CN113799715B - Method and device for determining cause of abnormality of vehicle, communication equipment and storage medium - Google Patents
Method and device for determining cause of abnormality of vehicle, communication equipment and storage medium Download PDFInfo
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- CN113799715B CN113799715B CN202111243130.4A CN202111243130A CN113799715B CN 113799715 B CN113799715 B CN 113799715B CN 202111243130 A CN202111243130 A CN 202111243130A CN 113799715 B CN113799715 B CN 113799715B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
- B60R16/023—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for transmission of signals between vehicle parts or subsystems
- B60R16/0231—Circuits relating to the driving or the functioning of the vehicle
- B60R16/0232—Circuits relating to the driving or the functioning of the vehicle for measuring vehicle parameters and indicating critical, abnormal or dangerous conditions
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- 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
- B60W50/02—Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures
- B60W50/0205—Diagnosing or detecting failures; Failure detection models
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Abstract
The application is applicable to the field of Internet of vehicles and provides a method and a device for determining reasons of vehicle abnormality, communication equipment and a storage medium. The method for determining the cause of the abnormality of the vehicle comprises the following steps: acquiring driving state information and driving state information of a target vehicle, wherein the driving state information comprises any one or more of speed, acceleration, course angle, driving track and vehicle distance, and the driving state information comprises any one or more of steering wheel state, accelerator state, brake state, driving mode, ABS state and gear state; determining difference information between the driving state information of the target vehicle and the driving state information of surrounding vehicles; when the driving abnormality of the target vehicle is determined according to the difference information, the abnormality cause of the target vehicle is determined according to the driving state information and the driving state information of the target vehicle, so that the driving of the user can be reasonably guided according to the abnormality cause of the target vehicle.
Description
Technical Field
The application belongs to the field of Internet of vehicles, and particularly relates to a method and a device for determining a cause of abnormality of a vehicle, communication equipment and a storage medium.
Background
Along with the development of communication technology and artificial intelligence technology, the functions of the vehicle-mounted unit are more and more abundant, and the vehicle-mounted unit can timely discover the abnormality of the vehicle by collecting the vehicle information, so that the probability of traffic accidents is reduced.
The existing vehicle-mounted unit generally collects running data in the running process of the vehicle and reports the running data to a data center when abnormal data are collected, but the reason for abnormality of the running data cannot be accurately judged, so that effective countermeasures cannot be taken, and the running safety of the current vehicle is ensured.
Disclosure of Invention
In view of the above, the embodiments of the present application provide a method, an apparatus, a communication device, and a storage medium for determining a cause of abnormality of a vehicle, which can determine the cause of abnormality of the vehicle, so as to reasonably guide a user to drive.
A first aspect of an embodiment of the present application provides a method for determining a cause of a vehicle abnormality, including:
acquiring driving state information and driving state information of a target vehicle, and acquiring driving state information of surrounding vehicles, wherein the surrounding vehicles are vehicles with the distance from the target vehicle within a preset distance range, the driving state information comprises any one or more of speed, acceleration, course angle, driving track and vehicle distance, and the driving state information comprises any one or more of steering wheel state, accelerator state, brake state, driving mode, ABS state and gear state;
determining difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicles;
when the driving abnormality of the target vehicle is determined according to the difference information, determining the abnormality cause of the target vehicle according to the driving state information and the driving state information of the target vehicle.
In one possible implementation manner, the determining the cause of the abnormality of the target vehicle according to the driving state information and the driving state information of the target vehicle includes:
determining the driving state information and the driving state information of the target vehicle at abnormal driving time from the driving state information and the driving state information of the target vehicle;
and inputting the driving state information and the road surface condition information at the abnormal driving moment into the dynamics model of the target vehicle to obtain the driving state information output by the dynamics model of the target vehicle, and comparing the driving state information at the abnormal driving moment with the driving state information output by the dynamics model to determine the abnormal reason of the target vehicle.
In one possible implementation manner, the determining the abnormal running of the target vehicle according to the difference information includes:
and if the accumulated times of one or more pieces of difference information meeting the preset conditions in the preset period is greater than the preset times, determining that the target vehicle runs abnormally.
In one possible implementation manner, if the driving abnormality of the target vehicle is determined according to the difference information, determining the cause of the abnormality of the target vehicle according to the driving state information and the driving state information of the target vehicle includes:
acquiring the position relation between the running track of the target vehicle and the lane;
and if the running abnormality of the target vehicle is determined according to the difference information and the position relation, determining the abnormality reason of the target vehicle according to the running state information and the driving state information of the target vehicle.
