CN116757427A - Method and device for relieving endurance anxiety, medium and electronic equipment - Google Patents
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Abstract
The application provides a method, a device, a medium and electronic equipment for relieving endurance anxiety. The application obtains a plurality of anxiety factors of respective users of a plurality of vehicles in a preset area, further determines the anxiety level of the corresponding user through the plurality of anxiety factors of each user, and then generates a relief scheme of the corresponding user based on the anxiety level of each user and at least one rescue factor of the plurality of anxiety factors of the corresponding user. The uncertainty caused by the fact that the anxiety grades are divided by the single anxiety factors is avoided, the anxiety grades are comprehensively judged through the plurality of anxiety factors, and the reliability and the accuracy of anxiety grade division are improved. The anxiety grades are finely divided, a customized relieving scheme is provided for users with different anxiety grades, vehicles are prevented from blindly entering a charging pile service area, charging queuing is carried out, and endurance anxiety is increased, so that reasonable charging of the vehicles is effectively dredged.
Description
Technical Field
The application relates to the technical field of intelligent charging, in particular to a method and a device for relieving endurance anxiety, a medium and electronic equipment.
Background
Currently, the pure electric vehicle users commonly have endurance anxiety, especially long-distance travel. It is not known whether the front can be charged normally all the time. When the queuing charge time is too long, the user either waits in the emergency or decides on the next unknown charging station, further exacerbating the user anxiety.
Therefore, the application provides a method for relieving endurance anxiety, so as to solve the technical problems.
Disclosure of Invention
The application aims to provide a method, a device, a medium and electronic equipment for relieving endurance anxiety, which can solve at least one technical problem. The specific scheme is as follows:
according to a first aspect of the present application, there is provided a method for alleviating endurance anxiety, comprising:
acquiring a plurality of anxiety factors of respective users of a plurality of vehicles in a preset area;
determining anxiety levels for each user based on the plurality of anxiety factors for the corresponding user;
an mitigation regimen for each user is generated based on the anxiety level of the corresponding user and at least one rescue factor of the plurality of anxiety factors for the corresponding user.
Optionally, the determining the anxiety level of each user based on the plurality of anxiety factors of the corresponding user includes:
determining the respective interference types of all anxiety factors of each user;
performing binning treatment on all anxiety factors of all users according to types, and determining a plurality of bins of each anxiety factor;
obtaining characteristic values of related anxiety factors in each sub-box based on respective interference types of all anxiety factors in each sub-box;
calculating the sum of the characteristic values of all the sub-boxes of each anxiety factor, and obtaining the total characteristic value of the corresponding anxiety factor;
a respective anxiety level for each user is determined based on the respective total characteristic values of all anxiety factors and the respective interference types of the plurality of anxiety factors for each user.
Optionally, the interference type includes an interference type and a non-interference type;
accordingly, the characteristic value of the relevant anxiety factors in each sub-box is obtained based on the respective interference types of all the anxiety factors in each sub-box, and the characteristic value comprises the following formula:
TZ i ＝(γ pi -γ ni )×Q i ；
wherein TZ is i Characteristic value of any anxiety factor, gamma, in the ith bin representing the anxiety factor pi Representing the ratio of the number of anxiety factors with non-interference in the ith bin to the number of all anxiety factors in said bin, gamma ni Representing the ratio of the number of anxiety factors with interference in the ith bin to the number of all anxiety factors in the bin, Q i And the weight value of the focus factor in the ith bin is represented.
Optionally, obtaining the weight value of the anxiety factor in the ith bin of any anxiety factor includes the following formula:
wherein Q is i The weight value of the anxiety factor in the ith bin of any of the anxiety factors.
Optionally, the determining the respective anxiety level of each user based on the respective total feature values of all anxiety factors and the respective interference types of the plurality of anxiety factors of each user includes:
screening the total characteristic values of all anxiety factors to determine a plurality of qualified characteristic values;
and combining the interference types of the anxiety factors of each user with the qualified characteristic values, and respectively applying the interference types to a logistic regression model by taking the user as a unit to determine the anxiety level of each user.
