processing unit 1801 is specifically configured to configure the inspection item of the to-be-detected region according to the inspection item configuration instruction.

In a possible implementation manner, the processing unit 1801 is further configured to configure an automatic driving regulation manner for the one or more vehicles; the automatic driving regulation mode is a default regulation mode or a user-defined regulation mode, and the one or more vehicles randomly take any driving behaviors on the area to be detected according to the configured automatic driving regulation mode.

In a possible implementation manner, the receiving unit 1803 is further configured to receive a rule-based configuration instruction; the processing unit 1801 is specifically configured to configure the automatic driving regulation method for the one or more vehicles according to the regulation method configuration instruction.

In a possible implementation manner, the receiving unit 1803 is further configured to receive the map to be detected from the terminal device; the output unit 1804 is specifically configured to output the quality inspection report to the terminal device.

Fig. 19 is a schematic structural diagram of another data processing apparatus according to an embodiment of the present application. As shown in fig. 19, the data processing apparatus includes:

a receiving unit 1901, configured to receive a rule-based configuration instruction;

a processing unit 1902, configured to configure an automatic driving regulation and control manner for one or more vehicles according to the regulation and control manner configuration instruction; and performing effectiveness detection on the map to be detected according to the running condition of the one or more vehicles on the map to be detected according to the automatic driving regulation mode.

In a possible implementation manner, the receiving unit 1901 is specifically configured to receive a regulatory mode configuration file (or information) from a terminal device; the processing unit 1902 is specifically configured to configure an automatic driving regulation and control manner for the one or more vehicles according to the regulation and control manner configuration file (or information).

In a possible implementation manner, the processing unit 1902 is specifically configured to obtain a quality inspection report according to a road anomaly encountered by the one or more vehicles during the driving process on the map to be detected according to the automatic driving regulation method; the above-mentioned device still includes: an output unit 1903 is configured to output the quality inspection report.

In one possible implementation, the one or more vehicles include a first vehicle; a processing unit 1902, specifically configured to obtain first anomaly information representing an anomaly of the first road according to the first road anomaly encountered by the first vehicle during traveling on the map to be detected in the automatic driving regulation manner; summarizing and processing a plurality of items of abnormal information to obtain the quality inspection report; the plurality of items of abnormality information include the first abnormality information, and the quality inspection report includes the first abnormality information.

In a possible implementation manner, the processing unit 1902 is further configured to mark the second road anomaly in the map to be detected; the second road abnormality belongs to a road abnormality caused by a boundary of the map to be detected or a road abnormality caused by an un-mapped area in the map to be detected.

In a possible implementation manner, the processing unit 1902 is specifically configured to remove the second road anomaly from the multiple items of anomaly information, so as to obtain multiple items of initially selected anomaly information; and summarizing the plurality of items of initially selected abnormal information to obtain the quality inspection report.

In a possible implementation manner, the processing unit 1902 is further configured to configure an inspection item of the map to be detected; and detecting road abnormity encountered by the first vehicle in the process of running on the map to be detected according to the check item to obtain the first road abnormity.

In a possible implementation manner, the processing unit 1902 is further configured to determine an area to be detected in the map to be detected; the processing unit 1902 is specifically configured to perform validity detection on the map to be detected according to the driving conditions of the one or more vehicles on the area to be detected according to the automatic driving regulation method.

In a possible implementation manner, the receiving unit 1901 is further configured to receive a detection area selection instruction; the processing unit 1902 is specifically configured to determine the to-be-detected area in the to-be-detected map according to the detection area selection instruction.

Fig. 20 is a schematic structural diagram of another data processing apparatus according to an embodiment of the present application. As shown in fig. 20, the data processing apparatus includes:

a receiving unit 2001 for receiving a check item configuration instruction;

the processing unit 2002 is configured to configure the check item of the map to be detected according to the check item configuration instruction;

an obtaining unit 2003, configured to obtain an operation status of a traffic flow on the map to be detected;

the processing unit 2002 is further configured to detect, according to the check item, a road anomaly encountered by the traffic flow in the running process on the map to be detected; and carrying out validity detection on the map to be detected according to the detected road abnormity encountered by the traffic flow in the running process on the map to be detected.

