CN113479215A - Method, device, equipment and medium for transmitting automatic driving abnormal data - Google Patents
Method, device, equipment and medium for transmitting automatic driving abnormal data Download PDFInfo
- Publication number
- CN113479215A CN113479215A CN202110801667.1A CN202110801667A CN113479215A CN 113479215 A CN113479215 A CN 113479215A CN 202110801667 A CN202110801667 A CN 202110801667A CN 113479215 A CN113479215 A CN 113479215A
- Authority
- CN
- China
- Prior art keywords
- abnormal
- data
- user
- time point
- automatic driving
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000002159 abnormal effect Effects 0.000 title claims abstract description 182
- 238000000034 method Methods 0.000 title claims abstract description 51
- 230000005540 biological transmission Effects 0.000 claims abstract description 43
- 238000012790 confirmation Methods 0.000 claims abstract description 17
- 230000005856 abnormality Effects 0.000 claims abstract description 16
- 238000012544 monitoring process Methods 0.000 claims abstract description 13
- 230000006870 function Effects 0.000 claims description 38
- 238000005192 partition Methods 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 11
- 230000001960 triggered effect Effects 0.000 claims description 5
- 239000000126 substance Substances 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 12
- 238000004891 communication Methods 0.000 description 8
- 230000008569 process Effects 0.000 description 7
- 238000012545 processing Methods 0.000 description 6
- 230000002452 interceptive effect Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 239000002699 waste material Substances 0.000 description 3
- 241000282414 Homo sapiens Species 0.000 description 2
- 230000006399 behavior Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012163 sequencing technique Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 125000004122 cyclic group Chemical group 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000007429 general method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2556/00—Input parameters relating to data
- B60W2556/45—External transmission of data to or from the vehicle
Abstract
The disclosure provides a transmission method, a device, equipment and a medium for automatic driving abnormal data, and relates to the technical field of data transmission, in particular to the technical fields of Internet of vehicles, intelligent transportation and the like. The transmission of the automatic driving abnormality data includes: monitoring abnormal events occurring in the autonomous vehicle; responding to the abnormal event to display abnormal prompt information to a user, wherein the abnormal prompt information is used for prompting the user whether to upload abnormal data corresponding to the abnormal event; and if a confirmation uploading instruction generated by the user based on the abnormal prompt information is received, transmitting the abnormal data to a cloud. The present disclosure can improve the effectiveness of abnormal data transmission.
Description
Technical Field
The disclosure relates to the technical field of data processing, in particular to the technical fields of car networking, intelligent transportation and the like, and particularly relates to a method, a device, equipment and a medium for transmitting abnormal automatic driving data.
Background
An automatic vehicle (Self-driving automatic vehicle) is also called as an unmanned vehicle, a computer-driven vehicle or a wheeled mobile robot, and is an intelligent vehicle which realizes unmanned driving through a computer system.
In the operation process of the automatic driving vehicle, abnormal events are inevitable to occur, and the automatic driving vehicle can transmit abnormal data corresponding to the abnormal events to the cloud end, so that the cloud end analyzes the abnormal data, and basic data are provided for subsequent processes.
In the related art, the automatic driving vehicle can automatically transmit the abnormal data corresponding to the preset abnormal event to the cloud according to the information preset by the developer.
Disclosure of Invention
The disclosure provides a method, a device, equipment and a medium for transmitting automatic driving abnormity data.
According to an aspect of the present disclosure, there is provided a transmission method of automatic driving abnormality data, including: monitoring abnormal events occurring in the autonomous vehicle; responding to the abnormal event to display abnormal prompt information to a user, wherein the abnormal prompt information is used for prompting the user whether to upload abnormal data corresponding to the abnormal event; and if a confirmation uploading instruction generated by the user based on the abnormal prompt information is received, transmitting the abnormal data to a cloud.
According to another aspect of the present disclosure, there is provided an automatic driving abnormality data transmission device including: the monitoring module is used for monitoring abnormal events occurring in the automatic driving vehicle; the first prompting module is used for responding to the abnormal event so as to display abnormal prompting information to a user, wherein the abnormal prompting information is used for prompting the user whether to upload abnormal data corresponding to the abnormal event; and the first transmission module is used for transmitting the abnormal data to a cloud terminal if receiving a confirmation uploading instruction generated by the user based on the abnormal prompt information.
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 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 the above aspects.
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 the computer to perform the method according to any one of the above aspects.
According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of the above aspects.
According to the technical scheme disclosed by the invention, the effectiveness of abnormal data transmission can be improved.