Optionally, the screening the total characteristic values of all anxiety factors to determine a plurality of qualified characteristic values includes:
and when the total characteristic value of each anxiety factor is larger than a preset screening threshold value, determining the total characteristic value of the corresponding anxiety factor as a qualified characteristic value.
Optionally, the plurality of anxiety factors includes: average charge number in unit mileage, start electric quantity of each charge, end electric quantity of each charge, driving mileage of each charge, limit charge number, limit discharge number, remaining mileage of electric quantity support, number of available nearby charging piles and distance of each nearby charging pile;
the rescue factor includes: remaining mileage of charge support, number of nearby available charging posts, and distance of each nearby charging post.
According to a second aspect of the present application, there is provided a device for alleviating endurance anxiety, comprising:
the information acquisition unit is used for acquiring various anxiety factors of respective users of the vehicles in the preset area;
a level determining unit for determining anxiety levels of the corresponding users based on a plurality of anxiety factors of each user;
and a plan generating unit for generating a relief plan for the corresponding user based on the anxiety level of each user and at least one rescue factor of the plurality of anxiety factors of the corresponding user.
Optionally, the determining the anxiety level of each user based on the plurality of anxiety factors of the corresponding user includes:
determining the respective interference types of all anxiety factors of each user;
performing binning treatment on all anxiety factors of all users according to types, and determining a plurality of bins of each anxiety factor;
obtaining characteristic values of related anxiety factors in each sub-box based on respective interference types of all anxiety factors in each sub-box;
calculating the sum of the characteristic values of all the sub-boxes of each anxiety factor, and obtaining the total characteristic value of the corresponding anxiety factor;
a respective anxiety level for each user is determined based on the respective total characteristic values of all anxiety factors and the respective interference types of the plurality of anxiety factors for each user.
Optionally, the interference type includes an interference type and a non-interference type;
accordingly, the characteristic value of the relevant anxiety factors in each sub-box is obtained based on the respective interference types of all the anxiety factors in each sub-box, and the characteristic value comprises the following formula:
TZ i ＝(γ pi -γ ni )×Q i ；
wherein TZ is i Characteristic value of any anxiety factor, gamma, in the ith bin representing the anxiety factor pi Representing the ratio of the number of anxiety factors with non-interference in the ith bin to the number of all anxiety factors in said bin, gamma ni Representing the ratio of the number of anxiety factors with interference in the ith bin to the number of all anxiety factors in the bin, Q i And the weight value of the focus factor in the ith bin is represented.
Optionally, obtaining the weight value of the anxiety factor in the ith bin of any anxiety factor includes the following formula:
wherein Q is i The weight value of the anxiety factor in the ith bin of any of the anxiety factors.
Optionally, the determining the respective anxiety level of each user based on the respective total feature values of all anxiety factors and the respective interference types of the plurality of anxiety factors of each user includes:
screening the total characteristic values of all anxiety factors to determine a plurality of qualified characteristic values;
and combining the interference types of the anxiety factors of each user with the qualified characteristic values, and respectively applying the interference types to a logistic regression model by taking the user as a unit to determine the anxiety level of each user.
Optionally, the screening the total characteristic values of all anxiety factors to determine a plurality of qualified characteristic values includes:
and when the total characteristic value of each anxiety factor is larger than a preset screening threshold value, determining the total characteristic value of the corresponding anxiety factor as a qualified characteristic value.
Optionally, the plurality of anxiety factors includes: average charge number in unit mileage, start electric quantity of each charge, end electric quantity of each charge, driving mileage of each charge, limit charge number, limit discharge number, remaining mileage of electric quantity support, number of available nearby charging piles and distance of each nearby charging pile;
the rescue factor includes: remaining mileage of charge support, number of nearby available charging posts, and distance of each nearby charging post.
According to a third aspect of the present application, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of alleviating endurance anxiety as set forth in any one of the above.
