CN114841435A - Navigation path planning method and system - Google Patents
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- CN114841435A CN114841435A CN202210482271.XA CN202210482271A CN114841435A CN 114841435 A CN114841435 A CN 114841435A CN 202210482271 A CN202210482271 A CN 202210482271A CN 114841435 A CN114841435 A CN 114841435A
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- G01C21/20—Instruments for performing navigational calculations
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Abstract
The invention provides a navigation path planning method and a system, wherein the method comprises the steps of acquiring all target points required to be passed by transacting a preset transaction; determining the target point to be selected in the current step i; if only one target point to be selected in the current step i exists, recommending the target point to be selected as the preferred destination in the current step i; if a plurality of candidate target points of the current step i are available, calculating the arrival time from the current position to each candidate target point and the queuing time of each candidate target point, calculating the expected consumed time that each candidate target point transaction can begin to be transacted, and recommending the candidate target point with the shortest expected consumed time as the preferred destination of the current step i until the preferred destinations of all steps are determined. The navigation path planning method provided by the application intelligently recommends the path planning scheme with the shortest time consumption, reduces the time waste of user queuing to the maximum extent, and improves the work efficiency of users.
Description
Technical Field
The invention relates to the technical field of indoor navigation positioning, in particular to a navigation path planning method and a navigation path planning system.
Background
When handling affairs in public places, such as hospital physical examination, government office halls, station airports, shopping malls and other environments, users often encounter the situation that the users need to roll back and forth among a plurality of destinations (office windows, payment windows and the like) for many times and may need to queue up when arriving at one destination. When queuing is needed, the user generally does not know which team has the shortest queuing time, and does not know how to finish all things in the shortest time, so that the time of the user is wasted, and the transaction efficiency is low.
Disclosure of Invention
The invention aims to provide a navigation path planning method capable of improving work efficiency.
The purpose of the invention is realized by the following technical scheme:
a navigation path planning method, the method comprising:
s10, acquiring all target points needed to be passed by for transacting the preset transaction, and calculating the total step number N according to the number of the target points;
s20, acquiring the candidate target point of the current step i; wherein i is an integer from 1 to N, and the number of the target points to be selected is one or more;
s30, if there is only one target point candidate in the current step i, recommending the target point candidate as the preferred destination in the current step i, making i equal to i +1, and returning to step S20;
s40, if the number of the target point candidates in the current step i is multiple, calculating arrival time from the current position to each target point candidate, estimating queue time of each target point candidate, calculating expected consumed time that each target point candidate transaction can begin to be transacted according to the arrival time and the queue time corresponding to each target point candidate, recommending the target point candidate with the shortest expected consumed time as the preferred destination of the current step i, making i +1, and returning to step S20.
In one embodiment, the obtaining of the target point candidate in the current step i specifically includes:
acquiring all target points of which execution steps are to be determined;
identifying independent target points and associated target groups in all the target points of which the execution steps are to be determined, and acquiring one or more target points in the associated target groups in a first priority order;
the associated target group comprises a plurality of target points with a sequential execution order, and the associated target group can be a zero group, one group or a plurality of groups;
and taking the independent target point and all the target points corresponding to the first priority order as the candidate target points in the current step i.
In one embodiment, step S30 further includes:
calculating the arrival time length from the current position to the candidate target point and the queuing time length of the candidate target point;
calculating the expected time consumption that the transaction at the target point to be selected can begin to be transacted according to the arrival time length and the queuing time length;
the method further comprises the following steps: and determining the preferred destinations of the N steps, and accumulating the expected time consumption of the preferred destinations corresponding to each step to obtain the accumulated total time consumption of the current planning scheme.
In one embodiment, after determining the preferred destination of N steps, the method further comprises:
when there are a plurality of target point candidates, sequentially selecting the target point candidates other than the preferred destination as a new preferred destination in step i, making i equal to i +1, and returning to step S20;
recalculating the preferred destinations of the N steps, and accumulating the expected time consumption of the preferred destinations corresponding to each step to obtain the accumulated total time consumption of the new planning scheme;
and outputting a plurality of different planning schemes and the corresponding accumulated total consumed time.