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 schematic diagram according to a first embodiment of the present disclosure;
FIG. 2 is a schematic diagram according to a second embodiment of the present disclosure;
FIG. 3 is a schematic diagram according to a third embodiment of the present disclosure;
FIG. 4 is a schematic diagram according to a fourth embodiment of the present disclosure;
FIG. 5 is a schematic diagram according to a fifth embodiment of the present disclosure;
FIG. 6 is a schematic diagram according to a sixth embodiment of the present disclosure;
FIG. 7 is a schematic diagram according to a seventh embodiment of the present disclosure;
fig. 8 is a schematic diagram of an electronic device for implementing any one of the transmission methods of the automated driving abnormality data according to the embodiments 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.
In the related art, the automatic driving automobile can automatically transmit the abnormal data corresponding to the preset abnormal events to the cloud according to the information preset by the developer. However, according to the manner of automatically uploading data according to the preconfigured information, some useless data may be transmitted to the cloud, which wastes data traffic.
To address the problems caused by automatic uploading of data, the present disclosure provides some embodiments as follows.
Fig. 1 is a schematic diagram according to a first embodiment of the present disclosure. The embodiment provides an automatic driving abnormity data transmission method, which comprises the following steps:
101. an exception event of the autonomous vehicle is monitored.
102. And responding to the abnormal event to display abnormal prompt information to the user, wherein the abnormal prompt information is used for prompting the user whether to upload abnormal data corresponding to the abnormal event.
103. And if a confirmation uploading instruction generated by the user based on the abnormal prompt information is received, transmitting the abnormal data to a cloud.
The method of the embodiment can be applied to an automatic driving vehicle, and the automatic driving vehicle can interact with a cloud.
As shown in fig. 2, the autonomous driving vehicle may include a data source module and an abnormal event monitoring module, where the data source module may collect various data of the autonomous driving vehicle, such as system information, sensor data, Controller Area Network (CAN) information, function module data, and the like.
The abnormal event monitoring module is used for monitoring abnormal events, and the abnormal events can comprise: system exceptions, status exceptions, operational exceptions, and the like.
The system abnormality is software and hardware abnormality, the hardware abnormality is abnormality such as vehicle and sensor, the software abnormality is abnormality of system operation environment and function module, and the system abnormality is generally caused by system fault.
The state anomaly is typically caused by the external environment. Taking an Automated Valet Parking (AVP) function as an example, the status exception may include: training exception, opening condition exception, execution exception. The training abnormity is caused by the reasons that the external environment exceeds the learning range, the vehicle state does not meet the learning requirement, the vehicle sensor is shielded and the like. The abnormal start condition is usually generated when the automatic parking function is started, and is mainly caused by a Global Positioning System (GPS) Positioning error, inconsistency of use and learning conditions, and the like. The execution abnormity generally occurs when the vehicle automatically executes the parking function, and is mainly caused by the fact that the external environment, such as the vehicle is interfered by obstacles and has no parking space which can be parked, does not meet the execution requirement.
The abnormal operation refers to the condition that the automatic parking is interrupted or stopped due to the fact that a driver (or called a user) actively executes operation under the condition that the system is normal and the running state is normal, and generally includes three types, namely that the user takes over the vehicle, the user cancels the parking and the user breaks the operation. The process of taking over the vehicle by the user generally comprises the steps of taking over a steering wheel by the driver, switching gears, stepping on an accelerator pedal, stepping on a brake pedal and the like, and mainly occurs that the user takes intervention measures to correct or strengthen the automatic driving behavior when considering that the automatic parking state is not expected, and the automatic parking can still be carried out under the state, but the occurrence of the intervention measures means that the automatic driving model has results which are not expected by human beings. The user cancels the parking, namely the driver operates through a vehicle end key or remote mobile phone software, and the automatic parking is completely stopped. The automatic parking function is finished in the state that a user thinks that the automatic parking function cannot meet the current requirement or needs to be completely driven manually due to human factors, and the occurrence of the automatic parking function means that the automatic driving model has the problem that the automatic parking function cannot meet the current environmental parking requirement. The illegal operation of a user is usually caused by improper operation of a driver, for example, the normal driving behavior is influenced by opening a vehicle door in the automatic parking process, loosening a safety belt on the main driving half way, opening an oil tank cover in the driving process and the like, and the occurrence of the state means that an automatic driving model is seriously interfered and does not accord with the automatic parking function condition.
The exception event may correspond to exception data, which may be retrieved from a data source. The exception data may include multiple types, for example, AVP functionality, and as shown in fig. 3, the exception data may include one or more of these.
Further, an abnormal event to be prompted may be configured in the autonomous vehicle in advance, for example, if the occurred abnormal event belongs to a preset abnormal event, a user may be prompted. The preset abnormal event is, for example, a braking event of the user's initiative. Specifically, different exception codes may be configured for different exception events, and a prompt is given when an exception code of an occurred exception event belongs to a preset exception code.