According to a fourth aspect of the present application, there is provided an electronic device comprising: one or more processors; and a storage means for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the method of alleviating endurance anxiety as claimed in any one of the preceding claims.
Compared with the prior art, the scheme provided by the embodiment of the application has at least the following beneficial effects:
the application provides a method, a device, a medium and electronic equipment for relieving endurance anxiety. The application obtains a plurality of anxiety factors of respective users of a plurality of vehicles in a preset area, further determines the anxiety level of the corresponding user through the plurality of anxiety factors of each user, and then generates a relief scheme of the corresponding user based on the anxiety level of each user and at least one rescue factor of the plurality of anxiety factors of the corresponding user. The uncertainty caused by the fact that the anxiety grades are divided by the single anxiety factors is avoided, the anxiety grades are comprehensively judged through the plurality of anxiety factors, and the reliability and the accuracy of anxiety grade division are improved. The anxiety grades are finely divided, a customized relieving scheme is provided for users with different anxiety grades, vehicles are prevented from blindly entering a charging pile service area, charging queuing is carried out, and endurance anxiety is increased, so that reasonable charging of the vehicles is effectively dredged.
Drawings
FIG. 1 illustrates a flow chart of a method of alleviating endurance anxiety according to an embodiment of the present application;
fig. 2 shows a block diagram of a unit of a device for alleviating endurance anxiety according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail below with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The terminology used in the embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application 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 "plurality" generally includes at least two.
It should be understood that the term "and/or" as used herein is merely one relationship describing the association of the associated objects, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
It should be understood that although the terms first, second, third, etc. may be used in embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish one from another. For example, a first may also be referred to as a second, and similarly, a second may also be referred to as a first, without departing from the scope of embodiments of the application.
The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrase "if determined" or "if detected (stated condition or event)" may be interpreted as "when determined" or "in response to determination" or "when detected (stated condition or event)" or "in response to detection (stated condition or event), depending on the context.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a product or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such product or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a commodity or device comprising such element.
In particular, the symbols and/or numerals present in the description, if not marked in the description of the figures, are not numbered.
Alternative embodiments of the present application will be described in detail below with reference to the accompanying drawings.
The embodiment provided by the application is an embodiment of a method for relieving endurance anxiety.
An embodiment of the present application will be described in detail with reference to fig. 1.
Step S101, obtaining a plurality of anxiety factors of respective users of a plurality of vehicles in a preset area.
In the embodiment of the application, the vehicle is a new energy vehicle. The new energy vehicle remote monitoring platform is communicated with the vehicle through a wireless network communication technology, and electricity utilization and charging data of the vehicle are recorded in real time.
According to the embodiment of the application, all vehicles and all charging piles in the preset area are taken as analysis objects, so that the problem of endurance anxiety of the vehicles in the preset area is solved.
Anxiety factor refers to statistics of electricity and charge for a vehicle and information of nearby assistance devices that cause anxiety to the user.
According to the embodiment of the application, through carrying out cluster analysis on the electricity utilization information and the charging information of the user vehicle, various anxiety factors representing mileage anxiety are extracted.
In some embodiments, the plurality of anxiety factors includes: average number of charges per unit mileage, starting power per charge, ending power per charge, driving mileage per charge, limit number of charges, limit number of discharges, remaining mileage supported by power, number of available nearby charging posts, and distance of each nearby charging post.
The rescue factor includes: remaining mileage of charge support, number of nearby available charging posts, and distance of each nearby charging post.
The detailed data of electricity consumption and charging of each vehicle is counted so as to carry out detailed analysis on each vehicle, determine the respective anxiety level of each vehicle and provide a targeted relief scheme.
Step S102, determining anxiety grades of the corresponding users based on various anxiety factors of each user.
The present examples divide anxiety grades into five anxiety grades: severe anxiety grades, moderate anxiety grades, general anxiety grades, mild anxiety grades, and anxiolytic grades.
In some embodiments, the determining the anxiety level of each user based on the plurality of anxiety factors of the corresponding user includes the steps of:
step S102-1, determining the respective interference types of all anxiety factors of each user.