In one possible implementation manner, the determining the difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicle includes:
determining an average speed from the speeds of the surrounding vehicles;
and determining difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles according to the average speed and the speed of the target vehicle.
In one possible implementation manner, the determining the difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicle includes:
determining an average distance according to the vehicle distance of the surrounding vehicles;
and determining difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles according to the average distance and the vehicle distance of the target vehicle.
In one possible implementation manner, the determining the difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicle includes:
determining a similarity between the travel track of the target vehicle and the travel track of the surrounding vehicles;
and determining difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles according to the similarity.
In one possible implementation manner, the acquiring the driving state information of the target vehicle includes:
acquiring first state information detected by a vehicle-mounted unit of the target vehicle, second state information sent by surrounding vehicles and third state information sent by road side sensing equipment;
and determining the running state information of the target vehicle according to the fusion information of any one or more of the first state information, the second state information and the third state information.
In one possible implementation manner, after the determining the cause of the abnormality of the target vehicle, the method further includes:
and outputting first prompt information according to the abnormality reasons, and/or sending second prompt information to the surrounding vehicles according to the abnormality reasons.
A second aspect of the embodiments of the present application provides a determination apparatus for a cause of a vehicle abnormality, including:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring running state information and driving state information of a target vehicle and running state information of surrounding vehicles, the surrounding vehicles are vehicles, the distance between the surrounding vehicles and the target vehicle is within a preset distance range, the running state information comprises any one or more of speed, acceleration, course angle, running track and vehicle distance, and the driving state information comprises any one or more of steering wheel state, accelerator state, brake state, running mode, ABS state and gear state;
a determining module configured to determine difference information between driving state information of the target vehicle and driving state information of the surrounding vehicles;
and the analysis module is used for determining the abnormality reason of the target vehicle according to the driving state information and the driving state information of the target vehicle when the driving abnormality of the target vehicle is determined according to the difference information.
In one possible implementation, the analysis module is specifically configured to:
determining the driving state information and the driving state information of the target vehicle at abnormal driving time from the driving state information and the driving state information of the target vehicle;
and inputting the driving state information and the road surface condition information at the abnormal driving moment into the dynamics model of the target vehicle to obtain the driving state information output by the dynamics model of the target vehicle, and comparing the driving state information at the abnormal driving moment with the driving state information output by the dynamics model to determine the abnormal reason of the target vehicle.
In one possible implementation, the analysis module is specifically configured to:
acquiring the position relation between the running track of the target vehicle and the lane;
and if the running abnormality of the target vehicle is determined according to the difference information and the position relation, determining the abnormality reason of the target vehicle according to the running state information and the driving state information of the target vehicle.
A third aspect of the embodiments of the present application provides a communication device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the method for determining a cause of a vehicle abnormality according to the first aspect described above when the processor executes the computer program.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method for determining a cause of a vehicle abnormality as described in the first aspect above.
A fifth aspect of embodiments of the present application provides a computer program product, which when run on a communication device, causes the communication device to perform the method for determining a cause of a vehicle anomaly as set forth in any one of the first aspects above.
Compared with the prior art, the embodiment of the application has the beneficial effects that: the difference information between the running state information of the target vehicle and the running state information of the surrounding vehicle is determined by acquiring the running state information of the target vehicle, the driving state information, and the running state information of the surrounding vehicle. And when the driving abnormality of the target vehicle is determined according to the difference information, the abnormality cause of the target vehicle is further determined according to the driving state information and the driving state information of the target vehicle, so that the driving of the user can be reasonably guided according to the abnormality cause of the target vehicle.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments or the prior art will be briefly described below.
Fig. 1 is a schematic implementation flow chart of a method for determining a cause of a vehicle abnormality according to an embodiment of the present application;
fig. 2 is a schematic diagram of a device for determining a cause of an abnormality of a vehicle according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a communication device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The existing vehicle-mounted unit generally collects driving data in the driving process of a vehicle and reminds a user when abnormal data are collected, but the abnormal reason cannot be determined according to the abnormal driving data, so that the driving of the user cannot be reasonably guided.