In the related art, the braking event of the user initiative is generally regarded as an abnormal event, and when the braking event of the user initiative occurs, corresponding abnormal data can be automatically uploaded to the cloud. However, the active braking event of the user may be caused by different habits of the user, for example, some users are used to brake and do not necessarily have driving danger objectively, and if all braking events upload corresponding abnormal data, a large data traffic waste is undoubtedly caused.
In this embodiment, the braking event corresponding to the user initiative can prompt the user, and according to the user demand, the abnormal data after the user confirmation is uploaded to the cloud, so that the flow waste is avoided.
The abnormal prompt information may be displayed on the interactive interface, the interactive interface may be a display screen of the hardware device, or a display interface of an Application (APP) installed on the hardware device, and the hardware device may be an onboard device installed on an autonomous driving vehicle, such as a Head Up (HU) display device, or may also be a mobile device used by a user, such as a mobile phone.
As shown in fig. 4, the abnormal prompt message is, for example, a similar prompt message that "do you have brake abnormality and need to upload abnormal data", and in addition, a yes or no selection item may be displayed on the interactive interface, so that the user may select whether to upload abnormal data.
If the user generates a confirmation upload instruction, for example, the user selects "yes" from the above options, the autonomous vehicle transmits the abnormal data to the cloud.
The above description shows that the user is prompted after the abnormal event is monitored. When the user is prompted, the abnormal Data corresponding to the abnormal event may be synchronously stored in a memory of the autonomous vehicle, such as a Double Data Rate (DDR).
That is, the method may further include: after the abnormal event occurs in the automatic driving vehicle, storing abnormal data corresponding to the abnormal event in a memory of the automatic driving vehicle;
the transmitting the abnormal data to a cloud comprises: and reading the abnormal data from the memory, and transmitting the read abnormal data to a cloud.
When an abnormal event occurs, the corresponding abnormal data is stored in the memory, so that the abnormal data can be stored in time, and the abnormal data is prevented from being lost.
In another aspect, after storing the abnormal data in the memory of the autonomous vehicle, the method further comprises: and deleting the abnormal data in the memory if a negative uploading instruction generated by the user based on the abnormal prompt information is received, or the confirmation uploading instruction or the negative uploading instruction is not received within a preset time length.
For example, if the user selects "no" in the above options, the abnormal data is not uploaded. Or the user does not perform feedback, specifically, if the feedback instruction of the user is not received within the preset time, that is, the user does not select yes or no, the abnormal data is not uploaded. At this time, the abnormal data stored in the memory may be deleted.
When the user does not confirm to upload the abnormal data, the abnormal data in the memory is deleted, so that the memory resource can be released.
The exception data may be stored in the memory in the following manner:
storing the total usage data generated when the automatic driving vehicle uses the preset function in a first partition of the memory according to a preset period; when the abnormal event occurs in the automatic driving vehicle, taking the time point of the abnormal event as a reference time point, taking the time point of a first preset time length before the reference time point as a starting time point, taking the time point of a second preset time length after the reference time point as an ending time point, and taking the total usage data between the starting time point and the ending time point as the abnormal data; storing the exception data in a second partition of the memory, the first partition being different from the second partition.
The preset function is, for example, an AVP function, so that when the AVP function is used by the autonomous vehicle, full usage data corresponding to the AVP function may be acquired, and the type of the full usage data may be one or more of those shown in fig. 3.
The preset period is, for example, 10s, that is, the current 10s of full usage data can be used to cover the last 10s of full usage data, so as to implement the 10s periodic cyclic erasing.
The first preset duration and the second preset duration may be the same or different, for example, if the first preset duration is 10 seconds, and the second preset duration is 5 seconds, then the data of 10 seconds before the occurrence of the abnormal event and the data of 5 seconds after the occurrence of the abnormal event may be used as the abnormal data.
By using data of a period of time before and after the reference time point as abnormal data, the integrity of the abnormal data can be ensured.
And after the abnormal data are stored in the memory, if a network transmission condition exists, the abnormal data are transmitted to the cloud. The network transmission condition comprises the existence of network transmission signals, in addition, the data priority can be set, various data are transmitted in a sequencing mode according to the data priority, and when the sequencing sequence of abnormal data is achieved, the abnormal data are transmitted. For example, generally speaking, the priority of the function scheduling data is higher, the function scheduling data is transmitted preferentially, and after the transmission of the function scheduling data is completed, the abnormal data is transmitted again. And if the network transmission condition does not exist, storing the abnormal data into a nonvolatile memory of the automatic driving vehicle.
