CN116629439A

CN116629439A - Platform waiting number prediction method and device, terminal equipment and storage medium

Info

Publication number: CN116629439A
Application number: CN202310638237.1A
Authority: CN
Inventors: 曾明; 秦伟; 谢嘉乐
Original assignee: PCI Technology Group Co Ltd; PCI Technology and Service Co Ltd
Current assignee: PCI Technology Group Co Ltd; PCI Technology and Service Co Ltd
Priority date: 2023-05-31
Filing date: 2023-05-31
Publication date: 2023-08-22

Abstract

The embodiment of the application discloses a method, a device, terminal equipment and a storage medium for predicting the number of passengers on a platform. Then, whether trains exist at the current moment is further determined, if so, the number of boarding persons of each carriage is determined, and the number of waiting persons of each carriage is updated; if not, the number of waiting persons in each carriage is directly updated. According to the method and the device for predicting the waiting number of the platform, the probability that various platform arrival modes reach each carriage is determined, so that the accuracy of predicting the waiting number of each carriage can be improved, and the technical problem of poor accuracy in the mode of counting the waiting number of the platform in the prior art is solved.

Description

Platform waiting number prediction method and device, terminal equipment and storage medium

Technical Field

The embodiment of the application relates to the field of rail transit, in particular to a method, a device, terminal equipment and a storage medium for predicting the number of passengers waiting at a platform.

Background

At present, subways become an important transportation mode for people. Along with the increasing number of passengers taking subways, the number of people waiting for each shielding door of a station platform is different in the early peak period due to different arrival modes selected by the passengers for entering the station platform, so that the number of people waiting for each shielding door is different. Currently, researches on the number of people and crowding degree of all areas of a subway non-transfer station platform mainly utilize a simulation model to count the number of passengers on the whole station, however, the mode cannot accurately obtain the personnel distribution of all areas of the station, so that operators are difficult to control passenger flow according to the number of passengers.

In summary, in the prior art, the way of counting the number of passengers waiting at the platform has the technical problem of poor accuracy.

Disclosure of Invention

The embodiment of the invention provides a method, a device, terminal equipment and a storage medium for predicting the number of bus stops, which can improve the accuracy in predicting the number of bus stops and solve the technical problem of poor accuracy in the mode of counting the number of bus stops in the prior art.

In a first aspect, an embodiment of the present invention provides a method for predicting a waiting number of a platform, including:

Determining the number of downlink people in various platform arrival modes at each moment of a target station according to the current target time period, wherein the target time period is obtained by dividing the time granularity in advance;

determining the probability that various platform arrival modes reach each carriage, and determining the number of newly-increased waiting vehicles reaching each carriage at each moment in a target time period according to the probability and the number of pedestrians;

judging whether a train arrives at a station at the current moment;

if a train arrives at the station, determining the number of people on each carriage after the train arrives;

updating the waiting number of each carriage at the current moment according to the number of passengers on each carriage, the newly-increased waiting number of each carriage and the last updated waiting number of each carriage;

if no train arrives at the station, the waiting number of each carriage at the current moment is updated according to the newly increased waiting number of each carriage and the waiting number of each carriage at the previous moment.

In a second aspect, an embodiment of the present invention provides a device for predicting a number of waiting persons at a platform, including:

the descending number determining module is used for determining the number of descending people of various platform arrival modes at each moment of the target station according to the current target time period, and the target time period is obtained by dividing the time granularity in advance;

The waiting number determining module is used for determining the probability that various platform arrival modes reach each carriage and determining the newly-increased waiting number of each carriage at each moment in the target time period according to the probability and the number of pedestrians;

the arrival judging module is used for judging whether a train arrives at the station at the current moment;

the boarding number determining module is used for determining the boarding number of each carriage after the arrival of the train if the train arrives at the station;

the first person number updating module is used for updating the waiting number of each carriage at the current moment according to the number of passengers on each carriage, the newly added waiting number of each carriage and the waiting number of each carriage updated last time;

and the second number updating module is used for updating the number of waiting persons of each carriage at the current moment according to the newly increased number of waiting persons of each carriage and the number of waiting persons of each carriage at the previous moment if no train arrives at the station.

In a third aspect, an embodiment of the present invention provides a terminal device, where the terminal device includes a processor and a memory;

the memory is used for storing the computer program and transmitting the computer program to the processor;

the processor is configured to execute a method of predicting a waiting number of a platform according to the first aspect according to instructions in the computer program.

In a fourth aspect, embodiments of the present invention provide a storage medium storing computer-executable instructions that, when executed by a computer processor, are configured to perform a platform head room prediction method as in the first aspect.

In the embodiment of the invention, the number of the passengers arriving at each carriage at each moment in the target time period is determined by determining the number of the passengers arriving at each platform in the target station and determining the probability of arriving at each carriage in each platform arriving mode. Then, whether trains exist at the current moment is further determined, if so, the number of boarding persons of each carriage is determined, and the number of waiting persons of each carriage is updated; if not, the number of waiting persons in each carriage is directly updated. According to the method and the device for predicting the waiting number of the platform, the probability that various platform arrival modes reach each carriage is determined, so that the accuracy of predicting the waiting number of each carriage can be improved, and the technical problem of poor accuracy in the mode of counting the waiting number of the platform in the prior art is solved. In addition, the embodiment of the invention can obtain the personnel distribution of each area of the station, so that operators can more comprehensively obtain the personnel distribution condition in the station, thereby more scientifically performing guest flow control.

Drawings

Fig. 1 is a flowchart of a method for predicting the number of passengers waiting at a platform according to an embodiment of the present application.

Fig. 2 is a flowchart of another method for predicting the number of bus stops according to an embodiment of the present application.

Fig. 3 is a schematic flow chart of determining the number of passengers transported at each moment in time of an elevator according to an embodiment of the present application.

Fig. 4 is a schematic flow chart of determining the number of passengers transported at each moment of an escalator according to an embodiment of the present application.

Fig. 5 shows a probability of a passenger determining different arrival patterns at each car according to an embodiment of the present application.

Fig. 6 is a flowchart illustrating an example of determining the number of boarding passes for each car after a train arrives at a stop according to an embodiment of the present application.