In this particular embodiment, each user has a plurality of anxiety factors, and any of the anxiety factors of each user has a disturbance type. For example, a Kernel K-means clustering method of Gauss Kernel functions is adopted to respectively transform all anxiety factors of each user, and the interference type of each anxiety factor of each user is separated.
Step S102-2, all anxiety factors of all users are classified into boxes according to types, and a plurality of boxes of each anxiety factor are determined.
The binning, also known as discretization, is the conversion of a numerical value into a discrete value. For example, the average number of charges per unit mileage is divided into three bins: sub-box for 2 times or less, sub-box for 2 times to 5 times or more, sub-box for 5 times or more; if 20 vehicles exist, the average charging times in the unit mileage of 6 vehicles are included in the sub-tank of less than 2 times, the average charging times in the unit mileage of 10 vehicles are included in the sub-tank of 2 times to 5 times, and the average charging times in the unit mileage of 4 vehicles are included in the sub-tank of more than 5 times.
The method comprises the steps of carrying out box division processing on all anxiety factors of all users according to types, and determining a plurality of boxes of each anxiety factor, wherein after the box division processing, only one anxiety factor is in each box, and the plurality of boxes comprise the same anxiety factor; all anxiety factors for all users are assigned to one bin.
And step S102-3, obtaining characteristic values of the related anxiety factors in the corresponding sub-boxes based on the respective interference types of all the anxiety factors in each sub-box.
According to the embodiment, all anxiety factors of all users are distributed to all the sub-boxes through the sub-box processing, and the characteristic values of the related anxiety factors are extracted through all the sub-boxes, so that the data processing capacity is reduced, and the data processing efficiency is improved.
In some embodiments, the interference types include interference types and non-interference types.
The interference type refers to the influence of corresponding anxiety factors on mileage anxiety.
The non-interference type means that the corresponding anxiety factors have little influence on mileage anxiety.
Accordingly, the characteristic value of the relevant anxiety factors in each sub-box is obtained based on the respective interference types of all the anxiety factors in each sub-box, and the characteristic value comprises the following formula:
TZ i ＝(γ pi -γ ni )×Q i ；
wherein TZ is i Characteristic value of any anxiety factor, gamma, in the ith bin representing the anxiety factor pi Representing the ratio of the number of anxiety factors with non-interference in the ith bin to the number of all anxiety factors in said bin, gamma ni Representing the ratio of the number of anxiety factors with interference in the ith bin to the number of all anxiety factors in the bin, Q i And the weight value of the focus factor in the ith bin is represented.
In this embodiment, the characteristic value of the anxiety factor in each bin is the influence probability of the anxiety factor in the corresponding bin on mileage anxiety.
And a characteristic value representing predictive ability of the anxiety factor. The larger the value of the feature value is in the range of 0,1, the better the predictive power is indicated.
For example, for a bin of average charge times in unit mileage, the 2 nd bin of average charge times in unit mileage includes average charge times in unit mileage of 10 vehicles, wherein there are average charge times in 6 unit mileage with interference type, and average charge times in 4 unit mileage with non-interference type, then γ ni ＝6/10＝60％，γ pi =4/10=40%; if Q i = -0.405, then TZ i ＝(40％-60％)×(-0.405)＝0.081。
In some embodiments, obtaining the weight value of the anxiety factor in the ith bin of any one of the anxiety factors comprises the following formula:
wherein Q is i The weight value of the anxiety factor in the ith bin of any of the anxiety factors.
For example, continuing with the above example, Q i ＝ln(40％/60％)＝-0.405。
And step S102-4, calculating the sum of the characteristic values of all the sub-boxes of each anxiety factor and the respective associated anxiety factors to obtain the total characteristic value of the corresponding anxiety factor.
It is understood that the total characteristic value of each anxiety factor is equal to the sum of the characteristic values of the anxiety factors in all bins of the corresponding anxiety factor.
Step S102-5, determining the anxiety level of each user based on the total characteristic value of each anxiety factor and the interference type of each user.