To this end, the present application provides a method of determining a cause of a vehicle abnormality, by acquiring driving state information and driving state information of a target vehicle, and acquiring driving state information of surrounding vehicles, determining difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicles. And when the driving abnormality of the target vehicle is determined according to the difference information, the abnormality cause of the target vehicle is further determined according to the driving state information and the driving state information of the target vehicle, so that the driving of the user can be reasonably guided according to the abnormality cause of the target vehicle.
The following exemplifies a method for determining the cause of abnormality of a vehicle provided in the present application.
The method for determining the cause of the abnormality of the vehicle is performed in a communication device, and the communication device may be a vehicle-mounted unit installed on the vehicle, a road side sensing device installed on a road, or a cloud server.
Referring to fig. 1, a method for determining a cause of an abnormality of a vehicle according to an embodiment of the present application includes:
s101: the method includes the steps of obtaining running state information and driving state information of a target vehicle and obtaining running state information of surrounding vehicles, wherein the surrounding vehicles are vehicles which are the same as a running road section of the target vehicle and have a distance within a preset distance range.
The driving state information comprises any one or more of speed, acceleration, course angle, driving track and vehicle distance, and the driving state information comprises any one or more of steering wheel state, accelerator state, brake state, driving mode, ABS state and gear state.
The driving state information of the target vehicle is acquired from an on-vehicle unit of the target vehicle. The driving state information of the target vehicle and the driving state information of the surrounding vehicle may be acquired from an on-vehicle unit of the target vehicle, may be acquired from the surrounding vehicle, or may be acquired from a roadside sensing device.
In one possible implementation manner, first state information detected by an on-board unit of the target vehicle, second state information sent by surrounding vehicles, and third state information sent by road side sensing equipment are acquired. Wherein the first state information includes any one or more of a speed, an acceleration, a heading angle, a driving position, and a vehicle distance of the target vehicle and surrounding vehicles. The second state information and the third state information may be identical to the first state information. And determining the driving state information of the target vehicle according to the fusion information of any one or more of the first state information, the second state information and the third state information. And the running state information of the surrounding vehicles can be determined according to the fusion information of any one or more of the first state information, the second state information and the third state information, so that the accuracy of the determined running state information is improved. For example, the speed of the target vehicle in the first state information, the speed of the target vehicle in the second state information, and the speed of the target vehicle in the third state information are averaged to obtain the speed of the target vehicle. For another example, the driving position of the target vehicle in the first state information, the driving position of the target vehicle in the second state information, and the driving position of the target vehicle in the third state information are fitted to obtain the driving trajectory of the target vehicle. The driving position can be coordinates or longitude and latitude.
S102: and determining difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicles.
Wherein the driving state information of the target vehicle and the driving state information of the surrounding vehicles include: any one or more of a difference in speed, a difference in acceleration, a difference in heading angle, a difference in travel locus, and a difference in vehicle spacing between the target vehicle and the surrounding vehicles.
In one possible implementation, the speed of the surrounding vehicle is obtained, the average speed of the surrounding vehicle is calculated according to the speed of the surrounding vehicle, and the difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicle is determined according to the average speed of the surrounding vehicle and the speed of the target vehicle.
In one possible implementation, the average acceleration of the surrounding vehicle is calculated according to the accelerations of the surrounding vehicles, and the difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicle is determined according to the average acceleration of the surrounding vehicle and the acceleration of the target vehicle.
In one possible implementation, an average heading angle of the surrounding vehicle is calculated according to the heading angle of the surrounding vehicle, and difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicle is determined according to the average heading angle of the surrounding vehicle and the heading angle of the target vehicle. The course angle can be calculated according to the positions of the vehicles at two adjacent moments, and can also be directly obtained from a global navigation satellite system (Global Navigation Satellite System, GNSS). The average heading angle of the surrounding vehicle refers to an average of heading angles of the surrounding vehicle.
In one possible implementation, the vehicle distance of the target vehicle may be calculated from the traveling position of the target vehicle and the traveling positions of the adjacent vehicles, and the vehicle distance of the surrounding vehicle may be calculated from the traveling positions of the surrounding vehicles and the traveling positions of the adjacent vehicles. Wherein, the adjacent vehicles of the target vehicle refer to vehicles on the same lane immediately in front of or behind the target vehicle, or vehicles on left or right adjacent lanes of the target vehicle.