In one embodiment, in step S40, the calculating an arrival time length from the current position to each of the candidate target points includes:
acquiring the current position and the path length s of each candidate target point (0) (n), wherein n represents the number of the corresponding target point, and n is a natural number greater than or equal to 2;
according to a preset travelling speed v 0 Calculating the arrival time length T corresponding to each destination (0) (n)＝x (0) (n)*v 0 In an embodiment, the estimating a queuing time of each candidate target point includes:
if the candidate target point has a plurality of transaction windows, calculating the window queuing time of each transaction window, and taking the shortest window queuing time as the queuing time of the corresponding candidate target point.
In one embodiment, in step S40, the estimating a queuing time of each candidate target point specifically includes:
establishing a queuing time prediction model by adopting historical queuing data, and predicting the queuing time based on the current situation and the queuing time prediction model; wherein the current situation comprises a current time period and a current weather.
In one embodiment, the establishing a queuing time prediction model by using historical data specifically includes:
establishing an average queue population sequence x over the same time period (0) ＝(x 0 (1),x 0 (2),x 0 (3),.....,x 0 (n)); calculating a grade ratio; if all the stage ratios are in
Interval range, then x (0) As a satisfactory prediction model of the queuing time.
In one embodiment, in step S40, the estimating a queuing time of each candidate target point includes:
reporting the queuing condition in real time by an applet pre-downloaded at the terminal, and estimating the queuing time according to the queuing condition; or the terminal acquires the video image of the office in real time, acquires the queuing condition according to the video image and estimates the queuing time.
In addition, the invention also provides a navigation path planning system based on queuing time, which comprises:
the target step acquisition module is used for acquiring all target points which need to be passed by for transacting the preset transaction and calculating the total step number N according to the number of the target points;
a candidate target obtaining module, which is in communication connection with the target step obtaining module and is used for obtaining candidate target points of the current step i, wherein i is an integer from 1 to N, and the number of the candidate target points is one or more;
a necessary target point determining module, which is in communication connection with the candidate target obtaining module, and is used for recommending the candidate target point as the preferred destination of the current step i under the condition that the number of the candidate target points of the current step i is only one;
a preferred target determining module, communicatively connected to the candidate target obtaining module, configured to calculate, when the number of target candidates in step i is multiple, an arrival time from a current location to each of the target candidates, estimate a queuing time of each of the target candidates, calculate, according to the arrival time and the queuing time corresponding to each of the target candidates, an expected elapsed time at which a transaction at each of the target candidates can begin to be transacted, and recommend, as a preferred destination in step i, the target candidate with the shortest expected elapsed time.
Compared with the prior art, the invention has the following beneficial effects: the invention provides a navigation path planning method based on queuing time, which comprises the steps of acquiring all target points required to be passed by transacting a preset transaction; determining the target point to be selected in the current step i; if only one target point to be selected in the current step i exists, recommending the target point to be selected as the preferred destination in the current step i; if a plurality of candidate target points of the current step i are available, calculating the arrival time from the current position to each candidate target point and the queuing time of each candidate target point, calculating the expected consumed time that each candidate target point transaction can begin to be transacted, and recommending the candidate target point with the shortest expected consumed time as the preferred destination of the current step i until the preferred destinations of all steps are determined. The navigation path planning method provided by the application intelligently recommends the path planning scheme with the shortest time consumption, reduces the time waste of user queuing to the maximum extent, and improves the work efficiency of users.
Drawings
FIG. 1 is a schematic flow chart of a navigation path planning method based on queuing time according to an embodiment of the present invention;
fig. 2 is a simple schematic diagram of an implementation scenario of a navigation path planning method according to an embodiment of the present invention
FIG. 3 is a block diagram of a navigation path planning system based on queuing time according to a real-time embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, embodiments accompanying the present application are described in detail below with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures associated with the present application are shown in the drawings, not all of them. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "comprising" and "having," as well as any variations thereof, in this application are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Referring to fig. 1, a flow chart of a navigation path planning method according to an embodiment of the invention is shown. The navigation path planning method can be applied to environments such as hospitals, independent physical examination organizations, government offices, large shopping centers and the like, and a user needs to process a plurality of transactions at the same time. It will be appreciated that the user always wishes to process the corresponding transaction with the least amount of time spent. However, in the actual situation, the user cannot know which transaction needs the shortest time to process, and usually processes each transaction in turn by subjective judgment or random selection, which often takes a long time to queue up, and cannot process all transactions in a specified time, resulting in wasted time and delayed other transaction processing.
