CN112115323A - Driving behavior scoring method, cloud server, vehicle-mounted terminal and system - Google Patents
Driving behavior scoring method, cloud server, vehicle-mounted terminal and system Download PDFInfo
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Abstract
The application relates to a scoring method of driving behaviors, a cloud server, a vehicle-mounted end and a system, wherein the method applied to the cloud server comprises the following steps: after a journey starts, receiving driving event monitoring data sent by a vehicle-mounted end, wherein the driving event monitoring data comprises a preset driving event and corresponding event information; accumulating the occurrence frequency of each preset driving event according to the received driving event monitoring data; and after the journey is finished, scoring the driving behavior corresponding to the journey according to the accumulated result and the weight corresponding to each preset driving event. Through the mode, the driving behavior of the user at this time can be scored, and the driving level and the safe driving consciousness of a driver can be improved.
Description
Technical Field
The application relates to the technical field of vehicle networking, in particular to a scoring method of driving behaviors, a cloud server, a vehicle-mounted end and a system.
Background
With the development of society and the improvement of living standard of people, automobiles become more and more important transportation tools for people to go out.
In the driving process, the driving habits and moods of the driver can bring unnecessary driving risks. However, in the prior art, after the user finishes the trip, the driving behavior of the trip is not analyzed and fed back, so that the driver cannot know which driving risks exist in the driving behavior of the driver in time, and the driving level and the safe driving consciousness of the driver are not improved.
Disclosure of Invention
An object of the present application is to provide a scoring method for driving behaviors, a cloud server, a vehicle-mounted terminal and a system, which can solve the above technical problems and can score the driving behaviors of a user this time.
In order to solve the technical problem, the application provides a scoring method for driving behaviors, which is applied to a cloud server and comprises the following steps:
after a journey starts, receiving driving event monitoring data sent by a vehicle-mounted end, wherein the driving event monitoring data comprises a preset driving event and corresponding event information;
accumulating the occurrence frequency of each preset driving event according to the received driving event monitoring data;
and after the journey is finished, scoring the driving behavior corresponding to the journey according to an accumulated result and the weight corresponding to each preset driving event.
Wherein, the scoring the driving behavior corresponding to the travel according to the accumulated result and the weight corresponding to each preset driving event comprises:
normalizing the accumulated result according to the number value range corresponding to each preset driving event;
and scoring the driving behavior corresponding to the travel according to the result of the normalization processing and the weight corresponding to each preset driving event.
After scoring the driving behavior corresponding to the travel according to the accumulated result and the weight corresponding to each preset driving event, the method further comprises the following steps:
generating an analysis report of the driving behavior corresponding to the journey according to the grading result, wherein the analysis report comprises the accumulated occurrence frequency of each preset driving event, the occurrence place and the occurrence time of the occurred preset driving event;
and sending the analysis report to the vehicle-mounted end so that the vehicle-mounted end displays the analysis report according to a preset mode.
Wherein, the method further comprises:
determining the start of the journey when a navigation start signal is received;
and when a navigation ending signal is received, the travel ending is determined according to the track point information sent by the vehicle-mounted end.
The application also provides a cloud server, which comprises a memory and a processor, wherein the memory stores at least one program instruction, and the processor loads and executes the at least one program instruction to realize the scoring method applied to the driving behavior of the cloud server.
The application also provides a scoring method of driving behaviors, which is applied to a vehicle-mounted terminal and comprises the following steps:
acquiring state data of the vehicle after the journey is started;
judging whether a preset driving event occurs to the vehicle according to the acquired state data;
if a preset driving event occurs, sending driving event monitoring data to a cloud server so that the cloud server accumulates the occurrence frequency of each preset driving event according to the received driving event monitoring data, and after the journey is finished, scoring the driving behavior corresponding to the journey according to an accumulated result and the weight corresponding to each preset driving event, wherein the driving event monitoring data comprises the occurred preset driving event and corresponding event information.
Wherein, the method further comprises:
determining the start of the journey when a navigation start signal is received;
sending the navigation starting signal to the cloud server and uploading track point information of the vehicle in real time;
and when a navigation ending signal is received, sending the navigation ending signal to the cloud server so that the cloud server determines the end of the travel according to the track point information of the vehicle.
