CN115985083B - Smart city-based shared electric vehicle management system and method - Google Patents
Smart city-based shared electric vehicle management system and method Download PDFInfo
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Abstract
The invention provides a shared electric vehicle management system and method based on a smart city, which belongs to the technical field of shared electric vehicles and specifically comprises the following steps: a positioning device; a vehicle information acquisition device; a server; position evaluation means; the positioning device is responsible for acquiring real-time positioning information of the shared electric vehicle; the vehicle information acquisition device is responsible for acquiring an initial position and a driving distance of the shared electric vehicle; the server is responsible for determining a basic parking area and a designated parking area of the shared electric vehicle and determining whether to allow vehicle returning; the position evaluation device is responsible for judging the reliability of the positioning device and the real-time positioning information; and the method is responsible for the evaluation of a reliable positioning mode, a positioning trusted value and position information, so that the accuracy and the reliability of position and vehicle returning judgment are further improved.
Description
Technical Field
The invention belongs to the technical field of shared electric vehicles, and particularly relates to a shared electric vehicle management system and method based on a smart city.
Background
In order to realize dynamic management of the shared electric vehicle, in the invention patent publication number CN113763641B, "method, device, equipment and storage medium for returning shared electric vehicle", an initial parking area is constructed according to an initial parking position of the shared electric vehicle to be returned, the initial parking area within an error range can be constructed, accurate positioning is performed when a partial overlapping area exists between the initial parking area and a specified parking area, and then whether the returning requirement of the shared electric vehicle is met is judged, however, the following technical problems exist:
1. The technical problem that the position positioning fault caused by the fault of the GPS positioning module of the shared electric vehicle is likely to exist in the actual position determining process when the final position of the parking area is determined by combining the driving mileage and the initial position of the shared electric vehicle is ignored, and the technical problem that the final position positioning is not accurate is likely to be caused if the driving mileage and the initial position of the shared electric vehicle cannot be combined.
2. The reliability of the positioning information is different under the condition that the positioning information of the plurality of positioning information is consistent or the positioning information of different positioning modes is inconsistent in the actual operation process, and the accurate evaluation of the position can not be accurately realized if the reliability of the positioning can not be combined.
Aiming at the technical problems, the invention provides a shared electric vehicle management system and method based on a smart city.
Disclosure of Invention
According to one aspect of the present invention, there is provided a smart city-based shared electric vehicle management method.
The utility model provides a sharing electric motor car management method based on smart city which characterized in that specifically includes:
s11, determining a basic parking area of the shared electric vehicle based on the initial position and the driving distance of the shared electric vehicle, judging whether the basic parking area is positioned in a designated parking area, if so, allowing the vehicle to return, and if not, entering step S12;
s12, acquiring the using distance of the shared electric vehicle based on the positioning device of the shared electric vehicle, and determining whether the positioning device is reliable or not at least based on the difference value between the using distance and the driving distance, the maximum value and the average value of the fluctuation amount of the positioning device in unit time in the driving process, if so, entering step S13, otherwise, determining that the positioning device is abnormal and the vehicle cannot be returned;
s13, screening base station positioning information and GPS positioning information of a mobile device of a user based on the real-time positioning information of the positioning device to obtain reliable positioning modes, determining whether the real-time positioning information of the shared electric vehicle is reliable or not based on the number of the reliable positioning modes, judging whether returning of the vehicle is allowed or not based on the real-time positioning information if yes, and entering step S14 if not;
S14, based on the real-time positioning information of the positioning device, the base station positioning information and GPS positioning information of the mobile device of the user and the basic parking area, evaluating a positioning reliability value and position information, and when the positioning reliability is greater than a set value, determining whether to allow returning or not based on the position information.
The basic parking area of the shared electric vehicle is determined by combining the initial position and the driving distance of the shared electric vehicle, so that the judging step of the vehicle returning position is further simplified, the judging efficiency of the vehicle returning is improved, and meanwhile, the reliability of the vehicle returning is also ensured.
Through the reliable judgment of the positioning device, the reliability of the positioning device is judged from multiple angles, so that the problem of error in vehicle returning judgment caused by positioning errors due to the failure of the positioning device is avoided, and the reliability of vehicle returning judgment is improved.