Fig. 7 is a schematic structural diagram of a platform waiting number prediction device according to an embodiment of the present application.

Fig. 8 is a schematic diagram of a terminal device according to an embodiment of the present application.

Detailed Description

The following description and the drawings sufficiently illustrate specific embodiments of the application to enable those skilled in the art to practice them. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in, or substituted for, those of others. The scope of embodiments of the application encompasses the full ambit of the claims, as well as all available equivalents of the claims. Embodiments may be referred to herein, individually or collectively, by the term "application" merely for convenience and without intending to voluntarily limit the scope of this application to any single application or inventive concept if more than one is in fact disclosed. Relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed. Various embodiments are described herein in a progressive manner, each embodiment focusing on differences from other embodiments, and identical and similar parts between the various embodiments are sufficient to be seen with each other. The structures, products and the like disclosed in the embodiments correspond to the parts disclosed in the embodiments, so that the description is relatively simple, and the relevant parts refer to the description of the method parts.

Referring to fig. 1, fig. 1 is a flowchart of a method for predicting the number of bus stops according to an embodiment of the present invention. The platform waiting number prediction method provided by the embodiment of the invention can be executed by the terminal equipment, the terminal equipment can be realized in a software and/or hardware mode, and the terminal equipment can be formed by two or more physical entities or one physical entity. For example, the terminal device may be a computer, an upper computer, a server, or the like. In addition, the embodiment of the invention is realized on the basis that after the train arrives at the station, passengers completely come out or arrive at the station hall before the next train arrives, and the method comprises the following steps:

step 101, determining the number of downlink people in various platform arrival modes at each moment of a target station according to the current target time period, and dividing the time granularity in advance by the target time period.

First, 24 hours are divided in advance according to time granularity in this embodiment, thereby obtaining a plurality of time periods. For example, when dividing by temporal granularity, the temporal granularity may be divided into 5 minutes or 10 minutes, i.e., one period of time every 5 minutes or every 10 minutes. And then, according to the current time, determining the current target time period, and predicting the number of platform waiting persons at each moment in the target time period. Specifically, during prediction, firstly, the number of downlink people in various platform arrival modes at each moment of a target station in the current target time period needs to be determined. The target station refers to a station appointed by a user in advance, and can be set according to actual needs. The arrival mode of the station means an arrival mode between a hall and a station, and for example, passengers can arrive at the station from the hall by lifting/lowering an elevator, arrive at the station from the hall by escalator, or arrive at the station from the hall by stairs. In one embodiment, historical statistics of a target time period can be obtained, wherein the historical statistics comprise subway passenger flow OD data, elevator data and escalator data, wherein the subway passenger flow OD data comprises traffic card ID, identity card ID, mobile phone number, traffic card type, entrance ID, entrance time, exit ID, exit time and the like, the elevator data comprises elevator numbers, elevator running direction (ascending/descending), elevator passenger closing time, elevator running period load and the like, and the escalator data comprises escalator numbers, escalator length, escalator speed, load at each moment of the escalator and the like. And finally, determining the downlink number of the different platform arrival modes at each moment according to the uplink and downlink ratios of the passenger flows and the number of the passengers transported by the different platform arrival modes at each moment in the target time period.

Step 102, determining the probability that each platform arrival mode arrives at each carriage, and determining the number of newly-increased waiting vehicles arriving at each carriage at each moment in the target time period according to the probability and the number of pedestrians.

After determining the number of downlink persons in different arrival modes of the platform, the probability that each arrival mode of the platform arrives at each carriage needs to be further determined. By way of example, the time that a passenger moves to a screening door corresponding to each car after arriving at the station via various station arrival patterns can be determined, thereby determining the probability that the various station arrival patterns arrive at each car. It can be appreciated that the longer the time, the lower the probability of reaching the car. And then determining the number of newly-increased waiting vehicles reaching each carriage at each moment in the target time period according to the probability of reaching each carriage at each station arrival mode and the number of downlink persons of different station arrival modes at each moment.

Step 103, judging whether a train arrives at the station at the current moment.

After determining the number of new waiting persons reaching each carriage at each moment, further judging whether a train arrives at the station at the current moment.

Step 104, if a train arrives at the station, determining the number of boarding persons of each carriage after the train arrives.

If the train arrives at the station at the current moment, the number of people on each carriage after the train arrives at the station is further determined. For example, the number of boarding persons in each carriage after the train arrives at the platform at different moments can be counted according to the historical statistical data and stored in the boarding person table. The number of people on each carriage after the train arrives can be determined by inquiring the number of people on the train.

Step 105, updating the waiting number of each carriage at the current moment according to the number of passengers on each carriage, the newly added waiting number of each carriage and the last updated waiting number of each carriage.

And then, the number of the waiting persons of each carriage updated last time can be obtained, the number of the waiting persons of each carriage is updated according to the number of the boarding persons of each carriage and the number of the newly-increased waiting persons of each carriage after the train arrives at the station, so that the number of the waiting persons of each carriage at the current moment is obtained, and the waiting congestion degree of each carriage is determined according to the number of the waiting persons of each carriage.

And 106, if no train arrives at the station, updating the number of waiting persons of each carriage at the current moment according to the newly increased number of waiting persons of each carriage and the number of waiting persons of each carriage at the previous moment.

If no train arrives at the station, the number of the waiting persons of each carriage at the current moment can be updated according to the newly increased number of the waiting persons of each carriage and the number of the waiting persons of each carriage at the previous moment, and the waiting congestion degree of each carriage is determined according to the number of the waiting persons of each carriage.

As shown in fig. 2, fig. 2 is a flowchart of another method for predicting the number of bus stops according to an embodiment of the present invention, and the method shown in fig. 2 is a specific method for predicting the number of bus stops, where the method includes:

step 201, obtaining the uplink and downlink proportion of the passenger flow in the current target time period.

