A navigation path planning method and system

Abstract

The present invention provides a navigation path planning method and system, which obtains all target points that need to be passed through to handle a predetermined transaction; and determines the candidate target point of the current step i; if there is only one candidate target point of the current step i, recommends the candidate target point as the preferred destination of the current step i; if there are multiple candidate target points of the current step i, calculates the arrival time from the current position to each candidate target point and the queuing time of each candidate target point, calculates the estimated time that the affairs of each candidate target point can be handled, and recommends the candidate target point with the shortest estimated 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 present application intelligently recommends the path planning scheme with the shortest time consumption, minimizes the time wasted by users queuing, and improves the efficiency of users.

Description

Technical Field

[0001] The present invention relates to the field of indoor navigation and positioning technology, and in particular to a navigation path planning method and system. Background Art

[0002] When handling affairs in public places, such as hospital physical examinations, government service halls, stations and airports, and large shopping malls, users often need to go back and forth between multiple destinations (service windows, payment windows, etc.) and may need to queue up at each destination. When they need to queue up, users generally do not know which queue has the shortest waiting time, and do not know how to complete all tasks in the shortest time, resulting in a waste of user time and low efficiency. Summary of the invention

[0003] The purpose of the present invention is to provide a navigation path planning method capable of improving work efficiency.

[0004] The objective of the present invention is achieved through the following technical solutions:

[0005] A navigation path planning method, the method comprising:

[0006] S10, obtaining all target points that need to be passed through to handle the scheduled affairs, and calculating the total number of steps N according to the number of the target points;

[0007] S20, 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;

[0008] S30, if there is only one candidate target point in the current step i, recommend the candidate target point as the preferred destination of the current step i, so that i=i+1, and return to step S20;

[0009] S40. If there are multiple alternative target points in the current step i, calculate the arrival time from the current position to each of the alternative target points, estimate the queuing time of each of the alternative target points, and calculate the estimated time required for the transaction to be processed at each of the alternative target points based on the arrival time and the queuing time corresponding to each of the alternative target points. Recommend the alternative target point with the shortest estimated time as the preferred destination for the current step i, so that i=i+1, and return to step S20.

[0010] In one embodiment, obtaining the candidate target point of the current step i specifically includes:

[0011] Obtaining the target points of all the execution steps to be determined;

[0012] Identify independent target points and associated target groups among all the target points of the to-be-determined execution steps, and obtain one or more target points of the first priority order in the associated target group;

[0013] Wherein, the associated target group includes a plurality of the target points having a sequential execution order, and the associated target group may be zero group, one group or multiple groups;

[0014] The independent target point and all the target points corresponding to the first priority order are used as the candidate target points of the current step i.

[0015] In one embodiment, step S30 further includes:

[0016] Calculate the arrival time from the current position to the candidate target point and the queuing time of the candidate target point;

[0017] Calculate the estimated time required for the candidate target point transaction to be processed based on the arrival time and the queuing time;

[0018] The method further includes: after determining the preferred destinations of N steps, accumulating the estimated time consumption of the preferred destinations corresponding to each step to obtain the cumulative total time consumption of the current planning scheme.

[0019] In one embodiment, after determining the preferred destinations of the N steps, the method further includes:

[0020] When there are multiple candidate target points, sequentially select the candidate target points other than the preferred destination as the new preferred destination of the current step i, so that i=i+1, and return to step S20;

[0021] Recalculate the preferred destination of N steps, and add up the estimated time consumption of the preferred destination corresponding to each step to obtain the cumulative total time consumption of the new planning scheme;

[0022] Output multiple different planning schemes and the corresponding accumulated total time consumption.

[0023] In one embodiment, in step S40, the calculation of the arrival time from the current position to each candidate target point includes:

[0024] Get the path length s between the current position and each candidate target point (0) (n), where n represents the number of the corresponding target point, and n is a natural number greater than or equal to 2;

[0025] Calculate the arrival time T corresponding to each destination according to the preset travel speed v0 (0) (n) = x (0)(n)*v0 In one embodiment, estimating the queuing time of each candidate target point includes:

[0026] If there are multiple service windows at the candidate target point, the window queuing time of each service window is calculated, and the shortest window queuing time is used as the queuing time of the corresponding candidate target point.