On the other hand, if no network transmission condition exists, the abnormal data is stored in a nonvolatile memory of the autonomous vehicle. The non-volatile memory may be an Embedded multimedia memory (eMMC).
Since the memory is a volatile memory, taking the memory as DDR as an example, after the DDR is powered off, data in the DDR can be erased, so that, in order to avoid data loss, when the abnormal data cannot be transmitted to the cloud in real time, the abnormal data can be stored in the eMMC.
By storing the exception data in the non-volatile memory, data loss can be avoided.
Taking the AVP function as an example, when the AVP function is abnormal, the flow shown in fig. 5 may be executed. The method specifically comprises the following steps: when the user uses the AVP function, after an abnormal event occurs, an abnormal report may be performed through the HU or the APP, for example, an abnormal code is displayed in a pop-up window form, and a prompt is performed to the user, that is, a fault information reporting prompt is performed. In addition, after an abnormal event occurs, the collection of abnormal data can be triggered according to a preset abnormal strategy. After the abnormal data is collected, the data can be stored in the DDR. It is understood that the storage of the abnormal data in the DDR and the prompt to the user can be performed synchronously without the user agreeing or disapproving to upload the data for storage of the data.
After the prompt information is displayed to the user, the user can choose to agree or disagree, for example, click yes or no, if the user confirms uploading and the network condition allows, abnormal data are read from the DDR and then are transmitted back to the cloud in real time. If the user does not confirm the uploading, for example, the user clicks no, or the user does not feed back, the abnormal data in the DDR can be deleted, and in addition, after the DDR is powered off, the data in the DDR can be deleted. If the network condition is not allowed, the abnormal data in the DDR can be stored in the eMMC, and then the data can be read from the eMMC to the cloud, so that the eMMC caching return is realized.
In this embodiment, through after the unusual incident takes place at the autonomous driving vehicle, show unusual reminder information to the user, confirm the back of uploading at the user, just carry out the uploading of abnormal data, can improve the validity of abnormal data transmission, avoid useless data transmission to give the high in the clouds, in addition, can also guarantee user's right of knowledge, protection user privacy.
The above description is given by taking the example of prompting the user when abnormal data is transmitted, and the embodiment of the present disclosure may also prompt the user to transmit the full usage data. Full usage data is meant to include both normal data and abnormal data.
That is, the method may further include: acquiring full usage data corresponding to the latest preset times when the automatic driving vehicle uses the preset function; storing the full usage data not exceeding a preset capacity in a non-volatile memory of the autonomous vehicle.
If the preset function is, for example, an AVP function, and the preset number of times is, for example, 3 times, the full usage data of the autonomous vehicle using the AVP function for the last 3 times may be obtained, and the type of the full usage data may be one or more items as shown in fig. 3.
Taking the nonvolatile memory as the eMMC as an example, the full usage data may be stored in a loop overwriting manner, for example, when a new usage record of the AVP function is generated, the new full usage data is used to replace the old full usage data, and the last 3 times of full usage data is always stored in the eMMC.
The eMMC has a capacity limit, and for example, the maximum capacity of the eMMC is 240M, and when the data capacity is larger than 240M, the eMMC performs the overlay storage.
Accordingly, the full usage data of the last 3 times of no more than 240M may be stored in the eMMC.
By storing the full usage data in non-volatile memory, underlying data may be provided for subsequent data analysis.
The full usage data may also be transmitted to the cloud, i.e., the method further comprises: presenting an initial portal to the user; responding to a multi-level selection operation triggered by the user based on the initial entry to display a full data upload entry to the user; if a selection instruction of the user for the full data uploading entrance is received, displaying full prompt information to the user, wherein the full prompt information is used for prompting the user whether to upload the full usage data; and if a confirmation uploading instruction generated by the user based on the full amount prompt information is received, transmitting the full amount use data to a cloud.
Taking the AVP function as an example, the upload flow of the full usage data as shown in fig. 6 may be performed. The method specifically comprises the following steps: when a user uses the AVP function, the full usage data corresponding to the AVP function may be stored in the eMMC. In addition, the system for automatically driving the vehicle may further include an initial entry and a full data upload entry, for example, the initial entry in fig. 6 is "set", the full data upload entry is "report bug", and the full data upload entry "report bug" is displayed by a multi-level selection operation, for example, by clicking "set" first and then clicking "feedback" of the next level of "set". After clicking the 'bug report', the user can fill in the problem, in addition, full prompt information is displayed for the user, for example, similar information such as 'X flow needs to be consumed in the operation at this time' and the like, so as to inform the user of the flow, meanwhile, a selection button of 'yes' or 'no' can be provided on the interface, if the user clicks 'yes', the user confirms uploading, at the moment, if the network condition allows, the full use data is uploaded to the cloud, and instant return is realized. If the network condition is not allowed, the coverage is stopped and the return is waited. If the user clicks 'no', the user refuses to upload, and at the moment, the circular coverage storage can still be carried out.