By further combining the real-time positioning information of the positioning device, the base station positioning information and the GPS positioning information of the mobile device of the user are evaluated in a reliable positioning mode, so that the technical problem of inaccurate evaluation of the position information caused by the adoption of the real-time positioning information of the positioning device is avoided, the reliability of the real-time positioning information is judged in a simple judging mode, and the reliability of the evaluation is ensured.
By combining the real-time positioning information of the positioning device, the base station positioning information of the mobile device of the user, the GPS positioning information and the basic parking area to evaluate the positioning reliability value and the position information, the judgment of the positioning reliability of the position information from multiple angles is further realized, and the problem that the original evaluation result is inaccurate due to the fact that only a single means is adopted is avoided.
On the other hand, the embodiment of the application provides a shared electric vehicle management system based on a smart city, and the shared electric vehicle management method based on the smart city specifically includes:
a positioning device; a vehicle information acquisition device; a server; position evaluation means;
the positioning device is responsible for acquiring real-time positioning information of the shared electric vehicle;
the vehicle information acquisition device is responsible for acquiring an initial position and a driving distance of the shared electric vehicle;
the server is responsible for determining a basic parking area and a designated parking area of the shared electric vehicle and determining whether to allow vehicle returning;
the position evaluation device is responsible for judging the reliability of the positioning device and the real-time positioning information; is responsible for the evaluation of reliable positioning modes, positioning trusted values and position information.
In another aspect, embodiments of the present application provide a computer system, including: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor executes the above-mentioned method for managing the shared electric vehicle based on the smart city when running the computer program.
In another aspect, the present invention provides a computer storage medium having a computer program stored thereon, which when executed in a computer, causes the computer to perform a smart city-based shared electric vehicle management method as described above.
Additional features and advantages will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Additional features and advantages will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings;
fig. 1 is a flowchart of a smart city-based shared electric vehicle management method according to embodiment 1;
FIG. 2 is a flowchart of specific steps for determining whether a positioning device is reliable according to embodiment 1;
FIG. 3 is a flowchart of specific steps for evaluation of positioning confidence values according to embodiment 1;
fig. 4 is a block diagram of a smart city-based shared electric vehicle management system according to embodiment 2;
FIG. 5 is a block diagram of a computer system according to embodiment 3;
fig. 6 is a structural diagram of a computer storage medium according to embodiment 4.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus detailed descriptions thereof will be omitted.
The terms "a," "an," "the," and "said" are used to indicate the presence of one or more elements/components/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. in addition to the listed elements/components/etc.
Compared with the reliability of the positioning device of the shared electric vehicle, the GPS positioning information of the mobile terminal of the user of the shared electric vehicle can be modified by software modification, and the base station positioning information of the mobile device of the user can possibly exist that the user enters into areas such as office places and the like on the premise that the user does not return to the vehicle, and the areas are not related to the position of the positioning device of the shared electric vehicle, so that the positioning device of the shared electric vehicle needs to be distinguished and screened, and the reliability of the positioning device of the shared electric vehicle is obviously higher.
Example 1
In order to solve the above-mentioned problems, according to an aspect of the present invention, as shown in fig. 1, there is provided a smart city-based shared electric vehicle management method, which is characterized by comprising:
s11, determining a basic parking area of the shared electric vehicle based on the initial position and the driving distance of the shared electric vehicle, judging whether the basic parking area is positioned in a designated parking area, if so, allowing the vehicle to return, and if not, entering step S12;
Specifically, the driving distance is determined according to the driving time and the average driving speed of the shared electric vehicle.
For a specific example, when the travel time of the shared electric vehicle is 30 minutes and the average travel speed is 30km/h, the travel distance is determined to be 15km.
Specifically, the basic parking area is determined by using a circular area with the initial position of the shared electric vehicle as a center and the driving distance as a radius.
For a specific example, a circular area with an initial position as a coordinate and a radius of 15km is a basic parking area.
It should be noted that the return of the vehicle is allowed if and only if the basic parking area is completely inside the designated parking area, which is an area defined in advance by the shared electric vehicle provider according to the requirements of the operating area, generally belonging to a certain class during the actual operation.
