CN113722342A - High-precision map element change detection method, device and equipment and automatic driving vehicle - Google Patents
High-precision map element change detection method, device and equipment and automatic driving vehicle Download PDFInfo
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Abstract
The disclosure provides a high-precision map element change detection method and device, electronic equipment, a readable storage medium and a computer program product, and relates to the field of automatic driving and intelligent transportation. The specific implementation scheme is as follows: detecting the triggering condition of manual takeover in the current running order operation process of the automatic driving vehicle; under the condition that the manual takeover is triggered, generating vehicle running data of the automatic driving vehicle within a specified time range before and after the manual takeover is triggered; and detecting a change situation of the map elements in the high-precision map according to the vehicle running data when the current running order operation is finished. In this case, when the current travel order operation is completed, the change of the map elements in the high-precision map can be detected based on the vehicle travel data. Therefore, the timeliness of changing and detecting the map elements in the high-precision map is ensured.
Description
Technical Field
The present disclosure relates to the field of artificial intelligence, and in particular to an automatic driving and intelligent transportation technology, which can be used in automatic driving, data processing and other scenes.
Background
The travel of the autonomous vehicle requires support depending on a high-precision map. Therefore, it is an important step to detect a change in map elements in a high-precision map in time and to change the map elements in the high-precision map, thereby ensuring the timeliness of the high-precision map and the safety of an automatically driven vehicle.
However, in the existing scheme for detecting the change of the map elements in the high-precision map, the timeliness is often low, so that the timeliness of the high-precision map is poor.
Disclosure of Invention
The present disclosure provides a high-precision map element change detection method, device, electronic apparatus, readable storage medium, and computer program product to improve timeliness of change detection of map elements in a high-precision map.
According to an aspect of the present disclosure, there is provided a high-precision map element change detection method, which may include:
detecting the triggering condition of manual takeover in the current running order operation process of the automatic driving vehicle;
under the condition that the manual takeover is triggered, generating vehicle running data of the automatic driving vehicle within a specified time range before and after the manual takeover is triggered;
and detecting a change situation of the map elements in the high-precision map according to the vehicle running data when the current running order operation is finished.
According to a second aspect of the present disclosure, there is provided a high-precision map element change detection apparatus, which may include:
the manual takeover triggering detection module is used for detecting the triggering condition of manual takeover in the current running order operation process of the automatic driving vehicle;
the vehicle running data generation module is used for generating vehicle running data of the automatic driving vehicle within a specified time range before and after triggering the manual takeover under the condition that triggering of the manual takeover is detected;
and the map element change detection module is used for detecting the change situation of the map elements in the high-precision map according to the vehicle driving data when the current driving order operation is finished.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method according to any one of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform a method in any of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the method in any of the embodiments of the present disclosure.
According to another aspect of the present disclosure, an autonomous vehicle is provided, including the electronic device provided in the embodiments of the present disclosure.
The disclosed technology can detect a change of a map element in a high-precision map from vehicle travel data when the current travel order operation is completed. Therefore, the timeliness of changing and detecting the map elements in the high-precision map is ensured.
In addition, only vehicle travel data is generated during the current travel order operation of the autonomous vehicle, and when the current travel order operation is completed, the map elements in the high-precision map are detected to be changed. Therefore, the change detection of high-precision map elements can be greatly reduced, and the occupation of vehicle-end resources in the running process of the automatic driving vehicle can be greatly reduced.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a flowchart of a high-precision map element change detection method provided in an embodiment of the present disclosure;
fig. 2 is a flowchart of a method of generating vehicle travel data provided in an embodiment of the present disclosure;
FIG. 3 is a flowchart of a method for detecting changes in map elements provided in an embodiment of the present disclosure;
FIG. 4 is a flowchart of a method for detecting changes in map elements according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a map element change that may occur in an embodiment of the present disclosure;
fig. 6 is a schematic diagram of a high-precision map element change detection apparatus provided in an embodiment of the present disclosure;
fig. 7 is a schematic view of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The present disclosure provides a high-precision map element change detection method, and specifically refers to fig. 1, which is a flowchart of a high-precision map element change detection method provided in an embodiment of the present disclosure. The method may comprise the steps of:
step S101: and detecting the triggering condition of manual take-over in the current running order operation process of the automatic driving vehicle.
Step S102: and under the condition that triggering manual takeover is detected, generating vehicle running data of the automatic driving vehicle within a specified time range before and after triggering manual takeover.
Step S103: when the current travel order operation is completed, a change situation of a map element in the high-precision map is detected according to the vehicle travel data.
In the high-precision map element change detection method provided in the embodiments of the present disclosure, the execution subject is mainly a client, and the client may be a target program, an application, or software installed on an autonomous vehicle.
The target program, application, or software may be a program, application, or software having a function of detecting a change in a map element with high accuracy.
The high-precision map element change detection method provided by the embodiment of the disclosure can detect the change situation of the map element in the high-precision map according to the vehicle running data when the current running order operation is finished. Therefore, the timeliness of changing and detecting the map elements in the high-precision map is ensured.
In addition, only vehicle travel data is generated during the current travel order operation of the autonomous vehicle, and when the current travel order operation is completed, the map elements in the high-precision map are detected to be changed. Therefore, the change detection of high-precision map elements can be greatly reduced, and the occupation of vehicle-end resources in the running process of the automatic driving vehicle can be greatly reduced.
The high-precision map generally means that the electronic map has higher precision, and road traffic information elements contained in the electronic map are richer and more detailed.
Wherein, the higher precision means that the precision of the electronic map is generally at least as accurate as centimeter level.
The road traffic information contained in the electronic map includes: lane information such as the position, type, width, gradient, and curvature of a lane line; traffic signs, traffic lights, etc.; lane limits, sewer ports, obstacles and other road details, and infrastructure information such as overhead objects, guard rails, numbers, road edge types, roadside landmarks, etc.
The electronic map contains more abundant and detailed road traffic information elements, and generally means that the electronic map not only contains an accurate road shape, but also contains data of the gradient, curvature, course, elevation and heeling of each lane. The electronic map not only depicts roads, but also depicts how many lanes are on one road and the actual style of the road.
For the automatic driving vehicle, after the starting point and the end point are determined, the automatic driving vehicle automatically plans and generates a driving route and a process from the starting point to the end point, and at the moment, the automatic driving vehicle is considered to obtain a driving order.
The running order operation process means that the automatic driving vehicle executes a running process from a starting point to a terminal point according to a planned running route and process. The starting of the operation of the driving order means that the automatic driving vehicle starts to drive to the end point according to the planned driving route and process. The driving order operation is finished, namely the automatic driving vehicle reaches the terminal, or the driving order operation is finished in advance before the terminal is reached.
Map elements in the embodiments of the present disclosure often refer to traffic indicators in road traffic information, and the traffic indicators include, but are not limited to, traffic signs, traffic lights, lane lines, and the like.
The common traffic signs are speed limit signs, height limit signs, turning prohibition signs and the like, and the traffic lights are generally traffic lights.
The map elements of the present disclosure may be road traffic information other than traffic indicators, such as: guard rails, obstacles, etc.
The following describes in detail a high-precision map element change detection method provided by an embodiment of the present disclosure, taking map elements as traffic indicators as an example. For the map elements that are traffic information other than the traffic indicator, the principle of the high-precision map element change detection is the same, and please refer to the implementation process of the high-precision map element change detection method when the map elements are the traffic indicator, which is not described in detail herein.
The map element change means that a map element whose map position corresponds to a high-accuracy map is changed from an actual map element corresponding to a designated position with respect to the designated position and a map position at which the designated position matches the high-accuracy map.
Specifically, for a certain intersection, it is shown in the high-precision map that the intersection has no red street lamp, and the road driving image and the like acquired by the automatic driving vehicle reflect that the intersection actually has a red street lamp at present, and at this time, it is considered that the map element of the high-precision map at the intersection is changed.
Further, for example, in the case where a high-accuracy map of a road shows a white dotted line at a specified position, the white dotted line at the specified position is reflected in a road traveling image or the like acquired by an autonomous vehicle, and the white solid line is actually reflected in the road traveling image or the like, and it is considered that the map element of the high-accuracy map at the specified position is changed.
For autonomous driving, if a manual take over occurs during this process, the driving order operation is considered to have failed. However, changes in map elements, vehicle system failures, sudden road traffic conditions, etc. may trigger manual takeover. Therefore, if the map elements in the high-precision map are not timely detected and changed, the automatic driving vehicle can take over the map elements at the changed position manually, and the failure rate of the driving order is greatly increased.
It should be noted that the failure of the driving order does not mean that the driving order operation is finished, and for one driving order, multiple manual takeover may occur in the driving order operation process, but there is often no necessary management between the driving order operation completion and the manual takeover.
The map element change detection is carried out on the map elements in time, so that the timeliness of the change detection of the map elements in the high-precision map can be ensured, and the change speed of the high-precision map can be promoted to ensure the timeliness of the high-precision map. In addition, ensuring the timeliness of the high-precision map can greatly reduce the failure rate of the failure of the driving order.
In the embodiment of the present disclosure, the step of generating the vehicle driving data is shown in fig. 2, and fig. 2 is a flowchart of a method for generating the vehicle driving data provided in the embodiment of the present disclosure.
Step S201: and under the condition that the operation of the current driving order is started, detecting that the automatic driving vehicle triggers manual takeover.
Step S202: and generating vehicle driving data under the condition that triggering manual take-over is detected.
In the running order operation process, the map elements may be changed for many times, and many times of manual takeover may occur. Therefore, in order to ensure the accuracy of the element change detection, when the current driving order operation is started, the real-time detection of the automatic driving vehicle trigger manual takeover is started. And generating vehicle running data of the automatic driving vehicle within a specified time range before and after triggering the manual takeover as long as the triggering of the manual takeover is detected. Therefore, when the change condition of the map elements in the high-precision map is detected according to the vehicle running data, whether manual takeover is triggered by the change of the map elements can be determined, and therefore the change of the map elements can be detected every time.
By vehicle driving data is meant data that is continuously collected by the tachograph and various sensors during the driving of the autonomous vehicle, which data can be stored for later retrieval. The vehicle driving data includes, but is not limited to, vehicle trajectory data, vehicle speed data, road number images collected by image collection equipment on the vehicle, and radar scan data collected by a vehicle-mounted radar on the vehicle.
In order to reduce the amount of data that needs to be stored and to ensure that the generated vehicle travel data can support the requirement of detecting the change of map elements, in the embodiment of the present disclosure, the vehicle travel data is generated by: firstly, determining the moment of triggering manual takeover each time; then, vehicle travel data is acquired based on the time at which each manual takeover is triggered and the specified time range.
Specifically, under the condition that triggering manual takeover is detected, the vehicle-mounted vehicle control platform records the moment of triggering manual takeover each time, and vehicle running data of the automatic driving vehicle in a specified time range before and after triggering manual takeover can be automatically intercepted and stored through the data dial falling module. After the vehicle driving data is obtained, prompt information for prompting that manual take-over is triggered and vehicle driving data of the automatic driving vehicle within a specified time range is obtained is generated, and the prompt information is displayed on a human-computer interaction interface through a vehicle control platform and used for prompting a driver for test driving.
The data-landing module is a module for writing vehicle travel data and the like into a predetermined magnetic disk.
The vehicle driving data automatically intercepted and stored by the data dropping module exists in the form of a record (record) packet, and the specified time range generally refers to the vehicle driving data in a time period of 10s (second) before and after triggering manual takeover. Of course, the time is not limited to 10s, and may be set to 15s, 20s, or the like according to the prior value and the average traveling speed of the autonomous vehicle.
In the embodiment of the present disclosure, a step of detecting a change detection situation of a map element in a high-precision map is shown in fig. 3, which is a flowchart of a map element change detection method provided in the embodiment of the present disclosure.
Step S301: and detecting whether the next driving order starts to operate or not when the current driving order is operated.
Step S302: when the next travel order is not started, a change of a map element in the high-precision map is detected based on the vehicle travel data.
For example, if the detection result in step S301 is negative, the change of the map elements in the high-precision map is detected based on the vehicle travel data. That is, when the next travel order is not started, the change of the map elements in the high-precision map is detected based on the vehicle travel data.
If the detection result in step S301 is yes, the detection of the change of the map element in the high-precision map is stopped. That is, when the next travel order starts to be operated, the detection of the change of the map element in the high-precision map is stopped.
In the embodiment of the disclosure, when the operation of the current driving order is finished and the operation of the next driving order is not started, the change condition of the map elements in the high-precision map is detected according to the vehicle driving data, so that the change detection of the map elements can be ensured, and the occupation of vehicle-end resources in the driving process of the automatic driving vehicle is avoided.
And detecting whether the next driving order starts to operate or not, wherein the detection is synchronous with the detection of the change situation of the map elements in the high-precision map, and the detection of the change situation of the map elements in the high-precision map is stopped once the next driving order starts to operate.
The step of detecting the change detection condition of the map element in the high-precision map is shown in fig. 4, which is a flowchart of a method for detecting the change condition of the map element provided in the embodiment of the present disclosure.
Step S401: and determining the position information of the automatic driving vehicle on the driving road according to the vehicle driving data.
Step S402: and determining map position information matched with the position information on the driving road in the high-precision map.
Step S403: and obtaining a first map element corresponding to the map position information in the high-precision map.
Step S404: a second map element corresponding to the position information on the travel road is specified based on the vehicle travel data.
Step S405: and comparing the first map element with the second map element to detect the change condition of the map element in the high-precision map.
If the change is detected in step S405, the vehicle travel data corresponding to the map element change is transmitted to the server for executing the map element change of the high-precision map. That is, when a change of a map element in the high-accuracy map is a change of a map element, the vehicle travel data corresponding to the change of the map element is transmitted to the server for executing the change of the map element in the high-accuracy map.
If the detection result in step S405 is that no change has occurred, change detection of the next map element is performed.
The method comprises the steps of firstly determining the position information of the automatic driving vehicle on the driving road, then carrying out element comparison on the map position information matched with the position information on the driving road in the high-precision map, further obtaining a first map element corresponding to the map position information in the high-precision map, and a second map element corresponding to the position information on the driving road, so that the comparison accuracy can be ensured, and the accuracy of detecting the change condition of the map elements can be improved.
In addition, the vehicle travel data matching the map element change is transmitted to the server for executing the map element change of the high-precision map, so that the server can change the high-precision map according to the vehicle travel data matching the map element change. Compared with the prior art that the vehicle running data is uploaded to the server every day to detect the map element change, after the running order operation is finished, the map element change is carried out, and the vehicle running data matched with the map element change is sent to the server, so that the speed of the high-precision map element change can be increased, and the timeliness of the high-precision map is guaranteed.
The first map element is a map element described in the high-precision map, and the second map element is a real-time geographic element on the travel road.
In the embodiment of the present disclosure, a specific implementation manner of obtaining the first map element and the second map element and comparing the first map element with the second map element to detect the change condition of the map element in the high-precision map may be as follows:
first, a map element of a specified area range of a position of the autonomous vehicle on the travel road is three-dimensionally constructed from a road image of vehicle travel data and radar scan data, and three-dimensional space data is obtained as second map element data.
Then, data conversion is performed based on the map elements of the specified area range of the map position, and three-dimensional space map element data is obtained as first map element data.
Finally, the first map element data and the second map element data are compared to detect the change condition of the map elements in the high-precision map.
In the embodiment of the present disclosure, a specific implementation manner of obtaining the first map element data and the second map element data, and comparing the first map element data with the second map element data to detect the change condition of the map element in the high-precision map may further be:
first, second map element data, which is a traffic indicator image, is divided from a road image of vehicle travel data.
Wherein the image segmentation method includes but is not limited to at least one of the following: the method comprises a threshold-based segmentation method, a watershed algorithm, an edge detection-based segmentation method, a wavelet analysis and wavelet transformation-based image segmentation method, an Active Contour model (Active Contour Models) -based segmentation method and a deep learning-based segmentation model.
And then acquiring the attitude data of the image acquisition equipment corresponding to the road image.
The posture of the image acquisition equipment can be the posture of the vehicle-mounted camera.
And finally, according to the attitude data of the image acquisition equipment, projecting the map data corresponding to the map position data in the high-precision map to the plane where the road image is located, and generating a projection image based on the comparison between the traffic indicator image and the projection image.
The map data comprise three-dimensional data of the traffic indicator with the position and the orientation meeting preset requirements, and the three-dimensional data are first map element data.
As shown in fig. 5, fig. 5 is a schematic diagram of a map element change in an embodiment of the present disclosure. Specifically, only zebra crossings are arranged on a certain road displayed on the high-precision map, red street lamps are not arranged at two ends of each zebra crossing, and the road image corresponding to the road is not only provided with the zebra crossings at the position, and the red street lamps are arranged at two ends of each zebra crossing, so that the map elements in the high-precision map are changed.
The high-precision map element change detection method provided by the embodiment of the disclosure can detect the change situation of the map element in the high-precision map according to the vehicle running data when the current running order operation is finished. Therefore, the timeliness of changing and detecting the map elements in the high-precision map is ensured.
As shown in fig. 6, a high-precision map element change detection device provided in an embodiment of the present disclosure includes:
the manual takeover triggering detection module 601 is used for detecting the triggering condition of manual takeover in the current running order operation process of the automatic driving vehicle;
a vehicle driving data generating module 602, configured to generate vehicle driving data of an autonomous vehicle within a specified time range before and after triggering manual takeover when it is detected that manual takeover is triggered;
a map element change detection module 603 configured to detect a change of a map element in the high-precision map based on the vehicle travel data when the current travel order operation is completed.
In one embodiment, the vehicle driving data generation module 602 may further include:
the manual takeover time determining submodule is used for determining the time of triggering manual takeover each time;
and the vehicle running data acquisition submodule is used for acquiring vehicle running data based on the moment of triggering manual takeover each time and the specified time range.
In one embodiment, the map element change detection module 603 may further include:
the next driving order detection submodule is used for detecting whether the next driving order starts to operate or not under the condition that the operation of the current driving order is finished;
and a map element change detection sub-module for detecting a change of a map element in the high-precision map based on the vehicle travel data when the next travel order is not started.
In one embodiment, the map element change detection sub-module may further include:
the position information determining submodule is used for determining the position information of the automatic driving vehicle on the high-precision map according to the vehicle running data;
the map element obtaining submodule is used for obtaining map elements corresponding to the position information of the high-precision map;
the map element determining submodule is used for determining map elements of the automatic driving vehicle on a driving road according to the vehicle driving data;
and the map element comparison submodule is used for comparing the map elements on the driving road of the automatic driving vehicle with the map elements corresponding to the high-precision map position information so as to detect the change situation of the map elements in the high-precision map.
In one embodiment, the apparatus further comprises:
and the vehicle running data transmitting module is used for transmitting the vehicle running data matched with the map element change to a server side for executing the map element change of the high-precision map when the change of the map element in the high-precision map is the map element change.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.
According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.
In addition, the present disclosure also provides an autonomous vehicle including the electronic device provided by the present disclosure.
FIG. 7 illustrates a schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 7, the device 700 comprises a computing unit 701, which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM)702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (14)
1. A high-precision map element change detection method comprises the following steps:
detecting the triggering condition of manual takeover in the current running order operation process of the automatic driving vehicle;
under the condition that the manual takeover is triggered, generating vehicle running data of the automatic driving vehicle within a specified time range before and after the manual takeover is triggered;
and detecting a change situation of the map elements in the high-precision map according to the vehicle running data when the current running order operation is finished.
2. The method of claim 1, wherein the generating vehicle travel data for the autonomous vehicle within a specified time frame before and after triggering manual takeover comprises:
determining the moment of triggering the manual takeover each time;
and acquiring the vehicle driving data based on the time for triggering the manual takeover each time and the specified time range.
3. The method according to claim 1, wherein the detecting a change of a map element in a high-precision map from the vehicle travel data when the current travel order operation is ended includes:
under the condition that the operation of the current driving order is finished, detecting whether the operation of the next driving order is started or not;
when the next travel order is not started, a change of a map element in the high-precision map is detected based on the vehicle travel data.
4. The method of claim 3, wherein the detecting a change in a map element in a high-precision map from the vehicle travel data comprises:
determining position information of the automatic driving vehicle on a driving road according to the vehicle driving data;
determining map position information matched with the position information on the driving road in the high-precision map;
obtaining a first map element corresponding to the map position information in the high-precision map;
determining a second map element corresponding to the position information on the driving road according to the vehicle driving data;
and comparing the first map element with the second map element to detect the change condition of the map element in the high-precision map.
5. The method of claim 4, further comprising:
and transmitting the vehicle travel data matched with the map element change to a server for executing the map element change of the high-precision map when the change of the map element in the high-precision map is the map element change.
6. A high-precision map element change detection device includes:
the manual takeover triggering detection module is used for detecting the triggering condition of manual takeover in the current running order operation process of the automatic driving vehicle;
the vehicle running data generation module is used for generating vehicle running data of the automatic driving vehicle within a specified time range before and after triggering the manual takeover under the condition that triggering of the manual takeover is detected;
and the map element change detection module is used for detecting the change situation of the map elements in the high-precision map according to the vehicle driving data when the current driving order operation is finished.
7. The apparatus of claim 6, wherein the vehicle travel data generation module comprises:
the manual takeover time determining submodule is used for determining the time for triggering the manual takeover each time;
and the vehicle running data acquisition submodule is used for acquiring the vehicle running data based on the time for triggering the manual takeover each time and the specified time range.
8. The apparatus of claim 6, wherein the map element change detection module comprises:
the next driving order detection submodule is used for detecting whether the next driving order starts to operate or not under the condition that the operation of the current driving order is finished;
and a map element change detection sub-module configured to detect a change of a map element in the high-accuracy map based on the vehicle travel data when the next travel order is not started.
9. The apparatus of claim 8, wherein the map element alteration detection sub-module comprises:
the position information determining submodule is used for determining the position information of the automatic driving vehicle on the high-precision map according to the vehicle running data;
the map element obtaining submodule is used for obtaining the map element corresponding to the position information of the high-precision map;
the map element determining submodule is used for determining map elements of the automatic driving vehicle on a driving road according to the vehicle driving data;
and the map element comparison submodule is used for comparing the map elements on the driving road of the automatic driving vehicle with the map elements corresponding to the position information of the high-precision map so as to detect the change condition of the map elements in the high-precision map.
10. The apparatus of claim 9, further comprising:
and a vehicle running data transmitting module for transmitting the vehicle running data matched with the map element change to a server for executing the map element change of the high-precision map when the change of the map element in the high-precision map is the map element change.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1 to 5.
13. A computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the steps of the method of claims 1 to 5.
14. An autonomous vehicle comprising the electronic device of claim 11.
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