Through setting up the full data upload entry, can be so that full service data is transmitted to the high in the clouds, the cloud of being convenient for is to full service data analysis. Through multi-level selection, the uploading entrance of the full data can be hidden, and the user is prevented from being easily contacted. The user can be informed of the flow consumption through the full amount of prompt information, the right of awareness of the user is guaranteed, and useless flow consumption is avoided.
It should be noted that in the embodiment of the present disclosure, the executing subject of the transmission method of the abnormal automatic driving data may obtain the abnormal data, the full usage data, and the like in various public and legally compliant manners, for example, the abnormal data, the full usage data, and the like may be obtained from a public data set or obtained from a user after authorization of the user. The transmission method of the embodiment of the disclosure is executed after being authorized by a user, and the execution process of the transmission method conforms to relevant laws and regulations. The transmission method in the embodiment of the disclosure is a general method provided for general users, is not specially used for portraying specific users, and cannot uniquely identify privacy data of specific individuals.
Fig. 7 is a schematic diagram of a seventh embodiment of the present disclosure, which provides an automatic driving abnormality data transmission device. As shown in fig. 7, the apparatus 700 includes a monitoring module 701, a first prompting module 702, and a first transmitting module 703.
The monitoring module 701 is used for monitoring abnormal events of the automatic driving vehicle; the first prompting module 702 is configured to respond to the abnormal event to display abnormal prompting information to a user, where the abnormal prompting information is used to prompt the user whether to upload abnormal data corresponding to the abnormal event; the first transmission module 703 is configured to transmit the abnormal data to the cloud end if a confirmation upload instruction generated by the user based on the abnormal prompt information is received.
In some embodiments, the apparatus further comprises:
the first storage module is used for storing abnormal data corresponding to the abnormal event in a memory of the automatic driving vehicle after the abnormal event occurs to the automatic driving vehicle; the first transmission module is specifically configured to: and reading the abnormal data from the memory, and transmitting the read abnormal data to a cloud.
In some embodiments, the first storage module is specifically configured to: storing full usage data generated when the automatic driving vehicle uses a preset function in a first partition of the memory according to a preset period; when the abnormal event occurs in the automatic driving vehicle, taking the time point of the abnormal event as a reference time point, taking the time point of a first preset time length before the reference time point as a starting time point, taking the time point of a second preset time length after the reference time point as an ending time point, and taking the total usage data between the starting time point and the ending time point as the abnormal data; storing the exception data in a second partition of the memory, the first partition being different from the second partition.
In some embodiments, the apparatus further comprises: and the deleting module is used for deleting the abnormal data in the memory if a negative uploading instruction generated by the user based on the abnormal prompt information is received, or the confirmation uploading instruction or the negative uploading instruction is not received within a preset time length.
In some embodiments, the abnormal data is transmitted to a cloud when a network transmission condition exists, and the apparatus further includes: and the second storage module is used for storing the abnormal data in a nonvolatile memory of the automatic driving vehicle if the network transmission condition does not exist.
In some embodiments, the apparatus further comprises: the third storage module is used for acquiring full usage data corresponding to the latest preset times when the automatic driving vehicle uses the preset function; storing the full usage data that does not exceed a maximum capacity of the non-volatile memory in a non-volatile memory of the autonomous vehicle.
In some embodiments, the apparatus further comprises: the first display module is used for displaying an initial entrance to the user; a second display module, configured to respond to a multi-level selection operation triggered by the user based on the initial entry, so as to display a full-data upload entry to the user; the second prompting module is used for displaying full amount prompting information to the user if a selection instruction of the user to the full amount data uploading entrance is received, wherein the full amount prompting information is used for prompting the user whether to upload the full amount usage data; and the second transmission module is used for transmitting the full usage data to a cloud end if receiving a confirmation uploading instruction generated by the user based on the full prompt message.
In this embodiment, through after the unusual incident takes place at the autonomous driving vehicle, show unusual reminder information to the user, confirm the back of uploading at the user, just carry out the uploading of abnormal data, can improve the validity of abnormal data transmission, avoid useless data transmission to give the high in the clouds, in addition, can also guarantee user's right of knowledge, protection user privacy.