The vehicle pitch includes a lateral pitch, which may refer to a distance of two vehicles in a direction perpendicular to a traveling direction, and a longitudinal pitch, which may refer to a distance of two vehicles in the traveling direction. The average distance can be calculated according to the vehicle distances of all the surrounding vehicles, and the difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles is determined according to the average distance and the vehicle distance of the target vehicle.
In one possible implementation, the driving track of the surrounding vehicle is calculated according to the driving position of the surrounding vehicle within the preset period, and the driving track of the target vehicle is calculated according to the driving position of the target vehicle within the preset period. And determining the similarity between the running track of the target vehicle and the running track of the surrounding vehicles, and determining the difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles according to the similarity. The similarity may be obtained by averaging the similarity between the travel locus of the target vehicle and the travel locus of each of the surrounding vehicles. The driving track may be obtained by curve fitting the driving position within a preset period. The similarity of the driving track of the target vehicle and each surrounding vehicle can be calculated through a Frechet distance algorithm or a Hausdorff distance algorithm.
S103: when the driving abnormality of the target vehicle is determined according to the difference information, determining the abnormality cause of the target vehicle according to the driving state information and the driving state information of the target vehicle.
Specifically, whether the target vehicle runs abnormally is determined according to whether the difference information meets a preset condition. The difference information meeting the preset condition may include any one or more of the following: the difference between the average speed of the surrounding vehicles and the speed of the target vehicle is greater than a preset value, the difference between the average acceleration of the surrounding vehicles and the acceleration of the target vehicle is greater than a preset value, the difference between the average heading angle of the surrounding vehicles and the heading angle of the target vehicle is greater than a preset value, the difference between the average distance of the surrounding vehicles and the vehicle distance of the target vehicle is greater than a preset value, and the similarity between the driving track of the target vehicle and the driving track of the surrounding vehicles is less than a preset value.
In one possible implementation manner, if the cumulative number of times that one or more items of the difference information satisfy the preset condition is greater than the preset number of times in the preset period, it may be determined that the target vehicle is traveling abnormally. Specifically, the difference in speed, the difference in acceleration, the difference in heading angle, the difference in travel track, and the difference in vehicle spacing between the target vehicle and the surrounding vehicles may be counted to satisfy the cumulative number of times of the preset condition, respectively, and when at least one of the cumulative number of times is greater than the preset number of times, it may be determined that the target vehicle is traveling abnormally. In other embodiments, the number of times that any one of the difference information satisfies the preset condition may be counted, and if the cumulative number of times that all the items in the difference information satisfy the preset condition is greater than a threshold, the abnormal driving of the target vehicle may be determined. For example, if the number of anomalies in the difference in speed, the number of anomalies in the difference in acceleration, the number of anomalies in the difference in heading angle, the number of anomalies in the difference in travel track, the number of anomalies in the vehicle pitch, and N5 are N1, N2+ N3+ N4+ N5 > N (where N is a threshold value), relative to the surrounding vehicles, the target vehicle may be determined to be traveling anomalies.
In one possible implementation manner, a position relationship between a driving track of the target vehicle and the lane is obtained, and if the driving abnormality of the target vehicle is determined according to the difference information and the position relationship. Specifically, according to the positional relationship between the travel track of the target vehicle and the lane, the maintenance condition of the lane line of the target vehicle and the steady condition of the lane change process of the target vehicle can be determined. The lane line keeping condition of the target vehicle may be the number of times the target vehicle deviates from the current lane within a preset time period, and if the number of times the target vehicle deviates from the current lane within the preset time period is greater than the preset number of times, determining that the lane line keeping condition of the target vehicle is abnormal. The stable condition of the lane change process of the target vehicle can be the swing amplitude of the target vehicle in the lane change process, and if the swing amplitude of the target vehicle in the lane change process is larger than a preset value, the abnormal stable condition of the lane change process of the target vehicle is determined.
In an embodiment, whether the target vehicle deviates from the current lane may be determined by the degree of coincidence and similarity of the travel track of the target vehicle and the lane center line. The track of the lane center line can be obtained from a map, and can also be obtained after the road surface image shot by the front camera of the vehicle is identified. The degree of swing of the target vehicle within the lane may be determined by a ratio of an actual travel track length of the target vehicle to a length of a lane line within the current road section. For example, if the ratio is greater than the threshold value, it is determined that the swing amplitude of the target vehicle in the lane is greater than the preset value.