For the convenience of understanding, the present invention is described by taking a physical examination scene of a hospital physical examination center (or an independent physical examination institution) as an example. As is known, the physical examination usually includes a plurality of items, such as dozens or even dozens, each physical examination item has a special examination room, the queuing condition of each examination room is different, some examination items take longer time, some examination items have longer examination rooms, and the sequence of the physical examination items received by the user inevitably affects the time for completing the whole physical examination.
The embodiment provides a navigation path planning method based on queuing time. Referring to fig. 1, the method includes the following steps:
and step S10, acquiring all target points needed to be passed by for transacting the preset transaction, and calculating the total step number N according to the number of the target points.
The target point refers to a corresponding place where a user handles a plurality of transactions, and each target point corresponds to one to-be-processed transaction. Taking the above physical examination scene as an example, each examination room is equivalent to a target point, and all the target points are equivalent to the places that all the physical examination items need to pass through.
The target points also include transit points which are judged according to actual service scenes and are necessary to pass by for reaching subsequent target points or final destinations. In a hospital scene, when a user is at a doorway of a hospital, the user needs to navigate to an internal medicine examination room, at the moment, a preset transfer place is a registered place, and a target point further comprises the transfer place. In the scene of a government office hall, a user needs to go to a certain counter at the entrance of the hall, and the preset transfer place is a queuing machine. When the situation of the transit points exists in the obtained actual service scene of the destination, counting all the transit points into the target points, and calculating the total step number N according to the total number of the target points. Specifically, when the number of target points is N, the total number of steps is also N.
The method for acquiring the target point of the user can be various, for example, the user actively inputs a target point keyword in a search box, the target point is quickly recommended according to the historical search result of the user, the target point is selected according to map clicking, a plurality of target points for actually transacting business are selected, and the target point of the user is shared by other people. In the above-described scenario of physical examination, the target point of the examination process may be imported in advance by the physical examination items.
Step S20, acquiring the candidate target point of the current step i; wherein i is an integer from 1 to N, and the number of the target point candidates is one or more.
Each step is provided with one or more candidate target points, and the candidate target point of the current step is identified through a preset algorithm. For example, in a hospital physical examination scenario, the first step needs to be registered on the counter, so there is only one target point candidate in step 1, i.e. the counter. When the registration is completed, the examination of the physical examination items is performed, and it is determined that all of the plurality of examination items can be performed in step 2, and therefore, the target candidate point of step 2 includes examination rooms corresponding to the plurality of examination items.
S30, if there is only one target point candidate in the current step i, recommending the target point candidate as the preferred destination in the current step i, making i equal to i +1, and returning to step S20;
s40, if the number of the candidate target points of the current step i is multiple, calculating arrival time from the current position to each candidate target point, estimating queue time of each candidate target point, calculating expected transaction time of each candidate target point according to the arrival time and the queue time corresponding to each candidate target point, recommending the corresponding candidate target point with the expected transaction time less than the expected transaction time of other candidate target points as the preferred destination of the current step i, making i equal to i +1, and returning to the step S20.
The above-mentioned steps S30 and S40 are the determination of the preferred destination of the current step i. Step S30 is to directly set the target point candidate as the preferred destination in case there is only one target point candidate at the current step i. That is, the current step i is the required passing point step of the candidate target point, and the candidate target point must be executed in the step i, such as the above physical examination scenario, the first step must be registered in the counter before the physical examination can be performed, so the target point-counter is the required passing point step of step 1. Step S40 is for selecting one of the multiple target point candidates that is shortest in time as the preferred destination of the current step. In the hospital physical examination scenario, if step 2 has a plurality of examination items, each examination item corresponds to one target point candidate, the queue duration and arrival duration of each examination item can be calculated according to the algorithm of step S40, and the examination item expected to consume the shortest time is recommended as the preferred destination of step 2 according to the queue duration and arrival duration.