In this embodiment, the initial position and the driving distance of the shared electric vehicle are combined to determine the basic parking area of the shared electric vehicle, so that the step of judging the position of the returning vehicle is further simplified, the efficiency of judging the returning vehicle is improved, and meanwhile, the reliability of the returning vehicle is also ensured.
S12, acquiring the using distance of the shared electric vehicle based on the positioning device of the shared electric vehicle, and determining whether the positioning device is reliable or not at least based on the difference value between the using distance and the driving distance, the maximum value and the average value of the fluctuation amount of the positioning device in unit time in the driving process, if so, entering step S13, otherwise, determining that the positioning device is abnormal and the vehicle cannot be returned;
specifically, as shown in fig. 2, the specific steps for determining whether the positioning device is reliable are as follows:
s21, determining the basic reliability of the positioning device based on the difference value between the using distance and the driving distance, and determining whether the positioning device has a problem or not based on the basic reliability, if so, determining that the positioning device is unreliable, and if not, entering a step S22;
specifically, for example, when the distance is 10km, the driving distance is 15km, the difference is 1/3 of the driving distance, the basic reliability is 0.33, and if the limit value is 0.9, the positioning device is determined to be unreliable, and the position of the shared electric vehicle cannot be determined.
It should be noted that, generally, by defining a value by a certain percentage of the travel distance, when the base reliability is smaller than the defined value, it is determined that the current positioning device is unreliable.
It is understood that the base reliability is at most 1 and at least 0.
S22, confirming whether the accuracy of the positioning device meets the requirement or not based on the basic reliability of the positioning device, if so, entering a step S23, and if not, entering a step S25;
specifically, if the limit value is 0.9, the number of determinations of accuracy of the positioning device is at least 0.95 or more, and if the base reliability is high, it can be determined that the positioning reliability at that time is high, and therefore, the determination of reliability of the positioning device can be performed by a simple determination.
S23, determining the stability of the positioning device based on the maximum value and the average value of the fluctuation amount of the positioning device in unit time in the running process, judging whether the stability of the positioning device meets the requirement, if so, determining that the positioning device is reliable, and if not, entering step S24;
it will be appreciated that the unit time is generally 1 minute or less or 3 minutes, if the maximum value of the variation amount of the positioning device per unit time, i.e. 1 minute, during running is 2km, the average value is 1km, and the fastest running speed of a normal shared electric vehicle is 30km/h, the stability of the positioning device at this time obviously cannot meet the requirement.
In the actual operation process, the maximum value and the average value of the fluctuation amount of the unit time of the positioning device in the running process can be respectively based on the determination of the ratio to the fastest running speed of the shared electric vehicle, and the judgment of the stability can be carried out according to the data of the ratio of the maximum value and the average value.
For example, if the maximum value of the fluctuation amount of the positioning device per unit time, i.e., 1 minute, during traveling is 2km, the average value is 1km, and the fastest traveling speed of a normal shared electric vehicle is 30km/h, the ratio is 4 and 2, respectively, and when both are greater than 1, it can be determined that the stability of the positioning device at this time is poor.
S24, constructing a running fluctuation amount in unit time based on the fastest running speed of the shared electric vehicle, determining the positioning stability of the positioning device based on the number of times that the fluctuation amount of the positioning device in unit time is larger than the running fluctuation amount in the running process, judging whether the positioning stability of the positioning device meets the requirement, if so, determining that the positioning device is reliable, and if not, entering step S25;
specifically, when the running fluctuation amount of 1 minute is 0.5km, the number of times of fluctuation amount per unit time of the positioning device during running is more than 0.5km is more than 10 times, further evaluation of reliability is required, and when it is less than 10 times, the positioning device is determined to be reliable.
S25, evaluating the reliability of the positioning device at least based on the basic reliability, the maximum value and the average value of the fluctuation amount of the positioning device in unit time during running, the ratio of the number of times that the fluctuation amount of the positioning device in unit time during running is larger than the fluctuation amount of running to the running time, and determining whether the positioning device is reliable or not based on the reliability.
Specific examples of the determination of reliability of the positioning device are that a machine learning model based on an ISSA-LSSVM algorithm is adopted for determination, and the specific steps are as follows:
(1) Performing kernel principal component analysis dimension reduction processing on the sample data;
(2) ISSA parameters and population initialization; setting parameters such as the number of sparrow individuals, optimizing iteration times and the like, and eliting and diversifying an initial population in a search space;
(3) Determining the ranges of LSSVM parameters c and g, wherein the value range of c is (0, 100), and the value range of g is (0, 100);
(4) The ISSA is used for updating the optimal solution of the key parameters continuously approaching the LSSVM through individual iteration of the searcher, the follower and the alerter in the sparrow, and updating the iteration times t;
(5) Preprocessing a data set through KPCA, dividing main component data of a salient index into two parts, namely a training set and a testing set, so as to perform model training and actual testing, taking the root mean square error of an output predicted value and an actual salient value of an ISSA-LSSVM model as a fitness function, taking the fitness function as an optimal solution when the fitness is optimal, and adopting the following fitness function formula:
(6) Judging whether a termination condition is satisfied: if yes, continuing to execute the step (7), otherwise, returning to the step (4);
(7) Outputting an optimal solution, namely a kernel function parameter value and a penalty parameter value of the LSSVM model, and training the LSSVM model by utilizing the optimized parameters, namely completing the establishment of a machine learning model of the ISSA-LSSVM.
Wherein, the LSSVM regression prediction function is as follows:
in (1) the->
Representing a nonlinear mapping; />
Representing a normal vector; b represents the offset, and the target optimization constraint function is:
Specifically, when a follower in the standard SSA algorithm moves to an optimal position, the situation that the population is gathered rapidly in a short time is easy to occur, the diversity of the population is suddenly reduced although the effect of rapid convergence can be achieved, the probability that the algorithm falls into local optimization is greatly increased, the chicken swarm optimization algorithm is a random optimization algorithm with excellent global optimization capability, the random following strategy is that hens approach to cocks with a certain probability, the convergence is guaranteed, the diversity of the population is not reduced, local development and global search can be well considered, and the position update formula of the cocks is as follows:
And introducing a random following strategy into a follower position updating process in a sparrow searching algorithm, and fully utilizing the position information and probabilistic change of the previous generation of individuals. The improved follower position update formula is as follows:
The value range of the basic reliability is between 0 and 1, and is specifically related to the difference between the usage distance and the driving distance, and when the absolute value of the difference between the usage distance and the driving distance is larger, the basic reliability is smaller.
When the maximum value and the average value of the fluctuation amount of the positioning device in the unit time during running are smaller than the running fluctuation amount in the unit time, the stability of the positioning device is determined to meet the requirement.
In the embodiment, through judging whether the positioning device is reliable or not, the reliability of the positioning device is judged from multiple angles, so that the problem of error in vehicle returning judgment caused by positioning error due to the fault of the positioning device is avoided, and the reliability of vehicle returning judgment is improved.
S13, screening base station positioning information and GPS positioning information of a mobile device of a user based on the real-time positioning information of the positioning device to obtain reliable positioning modes, determining whether the real-time positioning information of the shared electric vehicle is reliable or not based on the number of the reliable positioning modes, judging whether returning of the vehicle is allowed or not based on the real-time positioning information if yes, and entering step S14 if not;
specifically, whether the base station positioning mode is a reliable positioning mode is determined based on the error of the base station positioning information of the mobile device of the user and the real-time positioning information of the positioning device, and whether the GPS positioning mode is a reliable positioning mode is determined based on the error of the GPS positioning information of the mobile device of the user and the real-time positioning information of the positioning device.
In this embodiment, by further combining with the real-time positioning information of the positioning device, the base station positioning information and the GPS positioning information of the mobile device of the user are evaluated in a reliable positioning manner, so that the technical problem of inaccurate evaluation of the position information caused by simply adopting the real-time positioning information of the positioning device is avoided, the reliability of the real-time positioning information is judged in a simple judging manner, and the reliability of the evaluation is ensured.
S14, based on the real-time positioning information of the positioning device, the base station positioning information and GPS positioning information of the mobile device of the user and the basic parking area, evaluating a positioning reliability value and position information, and when the positioning reliability is greater than a set value, determining whether to allow returning or not based on the position information.
Specifically, as shown in fig. 3, the specific steps of the evaluation of the positioning trusted value are as follows:
s31, judging whether the base station positioning information and the GPS positioning information of the mobile device of the user are not in the basic parking area, if so, determining that the current positioning reliability value is 0, and if not, entering step S32;
s32, judging whether the base station positioning information and the GPS positioning information of the mobile device of the user are in the basic parking area, if so, proceeding to step S33, otherwise, proceeding to step S34
S33, determining whether current real-time positioning information is reliable or not based on error values of base station positioning information of the mobile device of the user and real-time positioning information of the positioning device, if so, determining that the positioning reliability value of the current right is 1, taking an average value of the base station positioning information of the mobile device of the user and the real-time positioning information of the positioning device as position information, and if not, entering step S34;
s34, based on the real-time positioning information of the positioning device, the base station positioning information of the mobile device of the user, the GPS positioning information and the basic parking area, evaluating a positioning credible value, and taking the real-time positioning information of the positioning device as position information when the positioning credible value is larger than a credible preset value.
In this embodiment, by combining the real-time positioning information of the positioning device, the base station positioning information of the mobile device of the user, the GPS positioning information, and the evaluation of the positioning reliability value and the position information in the basic parking area, the judgment of the positioning reliability of the position information from multiple angles is further realized, and the problem that the original evaluation result is inaccurate due to the adoption of only a single means is avoided.
For ease of understanding, this application presents an additional specific embodiment:
determining that a basic parking area of the shared electric vehicle is a basic parking area when the running time of the shared electric vehicle is 30 minutes and the average running speed is 30km/h based on the initial position and the running distance of the shared electric vehicle, determining that the running distance is 15km, taking the initial position as a coordinate, taking a circular area with the radius of 15km as the basic parking area, and further judging when the basic parking area is not positioned in the designated parking area;
determining whether the positioning device is reliable or not at least based on the difference value between the using distance and the driving distance, the maximum value of the fluctuation amount of the positioning device in unit time in the driving process and the average value, specifically, as shown in fig. 2, determining based on an evaluation model of an ISSA-LSSVM algorithm, and further judging when the reliability is not reliable enough;
determining whether a base station positioning mode is a reliable positioning mode or not based on the errors of the base station positioning information of the mobile device of the user and the real-time positioning information of the positioning device, determining whether the GPS positioning mode is the reliable positioning mode or not based on the errors of the GPS positioning information of the mobile device of the user and the real-time positioning information of the positioning device, and further judging when the number of the reliable positioning modes is smaller than 2;
And based on the real-time positioning information of the positioning device, the base station positioning information of the mobile device of the user, the GPS positioning information and the basic parking area, carrying out positioning reliability value and position information evaluation, wherein a specific evaluation mode is shown in fig. 3, and determining whether to allow returning or not based on the position information when the positioning reliability is greater than a set value.
Example 2
As shown in fig. 4, an embodiment of the present application provides a smart city-based shared electric vehicle management system, and the method for managing a smart city-based shared electric vehicle specifically includes:
a positioning device; a vehicle information acquisition device; a server; position evaluation means;
the positioning device is responsible for acquiring real-time positioning information of the shared electric vehicle;
the vehicle information acquisition device is responsible for acquiring an initial position and a driving distance of the shared electric vehicle;
specifically, the driving distance is determined according to the driving time and the average driving speed of the shared electric vehicle.
For a specific example, when the travel time of the shared electric vehicle is 30 minutes and the average travel speed is 30km/h, the travel distance is determined to be 15km.
Specifically, the basic parking area is determined by using a circular area with the initial position of the shared electric vehicle as a center and the driving distance as a radius.
For a specific example, a circular area with an initial position as a coordinate and a radius of 15km is a basic parking area.
The server is responsible for determining a basic parking area and a designated parking area of the shared electric vehicle and determining whether to allow vehicle returning;
the position evaluation device is responsible for judging the reliability of the positioning device and the real-time positioning information; is responsible for the evaluation of reliable positioning modes, positioning trusted values and position information.
Specifically, based on the initial position and the running distance of the shared electric vehicle, determining that the basic parking area of the shared electric vehicle is a basic parking area with the initial position as a coordinate and a circular area with the radius of 15km as a radius as a basic parking area when the running time of the shared electric vehicle is 30 minutes and the average running speed is 30km/h, and further judging is needed when the basic parking area is not located in the designated parking area;
specifically, whether the positioning device is reliable or not is determined at least based on the difference value between the using distance and the driving distance, the maximum value and the average value of the fluctuation amount of the positioning device in unit time in the driving process, specifically, as shown in fig. 2, the determination is performed based on an evaluation model of an ISSA-LSSVM algorithm, and when the reliability is not enough, further judgment is performed;
Specifically, the reliability of the positioning device is evaluated by using a machine learning model based on an ISSA-LSSVM algorithm, and the method specifically comprises the following steps:
(1) Performing kernel principal component analysis dimension reduction processing on the sample data;
(2) ISSA parameters and population initialization; setting parameters such as the number of sparrow individuals, optimizing iteration times and the like, and eliting and diversifying an initial population in a search space;
(3) Determining the ranges of LSSVM parameters c and g, wherein the value range of c is (0, 100), and the value range of g is (0, 100);
(4) The ISSA is used for updating the optimal solution of the key parameters continuously approaching the LSSVM through individual iteration of the searcher, the follower and the alerter in the sparrow, and updating the iteration times t;
(5) Preprocessing a data set through KPCA, dividing main component data of a salient index into two parts, namely a training set and a testing set, so as to perform model training and actual testing, taking the root mean square error of an output predicted value and an actual salient value of an ISSA-LSSVM model as a fitness function, taking the fitness function as an optimal solution when the fitness is optimal, and adopting the following fitness function formula:
(6) Judging whether a termination condition is satisfied: if yes, continuing to execute the step (7), otherwise, returning to the step (4);
(7) Outputting an optimal solution, namely a kernel function parameter value and a penalty parameter value of the LSSVM model, and training the LSSVM model by utilizing the optimized parameters, namely completing the establishment of a machine learning model of the ISSA-LSSVM.
Wherein, the LSSVM regression prediction function is as follows:
in (1) the->
Representing a nonlinear mapping; />
Representing a normal vector; b represents the offset, and the target optimization constraint function is: />
Specifically, when a follower in the standard SSA algorithm moves to an optimal position, the situation that the population is gathered rapidly in a short time is easy to occur, the diversity of the population is suddenly reduced although the effect of rapid convergence can be achieved, the probability that the algorithm falls into local optimization is greatly increased, the chicken swarm optimization algorithm is a random optimization algorithm with excellent global optimization capability, the random following strategy is that hens approach to cocks with a certain probability, the convergence is guaranteed, the diversity of the population is not reduced, local development and global search can be well considered, and the position update formula of the cocks is as follows:
And introducing a random following strategy into a follower position updating process in a sparrow searching algorithm, and fully utilizing the position information and probabilistic change of the previous generation of individuals. The improved follower position update formula is as follows:
Determining whether a base station positioning mode is a reliable positioning mode or not based on the errors of the base station positioning information of the mobile device of the user and the real-time positioning information of the positioning device, determining whether the GPS positioning mode is the reliable positioning mode or not based on the errors of the GPS positioning information of the mobile device of the user and the real-time positioning information of the positioning device, and further judging when the number of the reliable positioning modes is smaller than 2;
And based on the real-time positioning information of the positioning device, the base station positioning information of the mobile device of the user, the GPS positioning information and the basic parking area, carrying out positioning reliability value and position information evaluation, wherein a specific evaluation mode is shown in fig. 3, and determining whether to allow returning or not based on the position information when the positioning reliability is greater than a set value.
Example 3
As shown in fig. 5, in an embodiment of the present application, there is provided a computer system including: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor executes the above-mentioned method for managing the shared electric vehicle based on the smart city when running the computer program.
Specifically, the embodiment also provides a computer system, which comprises a processor, a memory, a network interface and a database which are connected through a system bus; wherein the processor of the computer system is configured to provide computing and control capabilities; the memory of the computer system includes nonvolatile storage medium, internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The computer device network interface is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements a smart city-based shared electric vehicle management method as described above.
Example 4
As shown in fig. 6, the present invention provides a computer storage medium having a computer program stored thereon, which when executed in a computer, causes the computer to perform a smart city-based shared electric vehicle management method as described above.
Specifically, the method for managing the shared electric vehicle based on the smart city specifically comprises the following steps:
determining that a basic parking area of the shared electric vehicle is a basic parking area when the running time of the shared electric vehicle is 30 minutes and the average running speed is 30km/h based on the initial position and the running distance of the shared electric vehicle, determining that the running distance is 15km, taking the initial position as a coordinate, taking a circular area with the radius of 15km as the basic parking area, and further judging when the basic parking area is not positioned in the designated parking area;
determining whether the positioning device is reliable or not at least based on the difference value between the using distance and the driving distance, the maximum value of the fluctuation amount of the positioning device in unit time in the driving process and the average value, specifically, as shown in fig. 2, determining based on an evaluation model of an ISSA-LSSVM algorithm, and further judging when the reliability is not reliable enough;
Determining whether a base station positioning mode is a reliable positioning mode or not based on the errors of the base station positioning information of the mobile device of the user and the real-time positioning information of the positioning device, determining whether the GPS positioning mode is the reliable positioning mode or not based on the errors of the GPS positioning information of the mobile device of the user and the real-time positioning information of the positioning device, and further judging when the number of the reliable positioning modes is smaller than 2;
and based on the real-time positioning information of the positioning device, the base station positioning information of the mobile device of the user, the GPS positioning information and the basic parking area, carrying out positioning reliability value and position information evaluation, wherein a specific evaluation mode is shown in fig. 3, and determining whether to allow returning or not based on the position information when the positioning reliability is greater than a set value.
In particular, it will be understood by those skilled in the art that implementing all or part of the above-described methods of the embodiments may be implemented by a computer program, which may be stored in a non-volatile computer readable storage medium, and the computer program may include the steps of the embodiments of the above-described methods when executed. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
In the several embodiments provided in this application, it should be understood that the disclosed systems and methods may be implemented in other ways as well. The system embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present invention may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored on a computer readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
With the above-described preferred embodiments according to the present invention as an illustration, the above-described descriptions can be used by persons skilled in the relevant art to make various changes and modifications without departing from the scope of the technical idea of the present invention. The technical scope of the present invention is not limited to the description, but must be determined according to the scope of claims.
Claims (10)
1. The utility model provides a sharing electric motor car management method based on smart city which characterized in that specifically includes:
determining a basic parking area of the shared electric vehicle based on an initial position and a driving distance of the shared electric vehicle, judging whether the basic parking area is positioned in a designated parking area, if so, allowing the vehicle to return, and if not, entering the next step;
acquiring the using distance of the shared electric vehicle based on the positioning device of the shared electric vehicle, and determining whether the positioning device is reliable or not at least based on the difference value between the using distance and the driving distance, the maximum value and the average value of the fluctuation quantity of the positioning device in unit time in the driving process, if so, entering the next step, otherwise, the positioning device is abnormal and the vehicle cannot be returned;
the specific steps for determining whether the positioning device is reliable are as follows:
s21, determining the basic reliability of the positioning device based on the difference value between the using distance and the driving distance, and determining whether the positioning device has a problem or not based on the basic reliability, if so, determining that the positioning device is unreliable, and if not, entering a step S22;
s22, confirming whether the accuracy of the positioning device meets the requirement or not based on the basic reliability of the positioning device, if so, entering a step S23, and if not, entering a step S25;
S23, determining the stability of the positioning device based on the maximum value and the average value of the fluctuation amount of the positioning device in unit time in the running process, judging whether the stability of the positioning device meets the requirement, if so, determining that the positioning device is reliable, and if not, entering step S24;
s24, constructing a running fluctuation amount in unit time based on the fastest running speed of the shared electric vehicle, determining the positioning stability of the positioning device based on the number of times that the fluctuation amount of the positioning device in unit time is larger than the running fluctuation amount in the running process, judging whether the positioning stability of the positioning device meets the requirement, if so, determining that the positioning device is reliable, and if not, entering step S25;
s25, evaluating the reliability of the positioning device at least based on the basic reliability, the maximum value and the average value of the fluctuation amount of the positioning device in unit time during running, and the ratio of the number of times that the fluctuation amount of the positioning device in unit time during running is larger than the running fluctuation amount to the running time, and determining whether the positioning device is reliable or not based on the reliability;
Screening base station positioning information and GPS positioning information of a mobile device of a user based on the real-time positioning information of the positioning device to obtain reliable positioning modes, determining whether the real-time positioning information of the shared electric vehicle is reliable or not based on the number of the reliable positioning modes, judging whether to allow returning of the vehicle based on the real-time positioning information if the real-time positioning information is reliable, and entering the next step if the real-time positioning information is not reliable;
and evaluating a positioning reliability value and position information based on the real-time positioning information of the positioning device, the base station positioning information of the mobile device of the user, the GPS positioning information and the basic parking area, and determining whether to allow returning or not based on the position information when the positioning reliability is greater than a set value.