In one possible implementation manner, the number of abnormal keeping situations of the lane line of the target vehicle and the number of abnormal stable situations of the lane change process of the target vehicle are counted, and if the difference information of the target vehicle and surrounding vehicles meets the accumulated number of preset conditions, the number of abnormal keeping situations of the lane line of the target vehicle and the sum of the number of abnormal stable situations of the lane change process of the target vehicle are greater than a preset value, the running abnormality of the target vehicle is determined, so that the accuracy of determining the running abnormality of the vehicle is further improved.
After the driving abnormality of the target vehicle is determined, determining whether abnormal driving behaviors exist according to the corresponding relation between the driving state information and the driving state information, if the abnormal driving behaviors exist, determining that the abnormality cause of the target vehicle is improper driving, and if the abnormal driving behaviors do not exist, determining that the abnormality cause of the target vehicle is vehicle failure. The abnormality cause of the target vehicle is determined by comparing the difference information of the running state information of the target vehicle and the running state information of the surrounding vehicles, and the accuracy of evaluating the abnormality cause is improved.
In one possible implementation manner, after determining that the target vehicle is abnormal in running, from the running state information and the driving state information of the target vehicle, the running state information and the driving state information of the target vehicle at the moment of abnormal running are determined, the driving state information and the road surface condition information at the moment of abnormal running are input into the dynamics model of the target vehicle, and the running state information output by the dynamics model of the target vehicle is obtained. The road surface condition information may include information such as gradient of a road surface, degree of curve of a lane line, and the like. The vehicle dynamics model is a model for analyzing the stress of the vehicle and the motion of the vehicle. Parameters entered into the vehicle dynamics model may also include vehicle travel patterns. And comparing the running state information at the running abnormal moment with the running state information output by the dynamic model to determine the abnormal reason of the target vehicle.
In an embodiment, if the difference between the running state information at the running abnormality time and the running state information output by the dynamics model is within the preset range, it is determined that there is no abnormal driving behavior, the abnormality cause of the target vehicle is a vehicle failure, and if the difference between the running state information at the running abnormality time and the running state information output by the dynamics model is not within the preset range, it is determined that there is an abnormal driving behavior, the abnormality cause of the target vehicle is an improper driving.
In other possible implementations, the abnormal level of the abnormal driving behavior may be determined according to the difference between the driving state information at the driving abnormality time and the driving state information output by the dynamics model, and the abnormal level may be output. For example, the abnormality level may be determined based on a correspondence between the difference between the running state information at the time of the running abnormality and the running state information output from the dynamics model and a preset level.
In one possible implementation manner, after determining the abnormality cause of the target vehicle, the corresponding first prompt information is output according to the abnormality cause or the abnormality level of the target vehicle, where the first prompt information may be the abnormality cause or may be information prompting the driving error of the user, so that the driver of the target vehicle may be reminded of parking inspection or focusing on driving. After determining the abnormality cause of the target vehicle, generating corresponding second prompt information according to the abnormality cause or the abnormality grade of the target vehicle, and sending the prompt information to surrounding vehicles, wherein the second prompt information can be the abnormality cause of the target vehicle or the position of the target vehicle, so that the surrounding vehicles are reminded of avoiding. The first prompt information and the second prompt information can be information in a voice, vibration or text mode.
In the above-described embodiment, the difference information between the running state information of the target vehicle and the running state information of the surrounding vehicle is determined by acquiring the running state information of the target vehicle, the driving state information, and the running state information of the surrounding vehicle. If the driving abnormality of the target vehicle is determined according to the difference information, the abnormality cause of the target vehicle is determined according to the driving state information and the driving state information of the target vehicle, so that the driving of the user can be reasonably guided according to the abnormality cause of the target vehicle.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.
Corresponding to the method for determining the cause of the abnormality of the vehicle described in the above embodiments, fig. 2 shows a block diagram of the apparatus for determining the cause of the abnormality of the vehicle provided in the embodiment of the present application, and for convenience of explanation, only the portions related to the embodiments of the present application are shown.
As shown in fig. 2, the determination device of the cause of the abnormality of the vehicle includes an acquisition module 10, a determination module 20, and an analysis module 30.
The obtaining module 10 is configured to obtain driving state information of a target vehicle, and driving state information of surrounding vehicles, where the surrounding vehicles are vehicles having a distance from the target vehicle within a preset distance range, the driving state information includes any one or more of a speed, an acceleration, a heading angle, a driving track, and a vehicle distance, and the driving state information includes any one or more of a steering wheel state, a throttle state, a brake state, a driving mode, an ABS state, and a gear state.