Specifically, in step S40, the obtained arrival duration and the queuing duration are added to obtain the expected consumed time that the transaction at each target point candidate can begin to be transacted, the expected consumed times at each target point candidate are ranked, and the target point candidate with the shortest expected consumed time is recommended as the preferred destination of the current step. That is to say, the target point to be selected corresponding to which the transaction can be started as soon as possible is preferentially recommended as the preferred destination, and the transaction corresponding to the preferred destination is preferentially recommended, so that the waiting time of the user can be effectively saved, and the time utilization efficiency is improved.
And by analogy, the determination of the preferred destinations of all the steps is finished, and the execution step sequence of all the target points, namely the optimal navigation path planning scheme, is obtained. Therefore, each step of the navigation path planning method based on queuing time provided by the invention is the optimal destination with the shortest time consumption, and the path planning scheme with the shortest time consumption can be recommended intelligently, so that the time waste of user queuing is reduced to the maximum extent, and the work handling efficiency of the user is improved.
Specifically, the navigation path planning method is executed by the mobile terminal. The mobile terminal is carried by a user and has navigation and positioning functions, such as a smart watch, a smart phone, a smart bracelet, a smart tablet and the like. The current position of the user, namely the current position of the mobile terminal, can be obtained in real time through the mobile terminal, the navigation of the candidate target point can be carried out through the mobile terminal according to the candidate target point as a navigation destination, and therefore the arrival time from the current position to the candidate target point is calculated according to the path length. In this application, a mobile terminal may also be referred to simply as a terminal.
The current position of the user can be acquired in real time through the mobile terminal no matter the user is in an indoor or outdoor environment. If the mobile phone is in an outdoor scene, the current position is obtained by using positioning modes such as a GPS (global positioning system), a Beidou and the like; if under indoor environment, then can use positioning technology such as WIFI, bluetooth, earth magnetism to obtain the current position.
Further, in step S20, that is, the step of "obtaining the target point candidate in the current step i", the method specifically includes:
s22, acquiring the target points of all the execution steps to be determined;
s24, identifying independent target points and associated target groups in all the target points to be determined to execute the steps, and acquiring one or more target points in the associated target groups in a first priority order;
the associated target group comprises a plurality of target points with a sequential execution order, the associated target group can be a zero group, a group or a plurality of groups, the independent target points are the target points which can be independently executed, and the sequential execution order does not exist between the independent target points and other target points;
and S26, taking the independent target point and all the target points corresponding to the first priority order as the candidate target points in the current step i.
Acquiring all target points of the execution steps to be determined means that the target points of the execution steps already determined are removed under the condition of the current step i, and the rest target points are all used as the target points of the execution steps to be determined. Among all target points for which execution of a step is to be determined, there may be one or more associated target groups. Here, a group of associated targets is understood to mean a plurality of target points in a sequential execution order. A set of associated target sets may include 2 target points or a greater number of target points. The associated target group may include a target point of a first priority and a target point of a second priority in the execution priority order, and the second priority target point may be scheduled for execution only when all execution of the first priority target point is completed.
For an exemplary illustration, a hospital examination is taken as an example, and refer to fig. 2 specifically. In fig. 2, there are 6 total target points a-F, X represents the current position, i.e., the starting point D, E, F is an empty stomach examination item, C is an breakfast target point, and a and B are respectively common examination items, i.e., independent target points, which can be examined in an empty stomach or after meals. Thus, D, E, F and C have sequential execution orders, and are a group of related targets, with the target point in the first priority comprising D, E, F and the target point in the second priority being C, and target point D, E, F must be checked before target point C. Thus, when the user is at the starting point X, the target point candidates of the first step comprise 2 independent target points A and B and 3 target points D, E, F of the first preferred order in the associated target group.
There are many other situations in the related target groups, such as the blood drawing examination and the blood drawing number taking step of the hospital physical examination items, which must precede the blood drawing examination, and therefore, the blood drawing examination and the blood drawing number taking step are a group of related target groups, the blood drawing number taking a target point in the first priority order, and the blood drawing examination taking a target point in the second priority order.
Independent target points, namely target points which are executed independently, in all the candidate target points of which the execution steps are to be determined do not have a sequence. In the determination of the target point candidate in the current step, all the independent target points and one or more target points in the associated target group in the first priority order are used as the target point candidate in the current step i.
In an embodiment, step S30 further includes the following steps:
s32, calculating the arrival time length of the target point from the current position and the queuing time length of the target point;
s34, calculating the expected time consumption that the transaction at the target point to be selected can begin to be transacted according to the arrival time length and the queuing time length;
the above steps S32 and S34 are the same as the expected time consuming method for finding the candidate target point transaction in step S40, and are not described herein again.
In order to facilitate the user to roughly know the accumulated total time consumption of the navigation path planning scheme, the time is reasonably arranged. Further, the navigation path planning method further includes:
and S50, determining the preferred destinations of the N steps, and accumulating the expected consumed time of the preferred destinations corresponding to each step to obtain the accumulated total consumed time of the current planning scheme.
In order to facilitate reference comparison of a user, a plurality of path planning schemes are provided, and the user can conveniently select the path planning schemes. In one embodiment, after calculating the preferred destination of N steps, the method further comprises the steps of:
s52, when there are a plurality of target point candidates, sequentially selecting the target point candidates except the preferred destination as a new preferred destination in the current step i, making i equal to i +1, and returning to step S20;
s54, recalculating the preferred destinations of the N steps, and accumulating the expected time consumption of the preferred destinations corresponding to each step to obtain the accumulated total time consumption of new different planning schemes;
and S56, outputting a plurality of different planning schemes and corresponding accumulated total consumed time.
Further, in step S40, the step of calculating the arrival time duration from the current position to each of the target point candidates includes:
s42, acquiring the current position and each candidate targetPath length s of a point (0) (n), wherein n represents the number of the corresponding target point, and n is a natural number greater than or equal to 2;
s44, according to the preset travel speed v 0 Calculating the arrival time T corresponding to each candidate target point (0) (n)＝x (0) (n)*v 0 。
That is, under the condition of the current position, the path length reaching each target point candidate is calculated by taking the current position as the start, and the reaching time length reaching each target point candidate is calculated according to the path length and the traveling speed.
Obtaining the path length sequence s of the current position and each candidate target point according to the arrival time length of each candidate target point (0) ＝(s (0) (1)，s (0) (2)，s (0) (3)，......，s (0) (n)). According to the path length sequence and the preset travel speed v 0 Obtaining the arrival time length sequence T of each candidate target point (0) ＝s (0) /v 0 . Wherein v is 0 For walking speed, preset walking speed v 0 ＝0.8m/s。
In an embodiment, in step S40, namely, the step of "estimating the queuing time of each candidate target point", the method specifically includes:
if the candidate target point has a plurality of transaction windows, calculating the window queuing time of each transaction window, and taking the shortest window queuing time as the queuing time of the corresponding candidate target point.
In another embodiment, in step S40, namely the step of "estimating the queuing time of each candidate target point", the method specifically includes the steps of:
and establishing a queuing time prediction model by adopting historical queuing data, and predicting the queuing time based on the current situation and the queuing time prediction model.
It will be appreciated that the queue duration has historical data references, and that the number of people queued for the same time period will generally have data similarities. The queuing time can be predicted by using historical queuing data. In one embodiment, a queuing time prediction model is established by using historical queuing data, and the queuing time is predicted based on the current situation and the queuing time prediction model.
In a specific step, an average queue number x of people in the same time period is established (0) ＝(x 0 (1)，x 0 (2)，x 0 (3)，.....，x 0 (n)); calculating all the stage ratios λ (k); if all the stage ratios λ (k) are in
Interval range, then x (0) As a satisfactory queuing time prediction model.
Wherein, the calculation formula of λ (k) is:
the "average number of queued persons in the same time zone" is a sequence of average number of queued persons in the same time zone on different dates. Where n denotes the index of the different historical data dates, x (0) (n) the average number of queued persons in the same time zone on the date marked n, and the average number of queued persons in the same time zone on a plurality of different dates of the historical data are combined into a sequence to obtain x (0) . It will be appreciated that the number of queued people at the current or future time may be predicted by a historical sequence of queued people past the same time period.