In some specific embodiments, the determining the anxiety level of each user based on the total feature value of each anxiety factor and the interference type of each user, comprises the following steps:
and step S102-5-1, screening the total characteristic values of all anxiety factors, and determining a plurality of qualified characteristic values.
In this embodiment, the total feature value with small influence on mileage anxiety is screened out, and the total feature value with large influence on mileage anxiety is retained as a qualified feature value, so as to improve accuracy of anxiety classification.
Specifically, the screening of the total characteristic values of all anxiety factors to determine a plurality of qualified characteristic values includes the following steps:
and step S102-5-1a, when the total characteristic value of each anxiety factor is larger than a preset screening threshold value, determining the total characteristic value of the corresponding anxiety factor as a qualified characteristic value.
Since the range of the total characteristic value is [0,1], if the total characteristic value of the anxiety factor is too small, the influence probability of the anxiety factor on mileage anxiety is smaller, and therefore the total characteristic value of the anxiety factor is eliminated.
For example, a screening threshold value of 0.1 is preset, the total characteristic values smaller than or equal to 0.1 are removed, and the total characteristic values larger than 0.1 are reserved and used as qualified characteristic values.
And step S102-5-2, combining the interference types of the anxiety factors of each user with the qualified characteristic values, and respectively applying the interference types to a logistic regression model by taking the user as a unit to determine the anxiety level of each user.
The logistic regression model is a classification model in machine learning, has the advantages of simplicity and high efficiency of an algorithm, and can determine the anxiety level of each user based on various anxiety factors of the respective users of a plurality of vehicles in a preset area, so that a rapid and high-efficiency relieving scheme is provided. The quick response to endurance anxiety is ensured.
Step S103, generating a relief scheme for the corresponding user based on the anxiety level of each user and the relief factors among the plurality of anxiety factors of the corresponding user.
In the above specific embodiment, the rescue factors among the plurality of anxiety factors include: remaining mileage of charge support, number of nearby available charging posts, and distance of each nearby charging post.
In the embodiment of the application, a customized mitigation scheme is provided according to the anxiety level of the user in combination with the remaining mileage supported by the electric quantity, the number of nearby available charging posts and the distance of each nearby charging post. For example, for a user of a severe anxiety class, when the electric quantity of the vehicle is less than 40%, the remaining mileage of the electric quantity support can reach a nearby charging post, and the charging post can be charged, a relief scheme is provided to the user through the mobile phone app so that the user can charge for rest; when the electric quantity is lower than 30%, the remaining mileage supported by the electric quantity can reach a nearby charging pile, and the charging pile can be charged, a relief scheme is provided for a user through a vehicle machine; when the electric quantity is lower than 20%, reminding a user to switch the energy-saving mode through the vehicle and the machine, and navigating to the nearest charging pile.
The embodiment of the application obtains a plurality of anxiety factors of respective users of a plurality of vehicles in a preset area, further determines the anxiety level of the corresponding user through the plurality of anxiety factors of each user, and then generates a relief scheme of the corresponding user based on the anxiety level of each user and at least one rescue factor of the plurality of anxiety factors of the corresponding user. The uncertainty caused by the fact that the anxiety grades are divided by the single anxiety factors is avoided, the anxiety grades are comprehensively judged through the plurality of anxiety factors, and the reliability and the accuracy of anxiety grade division are improved. The anxiety grades are finely divided, a customized relieving scheme is provided for users with different anxiety grades, vehicles are prevented from blindly entering a charging pile service area, charging queuing is carried out, and endurance anxiety is increased, so that reasonable charging of the vehicles is effectively dredged.
The present application also provides an embodiment of the device adapted to the above embodiment, which is used to implement the method steps described in the above embodiment, and the explanation based on the meaning of the same names is the same as that of the above embodiment, and has the same technical effects as those of the above embodiment, and is not repeated herein.