In this embodiment, the ratio of the up-and-down traffic in the current target time period needs to be obtained first, where the ratio of the up-and-down traffic refers to the ratio of the number of pedestrians in the traffic to the number of people in the down traffic. In one embodiment, historical subway passenger flow OD data of a target station can be obtained, the average pedestrian number and the average pedestrian number in a target time period are calculated according to the historical subway passenger flow OD data, and the ratio of the average pedestrian number to the average pedestrian number is calculated, so that the up-down ratio of the passenger flow can be obtained. In another embodiment, in order to increase the data processing speed, the up-down ratio of the passenger flow in each time period may be stored in a table of up-down ratio of the passenger flow, and then the up-down ratio of the passenger flow in the target time period may be obtained quickly by means of table lookup.

Step 202, obtaining the number of passengers corresponding to the arrival modes of various platforms in the target station in each moment of the target time period.

Then, the number of passengers corresponding to the arrival modes of various platforms in the target station needs to be further acquired at each moment of the target time period. The number of passengers corresponding to the arrival modes of the various platforms refers to the number of passengers currently transported by the arrival modes of the various platforms. In one embodiment, the number of passengers corresponding to the arrival modes of various platforms in the target station at each moment can be obtained through a table look-up mode.

In one embodiment, the arrival modes of the platform include elevator, escalator and stairway, and correspondingly, the number of passengers corresponding to the arrival modes of the various platforms in the target station in each moment of acquiring the target time period in step 202 includes:

step 2021, acquiring the first passenger number corresponding to the elevator in the target station, the second passenger number corresponding to the escalator and the third passenger number corresponding to the stair in each time of the target time period from the pre-constructed passenger number information table.

In one embodiment, the user may calculate the first passenger number corresponding to the elevator, the second passenger number corresponding to the escalator and the third passenger number corresponding to the stairway in each time of the target time period in advance according to the subway passenger flow OD data of the history of the target station, that is, the passenger number transported by the elevator, the passenger number transported by the escalator and the passenger number using the stairway in each time of the target time period. And then, constructing a passenger number information table according to the passenger numbers corresponding to different arrival modes of the platform at each moment, and storing the passenger number information table. And then, acquiring the first passenger number corresponding to the elevator in the target station, the second passenger number corresponding to the escalator and the third passenger number corresponding to the stair in each moment of the target time period from the passenger number information table.

On the basis of the above embodiment, the passenger number information table is constructed in advance by the following method:

step 20211, counting historical passenger flow of each time period in the history of the target station.

When the passenger number information table is built, firstly, the historical passenger flow of each time period on the history of the target station is counted according to the subway passenger flow OD data of the history of the target station, and the historical number of passengers entering the station and the historical number of passengers exiting the station in each time period can be determined according to the historical passenger flow.

Step 20212, determining the passenger carrying number of the elevator in each lifting time in each time period, and counting the number of the first passengers transported at each time in the history of the elevator according to the passenger carrying number.

And then, further determining the passenger carrying number of the historical elevator in each lifting time period, and counting the number of the first passengers transported at each time in the history of the elevator according to the passenger carrying number and time of each lifting time. For example, the passenger carrying number of the elevator in each lifting process can be calculated according to the load data of the elevator after the elevator is closed in each lifting process.

On the basis of the above embodiment, step 20212 determines the number of passengers carried by the elevator during each lifting in each time period, and counts the number of primary passengers transported by the elevator at each time in history according to the number of passengers, including:

Step 202121, determining a first time when the elevator ascends each time and a second time when the elevator descends each time.

When counting the number of first passengers transported at each moment in the history of the elevator, the number of times of lifting of the elevator in each time period can be firstly obtained, and the first moment when the elevator ascends each time and the second moment when the elevator descends each time are determined.

And 202122, acquiring ascending load data of the elevator after the door is closed in the platform when the elevator ascends each time.

After the first moment when each lifting elevator rises is determined, the rising load data after the door is closed in the platform when each lifting elevator rises can be obtained according to the first moment.

And 202123, determining the number of passengers transported by the elevator during each ascending according to the ascending load data and the no-load data of the elevator.

After the ascending load data of the elevator after the door is closed in the platform at each time is obtained, the number of passengers transported by the elevator at each ascending time can be determined according to the ascending load data and the no-load data of the elevator. Specifically, the number of passengers transported by the elevator during each ascent can be determined by subtracting the empty load data from the ascent load data and dividing the data by the average weight.

And 202124, acquiring descending load data after the door is closed in a hall when the elevator descends each time.

And 202125, determining the number of passengers transported by the elevator during each descending according to the descending load data and the no-load data.

Similarly, when the number of passengers transported by the elevator is calculated when the elevator descends each time, the descending load data after the elevator is closed in the hall is required to be obtained when the elevator descends each time, and the average weight is divided by the descending load data minus the no-load data, so that the number of passengers transported by the elevator descends each time can be obtained.

Step 202126, counting the number of first passengers transported at each time in the history of the elevator according to the first time, the second time, the number of passengers transported at each time of the elevator and the number of passengers transported at each time of the elevator.

And finally, the first time when the elevator ascends each time and the number of passengers transported each time can be stored, the second time when the elevator descends each time and the number of passengers transported each time can be stored, and the number of the first passengers transported at each time of the elevator can be counted according to the stored data. In one embodiment, the door opening time of each ascending time of the elevator can be obtained, the arrival information of the train can be matched according to the door opening time, and the number of passengers transported by the elevator in the corresponding summarized time period of the train can be subsequently obtained according to the door opening time, and the specific process is shown in fig. 3. In another embodiment, an average of the number of passengers transported per time instant of the elevator over a historical period of time may be calculated and taken as the first number of passengers transported per time instant of the elevator.

Step 20213, acquiring first load data of the escalator in each time period in history of the target station.

When the passenger number information table is constructed, the number of passengers transported by the escalator at each moment needs to be further counted. Specifically, first load data of the escalator in each time period in the history of the target station needs to be acquired.

Step 20214, determining second load data of each moment in the history of the escalator according to the first load data, and determining the number of second passengers transported by each moment in the history of the escalator according to the second load data.

After the first load data of each time period in the escalator history is obtained, the second load data of each moment in the escalator history can be further determined by taking seconds as a unit, and the number of second passengers transported at each moment in the escalator history is determined according to the second load data of each moment. The second passenger number transported in this way refers to the number of passengers leaving the escalator at this time, not the number of passengers on the escalator. In one embodiment, the average load data for each time instant may be used as the second load data for each time instant by calculating the average load data for each time instant over a period of time.