In another embodiment, the queuing duration prediction model is modeled using a gray system prediction model, denoted as GM (1, 1). The GM (1,1) modeling steps are as follows:
1. the original data x (0) An accumulation calculation is made.
Namely, it is
2. Constructing a data matrix B and a data vector Y
3. Estimation calculation using unary linear regression
That is, a is the coefficient of development, b is the amount of action of gray
And solving the values of a and b for the parameter vector to be estimated.
4. Modeling
For the gray differential equation of GM (1,1), if we will take the gray derivative x (0) (k) Is 2, 3, n is taken as a continuous variable t, then x (1) (t) can be considered as a function of time t.
X is then (0) (k) Corresponding reciprocal of
Differential equations can be obtained
5. Calculating the generated sequence value and model reduction value
Let k equal 1, 2, 3, 4.. 6. Can be obtained by time corresponding function
Calculating model values in sequence:
further, the queuing time required by the candidate target point can be predicted according to the average transaction processing time and the number of queuing people. The queuing time sequence is as follows:
t (0) ＝(t (0) (1)，t (0) (2)，...，t (0) (n))；
wherein, t (0) And (n) refers to the time length of queuing required at the current stage at the different target point candidates n.
In order to guarantee the accuracy of the established queuing time length prediction model, the queuing time length prediction model needs to be checked. The model verification may take historical queuing data over a period of time, with the remaining historical queuing data being used for modeling. When the verification accuracy meets the requirement, the prediction of the queuing time length prediction model is considered to be credible. The method of model checking is described in detail below.
(1) Data comparison difference value between check model value and original value
Formula of relative residual error
If the | epsilon (k) | is less than 0.1, the higher requirement is considered to be met, and if the | epsilon (k) | is less than 0.2, the general requirement is met.
(2) Check grade ratio deviation value
Deviation value of class ratio
If | p (k) | is less than 0.1, the higher requirement is considered to be met, and if less than 0.2, the general requirement is met
And if the data deviation value obtained by the verification method is less than or equal to 0.2, the queuing time length prediction model is considered to be capable of predicting.
In order to improve the accuracy of prediction, the historical queuing data is classified in advance, and the classification standard is carried out according to factors influencing the number of queuing people, such as weather, time periods and working days or non-working days. In a specific embodiment, the historical queuing data is classified according to time periods and normal weather and abnormal weather, and the current condition comprises the current time period and the current weather. In some embodiments, the target point also transacts transactions on a non-weekday, and further, the time periods are further divided by weekday time periods and non-weekday time periods. After the queuing time length prediction model is divided according to factors influencing the number of queuing people, the prediction accuracy of the queuing time length prediction model can be obviously improved.
The method for estimating the queuing time needs to rely on historical queuing data, and belongs to a non-real-time estimation method. In further embodiments, the queuing time may also be estimated in real time. Specifically, the queuing condition of each candidate target point is identified in real time, and the corresponding queuing time is estimated according to the queuing condition. The queuing condition can be reported in real time by the small program pre-downloaded at the terminal, and the queuing time length is estimated according to the queuing condition; or, the terminal acquires the video image of the office in real time, acquires the queuing condition according to the video image and estimates the queuing time. In the embodiments for estimating the queuing time in real time, the estimation of the queuing time refers to real-time data, so that the current queuing situation can be reflected more accurately, and the queuing time can be estimated more accurately.
It should be noted that, if the candidate target point does not need to queue, the queue duration is zero. And if the candidate target point has a plurality of transaction windows, calculating the window queuing time of each transaction window, and taking the shortest window queuing time as the queuing time of the corresponding candidate target point.
In a specific step, the expected time consumption for starting transaction at each target point candidate is calculated:
the arrival time length sequence T is formed (0) And queuing time length sequence t (0) Adding to obtain the predicted time-consuming sequence T of each destination (1) 。
The predicted time-consuming sequence T of each candidate target point (1) Arranging according to the following formula:
wherein:
this indicates that r elements are extracted from n elements and arranged (sorted).
n is the total number of elements (total number of candidate points); r is the number of elements participating in selection; | A Representing a factorial.
After the arrangement, the candidate target point which is expected to take the first r bits in time can be obtained.