Wherein, the method further comprises:
receiving an analysis report of the driving behavior corresponding to the journey, which is sent by the cloud server, wherein the analysis report comprises the accumulated occurrence frequency of each preset driving event, the occurrence place and the occurrence time of the occurred preset driving event;
and displaying the analysis report according to a preset mode.
The application also provides a vehicle-mounted terminal, which comprises a memory and a processor, wherein the memory stores at least one program instruction, and the processor loads and executes the at least one program instruction to realize the scoring method applied to the driving behavior of the vehicle-mounted terminal.
The application also provides a scoring system for driving behaviors, which comprises the cloud server and the vehicle-mounted end.
According to the scoring method of the driving behaviors, the cloud server, the vehicle-mounted end and the system, after a journey starts, the cloud server receives driving event monitoring data sent by the vehicle-mounted end, the driving event monitoring data comprise occurring preset driving events and corresponding event information, in the driving process, the occurrence times of the preset driving events are accumulated according to the received driving event monitoring data, and after the journey is finished, the driving behaviors corresponding to the journey are scored according to the accumulation results and the weight corresponding to the preset driving events. Through the mode, the driving behavior of the user at this time can be scored, and the driving level and the safe driving consciousness of a driver can be improved.
The foregoing description is only an overview of the technical solutions of the present application, and in order to make the technical means of the present application more clearly understood, the present application may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present application more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
FIG. 1 is a flow diagram illustrating a method for scoring driving behavior according to an exemplary embodiment.
FIG. 2 is a flow chart illustrating a method of scoring driving behavior according to another exemplary embodiment.
Fig. 3 is a schematic structural diagram illustrating a system for scoring driving behavior according to an exemplary embodiment.
Detailed Description
To further illustrate the technical means and effects of the present application for achieving the predetermined application purpose, the following detailed description is provided with specific embodiments, methods, steps, structures, features and effects of the scoring method, the cloud server, the vehicle-mounted terminal and the system according to the driving behavior of the present application in combination with the accompanying drawings and preferred embodiments.
The foregoing and other technical matters, features and effects of the present application will be apparent from the following detailed description of preferred embodiments, which is to be read in connection with the accompanying drawings. While the present application is susceptible to embodiment and specific details, specific reference will now be made in detail to the present disclosure for the purpose of illustrating the general principles of the invention.
FIG. 1 is a flow diagram illustrating a method for scoring driving behavior according to an exemplary embodiment. Referring to fig. 1, the method for scoring driving behaviors of the present embodiment is applied to a cloud server, and includes:
and step 110, after the journey starts, receiving driving event monitoring data sent by the vehicle-mounted end, wherein the driving event monitoring data comprises a preset driving event and corresponding event information.
When a user starts navigation by using the vehicle-mounted end, the vehicle-mounted end judges that a travel starts, further starts to acquire the state data of the vehicle, and judges whether a preset driving event occurs to the vehicle according to the acquired state data. During actual implementation, after the vehicle-mounted end acquires the state data, whether the state data meets the occurrence condition of the preset driving event is judged according to the judgment rule corresponding to the type of the state data, and if the state data meets the occurrence condition of the preset driving event, the occurring preset driving event is determined.
The state data of the vehicle comprises at least one of an angular velocity signal, a velocity signal, an acceleration signal, a gravity sensing signal, a face recognition signal, an image acquisition signal and a vehicle distance detection signal, the preset driving event comprises at least one of sharp turning, sharp acceleration, sharp deceleration, overspeed, fatigue driving, bumping, overturning, ascending and descending, and small vehicle distance, wherein, whether sharp turning occurs or not can be judged according to the angular velocity signal, whether overspeed occurs or not can be judged by combining the velocity signal and the speed limit value of image acquisition, can judge whether rapid acceleration and rapid deceleration occur according to the acceleration signal, can judge whether fatigue driving occurs according to the face identification signal, whether bumping, overturning, ascending and descending can be judged according to the corresponding change rule of the gravity sensing signal, whether the vehicle distance is small can be judged according to the vehicle distance detection signal, and the vehicle distance detection signal can be generated according to an image recognition signal or a radar signal.