On the basis of the above embodiment, determining the number of second passengers transported at each moment in the history of the escalator according to the second load data in step 20214 includes:

step 202141, determining a first transportation period when the passenger is present on the escalator and a second transportation period when the passenger is not present according to the second load data.

After the second load data is acquired, a plurality of first transportation periods when passengers are present on the escalator and a plurality of second transportation periods when no passengers are present on the escalator can be determined according to the second load data.

Step 202142, for each first transportation session, determining a start time and an end time of the first transportation session, while determining a first time length required for the passenger from the start of the escalator to the end of the escalator.

After a plurality of first transportation periods are determined, for each first transportation period, a start time and an end time of the first transportation period are determined. While determining the first time period required for the passenger from the start point of the escalator to the end point of the escalator, in particular, the first time period required for the passenger from the start point of the escalator to the end point of the escalator can be determined by the following formula:

Where len denotes the length of the escalator and speed denotes the average speed of the escalator during operation.

Step 202143, traversing each time in the first transportation period, and determining whether the currently traversed time is greater than the first duration from the starting time.

And then, traversing in units of seconds in each first transportation period, and determining whether the currently traversed time is greater than the first duration from the starting time of the first transportation period.

And step 202144, if the data is larger than the first load data, acquiring second load data corresponding to the current traversing time and second load data corresponding to the last traversing time.

If it is determined that the current traversed time is greater than the first duration from the start time of the first transportation period, the second load data corresponding to the current traversed time and the second load data corresponding to the last traversed time are further provided.

Step 202145, determining the number of second passengers transported at each time in the history of the escalator according to the second load data corresponding to the current time and the second load data corresponding to the last time.

And then, determining the number of second passengers transported at each moment in the history of the escalator according to the second load data corresponding to the current traversing moment and the second load data corresponding to the last traversing moment. Specifically, if the second load data corresponding to the current traversed moment is greater than the second load data corresponding to the last traversed moment, determining that the number of people leaving the escalator at the current traversed moment is 1; if the second load data corresponding to the current traversing moment = the second load data corresponding to the last traversing moment, determining that the number of people leaving the escalator at the current traversing moment is 2; and if the second load data corresponding to the current traversed moment is the second load data corresponding to the last traversed moment, continuously acquiring the full load rate of the escalator at the current traversed moment, if the full load rate > =0.85, determining that the number of people leaving the escalator at the current traversed moment is 3, and if the full load rate is less than 0.85, determining that the number of people leaving the escalator at the current traversed moment is 2. In one embodiment, the process of determining the number of secondary passengers is shown in FIG. 4.

Step 20215, determining the number of third passengers passing at each moment on the stair history according to the historical passenger flow, the number of first passengers and the number of second passengers.

After the number of first passengers transported at each moment in the history of the elevator and the number of second passengers transported at each moment in the history of the escalator are determined, the number of third passengers passing at each moment in the history of the escalator can be determined further according to the historical passenger flow of each time period, the number of first passengers and the number of second passengers.

Based on the above embodiment, determining the number of third passengers passing at each time on the stair history according to the historical passenger flow volume, the number of first passengers and the number of second passengers in step 20215 includes:

step 202151, counting the first total passenger number transported by the elevator and the second total passenger number transported by the escalator in each time period according to the first passenger number and the second passenger number.

First, the first total passenger number transported by the elevator and the second total passenger number transported by the escalator in each time period in the history can be counted according to the first passenger number transported by the elevator in each time in the history and the second passenger number transported by the escalator in each time in the history.

And 202152, subtracting the first total passenger number and the second total passenger number from the historical passenger flow of each time period to obtain the third total passenger number of the stairs passing through each time period historically.

And then, subtracting the first total passenger number and the second total passenger number from the historical passenger flow of each time period to obtain the third total passenger number which is passed by the stairs in each time period. It can be understood that in this embodiment, the first total passenger number and the second total passenger number are respectively for one elevator and one escalator, when there are multiple elevators and escalators, the historical passenger flow of each time period in this step needs to be subtracted by the first total passenger number corresponding to all elevators and the second total passenger number corresponding to all escalators, so that the third total passenger number passing through the stairs in each time period can be obtained.

And 202153, determining the number of third passengers passing at each moment on the stair history according to the number of the third passengers.

And finally, according to the number of the third passengers passing through the stairs in each time period in the history, the number of the third passengers passing through the stairs in each time period in the history can be calculated. For example, the distribution of passengers passing through the stairs at each moment in each time period can be counted, and the number of third passengers passing through the stairs at each moment in the history can be calculated according to the number of third passengers and the distribution. In addition, when a plurality of stairs exist, the number of third passengers can be divided by the number of the stairs to obtain the number of third passengers passing through each stair in each time period in history, and finally, the number of third passengers passing through each moment in each stair in history is determined according to the number of third passengers passing through each stair.

Step 20216, constructing a passenger number information table according to the number of first passengers, the number of second passengers and the number of third passengers.

And finally, constructing a passenger number information table according to the number of first passengers transported at each moment in the history of the elevator, the number of second passengers transported at each moment in the history of the escalator and the number of third passengers transported at each moment in the history of the stair.

And 203, determining the number of downstream people in the arrival mode of each platform at each moment in the target time period according to the number of passengers and the up-down proportion of the passenger flow.

And then determining the number of the passengers descending in the arrival modes of the various platforms at each moment according to the calculated number of the first passengers, the number of the second passengers and the number of the third passengers and the up-down proportion of the passenger flow. The number of pedestrians in the arrival mode of each platform at each moment in the target time period includes the number of pedestrians going down each elevator, the number of pedestrians going down each escalator and the number of pedestrians going down each stair at each moment.

Step 204, determining the time required for each elevator to move to each shield door, the time required for each escalator to move to each shield door, and the time required for each stairway to move to each shield door.