[0027] In one embodiment, in step S40, estimating the queuing time of each candidate target point specifically includes:

[0028] A queue duration prediction model is established using historical queue data, and the queue duration is predicted based on the current situation and the queue duration prediction model; wherein the current situation includes the current time period and the current weather.

[0029] In one embodiment, the use of historical data to establish a queuing time prediction model specifically includes:

[0030] Establish the average queue number sequence x in the same time period (0) =(x 0 (1),x 0 (2),x 0 (3),.....,x 0 (n)); calculate the level ratio; if all the level ratios are in If the range is x (0) As a satisfactory queuing time prediction model.

[0031] In one embodiment, in step S40, estimating the queuing time of each candidate target point includes:

[0032] The queuing situation is reported in real time by a small program pre-downloaded on the terminal, and the queuing duration is estimated based on the queuing situation; or, the terminal obtains office video images in real time, obtains the queuing situation based on the video images, and estimates the queuing duration.

[0033] In addition, the present invention also provides a navigation path planning system based on queuing time, comprising:

[0034] A target step acquisition module is used to acquire all target points that need to be passed through to handle the scheduled affairs, and calculate the total number of steps N according to the number of the target points;

[0035] A candidate target acquisition module, which is in communication with the target step acquisition module and is used to acquire a candidate target point 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;

[0036] a must-go point target determination module, which is in communication connection with the candidate target acquisition module, and is used to recommend the candidate target point as the preferred destination of the current step i when there is only one candidate target point in the current step i;

[0037] The preferred target determination module is communicated with the alternative target acquisition module and is used to calculate the arrival time from the current position to each alternative target point when there are multiple alternative target points in the current step i, estimate the queuing time of each alternative target point, calculate the estimated time for the transaction of each alternative target point to be processed based on the arrival time and the queuing time corresponding to each alternative target point, and recommend the alternative target point with the shortest estimated time as the preferred destination for the current step i.

[0038] Compared with the prior art, the present invention has the following beneficial effects: the present invention provides a navigation path planning method based on queuing time, by obtaining all the target points that need to be passed to handle the scheduled affairs; and determining the alternative target point of the current step i; if there is only one alternative target point of the current step i, recommend the alternative target point as the preferred destination of the current step i; if there are multiple alternative target points of the current step i, calculate the arrival time from the current position to each alternative target point and the queuing time of each alternative target point, calculate the estimated time that the affairs of each alternative target point can be handled, and recommend the alternative target point with the shortest estimated 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 present application intelligently recommends the path planning scheme with the shortest time consumption, minimizes the time wasted by users in queuing, and improves the efficiency of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flowchart of a navigation path planning method based on queuing time provided by an embodiment of the present invention;

[0040] Figure 2 A simple schematic diagram of an implementation scenario of a navigation path planning method provided by an embodiment of the present invention

[0041] Figure 3 It is a module schematic diagram of a navigation path planning system based on queuing time provided by a real-time example of the present invention. DETAILED DESCRIPTION

[0042] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. It is to be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only some structures related to the present application are shown in the accompanying drawings, rather than all structures. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0043] The terms "including" and "having" and any variations thereof in this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0044] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0045] See also Figure 1 As shown, an embodiment of the present invention provides a flowchart of a navigation path planning method. The application scenarios of the navigation path planning method may include hospitals, independent medical examination institutions, government offices, large shopping malls and other environments, where users need to handle multiple transactions at the same time. It is understandable that users always hope to complete the corresponding transactions in the shortest time. However, the reality is that users cannot know which transaction takes the shortest time to process, and usually process each transaction in turn based on subjective judgment or random selection. It often takes a long time to queue up, and all transactions cannot be completed within the specified time, resulting in a waste of time and delays in the processing of other transactions.