It is understood that the same or corresponding contents in different embodiments of the present disclosure may be mutually referred, and the contents not described in detail in the embodiments may be referred to the related contents in other embodiments.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 8 illustrates a schematic block diagram of an example electronic device 800 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, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, 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. 8, the electronic device 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the electronic apparatus 800 can also be stored. The calculation unit 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
A number of components in the electronic device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, or the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 809 such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows the electronic device 800 to exchange information/data with other devices through 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 can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a 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 or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
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 (17)
1. A transmission method of automatic driving abnormity data comprises the following steps:
monitoring abnormal events occurring in the autonomous vehicle;
responding to the abnormal event to display abnormal prompt information to a user, wherein the abnormal prompt information is used for prompting the user whether to upload abnormal data corresponding to the abnormal event;
and if a confirmation uploading instruction generated by the user based on the abnormal prompt information is received, transmitting the abnormal data to a cloud.
2. The method of claim 1, further comprising:
after the abnormal event occurs in the automatic driving vehicle, storing abnormal data corresponding to the abnormal event in a memory of the automatic driving vehicle;
the transmitting the abnormal data to a cloud comprises:
and reading the abnormal data from the memory, and transmitting the read abnormal data to a cloud.
3. The method of claim 2, wherein the storing of the anomaly data corresponding to the anomaly event in the memory of the autonomous vehicle comprises:
storing full usage data generated when the automatic driving vehicle uses a preset function in a first partition of the memory according to a preset period;
when the abnormal event occurs in the automatic driving vehicle, taking the time point of the abnormal event as a reference time point, taking the time point of a first preset time length before the reference time point as a starting time point, taking the time point of a second preset time length after the reference time point as an ending time point, and taking the total usage data between the starting time point and the ending time point as the abnormal data;
storing the exception data in a second partition of the memory, the first partition being different from the second partition.
4. The method of claim 2, wherein after storing the anomaly data in the memory of the autonomous vehicle, the method further comprises:
and deleting the abnormal data in the memory if a negative uploading instruction generated by the user based on the abnormal prompt information is received, or the confirmation uploading instruction or the negative uploading instruction is not received within a preset time length.
5. The method of claim 1, wherein the anomaly data is transmitted to a cloud when a network transmission condition exists, the method further comprising:
and if the network transmission condition does not exist, storing the abnormal data in a nonvolatile memory of the automatic driving vehicle.
6. The method of any of claims 1-5, further comprising:
acquiring full usage data corresponding to the latest preset times when the automatic driving vehicle uses the preset function;
storing the full usage data that does not exceed a maximum capacity of the non-volatile memory in a non-volatile memory of the autonomous vehicle.
7. The method of claim 6, further comprising:
displaying an initial entry to the user;
responding to a multi-level selection operation triggered by the user based on the initial entry to display a full data upload entry to the user;
if a selection instruction of the user for the full data uploading entrance is received, displaying full prompt information to the user, wherein the full prompt information is used for prompting the user whether to upload the full usage data;
and if a confirmation uploading instruction generated by the user based on the full amount prompt information is received, transmitting the full amount use data to a cloud.
8. An automatic driving abnormality data transmission device comprising:
the monitoring module is used for monitoring abnormal events occurring in the automatic driving vehicle;
the first prompting module is used for responding to the abnormal event so as to display abnormal prompting information to a user, wherein the abnormal prompting information is used for prompting the user whether to upload abnormal data corresponding to the abnormal event;
and the first transmission module is used for transmitting the abnormal data to a cloud terminal if receiving a confirmation uploading instruction generated by the user based on the abnormal prompt information.
9. The apparatus of claim 8, further comprising:
the first storage module is used for storing abnormal data corresponding to the abnormal event in a memory of the automatic driving vehicle after the abnormal event occurs to the automatic driving vehicle;
the first transmission module is specifically configured to: and reading the abnormal data from the memory, and transmitting the read abnormal data to a cloud.
10. The apparatus of claim 9, wherein the first storage module is specifically configured to:
storing full usage data generated when the automatic driving vehicle uses a preset function in a first partition of the memory according to a preset period;
when the abnormal event occurs in the automatic driving vehicle, taking the time point of the abnormal event as a reference time point, taking the time point of a first preset time length before the reference time point as a starting time point, taking the time point of a second preset time length after the reference time point as an ending time point, and taking the total usage data between the starting time point and the ending time point as the abnormal data;
storing the exception data in a second partition of the memory, the first partition being different from the second partition.
11. The apparatus of claim 9, further comprising:
and the deleting module is used for deleting the abnormal data in the memory if a negative uploading instruction generated by the user based on the abnormal prompt information is received, or the confirmation uploading instruction or the negative uploading instruction is not received within a preset time length.
12. The apparatus of claim 8, wherein the anomaly data is transmitted to a cloud when a network transmission condition exists, the apparatus further comprising:
and the second storage module is used for storing the abnormal data in a nonvolatile memory of the automatic driving vehicle if the network transmission condition does not exist.