After determining the number of downlink persons in the arrival modes of the various platforms at each moment in the target time period, the probability that the passengers in the arrival modes of the different platforms select the various carriages and the probability that the passengers in the various carriages select the arrival modes of the different platforms need to be further determined. Specifically, it is first necessary to determine the correspondence between the platform screen door and each car of the train. Then, determining the shortest distance of each elevator, each escalator and each stair moving to each shielding door, and calculating the time required by each elevator to move to each shielding door, the time required by each escalator to move to each shielding door and the time required by each stair to move to each shielding door according to the shortest distance, wherein the formula is as follows:

where t_control is time, distance is shortest distance, speed is the traveling speed of the passenger, and in this embodiment, 1 m/s is taken.

Step 205, determining the probability of the passenger of each elevator arriving at each carriage, the probability of the passenger of each escalator arriving at each carriage and the probability of the passenger of each stair arriving at each carriage according to the time.

Then, according to the time, the probability that the passenger of each elevator arrives at each carriage, the probability that the passenger of each escalator arrives at each carriage and the probability that the passenger of each stair arrives at each carriage can be further determined. Specifically, if the time is longer, the probability that the passenger selects the cabin is smaller, and in this embodiment, the time is converted by using the following formula, so as to obtain conversion data:

Wherein t_Consume_change is conversion data.

Then, according to the conversion data, the probability is converted by using a normalization method, and the formula is as follows:

where choose_prob is the probability. max (t_control_change) is the maximum value of the conversion data corresponding to each elevator, each escalator or each stairway, and min (t_control_change) is the minimum value of the conversion data corresponding to each elevator, each escalator or each stairway.

In addition, it should be further noted that the probabilities calculated according to the above formulas, that is, the probabilities of each elevator, each escalator, and each stairway are selected for the passengers on each car. In one embodiment, a specific process for calculating the probability of passengers arriving at each car for each station arrival is shown in fig. 5.

And 206, determining the number of newly-increased waiting vehicles reaching each carriage at each moment in the target time period according to the probability and the number of pedestrians.

After determining the probability that each elevator passenger arrives at each carriage, the probability that each escalator passenger arrives at each carriage, and the probability that each stair passenger arrives at each carriage, the newly-increased number of passengers arriving at each carriage at each moment in the target time period can be determined according to the probability and the number of pedestrians. For example, the number of newly-increased passengers arriving at each carriage at each time in each elevator can be counted according to the number of descending passengers arriving at each carriage at each time of each elevator and the probability of passengers arriving at each carriage at each elevator, and after the number of newly-increased passengers arriving at each carriage at all elevators arriving at each carriage, the number of newly-increased passengers arriving at each carriage at all escalators and the number of newly-increased passengers arriving at each carriage at all stairways in the target time period are summarized, the number of newly-increased passengers arriving at each carriage at each time can be determined.

Step 207, judging whether a train arrives at the station at the current moment.

Step 208, if a train arrives at the station, determining the number of boarding persons of each carriage after the train arrives.

On the basis of the above embodiment, after determining that the train arrives at the station in step 208, the number of boarding persons for each carriage includes:

step 2081, determining a third time when the train arrives at the station and a fourth time when the next train arrives at the station.

After determining that there is a train arrival, first, it is necessary to determine the third time instant metro_1 when the train arrives at the station and the fourth time instant metro_2 when the next train arrives at the station.

Step 2082, determining the number of outbound persons in the arrival mode of each station between the third time and the fourth time.

Then, the number of outbound persons in different arrival modes of the station between the third time and the fourth time needs to be further determined. In one embodiment, the number of passengers transported by different arrival means at the platform between the third time and the fourth time may be obtained from a pre-constructed passenger number information table. And then, the up-down proportion of the passenger flow between the third moment and the fourth moment is obtained, and the number of the passengers transported by different platform arrival modes between the third moment and the fourth moment and the up-down proportion of the passenger flow can be calculated according to the number of the passengers transported by different platform arrival modes between the third moment and the fourth moment. The number of the outbound persons in different platform arrival modes includes the number of the outbound persons of each elevator, the number of the outbound persons of each escalator and the number of the outbound persons of each stair.

Step 2083, determining the number of passengers in each carriage according to the probability and the number of passengers in each carriage in the arrival mode of each platform.

Then, since the probability of arrival of the passenger of each elevator at the respective cars, the probability of arrival of the passenger of each escalator at the respective cars, and the probability of arrival of the passenger of each staircase calculated in the above steps are also selected for the passenger on each car, the probability of selection of each escalator, and the probability of selection of each staircase, the number of alighting from the respective cars can be calculated from the probability of arrival of the passenger of each elevator at the respective cars, the probability of arrival of the passenger of each escalator at the respective cars, and the number of alighting from the respective elevators, the number of alighting from the respective escalators, and the number of alighting from the respective stairways.

Specifically, the number of elevators is assumed to be n ₁ The number of the escalator is n ₂ The number of the stairs is n ₃ The number of the corresponding elevator is respectivelyThe number of people going out of the corresponding escalator is +.>The number of people going out of the corresponding stairs is respectively Assuming n cars, then: since the number of the lifting elevators is n ₁ The probability distribution of the ith elevator to each car is elevator_prob _i1 、elevator_prob _i2 、…、elevator_prob _im 、elevator_prob _in . Since the number of automatic elevators is n ₂ The probability distribution of the kth automatic elevator to each car is auto_lift_prob _k1 、auto_lift_prob _k2 、…、elevator_prob _km 、auto_lift_prob _kn . Due to the number of the stairs being n ₃ The probabilities of selecting the jth stairs are autotcase_prob respectively _j1 、autocase_prob _j2 、…、elevator_prob _jm 、autocase_prob _jn 。

The calculation formula of the number of passengers getting off the mth carriage after the train arrives at the station is as follows:

step 2084, obtaining a first load when each carriage arrives at a station and a second load after leaving the station on the train history.

Then, the first load of each carriage on the history of the train when arriving at the station and the second load after leaving the station can be further obtained.

And step 2085, determining the boarding number of each carriage of the train according to the number of boarding numbers of each carriage, the first load and the second load.

And finally, determining the boarding number of each carriage of the train according to the number of the alighting number, the first load and the second load of each carriage. The specific calculation formula is as follows:

up_passenger _m ＝after_on_passenger _m +down_passenger _m -before_on_passenger _m

wherein: down_passenger _m Is the number of passengers getting off the mth carriage.

up_passenger _m Is the number of boarding persons for the mth carriage.

after_on_passenger _m Is the second load when the mth carriage leaves the station.

before_on_passenger _m Is the first load when the mth car arrives at the station.