[0046] For ease of understanding, the present invention takes the physical examination scenario of a hospital physical examination center (or an independent physical examination institution) as an example for explanation. As we all know, a physical examination usually includes multiple items, more than a dozen or even dozens, each physical examination item has a dedicated examination room, and the queue situation of each examination room is different. Some examination items take a long time, and some examination items have examination rooms far away. The order in which users accept physical examination items will inevitably affect the time it takes to complete the entire physical examination.

[0047] This embodiment provides a navigation path planning method based on queuing time. Figure 1 , the method comprises the following steps:

[0048] Step S10, obtaining all target points that need to be passed through to handle the scheduled affairs, and calculating the total number of steps N according to the number of the target points.

[0049] Among them, the target point refers to the corresponding location where the user handles multiple affairs, and each target point corresponds to a pending transaction. Taking the above physical examination scenario as an example, each examination room is equivalent to a target point, and all target points are equivalent to the locations that all physical examination items need to pass through.

[0050] The above-mentioned target points also include the transfer points that must be passed to reach the subsequent target location or the final destination, which are determined based on the actual business scenario. In the hospital scenario, when the user is at the hospital gate, he needs to navigate to the internal medicine clinic. At this time, the pre-set transfer point is the registration office, and the target point also includes the transfer point. In the government service hall scenario, the user needs to go to a certain counter at the entrance of the hall. At this time, the pre-set transfer point is the number-taking machine. When there are transfer points in the actual business scenario of the acquired destination, all transfer points are counted in the target point, and the total number of steps N is calculated based on the total number of target points. Specifically, when the number of target points is N, the total number of steps is also N.

[0051] There are many ways to obtain the user's target point, such as the user actively inputting the target point keyword in the search box, quick recommendation based on the user's historical search results, selecting the target point by clicking on the map, multiple target points based on actual business operations, and target points shared by others. In the above physical examination scenario, the target points of the examination process can be imported in advance by the physical examination items.

[0052] Step S20, obtaining candidate target points for 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.

[0053] Each step has one or more candidate target points, and the candidate target points of the current step are identified by a preset algorithm. For example, in a hospital physical examination scenario, the first step is to register at the counter, so there is only one candidate target point for step 1, which is the counter. When the registration is completed, the physical examination items are checked, and it is determined that multiple examination items can be performed in step 2. Therefore, the candidate target points of step 2 include the examination rooms corresponding to the multiple examination items.

[0054] S30, if there is only one candidate target point in the current step i, recommend the candidate target point as the preferred destination of the current step i, so that i=i+1, and return to step S20;

[0055] S40. If there are multiple alternative target points in the current step i, calculate the arrival time from the current position to each of the alternative target points, estimate the queuing time of each of the alternative target points, calculate the estimated time required for the transaction of each of the alternative target points to be processed based on the arrival time and the queuing time corresponding to each of the alternative target points, recommend the corresponding alternative target point whose estimated time is less than that of other alternative target points as the preferred destination for the current step i, make i=i+1, and return to step S20.

[0056] The above steps S30 and S40 are to determine the preferred destination of the current step i. Step S30 is to directly set the alternative target point as the preferred destination when the current step i has only one alternative target point. In other words, the current step i is a must-go step for the alternative target point, and the alternative target point must be executed in this step i. For example, in the above-mentioned physical examination scenario, the first step is to register at the counter before the physical examination can be carried out. Therefore, the target point-counter is the must-go step for step 1. Step S40 is used to select an alternative target point with the shortest time from multiple alternative target points as the preferred destination of the current step. In the hospital physical examination scenario, if step 2 has multiple examination items, each examination item corresponds to an alternative target point. According to the algorithm of step S40, the queuing time and arrival time of each examination item can be calculated, and the examination item with the shortest estimated time is recommended as the preferred destination of the current step 2 based on the queuing time and arrival time.

