CN113110266B - Remote control monitoring early warning method for automatic driving vehicle and storage medium - Google Patents
Remote control monitoring early warning method for automatic driving vehicle and storage medium Download PDFInfo
- Publication number
- CN113110266B CN113110266B CN202110582581.4A CN202110582581A CN113110266B CN 113110266 B CN113110266 B CN 113110266B CN 202110582581 A CN202110582581 A CN 202110582581A CN 113110266 B CN113110266 B CN 113110266B
- Authority
- CN
- China
- Prior art keywords
- data
- abnormal
- vehicle
- positioning system
- steps
- 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.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0423—Input/output
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/23—Pc programming
- G05B2219/23051—Remote control, enter program remote, detachable programmer
Abstract
The invention provides a monitoring and early warning method and a storage medium for a remote control take-over of an automatic driving vehicle, wherein the method comprises the steps of monitoring the running state data of the automatic driving vehicle; analyzing the running state data, recording abnormal state data and classifying; and starting vehicle emergency treatment and remote takeover according to the type of the abnormal state. The monitoring and early warning method for the remote control connection pipe of the automatic driving vehicle improves the real-time performance and the accuracy of the abnormal state acquisition of the automatic driving vehicle.
Description
Technical Field
The invention belongs to the field of automatic driving, and particularly relates to a remote control monitoring and early warning method and a storage medium for an automatic driving vehicle.
Background
The current automatic driving technology is not developed completely, so that the automatic driving technology cannot be implemented on the ground in many scenes. Remote control driving is used as a safety auxiliary system of an automatic driving vehicle, a remote driver can take over the vehicle under the working condition that the remote driving vehicle cannot handle the safety auxiliary system and carry out transition processing, and therefore the automatic driving technology can be guaranteed to be practically applied in a part of scenes. On the premise of taking remote driving as a safety auxiliary system of an automatic driving vehicle, how to accurately capture the low confidence state of the automatic driving system in real time, how to emergently deal with the low confidence state of the automatic driving vehicle and how to safely take over the driving right of the vehicle by the remote taking-over system are the most core technical problems of the system. The current mainstream method is that a worker monitors the vehicle through monitoring videos and parameters returned by the vehicle in a remote control center, and once abnormal vehicle behavior or parameter errors are found, an emergency takeover process is started, so that the driving right of the vehicle is changed from automatic driving to remote manual driving. The method can ensure the safe operation of the automatic driving motorcade to a certain extent, but has a plurality of defects at the same time.
The manual monitoring mode has lower real-time performance; monitoring personnel of the control center monitor through videos and data returned by the site or the vehicle, and enter an emergency treatment process through manual operation when an abnormal condition occurs. In the process, certain time is required for data return, personnel reaction and judgment and manual operation; the accuracy of a manual monitoring mode is low; the possibility of misjudgment caused by the fact that the naked eye is required to judge through the video in manual monitoring cannot be ignored; meanwhile, misjudgment is easily caused by classification of abnormal states; the number of target vehicles is greatly limited in a manual monitoring mode; the mode of monitoring is mainly carried out through videos, and the number of target vehicles which can be simultaneously and accurately monitored by a single worker is limited. If more target vehicles need to be monitored simultaneously, monitoring personnel need to be increased, and the cost is high.
In view of the above, it is desirable to provide a remote control monitoring and early warning method and a storage medium for an autonomous vehicle, which have real-time performance, accuracy and low cost.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to provide a remote control monitoring and early warning method for an automatic driving vehicle.
The invention discloses a remote control monitoring and early warning method for an automatic driving vehicle, which comprises the following steps:
s1, monitoring running state data of an automatic driving vehicle;
s2, analyzing the running state data, recording abnormal state data and classifying;
and S3, starting vehicle emergency treatment and remote take-over according to the type of the abnormal state.
Further, the operation status data in step S1 includes sensing system data and positioning system data.
Further, the specific process in the step S3 includes positioning system data processing and sensing system data processing, and the analyzing and classifying of the positioning system data includes the following steps;
s201a, monitoring whether the reading of the positioning system is abnormal or not, and entering the next step when the reading of the positioning system is abnormal;
s201b, monitoring whether the obstacle detection is abnormal or not, and entering remote takeover processing if the obstacle detection is abnormal; if the obstacle detection is normal, entering the next step;
s201c, calculating accumulated abnormal time, wherein the accumulated abnormal time is the time from the abnormal reading of the positioning system in the step S201a to the step S201 c;
s201d, if the accumulated abnormal time is smaller than the early warning threshold value, executing the steps 201a to S201c in a circulating mode, and accumulating and calculating the accumulated abnormal time; and if the accumulated abnormal time is larger than the early warning threshold value, entering remote takeover processing.