If the vehicle-mounted end judges that the preset driving event occurs according to the state data of the vehicle, the vehicle-mounted end sends driving event monitoring data to the cloud server, the driving event monitoring data comprise the occurred preset driving event and corresponding event information, and the event information comprises the occurrence place and the occurrence time of the preset driving event.
And step 120, accumulating the occurrence frequency of each preset driving event according to the received driving event monitoring data.
Before the journey is finished, the cloud server accumulates the occurrence frequency of each preset driving event according to the received driving event monitoring data, namely, the cloud server accumulates the occurrence frequency of the corresponding preset driving event according to the driving event monitoring data every time the cloud server receives the driving event monitoring data, and for the preset driving events which do not occur all the time, the accumulation frequency is 0, for example, over speed is 1, sharp turn is 3, overturn is 0, and the like.
And step 130, after the journey is finished, scoring the driving behavior corresponding to the journey according to the accumulated result and the weight corresponding to each preset driving event.
After the end of the travel is judged, the cloud server scores the driving behaviors corresponding to the travel according to the accumulated result of each preset driving event and the weight corresponding to each preset driving event, and the score of the driving behavior corresponding to the travel is obtained.
In this embodiment, scoring the driving behavior corresponding to the trip according to the accumulated result and the weight corresponding to each preset driving event includes:
normalizing the accumulated result according to the number value range corresponding to each preset driving event;
and scoring the driving behavior corresponding to the travel according to the result of the normalization processing and the weight corresponding to each preset driving event.
The cloud server normalizes the times of each preset driving event according to a time value range corresponding to each preset driving event, for example, 100 kilometers allow overspeed for at most 20 times, the corresponding time value range is [0,20], the current trip is 10 kilometers in total and overspeed for 1 time, actually, 10 times of overspeed is needed relative to 100 kilometers, then normalization is carried out in the range to be 10-0/20-0-0.5, other preset driving events are normalized according to the method to obtain a certain value Si of [0,1], and finally, a total score value sigma AiSi is calculated according to a weight Ai corresponding to each preset driving event.
In practical implementation, the weight of each preset driving event is determined according to the influence degree of different preset driving events on driving safety, for example, the weight of overturning is far greater than the weight of ascending and descending slopes, so that the corresponding relation between the score and the driving quality can be more accurately reflected by the scoring result.
In one embodiment, after the step 130 of scoring the driving behavior corresponding to the trip according to the accumulated result and the weight corresponding to each preset driving event, the method further includes:
generating an analysis report of the driving behavior corresponding to the journey according to the grading result, wherein the analysis report comprises the accumulated occurrence times of all the preset driving events, the occurrence place and the occurrence time of the occurred preset driving events;
and sending the analysis report to the vehicle-mounted end so that the vehicle-mounted end displays the analysis report according to a preset mode.
After the cloud server calculates the scoring result, an analysis report of the driving behavior corresponding to the travel is generated according to the scoring result, the analysis report comprises the accumulated occurrence times of all the preset driving events, the occurrence places and the occurrence times of the occurred preset driving events, and the analysis report is sent to the vehicle-mounted terminal. After receiving the analysis report, the vehicle-mounted terminal displays the analysis report according to a preset mode, wherein the preset mode comprises at least one of a table, a graph and a map, for example, the accumulated occurrence frequency of each preset driving event is displayed in the table and the graph, the track of the current trip is displayed in the form of the map, and the icon, the occurrence place and the occurrence time of the occurred preset driving event are marked in the track, so that the display mode of the analysis report is more visual.
During actual implementation, the cloud server evaluates and analyzes the driving behavior in a preset period according to a rating result in the preset period, wherein the preset period is, for example, one week or one month, and then sends a driving prompt to the vehicle-mounted terminal according to the evaluation result, for example, the vehicle-mounted terminal is prompted to frequently overspeed and low rating in the week, and the driving habit is carefully adjusted.
In one embodiment, the method for scoring driving behavior of the present application further includes:
when a navigation start signal is received, determining the start of a journey;
and when a navigation ending signal is received, determining the end of the travel according to the track point information sent by the vehicle-mounted end.