[0057] Specifically, in step S40, the obtained arrival time and queuing time are added to obtain the estimated time required for each candidate target point to start processing the transaction, the estimated time required for each candidate target point is arranged, and the candidate target point with the shortest estimated time required is recommended as the preferred destination for the current step. In other words, the corresponding candidate target point that can start processing the transaction the fastest is recommended as the preferred destination, and the preferred destination is recommended to be used for processing the corresponding transaction, which can effectively save the user's waiting time and improve the time utilization efficiency.

[0058] By analogy, the determination of the preferred destination after executing all steps can obtain the execution step sequence of all target points, that is, the optimal navigation path planning scheme. Therefore, the navigation path planning method based on queuing time provided by the present invention is that each step is the preferred destination with the shortest time consumption, and can intelligently recommend the path planning scheme with the shortest time consumption, thereby minimizing the time wasted by users in queuing and improving the efficiency of users.

[0059] Specifically, the navigation path planning method is executed by a mobile terminal. The mobile terminal is carried by the user and has navigation and positioning functions, such as a smart watch, a smart phone, a smart bracelet, a smart tablet, etc. The mobile terminal can obtain the user's current location in real time, that is, the current location of the mobile terminal. According to the alternative target point as the navigation destination, the alternative target point can be navigated through the mobile terminal, so as to calculate the arrival time from the current position to the alternative target point according to the path length. In this application, the mobile terminal can also be referred to as the terminal.

[0060] Whether the user is indoors or outdoors, the user's current location can be obtained in real time through the mobile terminal. If in an outdoor scene, the current location is obtained using GPS, Beidou and other positioning methods; if in an indoor environment, the current location can be obtained using WIFI, Bluetooth, geomagnetic and other positioning technologies.

[0061] Furthermore, in step S20, namely the step of "obtaining the candidate target point of the current step i", it specifically includes:

[0062] S22, obtaining the target points of all the steps to be determined;

[0063] S24, identifying independent target points and associated target groups among all the target points of the to-be-determined execution steps, and acquiring one or more target points of the first priority order in the associated target group;

[0064] Wherein, the associated target group includes a plurality of target points having a sequential execution order, the associated target group may be zero, one or more groups, and the independent target point is a target point that can be executed independently, and there is no sequential execution order with other target points;

[0065] S26. Use the independent target point and all target points corresponding to the first priority as the candidate target points for the current step i.

[0066] Among them, obtaining the target points of all the pending execution steps means, in the case of the current step i, removing the target points of the execution steps that have been determined, and the remaining target points are used as the target points of the pending execution steps. Among all the target points of the pending execution steps, there may be one or more groups of associated target groups. Here, an associated target group is understood to be a plurality of target points with a sequential execution order. A group of associated target groups may include 2 target points, or may include a greater number of target points. The associated target groups may include target points of the first priority and target points of the second priority in order of execution priority, and the second priority target points can be arranged for execution only when all the first priority target points have been executed.

[0067] For example, we will take hospital physical examination as an example. Figure 2 .exist Figure 2 In the figure, there are a total of 6 target points AF. X represents the current position, i.e., the starting point. D, E, and F are fasting check items, C is the breakfast target point, and A and B are ordinary check items, i.e., independent target points, which can be checked on an empty stomach or after a meal. In this way, the above D, E, F, and C have a sequential execution order, forming an associated target group. The target points of the first priority order include D, E, and F, and the target point of the second priority order is C. Target points D, E, and F must be checked before target point C. Therefore, when the user is at the starting point X, the alternative target points of the first step include 2 independent target points A and B, and 3 target points D, E, and F of the first priority order in the associated target group.

[0068] There are many other situations for the above-mentioned associated target groups, such as the blood test and blood number taking steps in the hospital physical examination items. The blood drawing number taking step must be before the blood test. Therefore, the blood drawing test and blood number taking steps are a group of associated target groups. Blood drawing number taking is a target point with the first priority, and blood drawing test is a target point with the second priority.