In another embodiment, the number of boarding persons of each carriage after each train arrives at the station can be calculated in advance, and the number of boarding persons of each carriage is stored in the boarding person table, and then the number of boarding persons of each carriage of different trains can be obtained directly through a table lookup mode. In one embodiment, the specific process of counting the number of passengers is shown in fig. 6.

Step 209, updating the waiting number of each carriage at the current moment according to the number of passengers on each carriage, the newly added waiting number of each carriage and the last updated waiting number of each carriage.

And finally, obtaining the number of the waiting persons of each carriage updated in the last time, subtracting the number of the waiting persons of each carriage from the number of the waiting persons of each carriage updated in the last time, adding the number of the newly added waiting persons of each carriage, obtaining the number of the waiting persons of each carriage at the current moment, and calculating the waiting congestion degree of the platform according to the number of the waiting persons of each carriage. In one embodiment, the maximum number of waiting vehicles in each carriage can be set, whether the number of waiting vehicles at the current moment exceeds 0.8 x the maximum number of waiting vehicles is judged, if so, new waiting passengers randomly select other carriages to wait, and if not, the waiting vehicles are arranged according to normal sorting.

Step 210, if no train arrives at the station, updating the number of waiting persons in each carriage at the current moment according to the newly increased number of waiting persons in each carriage and the number of waiting persons in each carriage at the previous moment.

In the above-mentioned embodiment of the present invention, the number of passengers arriving at each car at each time in the target time period is determined by determining the number of passengers arriving at each car at each escalator, and the number of newly increased waiting persons arriving at each car at each time in the target time period. Then, whether trains exist at the current moment is further determined, if so, the number of boarding persons of each carriage is determined, and the number of waiting persons of each carriage is updated; if not, the number of waiting persons in each carriage is directly updated. According to the embodiment of the invention, the probability distribution model of arrival of different platform arrival modes at each carriage is constructed, and the newly-increased number of passengers of each carriage is determined in a multi-model fusion mode, so that the accuracy of predicting the number of passengers of each carriage can be improved. The technical problem of poor accuracy in a mode of counting the number of passengers waiting at a platform in the prior art is solved. In addition, the embodiment of the invention can obtain personnel distribution of each area of the platform, so that operators can perform guest flow control according to personnel distribution conditions. Meanwhile, the number of the passengers in various statistical platform arrival modes can also be used for supporting a passenger od prediction model, a passenger flow prediction model and other models.

As shown in fig. 7, fig. 7 is a schematic structural diagram of a device for predicting the number of bus stops according to an embodiment of the present invention, where the device for predicting the number of bus stops according to the embodiment of the present invention includes:

the number of pedestrians determining module 301 is configured to determine, according to a current target time period, a number of pedestrians going downstream in various platform arrival manners at each moment of a target station, where the target time period is obtained by dividing a time granularity in advance;

the waiting number determining module 302 is configured to determine a probability that each platform arrival mode arrives at each carriage, and determine a newly increased waiting number that each moment arrives at each carriage in a target time period according to the probability and the number of pedestrians;

an arrival judging module 303, configured to judge whether a train arrives at a station at the current moment;

the boarding number determining module 304 is configured to determine the boarding number of each carriage after the arrival of the train if the train arrives at the station;

the first person number updating module 305 is configured to update the number of waiting persons in each carriage at the current moment according to the number of boarding persons in each carriage, the number of newly added waiting persons in each carriage, and the number of waiting persons in each carriage updated last time;

and the second people number updating module 306 is configured to update the number of waiting people in each carriage at the current moment according to the number of newly increased waiting people in each carriage and the number of waiting people in each carriage at the previous moment if no train arrives at the station.

On the basis of the above embodiment, the pedestrian count determination module 301 includes:

the proportion determining submodule is used for obtaining the uplink and downlink proportion of the passenger flow in the current target time period;

the passenger number obtaining submodule is used for obtaining the number of passengers corresponding to the arrival modes of various platforms in the target station in each moment of the target time period;

and the descending number determining submodule determines the descending number of the various platform arrival modes at each moment in the target time period according to the number of passengers and the ascending and descending proportion of the passenger flow.

On the basis of the embodiment, the platform arrival mode comprises an elevator, an escalator and stairs;

the passenger number acquisition submodule is specifically used for acquiring the first passenger number corresponding to the elevator in the target station, the second passenger number corresponding to the escalator and the third passenger number corresponding to the stair in each moment of the target time period from a pre-constructed passenger number information table.

On the basis of the above embodiment, the vehicle passenger number information management system further includes an information table construction module, the information table construction module is used for constructing a passenger number information table in advance, and the information table construction module includes:

the passenger flow volume statistics sub-module is used for counting historical passenger flow volumes of all time periods in the history of the target station;

The first person number determining submodule is used for determining the number of passengers carried by the elevator in each lifting time in each time period, and counting the number of first passengers transported at each moment in the history of the elevator according to the number of passengers carried by the elevator;

the first load data acquisition sub-module is used for acquiring first load data of the escalator in each time period in the history of the target station;

the second people number determining submodule is used for determining second load data of each moment in the history of the escalator according to the first load data and determining the number of second passengers transported at each moment in the history of the escalator according to the second load data;

the third person number determining submodule is used for determining the number of third passengers passing at each moment on the stair history according to the historical passenger flow, the number of first passengers and the number of second passengers;

the passenger number information table construction submodule is used for constructing a passenger number information table according to the number of primary passengers, the number of secondary passengers and the number of tertiary passengers.

On the basis of the above embodiment, the first person number determination submodule includes:

a time determining unit for determining a first time corresponding to each ascending and a second time corresponding to each descending of the elevator;

The lifting load data acquisition unit is used for acquiring lifting load data after the door is closed in the platform when the lifting elevator ascends each time;

the lifting person number determining unit is used for determining the number of passengers transported by the lifting elevator during each lifting according to the lifting load data and the no-load data of the lifting elevator;

the descending load data acquisition unit is used for acquiring descending load data after the door is closed in the hall when the elevator descends every time;

the descending population determining unit is used for determining the number of passengers transported by the elevator during each descending according to the descending load data and the no-load data;

the first person number determining unit is used for counting the number of first passengers transported at each moment in the history of the elevator according to the first moment, the second moment, the number of passengers transported at each ascending time of the elevator and the number of passengers transported at each descending time of the elevator.