In a possible implementation, the receiving unit 2001 is specifically configured to receive the check item configuration file; the processing unit 2002 is specifically configured to configure the check item of the map to be detected according to the check item configuration file.

In a possible implementation manner, the processing unit 2002 is specifically configured to use an operation condition of one or more vehicles on the map to be detected as an operation condition of the traffic flow; randomly taking any driving behavior by the one or more vehicles on the map to be detected; detecting road anomalies encountered by the one or more vehicles in the process of running on the map to be detected according to the check items; and carrying out validity detection on the map to be detected according to the detected road abnormity encountered in the process that the one or more vehicles run on the map to be detected.

In a possible implementation manner, the processing unit 2002 is specifically configured to obtain a quality inspection report according to a road anomaly encountered during a process that the one or more vehicles travel on the map to be detected; the above-mentioned device still includes:

an output unit 2004 is configured to output the quality inspection report, where the quality inspection report includes a result of validity detection of the map to be detected.

In one possible implementation, the one or more vehicles include a first vehicle; a processing unit 2002, configured to obtain, according to a first road anomaly encountered during a process in which the first vehicle travels on the map to be detected, first anomaly information representing the first road anomaly; summarizing and processing a plurality of items of abnormal information to obtain the quality inspection report; the plurality of items of abnormality information include the first abnormality information, and the quality inspection report includes the first abnormality information.

In a possible implementation, the processing unit 2002 is further configured to configure an automatic driving regulation mode for the one or more vehicles; the automatic driving regulation and control mode is a default regulation and control mode or a user-defined regulation and control mode, and the one or more vehicles randomly adopt any driving behaviors on the map to be detected according to the configured automatic driving regulation and control mode.

In a possible implementation manner, the receiving unit 2001 is further configured to receive a rule-based configuration instruction; the processing unit 2002 is specifically configured to configure the automatic driving regulation method for the one or more vehicles according to the regulation method configuration command.

In a possible implementation manner, the processing unit 2002 is further configured to determine a to-be-detected area in the to-be-detected map; an obtaining unit 2003, specifically configured to obtain an operation status of a traffic flow on the area to be detected;

the processing unit 2002 is specifically configured to detect, according to the check item, a road anomaly encountered during operation of the traffic flow in the to-be-detected area; and performing effectiveness detection on the area to be detected according to the detected road abnormity encountered in the running process of the traffic flow on the area to be detected.

In a possible implementation manner, the receiving unit 2001 is further configured to receive a detection area selection instruction; the processing unit 2002 is specifically configured to determine the area to be detected in the map to be detected according to the detection area selection instruction.

Fig. 21 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in fig. 21, the terminal device 210 includes a processor 2101, a memory 2102, and an input/output device 2103. The processor 2101, the memory 2102 and the input/output device 2103 are connected to each other by a bus. The terminal device in fig. 21 may be the data processing apparatus in the foregoing embodiment.

The memory 2102 includes, but is not limited to, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a compact disc read-only memory (CDROM), and the memory 2102 is used for related instructions and data. The input-output device 2103 is used for inputting and outputting data.

The processor 2101 may be one or more Central Processing Units (CPUs), and in the case where the processor 2101 is one CPU, the CPU may be a single-core CPU or a multi-core CPU. The steps performed by the data processing apparatus in the above-described embodiment may be based on the structure of the terminal device shown in fig. 21. In some embodiments, the processor 2101 may implement the functions of the acquisition unit 1701 and the processing unit 1702; the input-output device 2103 may implement the function of the output unit 1703 and the function of the receiving unit 1704. In some embodiments, the processor 2101 may implement the functions of the processing unit 1801 and the functions of the acquisition unit 1802; the input-output device 2103 may implement the functions of the reception unit 1803 and the functions of the output unit 1804. In some embodiments, the processor 2101 may implement the functions of the processing unit 1902; the input-output device 2103 can realize the function of the receiving unit 1901 and the function of the output unit 1903. In some embodiments, the processor 2101 may implement the functions of the processing unit 2002 and the acquisition unit 2003; the input-output device 2103 can realize the function of the receiving unit 2001 and the function of the output unit 2004. For example, input output device 2103 includes a display that can display quality control information. For another example, the input/output device 2103 sends the quality inspection report to other devices through the communication interface.