[0069] The independent target points among all candidate target points of the steps to be determined, that is, the independently executed target points, have no order of precedence. When determining the candidate target points of the current step, all the independent target points and one or more target points of the first priority in the associated target group are used as the candidate target points of the current step i.

[0070] In one embodiment, step S30 further includes the following steps:

[0071] S32, calculating the arrival time from the current position to the candidate target point and the queuing time of the candidate target point;

[0072] S34, calculating the estimated time required for the transaction at the candidate target point to be processed according to the arrival time and the queuing time;

[0073] The above steps S32 and S34 are the same as the method for obtaining the estimated time required for the candidate target point transaction to be processed in step S40, and will not be described in detail here.

[0074] In order to facilitate the user to roughly understand the total cumulative time consumed by the navigation path planning scheme and arrange time reasonably. Further, the navigation path planning method also includes:

[0075] S50. After determining the preferred destinations of N steps, the estimated time consumption of the preferred destination corresponding to each step is accumulated to obtain the total accumulated time consumption of the current planning scheme.

[0076] In order to facilitate user reference and comparison, multiple route planning solutions are provided to facilitate user selection. In one embodiment, after calculating the preferred destination in N steps, the method further includes the following steps:

[0077] S52, when there are multiple candidate target points, sequentially select the candidate target points other than the preferred destination as the new preferred destination of the current step i, so that i=i+1, and return to step S20;

[0078] S54, recalculating the preferred destinations of N steps, and accumulating the estimated time consumption of the preferred destinations corresponding to each step to obtain a new cumulative total time consumption of different planning schemes;

[0079] S56: Output multiple different planning schemes and the corresponding accumulated total time consumption.

[0080] Furthermore, in step S40, namely the step of "calculating the arrival time from the current position to each candidate target point", specifically includes:

[0081] S42: Obtain the path length s between the current position and each candidate target point. (0) (n), where n represents the number of the corresponding target point, and n is a natural number greater than or equal to 2;

[0082] S44, calculating the arrival time T corresponding to each candidate target point according to the preset travel speed v0. (0) (n) = x (0) (n)*v0.

[0083] That is, in the case of the current position, starting from the current position, the path length to each candidate target point is calculated, and the arrival time to each candidate target point is calculated based on the path length and the travel speed.

[0084] According to the arrival time of each candidate target point, the path length sequence s between the current position and each candidate target point is obtained (0) =(s (0) (1), s (0) (2), s (0) (3),......,s (0) (n)). According to the path length sequence and the preset travel speed v0, the arrival time sequence T of each candidate target point is obtained. (0) =s (0) / v0. Wherein, v0 is the walking speed, and the preset walking speed v0=0.8m / s.

[0085] In one embodiment, in step S40, namely the step of “estimating the queuing time of each candidate target point”, the following steps are specifically included:

[0086] If there are multiple service windows at the candidate target point, the window queuing time of each service window is calculated, and the shortest window queuing time is used as the queuing time of the corresponding candidate target point.

[0087] In another embodiment, in step S40, namely the step of "estimating the queuing time of each candidate target point", the steps are specifically included:

[0088] A queue duration prediction model is established using historical queue data, and the queue duration is predicted based on the current situation and the queue duration prediction model.

[0089] It is understandable that the queue time has historical data reference, and the number of people queuing in the same time period usually has data similarity. The queue time can be predicted using historical queue data. In one embodiment, a queue time prediction model is established using historical queue data, and the queue time is predicted based on the current situation and the queue time prediction model.

[0090] In the specific steps, establish the average queue number sequence x in the same time period (0) =(x 0 (1), x 0 (2), x 0 (3), ....., x 0 (n)); calculate all the level ratios λ(k); if all the level ratios λ(k) are in If the range is x (0) As a satisfactory queue time prediction model.