On the basis of the above embodiment, the second population determining submodule includes:

the time interval dividing unit is used for determining a first transportation time interval when passengers exist on the escalator and a second transportation time interval when no passengers exist on the escalator according to the second load data;

A time determining unit for determining, for each first transportation period, a start time and an end time of the first transportation period, while determining a first time period required for a passenger from a start point of the escalator to an end point of the escalator;

the traversing unit is used for traversing each time in the first transportation period and determining whether the distance from the currently traversed time to the starting time is larger than a first duration or not;

the load data acquisition unit is used for acquiring second load data corresponding to the current traversing moment and second load data corresponding to the last traversing moment if the load data is longer than the first duration;

and the second person number determining unit is used for determining the number of second passengers transported at each moment in the history of the escalator according to the second load data corresponding to the current traversing moment and the second load data corresponding to the last traversing moment.

On the basis of the above embodiment, the third population determining submodule includes:

the total number determining unit is used for counting the number of the first total passengers transported by the elevator and the number of the second total passengers transported by the escalator in each time period according to the number of the first passengers and the number of the second passengers;

The stair total number determining unit is used for subtracting the first total number of passengers and the second total number of passengers from the historical passenger flow volume of each time period to obtain the third total number of passengers passing by the stair in each time period;

and the third person number determining unit is used for determining the number of the third passengers passing at each moment on the stair history according to the number of the third total passengers.

On the basis of the embodiment, the platform arrival mode comprises an elevator, an escalator and stairs; the waiting number determination module 302 includes:

a moving time determining sub-module for determining a time required for each elevator to move to each shielding door, a time required for each escalator to move to each shielding door, and a time required for each stairway to move to each shielding door;

the probability determination submodule is used for determining the probability that each elevator passenger arrives at each carriage, the probability that each escalator passenger arrives at each carriage and the probability that each stair passenger arrives at each carriage according to time.

On the basis of the above embodiment, the boarding number determination module 304 includes:

the arrival time determining unit is used for determining a third time when the train arrives at the station and a fourth time when the next train arrives at the station;

The outbound population determining unit is used for determining the outbound population of various platform arrival modes between the third moment and the fourth moment;

the number of alighting people determining unit is used for determining the number of alighting people of each carriage according to the probability and the number of alighting people of various platform arrival modes.

The arrival load obtaining unit is used for obtaining a first load of each carriage on the history of the train when arriving at the station and a second load after leaving the station;

and the boarding number determining unit is used for determining the boarding number of each carriage of the train according to the boarding number, the first load and the second load of each carriage.

The platform waiting number prediction device provided by the embodiment of the invention is contained in the terminal equipment, can be used for executing the platform waiting number prediction method provided by the embodiment, and has corresponding functions and beneficial effects.

It should be noted that, in the embodiment of the platform waiting number prediction device, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, so long as the corresponding functions can be realized; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.

The present embodiment also provides a terminal device, as shown in fig. 8, the terminal device 40 includes a processor 400 and a memory 401;

the memory 401 is used for storing a computer program 402 and transmitting the computer program 402 to the processor 400;

the processor 400 is configured to execute the steps of one embodiment of a platform waiting number prediction method according to instructions in the computer program 402.

By way of example, computer program 402 may be partitioned into one or more modules/units, which are stored in memory 401 and executed by processor 400 to accomplish the present application. One or more of the modules/units may be a series of computer program instruction segments capable of performing particular functions to describe the execution of the computer program 402 in the terminal device 40.

The terminal device 40 may be a desktop computer, a notebook computer, a palm computer, a cloud server, or the like. Terminal device 40 may include, but is not limited to, a processor 400, a memory 401. It will be appreciated by those skilled in the art that fig. 8 is merely an example of terminal device 40 and is not intended to limit terminal device 40, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., terminal device 40 may also include input and output devices, network access devices, buses, etc.

The processor 400 may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 401 may be an internal storage unit of the terminal device 40, such as a hard disk or a memory of the terminal device 40. The memory 401 may also be an external storage device of the terminal device 40, such as a plug-in hard disk provided on the terminal device 40, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like. Further, the memory 401 may also include both an internal storage unit and an external storage device of the terminal device 40. The memory 401 is used to store computer programs and other programs and data required for the terminal device 40. The memory 401 may also be used to temporarily store data that has been output or is to be output.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.

In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media in which computer programs can be stored.

The present invention also provides a storage medium containing computer executable instructions which, when executed by a computer processor, are used to perform a method of predicting the number of bus stops waiting at a platform, the method comprising the steps of:

judging whether a train arrives at a station at the current moment;

Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the embodiments of the present invention are not limited to the particular embodiments described herein, but are capable of numerous obvious changes, rearrangements and substitutions without departing from the scope of the embodiments of the present invention. Therefore, while the embodiments of the present invention have been described in connection with the above embodiments, the embodiments of the present invention are not limited to the above embodiments, but may include many other equivalent embodiments without departing from the spirit of the embodiments of the present invention, and the scope of the embodiments of the present invention is determined by the scope of the appended claims.

Claims

1. A method for predicting the number of bus stops, comprising:

determining the probability that the arrival modes of the various platforms reach each carriage, and determining the number of newly-increased waiting vehicles reaching each carriage at each moment in the target time period according to the probability and the number of downlink persons;

judging whether a train arrives at a station at the current moment;

if the train arrives at the station, determining the number of people on each carriage after the train arrives;

if no train arrives at the station, updating the waiting number of each carriage at the current moment according to the newly increased waiting number of each carriage and the waiting number of each carriage at the previous moment.