The cloud server judges the start and stop of a section of travel according to track points uploaded by the vehicle-mounted end in real time and navigation start and end marks. During actual implementation, the vehicle-mounted end sends a navigation starting signal to the cloud server when the navigation is started, and uploads the real-time track point of the vehicle to the cloud server, when the navigation is finished, the vehicle-mounted end sends a navigation finishing signal to the cloud server, and after the cloud server receives the navigation finishing signal, if the real-time track point of the vehicle does not continuously change, the travel is determined to be finished.
According to the method for scoring the driving behaviors, the cloud server receives the driving event monitoring data sent by the vehicle-mounted end after a journey is started, the driving event monitoring data comprise occurring preset driving events and corresponding event information, the occurrence times of the preset driving events are accumulated according to the received driving event monitoring data before the journey is finished, and the driving behaviors corresponding to the journey are scored according to the accumulated results and the weight corresponding to the preset driving events after the journey is finished. Through the mode, the driving behavior of the user at this time can be scored, and the driving level and the safe driving consciousness of a driver can be improved.
The application also provides a cloud server, which comprises a memory and a processor, wherein the memory stores at least one program instruction, and the processor loads and executes the at least one program instruction to realize the scoring method applied to the driving behavior of the cloud server.
FIG. 2 is a flow chart illustrating a method of scoring driving behavior according to another exemplary embodiment. Referring to fig. 2, the scoring method for driving behavior of the present embodiment is applied to a vehicle-mounted terminal, and includes:
And step 220, judging whether the vehicle has a preset driving event according to the acquired state data.
When a user starts navigation by using the vehicle-mounted end, the vehicle-mounted end judges that a travel starts, further starts to acquire the state data of the vehicle, and judges whether a preset driving event occurs to the vehicle according to the acquired state data. During actual implementation, after the vehicle-mounted end acquires the state data, whether the state data meets the occurrence condition of the preset driving event is judged according to the judgment rule corresponding to the type of the state data, and if the state data meets the occurrence condition of the preset driving event, the occurring preset driving event is determined.
The state data of the vehicle comprises at least one of an angular velocity signal, a velocity signal, an acceleration signal, a gravity sensing signal, a face recognition signal, an image acquisition signal and a vehicle distance detection signal, the preset driving event comprises at least one of sharp turning, sharp acceleration, sharp deceleration, overspeed, fatigue driving, bumping, overturning, ascending and descending, and small vehicle distance, wherein, whether sharp turning occurs or not can be judged according to the angular velocity signal, whether overspeed occurs or not can be judged by combining the velocity signal and the speed limit value of image acquisition, can judge whether rapid acceleration and rapid deceleration occur according to the acceleration signal, can judge whether fatigue driving occurs according to the face identification signal, whether bumping, overturning, ascending and descending can be judged according to the corresponding change rule of the gravity sensing signal, whether the vehicle distance is small can be judged according to the vehicle distance detection signal, and the vehicle distance detection signal can be generated according to an image recognition signal or a radar signal.
If the vehicle-mounted end judges that the preset driving event occurs according to the state data of the vehicle, the vehicle-mounted end sends driving event monitoring data to the cloud server, the driving event monitoring data comprise the occurred preset driving event and corresponding event information, and the event information comprises the occurrence place and the occurrence time of the preset driving event.
Before the travel is finished, the cloud server accumulates the occurrence frequency of each preset driving event according to the received driving event monitoring data, that is, the cloud server accumulates the occurrence frequency of the corresponding preset driving event according to the driving event monitoring data every time the cloud server receives the driving event monitoring data, and for the preset driving event which does not occur all the time, the accumulation frequency is 0, for example, 1 overspeed, 3 sharp turns, 0 overturn and the like.
After the journey is finished, the cloud server scores the driving behaviors corresponding to the journey according to the accumulated result of each preset driving event and the weight corresponding to each preset driving event, and the score of the driving behavior corresponding to the journey is obtained.
And during evaluation, the cloud server normalizes the accumulated result according to the frequency value range corresponding to each preset driving event, and evaluates the driving behavior corresponding to the travel according to the normalized result and the weight corresponding to each preset driving event. For example, 100 kilometers allow 20 speeding at most, the corresponding number value range is [0,20], the current trip is 10 kilometers in total and speeding 1 time, actually, the trip should be speeding 10 times relative to 100 kilometers, then normalization is performed in the range to be 10-0/20-0-0.5, other preset driving events are normalized according to the method, a certain value Si of [0,1] is obtained respectively, and finally, the total score value is calculated to be Σ AiSi according to the weight Ai corresponding to each preset driving event.