13. The apparatus of any of claims 8-12, further comprising:
the third storage module is used for acquiring full usage data corresponding to the latest preset times when the automatic driving vehicle uses the preset function; storing the full usage data that does not exceed a maximum capacity of the non-volatile memory in a non-volatile memory of the autonomous vehicle.
14. The apparatus of claim 13, further comprising:
the first display module is used for displaying an initial entrance to the user;
a second display module, configured to respond to a multi-level selection operation triggered by the user based on the initial entry, so as to display a full-data upload entry to the user;
the second prompting module is used for displaying full amount prompting information to the user if a selection instruction of the user to the full amount data uploading entrance is received, wherein the full amount prompting information is used for prompting the user whether to upload the full amount usage data;
and the second transmission module is used for transmitting the full usage data to a cloud end if receiving a confirmation uploading instruction generated by the user based on the full prompt message.
15. 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 1-7.
16. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-7.
17. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110801667.1A CN113479215A (en) | 2021-07-15 | 2021-07-15 | Method, device, equipment and medium for transmitting automatic driving abnormal data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110801667.1A CN113479215A (en) | 2021-07-15 | 2021-07-15 | Method, device, equipment and medium for transmitting automatic driving abnormal data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113479215A true CN113479215A (en) | 2021-10-08 |
Family
ID=77939652
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110801667.1A Pending CN113479215A (en) | 2021-07-15 | 2021-07-15 | Method, device, equipment and medium for transmitting automatic driving abnormal data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113479215A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114666363A (en) * | 2022-02-25 | 2022-06-24 | 阿波罗智联(北京)科技有限公司 | Information transmission method and device, electronic equipment, storage medium and product |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102145683A (en) * | 2011-03-11 | 2011-08-10 | 广东铁将军防盗设备有限公司 | Video recording instrument of vehicle |
| JP2013037620A (en) * | 2011-08-10 | 2013-02-21 | Fujitsu Ltd | Information processing device mounted on vehicle and operation management server |
| US20140178031A1 (en) * | 2012-12-20 | 2014-06-26 | Brett I. Walker | Apparatus, Systems and Methods for Monitoring Vehicular Activity |
| CN105871587A (en) * | 2015-12-10 | 2016-08-17 | 乐视致新电子科技（天津）有限公司 | Log uploading method and device |
| CN108363659A (en) * | 2018-02-23 | 2018-08-03 | 青岛海信移动通信技术股份有限公司 | A kind of method and device of processing electronic equipment exception |
| CN109522147A (en) * | 2018-11-15 | 2019-03-26 | Oppo广东移动通信有限公司 | A kind of method, apparatus, storage medium and the terminal of record booting exception information |
| CN110505134A (en) * | 2019-07-04 | 2019-11-26 | 国家计算机网络与信息安全管理中心 | A kind of car networking CAN bus data detection method and device |
| CN110519362A (en) * | 2019-08-22 | 2019-11-29 | 东软睿驰汽车技术（沈阳）有限公司 | A kind of data uploading method and device |
| CN110709899A (en) * | 2017-06-02 | 2020-01-17 | 奥迪股份公司 | Method and apparatus for storing system data on a case-by-case basis |
| CN111586150A (en) * | 2020-04-30 | 2020-08-25 | 上海华东汽车信息技术有限公司 | Vehicle data uploading method and device, computer equipment and storage medium |
| CN111835799A (en) * | 2019-04-16 | 2020-10-27 | 上海博泰悦臻电子设备制造有限公司 | Automatic acquisition system and method for vehicle log |
| CN112258110A (en) * | 2020-10-23 | 2021-01-22 | 上海中通吉网络技术有限公司 | Method, device, equipment and system for reporting abnormity of real-time road condition and storage medium |
| CN113064384A (en) * | 2019-12-27 | 2021-07-02 | 海信集团有限公司 | Intelligent household appliance, cloud server and method for monitoring abnormity |
| WO2022063566A1 (en) * | 2020-09-28 | 2022-03-31 | Robert Bosch Gmbh | Method and device for recording event data in a vehicle |
-
2021
- 2021-07-15 CN CN202110801667.1A patent/CN113479215A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102145683A (en) * | 2011-03-11 | 2011-08-10 | 广东铁将军防盗设备有限公司 | Video recording instrument of vehicle |
| JP2013037620A (en) * | 2011-08-10 | 2013-02-21 | Fujitsu Ltd | Information processing device mounted on vehicle and operation management server |
| US20140178031A1 (en) * | 2012-12-20 | 2014-06-26 | Brett I. Walker | Apparatus, Systems and Methods for Monitoring Vehicular Activity |
| CN105871587A (en) * | 2015-12-10 | 2016-08-17 | 乐视致新电子科技（天津）有限公司 | Log uploading method and device |
| US20200210336A1 (en) * | 2017-06-02 | 2020-07-02 | Audi Ag | Method and device for situation-dependent storage of data of a system |
| CN110709899A (en) * | 2017-06-02 | 2020-01-17 | 奥迪股份公司 | Method and apparatus for storing system data on a case-by-case basis |
| CN108363659A (en) * | 2018-02-23 | 2018-08-03 | 青岛海信移动通信技术股份有限公司 | A kind of method and device of processing electronic equipment exception |
| CN109522147A (en) * | 2018-11-15 | 2019-03-26 | Oppo广东移动通信有限公司 | A kind of method, apparatus, storage medium and the terminal of record booting exception information |
| CN111835799A (en) * | 2019-04-16 | 2020-10-27 | 上海博泰悦臻电子设备制造有限公司 | Automatic acquisition system and method for vehicle log |
| CN110505134A (en) * | 2019-07-04 | 2019-11-26 | 国家计算机网络与信息安全管理中心 | A kind of car networking CAN bus data detection method and device |
| CN110519362A (en) * | 2019-08-22 | 2019-11-29 | 东软睿驰汽车技术（沈阳）有限公司 | A kind of data uploading method and device |
| CN113064384A (en) * | 2019-12-27 | 2021-07-02 | 海信集团有限公司 | Intelligent household appliance, cloud server and method for monitoring abnormity |
| CN111586150A (en) * | 2020-04-30 | 2020-08-25 | 上海华东汽车信息技术有限公司 | Vehicle data uploading method and device, computer equipment and storage medium |
| WO2022063566A1 (en) * | 2020-09-28 | 2022-03-31 | Robert Bosch Gmbh | Method and device for recording event data in a vehicle |
| CN112258110A (en) * | 2020-10-23 | 2021-01-22 | 上海中通吉网络技术有限公司 | Method, device, equipment and system for reporting abnormity of real-time road condition and storage medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114666363A (en) * | 2022-02-25 | 2022-06-24 | 阿波罗智联(北京)科技有限公司 | Information transmission method and device, electronic equipment, storage medium and product |
| CN114666363B (en) * | 2022-02-25 | 2024-03-01 | 阿波罗智联(北京)科技有限公司 | Information transmission method, device, electronic equipment, storage medium and product |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106170826B (en) | The monitoring method and system of cab-getter's number | |
| US9830749B2 (en) | Systems and methods for executing custom fleet vehicle management scripts | |
| US20200342418A1 (en) | Vehicle service center dispatch system | |
| CN114715139B (en) | Automatic parking abnormal data acquisition method, device, storage medium and product | |
| CN111038320B (en) | Charging pile monitoring method, electronic equipment and storage medium | |
| US20180082342A1 (en) | Predicting automobile future value and operational costs from automobile and driver information for service and ownership decision optimization | |
| CN110119824B (en) | Charging pile adaptive scheduling system and method | |
| CN110633033A (en) | Method, apparatus, and computer storage medium for task display | |
| US20200125356A1 (en) | Automated usage driven engineering | |
| CN111865949A (en) | Abnormal communication detection method and device, server and storage medium | |
| CN113479215A (en) | Method, device, equipment and medium for transmitting automatic driving abnormal data | |
| CN112445583A (en) | Task management method, task management system, electronic device, and storage medium | |
| CN113685284B (en) | Electric fuel pump control method, device, equipment and storage medium | |
| CN113341924A (en) | ECU power-off method, device, equipment and storage medium | |
| CN115484299A (en) | Whole vehicle global configuration method, device, equipment and medium | |
| CN107943500A (en) | A kind of combination instrument Oftware updating method | |
| CN110443910B (en) | Method, system, device and storage medium for monitoring state of unmanned device | |
| CN113065821A (en) | Vehicle transfer behavior early warning method, device, equipment and storage medium | |
| CN110659852B (en) | Method, system, device and storage medium for determining delivery information of delivery unit | |
| CN112232723A (en) | Method and device for detecting abnormal behaviors in real time, electronic equipment and storage medium | |
| US20190236543A1 (en) | Backup hours of service system | |
| US11443568B1 (en) | Presentation of messages by an in-vehicle head unit | |
| CN114047741B (en) | Implementation method and related device for temporary interruption function of self-repairing diagnosis limiting system | |
| CN114610003B (en) | Vehicle diagnosis method, device, equipment and medium | |
| US11653186B2 (en) | Systems and methods for determining application status |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20211008 |