Fig. 22 is a schematic structural diagram of a server 2200 provided in an embodiment of the present application, where the server 2200 may have a relatively large difference due to different configurations or performances, and may include one or more Central Processing Units (CPUs) 2222 (e.g., one or more processors) and a memory 2232, and one or more storage media 2230 (e.g., one or more mass storage devices) storing applications 2242 or data 2244. The memory 2232 and the storage medium 2230 can be, among other things, transient storage or persistent storage. The program stored in the storage medium 2230 may include one or more modules (not shown), each of which may include a series of instruction operations for the server. Further, the central processor 2222 may be configured to communicate with the storage medium 2230, and execute a series of instruction operations in the storage medium 2230 on the server 2200. The server 2200 may be the data processing apparatus described above.

The server 2200 may also include one or more power supplies 2226, one or more wired or wireless network interfaces 2250, one or more input-output interfaces 2258, and/or one or more operating systems 2241, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, etc.

The steps performed by the data processing apparatus in the above-described embodiment may be based on the server configuration shown in fig. 22. In some embodiments, the central processor 2222 may perform the functions of the acquisition unit 1701 and the functions of the processing unit 1702; input/output interface 2258 may perform the functions of output unit 1703 and the functions of receive unit 1704. In some embodiments, central processor 2222 may perform the functions of processing unit 1801 and the functions of acquisition unit 1802; the input-output interface 2258 may implement the functions of the reception unit 1803 and the functions of the output unit 1804. In some embodiments, central processor 2222 may perform the functions of processing unit 1902; the input-output interface 2258 may implement the functions of the receiving unit 1901 and the functions of the output unit 1903. In some embodiments, the central processor 2222 may implement the functions of the processing unit 2002 and the functions of the acquisition unit 2003; the input-output interface 2258 may implement the functions of the receiving unit 2001 and the functions of the output unit 2004.

In an embodiment of the present application, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the map validity detection method provided in the foregoing embodiment.

The embodiment of the present application provides a computer program product containing instructions, which when run on a computer, causes the computer to execute the map validity detection method provided by the foregoing embodiment.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A map validity detection method is characterized by comprising the following steps:

acquiring the running condition of a traffic flow on a map to be detected;

and performing validity detection on the map to be detected according to the running condition of the traffic flow on the map to be detected.

2. The method according to claim 1, wherein the acquiring the running condition of the traffic flow on the map to be detected comprises:

taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow; randomly taking any driving behavior by the one or more vehicles on the map to be detected;

the detecting the effectiveness of the map to be detected according to the operation condition of the traffic flow on the map to be detected comprises the following steps:

and carrying out validity detection on the map to be detected according to the running condition of the one or more vehicles on the map to be detected.

3. The method according to claim 2, wherein the validity check of the map to be detected according to the driving conditions of the one or more vehicles on the map to be detected comprises:

and outputting a quality inspection report according to the road abnormity encountered in the process of driving the one or more vehicles on the map to be detected.

4. The method of claim 3, wherein the one or more vehicles includes a first vehicle; the outputting a quality inspection report according to the road abnormality encountered in the process of driving the one or more vehicles on the map to be detected comprises:

obtaining first abnormal information representing the first road abnormity according to the first road abnormity encountered in the process of driving of the first vehicle on the map to be detected;

summarizing and processing a plurality of items of abnormal information, and outputting the quality inspection report; the plurality of items of exception information include the first exception information, and the quality inspection report includes the first exception information.

5. The method of claim 4, wherein the plurality of items of anomaly information include second anomaly information; the second abnormal information represents second road abnormality irrelevant to drawing factors in the map to be detected, and the quality inspection report does not include the second abnormal information.

6. The method of claim 5, further comprising:

marking the second road abnormity in the map to be detected; the second road abnormity belongs to road abnormity caused by the boundary of the map to be detected or road abnormity caused by an un-mapped area in the map to be detected.

7. The method according to any one of claims 4 to 6, characterized in that before obtaining first anomaly information characterizing a first road anomaly encountered by the first vehicle during its travel on the map to be detected, the method further comprises:

configuring a check item of the map to be detected;

and detecting road abnormity encountered in the process of driving of the first vehicle on the map to be detected according to the inspection item to obtain the first road abnormity.

8. The method according to any one of claims 2 to 7, further comprising:

configuring an automatic driving regulation and control mode for the one or more vehicles; the automatic driving regulation and control mode is a default regulation and control mode or a user-defined regulation and control mode, and the one or more vehicles randomly adopt any driving behaviors on the map to be detected according to the configured automatic driving regulation and control mode.

9. The method according to any one of claims 2 to 7, characterized in that before taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow, the method further comprises:

determining a region to be detected in the map to be detected;

the taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow comprises the following steps:

taking the running condition of one or more vehicles on the area to be detected as the running condition of the traffic flow;

the detecting the effectiveness of the map to be detected according to the running condition of the traffic flow on the map to be detected comprises the following steps:

and carrying out validity detection on the area to be detected according to the running condition of the traffic flow in the area to be detected.

10. The method of claim 9, prior to determining the area to be detected in the map to be detected, the method further comprising:

receiving a detection area selection instruction;

determining the area to be detected in the map to be detected comprises:

and determining the area to be detected in the map to be detected according to the detection area selection instruction.

11. A data processing apparatus, comprising:

the acquiring unit is used for acquiring the running condition of the traffic flow on the map to be detected;

12. The apparatus of claim 11,

the acquisition unit is specifically used for taking the running condition of one or more vehicles on the map to be detected as the running condition of the traffic flow; randomly taking any driving behavior by the one or more vehicles on the map to be detected;

the processing unit is specifically configured to perform validity detection on the map to be detected according to the running condition of the one or more vehicles on the map to be detected.

13. The apparatus of claim 12,

the processing unit is specifically configured to output a quality inspection report according to the road abnormality encountered during the driving process of the one or more vehicles on the map to be detected.

14. The apparatus of claim 13, wherein the one or more vehicles comprises a first vehicle;

the processing unit is specifically configured to obtain first abnormal information representing that the first road is abnormal according to the first road abnormality encountered during the driving process of the first vehicle on the map to be detected; summarizing and processing multiple items of abnormal information to obtain the quality inspection report; the device further comprises:

an output unit for outputting the quality inspection report; the plurality of items of exception information include the first exception information, and the quality inspection report includes the first exception information.

15. The apparatus of claim 14, wherein the plurality of items of exception information include second exception information; the second abnormal information represents second road abnormality irrelevant to drawing factors in the map to be detected, and the quality inspection report does not include the second abnormal information.

16. The apparatus of claim 15,

the processing unit is further used for marking the second road abnormity in the map to be detected; the second road abnormity belongs to road abnormity caused by the boundary of the map to be detected or road abnormity caused by an un-mapped area in the map to be detected.

17. The apparatus according to any one of claims 14 to 16,

the processing unit is also used for configuring the checking items of the map to be detected;

and detecting road abnormity encountered in the process of driving of the first vehicle on the map to be detected according to the check item to obtain the first road abnormity.

18. The apparatus of any one of claims 12 to 17,

the processing unit is further used for configuring an automatic driving regulation and control mode for the one or more vehicles; the automatic driving regulation and control mode is a default regulation and control mode or a user-defined regulation and control mode, and the one or more vehicles randomly adopt any driving behaviors on the map to be detected according to the configured automatic driving regulation and control mode.

19. The apparatus of any one of claims 12 to 17,

the processing unit is further used for determining a to-be-detected area in the to-be-detected map;

the acquiring unit is specifically configured to use an operation status of one or more vehicles in the area to be detected as an operation status of the traffic flow;

the processing unit is specifically configured to perform validity detection on the area to be detected according to the operation condition of the traffic flow in the area to be detected.

20. The apparatus of claim 19, further comprising:

a receiving unit, configured to receive a detection area selection instruction;

the processing unit is specifically configured to determine the area to be detected in the map to be detected according to the detection area selection instruction.

21. An electronic device, comprising:

a memory for storing a program;

a processor for executing the program stored by the memory, the processor being configured to perform the method of any of claims 1-10 when the program is executed.

22. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to carry out the method according to any one of claims 1-10.