In practical implementation, the weight of each preset driving event is determined according to the influence degree of different preset driving events on driving safety, for example, the weight of overturning is far greater than the weight of ascending and descending slopes, so that the corresponding relation between the score and the driving quality can be more accurately reflected by the scoring result.
In one embodiment, the method for scoring driving behavior of the present application further includes:
when a navigation start signal is received, determining the start of a journey;
sending a navigation starting signal to a cloud server and uploading track point information of the vehicle in real time;
and when the navigation ending signal is received, the navigation ending signal is sent to the cloud server, so that the cloud server determines the end of the travel according to the track point information of the vehicle.
The cloud server judges the start and stop of a section of travel according to track points uploaded by the vehicle-mounted end in real time and navigation start and end marks. During actual implementation, the vehicle-mounted end sends a navigation starting signal to the cloud server when the navigation is started, and uploads the real-time track point of the vehicle to the cloud server, when the navigation is finished, the vehicle-mounted end sends a navigation finishing signal to the cloud server, and after the cloud server receives the navigation finishing signal, if the real-time track point of the vehicle does not continuously change, the travel is determined to be finished.
In one embodiment, the method for scoring driving behavior of the present application further includes:
receiving an analysis report of driving behaviors corresponding to a journey, which is sent by a cloud server, wherein the analysis report comprises the accumulated occurrence frequency of each preset driving event, the occurrence place and the occurrence time of the occurred preset driving event;
and displaying the analysis report according to a preset mode.
After the cloud server calculates the scoring result, an analysis report of the driving behavior corresponding to the travel is generated according to the scoring result, the analysis report comprises the accumulated occurrence times of all the preset driving events, the occurrence places and the occurrence times of the occurred preset driving events, and the analysis report is sent to the vehicle-mounted terminal. After receiving the analysis report, the vehicle-mounted terminal displays the analysis report according to a preset mode, wherein the preset mode comprises at least one of a table, a graph and a map, for example, the accumulated occurrence frequency of each preset driving event is displayed in the table and the graph, the track of the current trip is displayed in the form of the map, and the icon, the occurrence place and the occurrence time of the occurred preset driving event are marked in the track, so that the display mode of the analysis report is more visual.
During actual implementation, the cloud server further evaluates and analyzes the driving behavior in the preset period according to the evaluation result in the preset period, wherein the preset period is, for example, one week or one month, and then sends corresponding driving reminders to the vehicle-mounted terminal according to the evaluation result, for example, the vehicle-mounted terminal is reminded that the current week has frequent overspeed and low evaluation, and the driving habit is carefully adjusted.
According to the scoring method of the driving behaviors, after a journey is started, a vehicle-mounted end acquires state data of a vehicle, whether a preset driving event occurs in the vehicle is judged according to the acquired state data, if the preset driving event occurs, driving event monitoring data are sent to a cloud server, so that the cloud server accumulates the occurrence frequency of each preset driving event according to the received driving event monitoring data, and after the journey is ended, the cloud server scores the driving behaviors corresponding to the journey according to the accumulation result and the weight corresponding to each preset driving event, and the driving event monitoring data comprise the occurred preset driving event and corresponding event information. Through the mode, the driving behavior of the user at this time can be scored, and the driving level and the safe driving consciousness of a driver can be improved.
The application also provides a vehicle-mounted terminal, which comprises a memory and a processor, wherein the memory stores at least one program instruction, and the processor loads and executes the at least one program instruction to realize the scoring method applied to the driving behavior of the vehicle-mounted terminal.
Fig. 3 is a schematic structural diagram illustrating a system for scoring driving behavior according to an exemplary embodiment. Referring to fig. 3, the driving behavior scoring system of the present embodiment includes a cloud server 310 and a vehicle-mounted terminal 320.
The specific steps of the cloud server 310 and the vehicle-mounted terminal 320 for implementing the driving behavior scoring are described with reference to the embodiments shown in fig. 1 and fig. 2, and are not repeated herein.