The terminal can also recommend a plurality of candidate target points with short expected time consumption for the user to select, rather than recommending only one destination with the shortest expected time consumption. Specifically, the terminal recommends the former r candidate target points as the preferential destinations according to the arrangement formula, and gives the predicted time consumption data as the reference, or gives the suggested selection priority according to the sequence of predicted time consumption from short to long, so that the user can freely select the target point. Therefore, the freedom degree of user selection is improved, and the use experience is better.
By the navigation method, when a user arrives at a certain place, each step can accurately select the candidate target point with the shortest time consumption to process transactions, the queuing time and the arrival time are shortest, and the user can finish all the transactions of the target point in the shortest time, so that the time for the user to go out to do the transactions is controllable, and the efficiency is higher.
In addition, as shown in fig. 3, the present invention further provides a navigation path planning system 100 based on queuing time, which includes a target step obtaining module 101, an alternative target obtaining module 102, a must-pass point target determining module 104, and a preferred target determining module 106.
The target step acquiring module 101 is configured to acquire all target points that need to be passed through for transacting a predetermined transaction, and calculate a total number N of steps according to the number of the target points;
a candidate target obtaining module 102, communicatively connected to the target step obtaining module 101, configured to obtain candidate target points in the current step i, where i is an integer from 1 to N, and the number of the candidate target points is one or more;
a necessary point target determining module 104, which is in communication connection with the candidate target obtaining module 102, and is configured to recommend the candidate target point as the preferred destination of the current step i when the number of the candidate target points of the current step i is only one;
and an optimal target determining module 106, communicatively connected to the candidate target obtaining module 102, configured to calculate an arrival time from the current location to each candidate target point, estimate a queuing time of each candidate target point, calculate expected time consumption, which is required for each candidate target point transaction to begin to be transacted, according to the arrival time and the queuing time corresponding to each candidate target point, and recommend the candidate target point with the shortest expected time consumption as the optimal destination in the current step i.
The navigation path planning system based on queuing time corresponds to the navigation path planning method based on queuing time, and functions of each module in the navigation path planning system based on queuing time in this embodiment are elaborated in detail in the corresponding method embodiment, and are not described herein again.
The present invention can implement all or part of the processes of the above methods, and can also be implemented by using a computer program to instruct related hardware, where the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above method embodiments can be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, in accordance with legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunications signals.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, server, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only for the purpose of illustrating embodiments of the present invention and is not intended to limit the scope of the present invention, and all modifications, equivalents, and equivalent structures or equivalent processes that can be used directly or indirectly in other related fields of technology shall be encompassed by the present invention.
Claims (10)
1. A method of navigation path planning, the method comprising:
s10, acquiring all target points needed to be passed by for transacting the preset transaction, and calculating the total step number N according to the number of the target points;
s20, acquiring the candidate target point of the current step i; wherein i is an integer from 1 to N, and the number of the target points to be selected is one or more;
s30, if there is only one target point candidate in the current step i, recommending the target point candidate as the preferred destination in the current step i, making i equal to i +1, and returning to step S20;
s40, if the number of the target point candidates in the current step i is multiple, calculating arrival time from the current position to each target point candidate, estimating queue time of each target point candidate, calculating expected consumed time that each target point candidate transaction can begin to be transacted according to the arrival time and the queue time corresponding to each target point candidate, recommending the target point candidate with the shortest expected consumed time as the preferred destination of the current step i, making i +1, and returning to step S20.
2. The navigation path planning method according to claim 1, wherein the acquiring the target point candidate in the current step i specifically includes:
acquiring all target points of which execution steps are to be determined;
identifying independent target points and associated target groups in all the target points of which the execution steps are to be determined, and acquiring one or more target points in a first priority order in the associated target groups;
the associated target group comprises a plurality of target points with a sequential execution order, and the associated target group can be a zero group, one group or a plurality of groups;
and taking the independent target point and all the target points corresponding to the first priority order as the target points to be selected in the current step i.
3. The navigation path planning method according to claim 1, wherein step S30 further includes:
calculating the arrival time length from the current position to the candidate target point and the queuing time length of the candidate target point;
calculating the expected time consumption that the transaction at the target point to be selected can begin to be transacted according to the arrival time length and the queuing time length;
the method further comprises the following steps: and determining the preferred destinations of the N steps, and accumulating the expected time consumption of the preferred destinations corresponding to each step to obtain the accumulated total time consumption of the current planning scheme.
4. The navigation path planning method of claim 3, wherein after determining the preferred destination of N steps, the method further comprises:
when there are a plurality of target point candidates, sequentially selecting the target point candidates other than the preferred destination as a new preferred destination in step i, making i equal to i +1, and returning to step S20;
recalculating the preferred destinations of the N steps, and accumulating the expected time consumption of the preferred destinations corresponding to each step to obtain the accumulated total time consumption of the new planning scheme;
and outputting a plurality of different planning schemes and the corresponding accumulated total consumed time.
5. The queuing time based navigation path planning method according to claim 1, wherein in step S40, the calculating an arrival time from the current position to each of the candidate target points comprises:
acquiring the current position and the path length s of each candidate target point (0) (n), wherein n represents the number of the corresponding target point, and n is a natural number greater than or equal to 2;
according to a preset travelling speed v 0 Calculating the arrival time length T corresponding to each destination (0) (n)＝x (0) (n)*v 0 。
6. The method for planning a navigation path according to claim 1, wherein in step S40, the estimating a queuing time of each of the candidate target points includes:
if the candidate target point has a plurality of transaction windows, calculating the window queuing time of each transaction window, and taking the shortest window queuing time as the queuing time of the corresponding candidate target point.
7. The method for planning a navigation path based on queuing time as claimed in claim 1, wherein in step S40, the estimating of the queuing time of each of the candidate target points specifically comprises:
establishing a queuing time prediction model by adopting historical queuing data, and predicting the queuing time based on the current situation and the queuing time prediction model; wherein the current situation comprises a current time period and a current weather.
8. The navigation path planning method based on queuing time according to claim 7, wherein the establishing of the queuing time prediction model by using the historical data specifically comprises:
establishing an average queue population sequence x over the same time period (0) ＝(x 0 (1),x 0 (2),x 0 (3),.....,x 0 (n)); calculating a grade ratio; if all the stage ratios are in
Interval range, then x (0) As a satisfactory prediction model of the queuing time.
9. The method for planning a navigation path based on queuing time of claim 1, wherein in step S40, the estimating the queuing time of each of the candidate target points comprises:
reporting the queuing condition in real time by an applet pre-downloaded at the terminal, and estimating the queuing time according to the queuing condition; or the terminal acquires the video image of the office in real time, acquires the queuing condition according to the video image and estimates the queuing time.
10. A navigation path planning system based on queuing time is characterized in that:
the target step acquisition module is used for acquiring all target points which need to be passed by for transacting the preset transaction and calculating the total step number N according to the number of the target points;
a candidate target obtaining module, which is in communication connection with the target step obtaining module and is used for obtaining candidate target points of the current step i, wherein i is an integer from 1 to N, and the number of the candidate target points is one or more;
a compulsory pass point target determining module, which is in communication connection with the candidate target obtaining module and is used for recommending the candidate target point as the preferred destination of the current step i under the condition that the number of the candidate target points of the current step i is only one;
and an optimal target determining module, communicatively connected to the candidate target acquiring module, configured to calculate an arrival time from a current location to each of the candidate target points when the number of the candidate target points in the current step i is multiple, estimate a queuing time of each of the candidate target points, calculate an expected time consumption at which a transaction at each of the candidate target points can begin to be handled according to the arrival time and the queuing time corresponding to each of the candidate target points, and recommend the candidate target point with the shortest expected time consumption as the optimal destination in the current step i.
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| CN115440074A (en) * | 2022-08-24 | 2022-12-06 | 中国人民解放军军事科学院战争研究院 | Emergency road recommendation method based on M/M/1/N queuing |
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| CN115440074A (en) * | 2022-08-24 | 2022-12-06 | 中国人民解放军军事科学院战争研究院 | Emergency road recommendation method based on M/M/1/N queuing |
| CN115440074B (en) * | 2022-08-24 | 2024-04-16 | 中国人民解放军军事科学院战争研究院 | Emergency road recommendation method based on M/M/1/N queuing |
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