2. The shared electric vehicle management method according to claim 1, wherein the travel distance is determined based on a travel time and an average travel speed of the shared electric vehicle.
3. The method according to claim 1, wherein the basic parking area is determined by a circular area having the initial position of the shared electric vehicle as a center and the travel distance as a radius.
4. The method according to claim 1, wherein the basic reliability has a value ranging from 0 to 1, and is specifically related to a difference between the usage distance and the travel distance, and the basic reliability is smaller as an absolute value of the difference between the usage distance and the travel distance is larger.
5. The method according to claim 1, wherein the stability of the positioning device is determined to satisfy the requirement when both a maximum value and an average value of fluctuation amounts per unit time of the positioning device during running are smaller than the running fluctuation amounts per unit time.
6. The method of claim 1, wherein determining whether the base station positioning mode is a reliable positioning mode is based on an error of base station positioning information of the mobile device of the user and real-time positioning information of the positioning device, and determining whether the GPS positioning mode is a reliable positioning mode is based on an error of GPS positioning information of the mobile device of the user and real-time positioning information of the positioning device.
7. The method for managing a shared electric vehicle as set forth in claim 1, wherein the specific step of evaluating the positioning reliability value is:
S31, judging whether the base station positioning information and the GPS positioning information of the mobile device of the user are not in the basic parking area, if so, determining that the current positioning reliability value is 0, and if not, entering step S32;
s32, judging whether the base station positioning information and the GPS positioning information of the mobile device of the user are in the basic parking area, if so, proceeding to step S33, otherwise, proceeding to step S34
S33, determining whether current real-time positioning information is reliable or not based on error values of base station positioning information of the mobile device of the user and real-time positioning information of the positioning device, if so, determining that the positioning reliability value of the right is 1, taking an average value of the base station positioning information of the mobile device of the user and the real-time positioning information of the positioning device as position information, and if not, entering step S34;
s34, based on the real-time positioning information of the positioning device, the base station positioning information of the mobile device of the user, the GPS positioning information and the basic parking area, evaluating a positioning credible value, and taking the real-time positioning information of the positioning device as position information when the positioning credible value is larger than a credible preset value.
8. A shared electric vehicle management system based on a smart city, adopting the shared electric vehicle management method based on a smart city as claimed in any one of claims 1-7, comprising the following steps:
a positioning device; a vehicle information acquisition device; a server; position evaluation means;
the positioning device is responsible for acquiring real-time positioning information of the shared electric vehicle;
the vehicle information acquisition device is responsible for acquiring an initial position and a driving distance of the shared electric vehicle;
the server is responsible for determining a basic parking area and a designated parking area of the shared electric vehicle and determining whether to allow vehicle returning;
the position evaluation device is responsible for judging the reliability of the positioning device and the real-time positioning information; is responsible for the evaluation of reliable positioning modes, positioning trusted values and position information.
9. A computer system, comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor, when executing the computer program, performs a smart city-based shared electric vehicle management method as claimed in any one of claims 1-7.
10. A computer storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform a smart city based shared electric vehicle management method as claimed in any of claims 1-7.
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