2. The method for predicting the number of bus stops according to claim 1, wherein the determining the number of downlink bus stops at each moment of the target station according to the current target time period comprises:

Acquiring the uplink and downlink proportion of the passenger flow in the current target time period;

acquiring the number of passengers corresponding to the arrival modes of various platforms in the target station in each moment of the target time period;

and determining the number of downstream people in the arrival modes of the various stations at each moment in the target time period according to the number of passengers and the up-down proportion of the passenger flow.

3. The method for predicting the number of bus stops according to claim 2, wherein the arrival mode of the bus stops includes an elevator, an escalator and a stairway;

in each time of obtaining the target time period, the number of passengers corresponding to the arrival modes of various platforms in the target station includes:

and acquiring the first passenger number corresponding to the elevator in the target station, the second passenger number corresponding to the escalator and the third passenger number corresponding to the stair in each moment of the target time period from a pre-constructed passenger number information table.

4. A platform waiting number prediction method according to claim 3, wherein the passenger number information table is constructed in advance by:

Counting historical passenger flow of each time period in the history of the target station;

determining the passenger carrying number of the elevator in each lifting time in each time period, and counting the number of first passengers transported at each time in the history of the elevator according to the passenger carrying number;

acquiring first load data of the escalator in each time period in the history of the target station;

determining second load data of each moment in the history of the escalator according to the first load data, and determining the number of second passengers transported by each moment in the history of the escalator according to the second load data;

determining the number of third passengers passing at each moment in the stair history according to the historical passenger flow volume, the number of first passengers and the number of second passengers;

and constructing the passenger number information table according to the first passenger number, the second passenger number and the third passenger number.

5. The method of claim 4, wherein said determining the number of passengers in each rise and fall of the elevator during each time period, and counting the number of first passengers transported at each time in the history of the elevator based on the number of passengers, comprises:

Determining a first moment when the elevator ascends each time and a second moment when the elevator descends each time;

acquiring ascending load data of the door closing in the platform when the lifting elevator ascends each time;

determining the number of passengers transported by the elevator during each ascending according to the ascending load data and the no-load data of the elevator;

acquiring descending load data of the elevator after closing a door in a hall when the elevator descends each time;

determining the number of passengers transported by the elevator during each descent according to the descent load data and the no-load data;

counting the number of first passengers transported at each moment in the history of the elevator according to the first moment, the second moment, the number of passengers transported by the elevator at each ascending time and the number of passengers transported by the elevator at each descending time.

6. The method of claim 4, wherein said determining the number of second passengers transported at each time in the history of the escalator based on the second load data comprises:

according to the second load data, determining a first transportation period when passengers exist on the escalator and a second transportation period when no passengers exist on the escalator;

For each of the first transportation periods, determining a start time and an end time of the first transportation period while determining a first time period required for the passenger to travel from a start point of the escalator to an end point of the escalator;

traversing each time in the first transportation period, and determining whether the current traversed time is greater than a first duration from the starting time;

if the first load data is larger than the second load data, acquiring second load data corresponding to the current traversing moment and second load data corresponding to the last traversing moment;

and determining the number of second passengers transported at each moment in the history of the escalator according to the second load data corresponding to the current traversing moment and the second load data corresponding to the last traversing moment.

7. The method of claim 4, wherein determining the number of third passengers traveling at each time in the stair history based on the historical passenger volume, the first passenger number, and the second passenger number comprises:

counting the first total number of passengers transported by the elevator and the second total number of passengers transported by the escalator in each time period historically according to the first number of passengers and the second number of passengers;

Subtracting the first total passenger number and the second total passenger number from the historical passenger flow of each time period to obtain a third total passenger number which is historically passed by the stairs of each time period;

and determining the number of third passengers passing at each moment in the stair history according to the number of third passengers.

8. The method for predicting the number of bus stops according to claim 1, wherein the arrival mode of the bus stops comprises an elevator, an escalator and a stairway;

the determining the probability that the arrival modes of the various stations reach the carriages comprises the following steps:

determining the time required for each of the elevators to move to each of the shielding doors, the time required for each of the escalators to move to each of the shielding doors, and the time required for each of the staircases to move to each of the shielding doors;

and determining the probability that each passenger of the elevator arrives at each carriage, the probability that each passenger of the escalator arrives at each carriage and the probability that each passenger of the stair arrives at each carriage according to the time.

9. The method for predicting the number of waiting persons at a platform according to claim 1, wherein said determining the number of boarding persons for each of said cars after said train arrives at the platform comprises:

Determining a third moment when the train arrives at the station and a fourth moment when the next train arrives at the station;

determining the number of outbound persons of the arrival modes of the various stations between the third moment and the fourth moment;

determining the number of passengers in each carriage according to the probability and the number of passengers out of the various platform arrival modes;

acquiring a first load of each carriage on the train when arriving at a station and a second load of each carriage after leaving the station;

and determining the boarding number of each carriage of the train according to the number of boarding numbers of each carriage, the first load and the second load.

10. A station waiting number prediction apparatus, comprising:

the system comprises a descending number determining module, a time granularity determining module and a time granularity determining module, wherein the descending number determining module is used for determining the number of descending people in various platform arrival modes at each moment of a target station according to a current target time period, and the target time period is obtained by dividing the time granularity in advance;

the waiting number determining module is used for determining the probability that the arrival modes of the various platforms reach each carriage, and determining the newly-increased waiting number of each carriage at each moment in the target time period according to the probability and the downlink number;

the boarding number determining module is used for determining the boarding number of each carriage after the train arrives if the train arrives at the station;

the first person number updating module is used for updating the waiting number of each carriage at the current moment according to the number of the passengers on each carriage, the newly-increased waiting number of each carriage and the waiting number of each carriage updated last time;

and the second number updating module is used for updating the number of waiting persons of each carriage at the current moment according to the newly increased number of waiting persons of each carriage and the number of waiting persons of each carriage at the previous moment if the train does not arrive at the station.

11. A terminal device, characterized in that the terminal device comprises a processor and a memory;

the memory is used for storing a computer program and transmitting the computer program to the processor;

the processor is configured to execute a method for predicting the number of bus stops according to any one of claims 1 to 9 according to instructions in the computer program.

12. A storage medium storing computer executable instructions which, when executed by a computer processor, are for performing a platform occupancy prediction method according to any one of claims 1 to 9.