[0091] The calculation formula of λ(k) is:

[0092]

[0093] It should be noted that the above “average queue number sequence in the same time period” is a sequence composed of the average queue number in the same time period on different dates. Where n represents the number of different historical data dates, x represents the average queue number in the same time period on different dates. (0) (n) represents the average number of people queuing in the same period of time with date number n. The average number of people queuing in the same period of time on multiple different dates of historical data is combined into a sequence to obtain x (0) It is understandable that the number of people queuing at the current or future time can be predicted by the historical queue number sequence of the same period in the past.

[0094] In another embodiment, the queue length prediction model is built using a grey system prediction model, which is denoted as GM(1,1) modeling. The steps of GM(1,1) modeling are as follows:

[0095] 1. The original data x(0) Do a cumulative calculation.

[0096] Right now

[0097]

[0098] 2. Construct data matrix B and data vector Y

[0099]

[0100]

[0101] 3. Use univariate linear regression to obtain valuation calculations

[0102] That is, a is the development coefficient, b is the grey action, and is the parameter vector to be estimated, and find the values ​​of a and b.

[0103]

[0104] 4. Build the model

[0105] For the grey differential equation of GM(1,1), if the grey derivative x (0) (k) time k = 2, 3..., n as a continuous variable t, then x (1) (t) can be viewed as a function of time t.

[0106] Then x (0) The corresponding reciprocal of (k) is

[0107] We can get the differential equation

[0108]

[0109] 5. Calculate the generated sequence value and model restoration value

[0110] Let k = 1, 2, 3, 4...6. From the time response function, we can get

[0111]

[0112] Calculate the model values ​​in sequence:

[0113]

[0114] Furthermore, the queue time required for the candidate target point can be predicted based on the average transaction processing time and the number of queued people. The queue time sequence is:

[0115] t (0) =(t(0) (1), t (0) (2), ..., t (0) (n));

[0116] Among them, t (0) (n) refers to the length of time required to queue at different alternative target points n at the current stage.

[0117] In order to ensure the accuracy of the queue time prediction model, it is also necessary to test the queue time prediction model. The model test can use historical queue data within a period of time, and the rest of the historical queue data is used for modeling. When the test accuracy meets the requirements, the prediction of the queue time prediction model is considered to be credible. The following is a detailed introduction to the model test method.

[0118] (1) Verify the difference between the model value and the original value data

[0119] ①Relative residual formula

[0120]

[0121] If |ε(k)| is less than 0.1, it is considered to meet higher requirements, and if it is less than 0.2, it meets general requirements.

[0122] (2) Check level ratio deviation value

[0123] ②Grade ratio deviation value

[0124]

[0125] If |p(k)| is less than 0.1, it is considered to meet the higher requirements. If it is less than 0.2, it meets the general requirements.

[0126] If the data deviation value obtained by the above verification method is less than or equal to 0.2, it is considered that the queue time prediction model can make a prediction.

[0127] In order to improve the accuracy of the prediction, the historical queue data is classified in advance, and the classification criteria are based on factors that affect the number of people in the queue, which can be weather, time period, and working days or non-working days. In a specific embodiment, the historical queue data is classified according to time periods and normal weather and abnormal weather, and the current situation includes the current time period and the current weather. In some embodiments, the target point also handles affairs on non-working days. Further, the time period is also divided according to the working day time period and the non-working day time period. After the classification according to the factors that affect the number of people in the queue, the prediction accuracy of the queue duration prediction model can be significantly improved.

[0128] The above-mentioned method of estimating the queuing time needs to rely on historical queuing data, which is a non-real-time estimation method. In other embodiments, the queuing time can also be estimated in real time. Specifically, the queuing situation of each candidate target point is identified in real time, and the corresponding queuing time is estimated according to the queuing situation. The queuing situation can be reported in real time by a small program pre-downloaded on the terminal, and the queuing time can be estimated according to the queuing situation; or, the terminal obtains the video image of the office in real time, and the queuing situation is known according to the video image to estimate the queuing time. In these embodiments of real-time estimation of the queuing time, the estimation of the queuing time refers to the real-time data, which can more accurately reflect the current queuing situation and estimate the queuing time more accurately.