The method for analyzing and classifying the perception system data comprises the following steps;
s202a, detecting whether the data of the sensing system is abnormal or not, and entering the next step when the data of the sensing system is abnormal;
s202b, executing the step S201a to the step S201d, and if the positioning system is normal, entering the next step;
s202c, whether the vehicle is in the marked place or not is detected, and if the vehicle is in the marked place, the remote takeover processing is carried out.
Further, step S2 further includes an out-of-type emergency process, including the steps of:
s203a, detecting whether the driving behavior of the vehicle is abnormal, and entering the next step when the driving behavior of the vehicle is abnormal;
s203b, synchronously executing the steps S201a to S201d and the steps S202a to S202c, if the remote takeover cannot be performed in the steps, directly performing the remote takeover, and reporting the abnormity.
Further, step S3 is followed by the step of,
and S4, recovering the driving right, and removing the remote takeover treatment and entering the vehicle emergency treatment when the vehicle runs to a certain distance behind the marked place.
Further, the sensing system data comprises laser radar data and millimeter wave radar data; the positioning system data includes GPS data and inertial navigation data.
The invention also provides a monitoring and early warning system for the remote control connection pipe of the automatic driving vehicle, which comprises,
the positioning system acquires the positioning system data of the vehicle through the GPS and the inertial navigation module;
the sensing system acquires peripheral sensing information data of the vehicle through the laser radar and the millimeter wave radar;
and the decision system is used for synchronously analyzing the data of the positioning system and the sensing system in real time and executing processing.
Further, the perception system further comprises a traffic light identification module based on a perception camera.
The present invention also provides a computer storage medium for implementing the steps of the method of the present invention.
Compared with the prior art, the technical scheme of the invention has the following advantages:
(1) Compared with a manual monitoring mode, the time delay of returning the video to the control center is hundreds of milliseconds, and monitoring personnel can respond to an abnormal state and need to monitor a plurality of video frames at the same time; the running state monitoring program of the vehicle end running in real time can detect the abnormal state of the automatic driving vehicle within millisecond time, and simultaneously starts the emergency processing flow of the vehicle end, so that the real-time performance is improved.
(2) The running state monitoring program running in real time at the vehicle end can analyze and read according to specific information of monitored contents, can accurately obtain information of the current abnormal state, and improves accuracy.
(3) Compared with a mode that manual monitoring mainly depends on video return, the automatic monitoring program runs in each target vehicle and is theoretically not limited by the target vehicle; and in the case of a large number of target vehicles, the cost is lower compared with the manual monitoring.
Drawings
FIG. 1 is a schematic flow chart of a method provided by an embodiment of the present invention;
FIG. 2 is a flow chart illustrating a method for analyzing and classifying positioning data according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of analyzing and classifying perception system data according to the method provided in the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
The monitoring and early warning method for the remote control take-over of the automatic driving vehicle comprises the following steps.
S1, monitoring running state data of the automatic driving vehicle.
And S2, analyzing the running state data, recording abnormal state data and classifying.
And S3, starting vehicle emergency treatment or remote take-over according to the type of the abnormal state.
The data monitored in step S1 include sensing system data and positioning data, and it should be noted that not only the sensing system data and the positioning system data are monitored in actual monitoring, but also the operation data of the sensor hardware, the operation data of the data processing module, and the data of the corresponding algorithm module are monitored, and positioning data and sensing system data with high correlation degree with the automatic driving safety of the vehicle are described in this embodiment.
After acquiring the positioning data and the sensing system data, analyzing the positioning data and the sensing system data simultaneously, and judging whether the positioning data and the sensing system data are abnormal or not, wherein the conditions for judging the abnormality between the positioning data and the sensing system data are as follows: (1) The vehicle completely loses the perception capability and cannot correctly judge the driving condition. (2) The vehicle positioning system cannot guide the vehicle to automatically drive along a predetermined route. (3) The data of the vehicle sensing system is normal, but the data system is abnormal, and the vehicle sensing system can be manually defined as abnormal after the vehicle can normally run and keep the state for a certain time.