As shown in fig. 2, the present application provides a device 200 for alleviating endurance anxiety, comprising:
an information acquisition unit 201 for acquiring a plurality of anxiety factors of respective users of a plurality of vehicles within a preset area;
a level determination unit 202 for determining an anxiety level of each user based on a plurality of anxiety factors of the corresponding user;
a scenario generation unit 203 for generating a mitigation scenario for the corresponding user based on the anxiety level of each user and at least one rescue factor of the plurality of anxiety factors for the corresponding user.
Optionally, the determining the anxiety level of each user based on the plurality of anxiety factors of the corresponding user includes:
determining the respective interference types of all anxiety factors of each user;
performing binning treatment on all anxiety factors of all users according to types, and determining a plurality of bins of each anxiety factor;
obtaining characteristic values of related anxiety factors in each sub-box based on respective interference types of all anxiety factors in each sub-box;
calculating the sum of the characteristic values of all the sub-boxes of each anxiety factor, and obtaining the total characteristic value of the corresponding anxiety factor;
a respective anxiety level for each user is determined based on the respective total characteristic values of all anxiety factors and the respective interference types of the plurality of anxiety factors for each user.
Optionally, the interference type includes an interference type and a non-interference type;
accordingly, the characteristic value of the relevant anxiety factors in each sub-box is obtained based on the respective interference types of all the anxiety factors in each sub-box, and the characteristic value comprises the following formula:
TZ i ＝(γ pi -γ ni )×Q i ；
wherein TZ is i Characteristic value of any anxiety factor, gamma, in the ith bin representing the anxiety factor pi Representing the ratio of the number of anxiety factors with non-interference in the ith bin to the number of all anxiety factors in said bin, gamma ni Representing the ratio of the number of anxiety factors with interference in the ith bin to the number of all anxiety factors in the bin, Q i And the weight value of the focus factor in the ith bin is represented.
Optionally, obtaining the weight value of the anxiety factor in the ith bin of any anxiety factor includes the following formula:
wherein Q is i The weight value of the anxiety factor in the ith bin of any of the anxiety factors.
Optionally, the determining the respective anxiety level of each user based on the respective total feature values of all anxiety factors and the respective interference types of the plurality of anxiety factors of each user includes:
screening the total characteristic values of all anxiety factors to determine a plurality of qualified characteristic values;
and combining the interference types of the anxiety factors of each user with the qualified characteristic values, and respectively applying the interference types to a logistic regression model by taking the user as a unit to determine the anxiety level of each user.
Optionally, the screening the total characteristic values of all anxiety factors to determine a plurality of qualified characteristic values includes:
and when the total characteristic value of each anxiety factor is larger than a preset screening threshold value, determining the total characteristic value of the corresponding anxiety factor as a qualified characteristic value.
Optionally, the plurality of anxiety factors includes: average charge number in unit mileage, start electric quantity of each charge, end electric quantity of each charge, driving mileage of each charge, limit charge number, limit discharge number, remaining mileage of electric quantity support, number of available nearby charging piles and distance of each nearby charging pile;
the rescue factor includes: remaining mileage of charge support, number of nearby available charging posts, and distance of each nearby charging post.
The embodiment of the application obtains a plurality of anxiety factors of respective users of a plurality of vehicles in a preset area, further determines the anxiety level of the corresponding user through the plurality of anxiety factors of each user, and then generates a relief scheme of the corresponding user based on the anxiety level of each user and at least one rescue factor of the plurality of anxiety factors of the corresponding user. The uncertainty caused by the fact that the anxiety grades are divided by the single anxiety factors is avoided, the anxiety grades are comprehensively judged through the plurality of anxiety factors, and the reliability and the accuracy of anxiety grade division are improved. The anxiety grades are finely divided, a customized relieving scheme is provided for users with different anxiety grades, vehicles are prevented from blindly entering a charging pile service area, charging queuing is carried out, and endurance anxiety is increased, so that reasonable charging of the vehicles is effectively dredged.
The present embodiment provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the one processor to enable the at least one processor to perform the method steps described in the embodiments above.
Embodiments of the present application provide a non-transitory computer storage medium storing computer executable instructions that perform the method steps described in the embodiments above.