[0129] It should be noted that if the candidate target point does not need to queue, the queue time is 0. If there are multiple service windows at the candidate target point, the window queue time of each service window is calculated, and the shortest window queue time is used as the queue time of the corresponding candidate target point.

[0130] In the specific steps, the estimated time required to start handling the affairs of each candidate target point is calculated:

[0131] The above arrival time sequence T (0) and the queue length sequence t (0) Add together to get the estimated time sequence T for each destination (1) .

[0132] The estimated time sequence T of each candidate target point (1) To arrange, the arrangement formula is:

[0133]

[0134] in: It means taking out r elements from n elements and arranging (sorting).

[0135] n: total number of elements (total number of candidate target points); r: number of elements involved in the selection; ! represents factorial.

[0136] After the above arrangement, the candidate target points with the estimated time consumption in the first r positions can be obtained.

[0137] The terminal can also recommend multiple candidate destinations with shorter estimated travel times for the user to choose from, rather than just recommending one of the destinations with the shortest estimated travel time. Specifically, the terminal recommends the first r candidate destinations as the priority destinations according to the above arrangement formula, and gives the estimated travel time data as a reference, or gives the priority of the recommended options in order from short to long estimated travel time, for the user to choose freely. In this way, the user's freedom of choice is improved, and the user experience is better.

[0138] Through the navigation method of the present invention, when a user arrives at a certain place, each step can accurately select an alternative target point with the shortest time required to handle affairs, with the shortest queuing time and arrival time. The user can handle all affairs of the target point in the shortest time, making the time for the user to go out for business controllable and more efficient.

[0139] In addition, if Figure 3 As shown, the present invention also proposes a navigation path planning system 100 based on queuing time, including a target step acquisition module 101, an alternative target acquisition module 102, a must-pass point target determination module 104 and a preferred target determination module 106.

[0140] The target step acquisition module 101 is used to acquire all target points that need to be passed through to handle the scheduled affairs, and calculate the total number of steps N according to the number of the target points;

[0141] The candidate target acquisition module 102 is in communication with the target step acquisition module 101 and is used to acquire the candidate target points of 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;

[0142] The must-go point target determination module 104 is in communication with the candidate target acquisition module 102, and is used to recommend the candidate target point as the preferred destination of the current step i when there is only one candidate target point in the current step i;

[0143] The preferred target determination module 106 is in communication with the alternative target acquisition module 102, and is used to calculate the arrival time from the current position to each alternative target point when there are multiple alternative target points in the current step i, estimate the queuing time of each alternative target point, calculate the estimated time for the transaction of each alternative target point to be processed based on the arrival time and queuing time corresponding to each alternative target point, and recommend the alternative target point with the shortest estimated time as the preferred destination for the current step i.

[0144] The navigation path planning system based on queuing time described in this embodiment corresponds to the above-mentioned navigation path planning method based on queuing time. The functions of each module in the navigation path planning system based on queuing time in this embodiment are explained in detail in the corresponding method embodiment and will not be repeated here.

[0145] The present invention implements all or part of the process in the above method, and can also be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0146] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, servers or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program codes.

[0147] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the description and drawings of this application, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A navigation path planning method, characterized in that: The method comprises: S10, obtaining all target points that need to be passed through to handle the scheduled affairs, and calculating the total number of steps N according to the number of the target points; S20, 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; S30, if there is only one candidate target point in the current step i, recommend the candidate target point as the preferred destination of the current step i, so that i=i+1, and return to step S20; S40, if there are multiple candidate destination points in the current step i, calculate the arrival time from the current position to each of the candidate destination points, estimate the queuing time of each of the candidate destination points, calculate the estimated time required for the affairs of each of the candidate destination points to be processed according to the arrival time and the queuing time corresponding to each of the candidate destination points, recommend the candidate destination point with the shortest estimated time as the preferred destination of the current step i, make i=i+1, and return to step S20; In step S40, estimating the queuing time of each candidate target point specifically includes: Establish the average queue number sequence in the same time period ; Calculate the level ratio; If all the level ratios are in The interval range will be used as the satisfactory queue time prediction model, and the queue time prediction model will be used to predict the queue time based on the current situation and the queue time prediction model; wherein the current situation includes the current time period and the current weather.

2. The navigation path planning method according to claim 1, characterized in that: The step of obtaining the candidate target point of the current step i specifically includes: Obtaining the target points of all the execution steps to be determined; Identify independent target points and associated target groups among all the target points of the to-be-determined execution steps, and obtain one or more target points of the first priority order in the associated target group; Wherein, the associated target group includes a plurality of the target points having a sequential execution order, and the associated target group may be zero group, one group or multiple groups; The independent target point and all the target points corresponding to the first priority order are used as the candidate target points of the current step i.

3. The navigation path planning method according to claim 1, characterized in that: Step S30 further includes: Calculate the arrival time from the current position to the candidate target point and the queuing time of the candidate target point; Calculate the estimated time required for the candidate target point transaction to be processed based on the arrival time and the queuing time; The method further includes: after determining the preferred destinations of N steps, accumulating the estimated time consumption of the preferred destinations corresponding to each step to obtain the cumulative total time consumption of the current planning scheme.

4. The navigation path planning method according to claim 3, characterized in that: After determining the preferred destinations of the N steps, the method further includes: When there are multiple candidate target points, sequentially select the candidate target points other than the preferred destination as the new preferred destination of the current step i, so that i=i+1, and return to step S20; Recalculate the preferred destination of N steps, and add up the estimated time consumption of the preferred destination corresponding to each step to obtain the cumulative total time consumption of the new planning scheme; Output multiple different planning schemes and the corresponding accumulated total time consumption.

5. The navigation path planning method according to claim 1, characterized in that: In step S40, the calculation of the arrival time from the current position to each candidate target point includes: Get the path length between the current position and each candidate target point , where n represents the number of the corresponding target point, and n is a natural number greater than or equal to 2; According to the preset travel speed Calculate the arrival time corresponding to each destination .

6. The navigation path planning method according to claim 1, characterized in that: In step S40, estimating the queuing time of each candidate target point includes: If there are multiple service windows at the candidate target point, the window queuing time of each service window is calculated, and the shortest window queuing time is used as the queuing time of the corresponding candidate target point.

7. The navigation path planning method according to claim 1, characterized in that: In step S40, estimating the queuing time of each candidate target point includes: The queuing situation is reported in real time by a small program pre-downloaded on the terminal, and the queuing duration is estimated based on the queuing situation; or, the terminal obtains office video images in real time, obtains the queuing situation based on the video images, and estimates the queuing duration.

8. A navigation path planning system based on queuing time, characterized in that: A target step acquisition module is used to acquire all target points that need to be passed through to handle the scheduled affairs, and calculate the total number of steps N according to the number of the target points; A candidate target acquisition module, which is in communication with the target step acquisition module and is used to acquire a candidate target point 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 must-go point target determination module, which is in communication connection with the candidate target acquisition module, and is used to recommend the candidate target point as the preferred destination of the current step i when there is only one candidate target point in the current step i; The preferred target determination module is in communication with the candidate target acquisition module and is used to calculate the arrival time from the current position to each of the candidate target points when there are multiple candidate target points in the current step i, and establish an average queue number sequence in the same time period. ; Calculate the level ratio; If all the level ratios are in interval range, it will be used as the satisfactory queuing time prediction model, and the queuing time will be predicted based on the current situation and the queuing time prediction model; wherein, the current situation includes the current time period and the current weather, and according to the arrival time and the queuing time corresponding to each alternative target point, the estimated time for the transaction to be processed at each alternative target point is calculated, and the alternative target point with the shortest estimated time is recommended as the preferred destination for the current step i.

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