Depending on the type of the anomaly, the embodiment further prefers that the specific process in step S3 includes positioning system data processing and sensing system data processing.
The analytical classification of the positioning system data comprises the following steps.
S201a, monitoring whether the reading of the positioning system is abnormal or not, and entering the next step when the reading of the positioning system is abnormal.
S201b, monitoring whether the obstacle detection is abnormal or not, and entering remote takeover processing if the obstacle detection is abnormal; and if the obstacle detection is normal, entering the next step.
And S201c, calculating accumulated abnormal time, wherein the accumulated abnormal time is the time from the abnormal reading of the positioning system in the step S201a to the step S201 c.
S201d, if the accumulated abnormal time is smaller than the early warning threshold value, executing the steps 201a to S201c in a circulating mode, and accumulating and calculating the accumulated abnormal time; and if the accumulated abnormal time is larger than the early warning threshold value, entering remote takeover processing.
When the positioning data of the detection system is abnormal, whether the obstacle detection function of the controlled vehicle is normal is first detected. If the obstacle detection function normally works at the moment, the vehicle is determined to have collision early warning capacity, and the vehicle can be stopped or detoured when encountering an obstacle within the collision early warning range. Therefore, in this case, it is determined that the vehicle can still safely travel in a short time, and only the vehicle needs to travel at a slow speed and start accumulating the time when the reading is abnormal. When the abnormal time reaches a set threshold value, a remote takeover request is sent to a remote takeover center, and the vehicle is braked; in another case, when the subsystem detects that the reading of the positioning system is abnormal and an unreliable state of the obstacle detection function occurs, the automatic driving system of the controlled vehicle is in a serious low confidence state, and the vehicle immediately enters into braking, reports the situation to the remote take-over center and sends a take-over request.
Further preferably, the positioning data in this embodiment includes inertial navigation data and GPS data, and the vehicle can acquire the current position in real time through the inertial navigation data and the GPS data.
The perception system data comprises perception camera hardware data, the monitoring result of the perception camera hardware is connected with the algorithm module which is responsible for the perception camera hardware, when the hardware of the perception camera is in fault, the algorithm module information is wrong, and therefore the type of the early warning information is the algorithm module information which is responsible for the early warning information.
The analytical classification of the perception system data comprises the following steps.
S202a, detecting whether the sensing system data is abnormal or not, and entering the next step when the sensing system data is abnormal.
S202b, executing the step S201a to the step S201d, and if the positioning system is normal, entering the next step.
S202c, whether the vehicle is in the marked place or not is detected, and if the vehicle is in the marked place, the remote takeover processing is carried out.
During actual travel of the autonomous vehicle, the sensing system data is of various types, including lidar data, millimeter-wave radar data, and traffic light identification module data based on a sensing camera (based on sensing camera hardware data).
It is further preferred, for example, that the lidar data aspect first needs to monitor for each individual device the frequency of the basic information emitted by its ROS-driven package, i.e. whether the message is emitted or not. If the frequency is too low or 0, the device is deemed to have been powered down, data connection interrupted, or otherwise severely failed. Secondly, the message frequency can be monitored for the fusion data of the laser radar point cloud realized by the upper layer. In addition to the frequency, the length of the overall output data also defines the legal value range for monitoring. The millimeter wave radar data method directly monitors the legal value range of the frequency and the data length of basic data output due to the particularity of the output data, and the monitoring method is similar to a laser radar. In the aspect of sensing cameras, each camera has a separately responsible task, so that each camera is monitored separately, and the monitoring method is also a legal value range of the frequency and the data length of output data.
The embodiment exemplifies the traffic light identification module data, and when the vehicle does not reach the intersection range, the vehicle is not treated as a high-priority fault. The emergency processing flow of the sensing module is divided into two types, wherein the first type is that when a sensor for determining the vehicle obstacle detection function or a related software module thereof breaks down, the vehicle is considered to have no basic safety guarantee at the moment and belongs to the most serious abnormity. In this case, the vehicle will immediately enter emergency braking and submit a take-over request to the remote control take-over center, where the intersection is the marked point in step S202 c.
Further preferably, after the step S3, the driving right is recovered, and when the vehicle travels to a certain distance from the marked place, the remote takeover process is released, and the vehicle emergency process is performed.
The embodiment provides a monitoring and early warning system for a remote control take-over of an automatic driving vehicle, which comprises a positioning system, a sensing system and a decision-making system.