Finally, it should be noted that: in the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. The system or the device disclosed in the embodiments are relatively simple in description, and the relevant points refer to the description of the method section because the system or the device corresponds to the method disclosed in the embodiments.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will 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.
Claims (10)
1. A method of alleviating endurance anxiety, comprising:
acquiring a plurality of anxiety factors of respective users of a plurality of vehicles in a preset area;
determining anxiety levels for each user based on the plurality of anxiety factors for the corresponding user;
an mitigation regimen for each user is generated based on the anxiety level of the corresponding user and at least one rescue factor of the plurality of anxiety factors for the corresponding user.
2. The method of claim 1, wherein the determining the anxiety level of each user based on the plurality of anxiety factors for the corresponding user comprises:
determining the respective interference types of all anxiety factors of each user;
performing binning treatment on all anxiety factors of all users according to types, and determining a plurality of bins of each anxiety factor;
obtaining characteristic values of related anxiety factors in each sub-box based on respective interference types of all anxiety factors in each sub-box;
calculating the sum of the characteristic values of all the sub-boxes of each anxiety factor, and obtaining the total characteristic value of the corresponding anxiety factor;
a respective anxiety level for each user is determined based on the respective total characteristic values of all anxiety factors and the respective interference types of the plurality of anxiety factors for each user.
3. The method of claim 2, wherein the step of determining the position of the substrate comprises,
the interference types include interference types and non-interference types;
accordingly, the characteristic value of the relevant anxiety factors in each sub-box is obtained based on the respective interference types of all the anxiety factors in each sub-box, and the characteristic value comprises the following formula:
TZ i ＝(γ pi -γ ni )×Q i ；
wherein TZ is i Characteristic value of any anxiety factor, gamma, in the ith bin representing the anxiety factor pi Representing the ratio of the number of anxiety factors with non-interference in the ith bin to the number of all anxiety factors in said bin, gamma ni Representing the ratio of the number of anxiety factors with interference in the ith bin to the number of all anxiety factors in the bin, Q i And the weight value of the focus factor in the ith bin is represented.
4. A method according to claim 3, wherein obtaining the weight value of the anxiety factor in the ith bin of any one of the anxiety factors comprises the following formula:
wherein Q is i The weight value of the anxiety factor in the ith bin of any of the anxiety factors.
5. The method of claim 2, wherein said determining a respective anxiety level for each user based on the respective total characteristic values of all anxiety factors and the respective interference types of the plurality of anxiety factors for each user comprises:
screening the total characteristic values of all anxiety factors to determine a plurality of qualified characteristic values;
and combining the interference types of the anxiety factors of each user with the qualified characteristic values, and respectively applying the interference types to a logistic regression model by taking the user as a unit to determine the anxiety level of each user.
6. The method of claim 5, wherein the screening the total feature values of each of all anxiety factors to determine a plurality of qualifying feature values comprises:
and when the total characteristic value of each anxiety factor is larger than a preset screening threshold value, determining the total characteristic value of the corresponding anxiety factor as a qualified characteristic value.
7. The method of claim 1, wherein the plurality of anxiety factors comprises: average charge number in unit mileage, start electric quantity of each charge, end electric quantity of each charge, driving mileage of each charge, limit charge number, limit discharge number, remaining mileage of electric quantity support, number of available nearby charging piles and distance of each nearby charging pile;
the rescue factor includes: remaining mileage of charge support, number of nearby available charging posts, and distance of each nearby charging post.
8. A device for alleviating endurance anxiety, comprising:
the information acquisition unit is used for acquiring various anxiety factors of respective users of the vehicles in the preset area;
a level determining unit for determining anxiety levels of the corresponding users based on a plurality of anxiety factors of each user;
and a plan generating unit for generating a relief plan for the corresponding user based on the anxiety level of each user and at least one rescue factor of the plurality of anxiety factors of the corresponding user.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any one of claims 1 to 7.
10. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
wherein the one or more processors implement the method of any of claims 1 to 7 when the one or more programs are executed by the one or more processors.
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