The application discloses driving behavior's system of grading, after the journey begins, on-vehicle end judges whether the vehicle takes place to predetermine the driving event according to the state data of vehicle, and send driving event monitoring data to the high in the clouds server when taking place to predetermine the driving event, driving event monitoring data is including the predetermined driving event and the event information that corresponds of taking place, the high in the clouds server is according to the number of times of occurrence of each predetermined driving event of the driving event monitoring data accumulation of receipt, after the journey ends, the high in the clouds server is according to the weight that the result of accumulation and each predetermined driving event correspond to the driving behavior of journey grading. Through the mode, the driving behavior of the user at this time can be scored, and the driving level and the safe driving consciousness of a driver can be improved.
Although the present application has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the application, and all changes, substitutions and alterations that fall within the spirit and scope of the application are to be understood as being included within the following description of the preferred embodiment.
Claims (10)
1. A scoring method of driving behaviors is applied to a cloud server and is characterized by comprising the following steps:
after a journey starts, receiving driving event monitoring data sent by a vehicle-mounted end, wherein the driving event monitoring data comprises a preset driving event and corresponding event information;
accumulating the occurrence frequency of each preset driving event according to the received driving event monitoring data;
and after the journey is finished, scoring the driving behavior corresponding to the journey according to an accumulated result and the weight corresponding to each preset driving event.
2. The method for scoring the driving behavior according to claim 1, wherein scoring the driving behavior corresponding to the trip according to the accumulated result and the weight corresponding to each preset driving event comprises:
normalizing the accumulated result according to the number value range corresponding to each preset driving event;
and scoring the driving behavior corresponding to the travel according to the result of the normalization processing and the weight corresponding to each preset driving event.
3. The method for scoring the driving behavior according to claim 1, wherein after scoring the driving behavior corresponding to the trip according to the accumulated result and the weight corresponding to each preset driving event, the method further comprises:
generating an analysis report of the driving behavior corresponding to the journey according to the grading result, wherein the analysis report comprises the accumulated occurrence frequency of each preset driving event, the occurrence place and the occurrence time of the occurred preset driving event;
and sending the analysis report to the vehicle-mounted end so that the vehicle-mounted end displays the analysis report according to a preset mode.
4. A scoring method for driving behavior according to claim 1, characterized in that the method further comprises:
determining the start of the journey when a navigation start signal is received;
and when a navigation ending signal is received, the travel ending is determined according to the track point information sent by the vehicle-mounted end.
5. Cloud server, characterized in that it comprises a memory and a processor, the memory stores at least one program instruction, and the processor implements the scoring method for driving behavior according to any one of claims 1 to 4 by loading and executing the at least one program instruction.
6. A scoring method of driving behaviors is applied to a vehicle-mounted terminal and is characterized by comprising the following steps:
acquiring state data of the vehicle after the journey is started;
judging whether a preset driving event occurs to the vehicle according to the acquired state data;
if a preset driving event occurs, sending driving event monitoring data to a cloud server so that the cloud server accumulates the occurrence frequency of each preset driving event according to the received driving event monitoring data, and after the journey is finished, scoring the driving behavior corresponding to the journey according to an accumulated result and the weight corresponding to each preset driving event, wherein the driving event monitoring data comprises the occurred preset driving event and corresponding event information.
7. The method of scoring driving behavior of claim 6, further comprising:
determining the start of the journey when a navigation start signal is received;
sending the navigation starting signal to the cloud server and uploading track point information of the vehicle in real time;
and when a navigation ending signal is received, sending the navigation ending signal to the cloud server so that the cloud server determines the end of the travel according to the track point information of the vehicle.
8. The method of scoring driving behavior of claim 6, further comprising:
receiving an analysis report of the driving behavior corresponding to the journey, which is sent by the cloud server, wherein the analysis report comprises the accumulated occurrence frequency of each preset driving event, the occurrence place and the occurrence time of the occurred preset driving event;
and displaying the analysis report according to a preset mode.
9. An on-board terminal, characterized by comprising a memory and a processor, wherein the memory stores at least one program instruction, and the processor implements the scoring method for driving behavior according to any one of claims 6 to 8 by loading and executing the at least one program instruction.
10. A scoring system for driving behavior, comprising the cloud server of claim 5 and the vehicle-mounted terminal of claim 9.
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