The positioning system acquires the positioning system data of the vehicle through the GPS and the inertial navigation module;
the sensing system acquires peripheral sensing information data of the vehicle through a laser radar and a millimeter wave radar;
and the decision system is used for synchronously analyzing the data of the positioning system and the sensing system in real time and executing processing.
Further preferably, the perception system further comprises a traffic light recognition module based on a perception camera, so as to realize the recognition of the state of the traffic light on the road and assist the operation of the decision making system.
Example two
The present embodiment provides a computer storage medium, which stores a computer program, wherein the computer program is configured to implement the steps of the method according to the first embodiment when executed by a processor.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (2)
1. A monitoring and early warning method for remote control take-over of an automatic driving vehicle is characterized by comprising the following steps:
s1, monitoring running state data of an automatic driving vehicle;
s2, analyzing the running state data, recording abnormal state data and classifying;
s3, starting vehicle emergency treatment and remote take-over according to the type of the abnormal state;
the operation state data in the step S1 comprises sensing system data and positioning system data;
the analysis and classification of the positioning system data comprises the following steps;
s201a, monitoring whether the reading of the positioning system is abnormal or not, and entering the next step when the reading of the positioning system is abnormal;
s201b, monitoring whether the obstacle detection is abnormal or not, and entering remote takeover processing if the obstacle detection is abnormal; if the obstacle detection is normal, entering the next step;
s201c, calculating accumulated abnormal time, wherein the accumulated abnormal time is the time from the abnormal reading of the positioning system in the step S201a to the step S201 c;
s201d, if the accumulated abnormal time is smaller than the early warning threshold value, executing the steps 201a to S201c in a circulating mode, and accumulating and calculating the accumulated abnormal time; if the accumulated abnormal time is larger than the early warning threshold value, entering remote take-over processing;
the method for analyzing and classifying the perception system data comprises the following steps;
s202a, detecting whether the data of the sensing system is abnormal or not, and entering the next step when the data of the sensing system is abnormal;
s202b, executing the step S201a to the step S201d, and if the positioning system is normal, entering the next step;
s202c, detecting whether the vehicle is in a marked place, and if the vehicle is in the marked place, performing remote takeover processing;
step S2 further includes an out-of-type emergency process, including the steps of:
s203a, detecting whether the driving behavior of the vehicle is abnormal, and entering the next step when the driving behavior of the vehicle is abnormal;
s203b, synchronously executing the steps S201a-S201d and the steps S202 a-S202 c, if the remote takeover cannot be performed in the steps, directly performing the remote takeover, and reporting an exception;
step S3 is followed by a step of,
s4, recovering the driving right, and removing the remote take-over processing and entering vehicle emergency processing when the vehicle runs to a certain distance behind the marked place;
the sensing system data comprises laser radar data and millimeter wave radar data; the positioning system data comprises GPS data and inertial navigation data;
the method is implemented by a system comprising:
the positioning system acquires the positioning system data of the vehicle through the GPS and the inertial navigation module;
the sensing system acquires peripheral sensing information data of the vehicle through a laser radar and a millimeter wave radar;
the decision system is used for synchronously analyzing the data of the positioning system and the sensing system in real time and executing processing;
the perception system also includes a perception camera-based traffic light identification module.