The determining module 20 is configured to determine difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicles;
the analysis module 30 is configured to determine, when it is determined that the target vehicle is traveling abnormally based on the difference information, a cause of abnormality of the target vehicle based on the traveling state information and the driving state information of the target vehicle.
In this embodiment, the acquiring module 10, the determining module 20 and the analyzing module 30 may be modules in a V2X vehicle-mounted unit with high-precision positioning. The acquisition module 10 may be an antenna of an on-board unit, a bluetooth, or a dedicated short range communication technology (Dedicated Short Range Communicatio, DSRC) chip, etc., and the determination module 20 and the analysis module 30 may be integrated with a computing chip, such as a digital signal processing (Digital Signal Processing, DSP) chip, on-board unit.
In one possible implementation, the analysis module 30 is specifically configured to:
determining the driving state information and the driving state information of the target vehicle at abnormal driving time from the driving state information and the driving state information of the target vehicle;
and inputting the driving state information and the road surface condition information at the abnormal driving moment into the dynamics model of the target vehicle to obtain the driving state information output by the dynamics model of the target vehicle, and comparing the driving state information at the abnormal driving moment with the driving state information output by the dynamics model to determine the abnormal reason of the target vehicle.
In one possible implementation, the analysis module 30 is specifically configured to:
and if the accumulated times of one or more of the difference information meeting the preset conditions in the preset period is greater than the preset times, determining that the target vehicle runs abnormally.
In one possible implementation, the analysis module 30 is specifically configured to:
acquiring the position relation between the running track of the target vehicle and the lane;
and if the running abnormality of the target vehicle is determined according to the difference information and the position relation, determining the abnormality reason of the target vehicle according to the running state information and the driving state information of the target vehicle.
In one possible implementation, the determining module 20 is specifically configured to:
determining an average speed from the speeds of the surrounding vehicles;
and determining difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles according to the average speed and the speed of the target vehicle.
In one possible implementation, the determining module 20 is specifically configured to:
determining an average distance according to the vehicle distance of the surrounding vehicles;
and determining difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles according to the average distance and the vehicle distance of the target vehicle.
In one possible implementation, the determining module 20 is specifically configured to:
determining a similarity between the travel track of the target vehicle and the travel track of the surrounding vehicles;
and determining difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles according to the similarity.
In one possible implementation, the obtaining module 10 is specifically configured to:
acquiring first state information detected by a vehicle-mounted unit of the target vehicle, second state information sent by surrounding vehicles and third state information sent by road side sensing equipment;
and determining the running state information of the target vehicle according to the fusion information of any one or more of the first state information, the second state information and the third state information.
In one possible implementation, the analysis module 30 is further configured to:
and outputting first prompt information according to the abnormality reasons, and/or sending second prompt information to the surrounding vehicles according to the abnormality reasons.
It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.
Fig. 3 is a schematic structural diagram of a communication device according to an embodiment of the present application. As shown in fig. 3, the communication device of this embodiment includes: a processor 11, a memory 12, and a computer program 13 stored in the memory 12 and executable on the processor 11. The processor 11 implements the steps in the embodiment of the method of determining the cause of the abnormality of the vehicle described above, such as steps S101 to S103 shown in fig. 1, when executing the computer program 13. Alternatively, the processor 11 may implement the functions of the modules/units in the above-described device embodiments when executing the computer program 13, for example, the functions of the acquisition module 10 to the analysis module 30 shown in fig. 2.
By way of example, the computer program 13 may be divided into one or more modules/units, which are stored in the memory 12 and executed by the processor 11 to complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program 13 in the communication device.
It will be appreciated by those skilled in the art that fig. 3 is merely an example of a communication device and is not limiting of the communication device, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the communication device may also include an input-output device, a network access device, a bus, etc.
The processor 11 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 12 may be an internal storage unit of the communication device, such as a hard disk or a memory of the communication device. The memory 12 may also be an external storage device of the communication device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the communication device. Further, the memory 12 may also include both internal storage units and external storage devices of the communication device. The memory 12 is used for storing the computer program as well as other programs and data required by the communication device. The memory 12 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each method embodiment described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (9)
1. A method for determining a cause of an abnormality in a vehicle, comprising:
acquiring driving state information and driving state information of a target vehicle, and acquiring driving state information of surrounding vehicles, wherein the surrounding vehicles are vehicles with the distance from the target vehicle within a preset distance range, the driving state information comprises any one or more of speed, acceleration, course angle, driving track and vehicle distance, and the driving state information comprises any one or more of steering wheel state, accelerator state, brake state, driving mode, ABS state and gear state;
determining difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicles;
when the running abnormality of the target vehicle is determined according to the difference information, the running state information and the driving state information of the running abnormality moment of the target vehicle are determined from the running state information and the driving state information of the target vehicle;
inputting driving state information and road surface condition information of the driving abnormality moment into a dynamics model of the target vehicle to obtain driving state information output by the dynamics model of the target vehicle, and comparing the driving state information of the driving abnormality moment with the driving state information output by the dynamics model; the vehicle dynamics model is a model for analyzing the stress and the motion of the vehicle;
and if the difference between the running state information at the running abnormal moment and the running state information output by the dynamic model is not in the preset range, determining that the abnormality cause of the target vehicle is improper driving.
2. The method according to claim 1, wherein the determining of the target vehicle traveling abnormality from the difference information includes:
and if the accumulated times of one or more of the difference information meeting the preset conditions in the preset period is greater than the preset times, determining that the target vehicle runs abnormally.
3. The method according to claim 1, wherein if the target vehicle is determined to be traveling abnormal based on the difference information, determining the cause of the abnormality of the target vehicle based on the traveling state information and the driving state information of the target vehicle includes:
acquiring the position relation between the running track of the target vehicle and the lane;
and if the running abnormality of the target vehicle is determined according to the difference information and the position relation, determining the abnormality reason of the target vehicle according to the running state information and the driving state information of the target vehicle.
4. The method according to claim 1, characterized in that the determining of the difference information of the running state information of the target vehicle and the running state information of the surrounding vehicles includes:
determining an average speed from the speeds of the surrounding vehicles; determining difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicles according to the average speed and the speed of the target vehicle;
or alternatively, the process may be performed,
determining an average distance according to the vehicle distance of the surrounding vehicles; determining difference information between the driving state information of the target vehicle and the driving state information of the surrounding vehicles according to the average distance and the vehicle distance of the target vehicle;
or alternatively, the process may be performed,
determining a similarity between the travel track of the target vehicle and the travel track of the surrounding vehicles; and determining difference information between the running state information of the target vehicle and the running state information of the surrounding vehicles according to the similarity.
5. The method according to claim 1, wherein the acquiring the running state information of the target vehicle includes:
acquiring first state information detected by a vehicle-mounted unit of the target vehicle, second state information sent by surrounding vehicles and third state information sent by road side sensing equipment;
and determining the running state information of the target vehicle according to the fusion information of any one or more of the first state information, the second state information and the third state information.
6. The method according to claim 1, characterized in that after said determining of the cause of the abnormality of the target vehicle, the method further comprises:
and outputting first prompt information according to the abnormality reasons, and/or sending second prompt information to the surrounding vehicles according to the abnormality reasons.
7. A vehicle abnormality cause determination device, characterized by comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring running state information and driving state information of a target vehicle and running state information of surrounding vehicles, the surrounding vehicles are vehicles, the distance between the surrounding vehicles and the target vehicle is within a preset distance range, the running state information comprises any one or more of speed, acceleration, course angle, running track and vehicle distance, and the driving state information comprises any one or more of steering wheel state, accelerator state, brake state, running mode, ABS state and gear state;
a determining module configured to determine difference information between driving state information of the target vehicle and driving state information of the surrounding vehicles;
the analysis module is used for determining the driving state information and the driving state information of the target vehicle at abnormal driving moment from the driving state information and the driving state information of the target vehicle when the abnormal driving of the target vehicle is determined according to the difference information;
inputting driving state information and road surface condition information of the driving abnormality moment into a dynamics model of the target vehicle to obtain driving state information output by the dynamics model of the target vehicle, and comparing the driving state information of the driving abnormality moment with the driving state information output by the dynamics model; the vehicle dynamics model is a model for analyzing the stress and the motion of the vehicle;
and if the difference between the running state information at the running abnormal moment and the running state information output by the dynamic model is not in the preset range, determining that the abnormality cause of the target vehicle is improper driving.
8. A communication device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 6 when executing the computer program.
9. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the method according to any one of claims 1 to 6.
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| WO2019142475A1 (en) * | 2018-01-22 | 2019-07-25 | パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカ | Data analysis device and program |
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