2. A computer storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method as claimed in claim 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110582581.4A CN113110266B (en) | 2021-05-25 | 2021-05-25 | Remote control monitoring early warning method for automatic driving vehicle and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110582581.4A CN113110266B (en) | 2021-05-25 | 2021-05-25 | Remote control monitoring early warning method for automatic driving vehicle and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113110266A CN113110266A (en) | 2021-07-13 |
| CN113110266B true CN113110266B (en) | 2022-10-18 |
Family
ID=76723425
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110582581.4A Active CN113110266B (en) | 2021-05-25 | 2021-05-25 | Remote control monitoring early warning method for automatic driving vehicle and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113110266B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113821010B (en) * | 2021-08-11 | 2023-03-31 | 安途智行(北京)科技有限公司 | Monitoring method for automatic driving vehicle drive test |
| CN114348025A (en) * | 2022-01-30 | 2022-04-15 | 中国第一汽车股份有限公司 | Vehicle driving monitoring system, method, equipment and storage medium |
| CN117135197A (en) * | 2022-05-18 | 2023-11-28 | 腾讯科技（深圳）有限公司 | Vehicle formation driving control method, device, equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105450990A (en) * | 2015-11-16 | 2016-03-30 | 合肥工业大学 | Down-hole mobile broadband streaming media network facing unmanned locomotive |
| CN105679069A (en) * | 2016-03-23 | 2016-06-15 | 傅春 | Intelligent road traffic system and method of controlling vehicle driving |
| WO2021088395A1 (en) * | 2019-11-05 | 2021-05-14 | 华为技术有限公司 | Vehicle navigation method and terminal |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106094830B (en) * | 2016-07-11 | 2019-09-06 | 百度在线网络技术（北京）有限公司 | Method and apparatus for controlling automatic driving vehicle |
| JP2019156330A (en) * | 2018-03-16 | 2019-09-19 | 本田技研工業株式会社 | Vehicle control device, vehicle control method, and program |
| CN110032176A (en) * | 2019-05-16 | 2019-07-19 | 广州文远知行科技有限公司 | Long-range adapting method, device, equipment and the storage medium of pilotless automobile |
| CN110077420B (en) * | 2019-05-23 | 2020-11-10 | 广州小鹏汽车科技有限公司 | Automatic driving control system and method |
| CN110764889B (en) * | 2019-09-19 | 2022-03-04 | 山东省科学院自动化研究所 | Remote monitoring method and system for automatic driving test vehicle |
| CN111016905A (en) * | 2019-12-06 | 2020-04-17 | 中国科学院自动化研究所 | Interaction method and system for automatic driving vehicle and driving remote control terminal |
-
2021
- 2021-05-25 CN CN202110582581.4A patent/CN113110266B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105450990A (en) * | 2015-11-16 | 2016-03-30 | 合肥工业大学 | Down-hole mobile broadband streaming media network facing unmanned locomotive |
| CN105679069A (en) * | 2016-03-23 | 2016-06-15 | 傅春 | Intelligent road traffic system and method of controlling vehicle driving |
| WO2021088395A1 (en) * | 2019-11-05 | 2021-05-14 | 华为技术有限公司 | Vehicle navigation method and terminal |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113110266A (en) | 2021-07-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113110266B (en) | Remote control monitoring early warning method for automatic driving vehicle and storage medium | |
| US20200074769A1 (en) | Vehicle Fault Handling Method, Apparatus, Device and Storage Medium | |
| CN109345829B (en) | Unmanned vehicle monitoring method, device, equipment and storage medium | |
| CN112622930A (en) | Unmanned vehicle driving control method, device and equipment and automatic driving vehicle | |
| CN107464416B (en) | Semi-automatic driving method and system for bus | |
| CN111830942A (en) | Safe automatic driving method and system | |
| CN115465293B (en) | Multi-sensor safety self-cognition and safety processing device and method | |
| CN113879324B (en) | Intelligent driving vehicle sensor fault processing method and device | |
| CN113895450A (en) | Safety redundancy system and control method for unmanned vehicle sensing system | |
| CN115257810A (en) | Unmanned vehicle parallel connection pipe control method and device, cloud control platform and electronic equipment | |
| CN114489004A (en) | Unmanned driving test method and system | |
| CN111800508B (en) | Automatic driving fault monitoring method based on big data | |
| CN114572138B (en) | Automatic driving vehicle accident fault self-checking method, device, equipment and storage medium | |
| CN115973180A (en) | Steering detection method, apparatus, device and medium for autonomous vehicle | |
| CN111626334B (en) | Key control target selection method for vehicle-mounted advanced auxiliary driving system | |
| CN112367352A (en) | Vehicle abnormality detection method and system | |
| CN114049614A (en) | Subway train emergency braking anti-collision control method | |
| CN113670360A (en) | Monitoring method, system, device, vehicle, medium and product | |
| CN113954826B (en) | Vehicle control method and system for vehicle blind area and vehicle | |
| CN113858208B (en) | Robot detection method and device, electronic equipment and storage medium | |
| CN113420725B (en) | Method, device, system and storage medium for identifying false alarm scenes of BSD (backup service discovery) product | |
| CN112346985B (en) | ACC function failure determination method, system, device and storage medium | |
| KR20180063734A (en) | Method and Apparatus for acquiring event image of vehicle | |
| CN115641569B (en) | Driving scene processing method, device, equipment and medium | |
| CN114407918B (en) | Takeover scene analysis method, takeover scene analysis device, takeover scene analysis equipment and storage medium |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |