A passenger flow diversion method and system based on big data

Abstract

The present invention is applicable to the technical field of passenger flow diversion, and provides a passenger flow diversion method and system based on big data, the method comprising: obtaining passenger flow data on a sub-section of the main route before the common section with the intersecting route; determining a first estimated time for the first vehicle of the main route to arrive at a common connecting point of the common section; obtaining the available driving data of the second vehicle passing through the common connecting point before the first estimated time based on the real-time driving data of the intersecting route, the available driving data including the available passenger capacity of each vehicle in the second vehicle and the destination reached. The technical solution of the embodiment of the present application can be combined with the actual movement of passengers to avoid excessive aggregation during diversion, and the first vehicle on the main route and the second vehicle on the forked route can jointly connect all passengers under the passenger flow data, thereby improving the efficiency of passenger diversion on the main route.

Description

Technical Field

[0001] The present invention belongs to the technical field of passenger flow diversion, and in particular relates to a passenger flow diversion method and system based on big data. Background Art

[0002] Passenger flow diversion is to clear and guide passenger flow through the reasonable arrangement of relevant equipment and facilities, so as to ensure the reduction of passenger flow pressure and avoid safety hazards.

[0003] In some regional passenger flow diversion scenarios, if it involves passenger flow diversion when traffic routes are interlaced, it is necessary to divert passengers from one end of the interlaced route to the other end. The existing technology achieves this by increasing the number and density of transportation vehicles.

[0004] However, through actual research, it is found that when the above existing technologies are used to deal with the diversion of passenger flow in traffic routes with interlaced situations, if passengers have actual movement needs, it is difficult to conduct effective and unified diversion, and the efficiency of diversion is also relatively low. Summary of the invention

[0005] The purpose of the embodiments of the present invention is to provide a passenger flow diversion method and system based on big data, aiming to solve the problems raised in the above-mentioned background technology.

[0006] The embodiment of the present invention is implemented as follows: on the one hand, a passenger flow diversion method based on big data includes:

[0007] Obtain passenger flow data on a sub-section of the main route before a common section with the intersecting route;

[0008] Determine a first estimated time for a first vehicle on the main route to arrive at a common connecting point on the common road segment;

[0009] Acquire, based on the real-time driving data of the intersecting route, the available driving data of the second vehicles passing through the common docking point before the first estimated time, the available driving data including the available passenger capacity of each of the second vehicles and the destination to be reached, the destination including the first end point of the main route or the second end point of the forked route;

[0010] Determine the movement distribution information of the gathered passengers according to the passenger flow data, and determine the positions and number of actual connecting points on the main route before the second estimated time according to the movement distribution information and the number of people limited at each connecting point, wherein the second estimated time and the first estimated time are within a preset time difference range, and the connecting points are selected as the actual connecting points according to a priority including from both sides to the middle before the common road section;

[0011] If the actual docking point includes at least a common docking point, the dispatch quantity of the first vehicle on the main route is determined according to the vacant vehicle data and the passenger flow data, so as to dock all passengers under the passenger flow data by the first vehicle and the second vehicle.

[0012] As an optional solution of the present invention, the step of obtaining passenger flow data on a sub-section of the main route before the common section with the intersecting route includes:

[0013] According to a preset statistical time interval, counting the passenger data that takes the first terminal or the second terminal as the target arrival point, the passenger data includes the passenger data that makes a remote reservation based on the sub-segment and the passenger data that makes an on-site reservation;

[0014] Determine valid passenger data for the remote reservation based on the passenger data for the remote reservation;

[0015] The valid passenger data of remote reservations and the passenger data of on-site reservations are aggregated to generate the passenger flow data.

[0016] As a further optional solution of the present invention, the determining of valid passenger data for the remote reservation based on the passenger data for the remote reservation comprises:

[0017] Obtaining the passenger location corresponding to the remotely booked passenger data;

[0018] Filtering the passenger locations within a preset distance range from the connecting point of the sub-section to obtain a filtering result;

[0019] The passenger data of the remote reservation corresponding to the screening result is used as the valid passenger data.

[0020] As a further optional solution of the present invention, the step of classifying the passenger flow data according to the first end point of the main route and the second end point of the bifurcated route to generate the passenger flow data includes:

[0021] Filtering the passenger data that takes the first destination as the target arrival point in the passenger flow data to obtain first passenger flow data;

[0022] Filter the passenger data that takes the second destination as the target arrival point in the passenger flow data to obtain second passenger flow data;

[0023] The passenger flow data includes first passenger flow classification data and second passenger flow data.

[0024] As a further optional solution of the present invention, the first estimated time for the first vehicle on the main route to arrive at the common connecting point on the common road section includes:

[0025] Obtaining currently dispatchable vehicles for passenger diversion at the connecting point;

[0026] Determining an estimated travel time according to the vehicle location of the currently dispatchable vehicle and the distance between the common docking point and the travel speed of the currently dispatchable vehicle;

[0027] Obtain the boarding waiting time at the connecting point;

[0028] The first estimated time is determined according to the estimated travel time and the waiting time for boarding.

[0029] As a further optional solution of the present invention, the step of obtaining the available driving data of the second vehicle passing through the common docking point before the first estimated time based on the real-time driving data of the intersecting routes includes:

[0030] Obtaining the fixed-point arrival time of the second vehicle before the common section of the intersecting route and the number of the second vehicles that can be dispatched;

[0031] determining the number of persons to be assigned to each second vehicle according to the number of dispatchable second vehicles, the maximum number of passengers of the second vehicles, and the total number of passengers before the common section of the intersecting routes;

[0032] Selecting the second vehicle for which there is a preset difference between the maximum number of passengers and the allocated number of passengers;

[0033] Determine the second vehicle among the screened second vehicles that passes through the common docking point before the first estimated time, and obtain a first determination result;

[0034] The available driving data is obtained according to the first determination result.

[0035] As a further optional solution of the present invention, the step of obtaining the available driving data of the second vehicle passing through the common docking point before the first estimated time based on the real-time driving data of the intersecting routes includes:

[0036] Determine the required vehicle passenger capacity according to the passenger flow before the common section of the intersecting routes and a preset floating ratio, wherein the preset floating ratio is greater than 1;

[0037] Determining a second vehicle that meets the passenger diversion demand based on the required vehicle passenger capacity and the single-vehicle passenger capacity;

[0038] According to the determined second vehicle that meets the diversion riding demand, determine a vehicle that passes through the common docking point before the first estimated time, and obtain a second determination result;

[0039] The available driving data is obtained according to the second determination result.

[0040] As a further optional solution of the present invention, determining the movement distribution information of the gathered passengers according to the passenger flow data, and determining the positions and number of actual connecting points on the main route before the second estimated time according to the movement distribution information and the limited number of people at each connecting point includes:

[0041] Sending the passenger flow data to the terminal where the guide is located on the main route, and waiting for a confirmation signal from the terminal;

[0042] If the confirmation signal is detected, it is determined whether there are gathered passengers arriving at the common docking point before the second estimated time according to the movement information of the terminal, and the confirmation signal is generated after confirming the passenger flow data and obtaining a live image of the gathered passengers;

[0043] If yes, determining the location and number of the actual docking points according to the aggregated passengers arriving at the common docking point before the second estimated time and the distribution of the remaining aggregated passengers corresponding to the passenger flow data;

[0044] If not, the location and number of the actual connecting points are determined directly based on the distribution of the aggregated passengers corresponding to the passenger flow data.

[0045] As a further optional solution of the present invention, if the actual docking point includes at least a common docking point, determining the number of dispatched first vehicles on the main route according to the vacant vehicle data and the passenger flow data so as to achieve docking of all passengers under the passenger flow data by the first vehicle and the second vehicle comprises:

[0046] Determine the total number of passengers in the passenger flow data, and determine the number of remaining passengers based on the total number of passengers and the total available passenger capacity in the available vehicle data;

[0047] The number of first vehicles to be dispatched on the main route is determined according to the number of remaining passengers and the preset passenger capacity of the first vehicle, and an additional connection instruction is generated according to the second estimated time and the total available passenger capacity, and the additional connection instruction is sent to the second vehicle with available passenger capacity.

[0048] A passenger flow diversion method based on big data is provided in an embodiment of the present invention. The method comprises the following steps: obtaining passenger flow data on a sub-section of a main route before a common section with an intersecting route; determining a first estimated time for a first vehicle on the main route to arrive at a common connecting point of the common section; obtaining free driving data of second vehicles passing through the common connecting point before the first estimated time based on real-time driving data of the intersecting route, wherein the free driving data includes the free passenger capacity of each of the second vehicles and the destination to be reached, wherein the destination includes the first end point of the main route or the second end point of the forked route; determining the movement distribution information of the gathered passengers based on the passenger flow data, and determining the position and number of actual connecting points on the main route before the second estimated time based on the movement distribution information and the number of people limited at each connecting point, wherein the second estimated time and the first estimated time are within a preset time difference range, and the connecting points are selected as actual connecting points according to a priority including from both sides to the middle before the common section; taking full account of the gathering of passengers on the main route, the gathered passengers (multiple passengers) can be selected based on, for example, the actual movement distribution information of the passengers. The actual environment impact of the docking point is considered to avoid excessive gathering during the guidance, and finally the position and number of the actual docking points on the main route are formed, that is, the pre-set docking point is selected as the actual passenger pick-up point when the subsequent vehicle picks up passengers, and the actual docking point is determined with the second estimated time as the reference time, the purpose of which is to refer to the time when the first vehicle arrives at the common docking point, so as to provide a more accurate time reference for the docking of the first vehicle and / or the second vehicle to the actual docking point, and ensure that the passengers at the docking point are ready or about to be ready when the docking is made. Ready; further, if the actual connecting point includes at least a common connecting point, the dispatch quantity of the first vehicle on the main route is determined according to the spare driving data and the passenger flow data, so as to realize the connection of all passengers under the passenger flow data by the first vehicle and the second vehicle. In combination with the actual movement needs of the passengers, the spare passenger capacity of the second vehicle on the forked route can be fully utilized to realize the guidance under the overall planning and improve the passenger load factor. The subsequent first vehicle can connect with more passengers on the first route, which is conducive to improving the guidance efficiency of the passengers on the main route.

[0049] On the other hand, a passenger flow diversion system based on big data, a passenger flow acquisition module, is used to acquire passenger flow data on a sub-section of a main route before a common section with an intersecting route;

[0050] A classification module, configured to determine a first estimated time for a first vehicle on the main route to arrive at a common connecting point on the common road segment;

[0051] a driving data acquisition module, configured to acquire, based on the real-time driving data of the intersecting route, the available driving data of the second vehicles passing through the common docking point before the first estimated time, wherein the available driving data includes the available passenger capacity of each of the second vehicles and the destination to be reached, wherein the destination includes the first end point of the main route or the second end point of the forked route;

[0052] A docking point determination module is used to determine the movement distribution information of gathered passengers based on passenger flow data, and determine the positions and number of actual docking points on the main route before a second estimated time based on the movement distribution information and the limited number of people at each docking point, wherein the second estimated time and the first estimated time are within a preset time difference range, and the docking point is selected as the actual docking point according to a priority including from both sides to the middle before a common section.

[0053] The embodiment of the present invention provides a passenger flow diversion system based on big data, which has the same beneficial effects as the passenger flow diversion method based on big data over the prior art, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a main flow chart of a passenger flow diversion method based on big data.

[0055] Figure 2 The invention discloses a flow chart for obtaining passenger flow data on a sub-section of a main route before a common section with an intersecting route in a passenger flow diversion method based on big data.

[0056] Figure 3 The invention discloses a flow chart for determining a first estimated time for a first vehicle on a main route to arrive at a common connecting point on a common road section in a passenger flow diversion method based on big data.

[0057] Figure 4 The invention discloses a flow chart for determining the location and quantity of actual connecting points on a main route before a second estimated time in a passenger flow diversion method based on big data.

[0058] Figure 5 It is the main structure diagram of a passenger flow diversion system based on big data. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0060] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0061] The present invention provides a passenger flow diversion method and system based on big data, which solves the technical problems in the background technology.

[0062] like Figure 1 As shown, it is a main flow chart of a passenger flow diversion method based on big data provided by an embodiment of the present invention, and the passenger flow diversion method based on big data includes:

[0063] Step S10: Obtain passenger flow data on the sub-section of the main route before the common section with the intersecting route;

[0064] It should be noted that the passenger flow diversion in the present invention is one-way diversion, that is, diversion is performed in another direction based on the connecting point of the starting section of the main route, and passes through the common section with the intersection. The intersection route and the main route share a certain section. The main route has a first terminal that is directly extended, and the intersection route has a second terminal that is directly extended. In the actual diversion process, if a vehicle starting from the main route can reach the first terminal (it will be explained in the subsequent implementation that passengers can also make reservations for the second terminal on the main route, and the number of reservations for the second terminal can be limited at this time), and a vehicle starting from the starting point of the intersection route can reach the first terminal or the second terminal, because the first terminal The point is the end point of the direct extension of the main route, which can provide more reliable support for the placement after diversion. It should be noted that the first end point and the second end point can be the same end point, indicating that the branch line and the main route have the same destination after being aggregated (the first case), and the first end point and the second end point can also be different (the second case) or the two are not far apart (the third case). When the first end point and the second end point become the placement points of the passengers after diversion, the difference is not large. Therefore, in the first case and the third case, even if the target end point is to go to one of the first end point and the second end point, it is allowed if the vehicle is finally converted to reach the other. The present invention mainly guides the passenger flow with the main route as the leading factor.

[0065] Specifically, the passenger flow data of the main route is the data on a certain number of passengers being diverted to the target point (first destination or second destination) on the sub-section before the common section. The passenger flow data is generally counted regularly so that passenger flow can be diverted in a timely manner based on the statistical data.

[0066] Step S11: determining a first estimated time for a first vehicle on the main route to arrive at a common connecting point on the common road section;

[0067] Specifically, on the main route, vehicles available for dispatch are pre-set. The first estimated time is generally calculated from the time when the passenger flow data is counted, plus the time it takes for the first vehicle on the main route to arrive at the common connecting point of the common section of the road. The first estimated time represents an estimated time for the first vehicle to arrive at the common connecting point.

[0068] Step S12: acquiring the available driving data of the second vehicles passing through the common docking point before the first estimated time according to the real-time driving data of the intersecting route, wherein the available driving data includes the available passenger capacity of each of the second vehicles and the destination to be reached, wherein the destination includes the first end point of the main route or the second end point of the bifurcated route;

[0069] Specifically, the cross route is an auxiliary route of the main route. Due to the existence of the auxiliary, the driving of the cross route (before the common section) is relatively loose or free, because it has relatively fewer passengers and less fluctuation. Therefore, the real-time driving data can be determined after the vehicle dispatch (departure time and number of departures, etc.) is involved, or it can be determined based on the given fixed number of departures and departure time. Based on the real-time driving data, the available driving data of the second vehicle passing through the common connection point before the first estimated time can be determined, that is, the available passenger capacity of each vehicle and the destination to be reached are obtained. The available passenger capacity represents its ability to continue to carry passengers.

[0070] Step S13: determining the movement distribution information of the gathered passengers according to the passenger flow data, and determining the positions and number of actual connecting points on the main route before the second estimated time according to the movement distribution information and the number limit of each connecting point, wherein the second estimated time and the first estimated time are within a preset time difference range, and the connecting point is selected as the actual connecting point according to the preset priority;

[0071] Specifically, before the arrival of the vehicle, due to the subjective factors of the passengers (such as their own needs) and objective factors (such as changes in the environment of the location, etc.), the movement of passengers on the main route varies greatly. Therefore, it is considered to predict and guide the gathered passengers (there may be multiple, representing groups of passengers) based on the actual movement distribution information of the passengers, and consider the actual environmental impact of the docking point to avoid excessive gathering during diversion (therefore, each docking point has a limited maximum number of people, that is, the number of people is limited. The docking point is a pre-set waiting diversion position beside the main route (or cross route), and is set on and before the common section (except for the common section where there is an end docking point), and finally forms the position and number of the actual docking points on the main route, that is, select the pre-set docking point. The docking point serves as the actual pick-up point when subsequent vehicles pick up passengers, and the actual docking point is determined with the second estimated time as a reference time. Its purpose is to refer to the time when the first vehicle arrives at the common docking point, so as to provide a more accurate time reference for the docking of the first vehicle and / or the second vehicle to the actual docking point, ensuring that the passengers at the docking point are ready or about to be ready when the docking occurs. When selecting the docking point, due to consideration of the mobile distribution information and the limit on the number of people, especially the former, the selection order of the docking point is inevitably involved, that is, the priority. For example, the actual docking point can be determined according to the distance from the common docking point. The closer to the common docking point, the closer the actual docking point is to the common docking point. On the contrary, the determined actual docking point is far from the common docking point.

[0072] Step S14: If the actual docking points include at least common docking points, the number of dispatched first vehicles on the main route is determined according to the available vehicle data and the passenger flow data, so as to dock all passengers under the passenger flow data by the first vehicle and the second vehicle.

[0073] Specifically, in one case, when the actual docking points include at least common docking points, all passengers under the passenger flow data can be docked by the first vehicle and the second vehicle together, that is, one part is achieved by the second vehicle under the spare driving data, and the other part is achieved by dispatching the first vehicle, thereby increasing the passenger load factor of the second vehicle. The subsequent first vehicle can dock with more passengers on the first route, which is conducive to improving the efficiency of passenger diversion on the main route, and this arrangement is determined based on the limit on the number of people and the actual mobile distribution information.

[0074] When this embodiment is applied, the passenger flow data on the sub-section of the main route before the common section with the intersection route is obtained; the first estimated time for the first vehicle of the main route to arrive at the common connecting point of the common section is determined; the free driving data of the second vehicle passing the common connecting point before the first estimated time is obtained according to the real-time driving data of the intersection route, the free driving data includes the free passenger capacity of each vehicle in the second vehicle and the destination to be reached, and the destination includes the first end point of the main route or the second end point of the forked route; the movement distribution information of the gathered passengers is determined according to the passenger flow data, and the position and number of the actual connecting points on the main route before the second estimated time are determined according to the movement distribution information and the limited number of people at each connecting point, wherein the second estimated time and the first estimated time are within the preset time difference range, and the connecting points are selected as the actual connecting points according to the priority including from both sides to the middle before the common section; taking full account of the gathering of passengers on the main route, the gathered passengers (multiple passengers in a group) can be predicted and guided by, for example, based on the actual movement distribution information of the passengers. The actual environment impact of the docking point is considered, and excessive gathering is avoided during the diversion, and finally the position and number of the actual docking point on the main route are formed, that is, the pre-set docking point is selected as the actual passenger pick-up point when the subsequent vehicle picks up passengers, and the actual docking point is determined with the second estimated time as the reference time, the purpose of which is to refer to the time when the first vehicle arrives at the common docking point, so that a more accurate time reference can be provided for the first vehicle and / or the second vehicle to connect with the actual docking point, ensuring that the passengers at the docking point are ready or about to be ready when connecting; further, if the actual docking point includes at least a common docking point, the dispatch number of the first vehicle on the main route is determined according to the spare driving data and the passenger flow data, so as to realize the connection of all passengers under the passenger flow data by the first vehicle and the second vehicle, and the spare passenger capacity of the second vehicle on the forked route can be fully utilized in combination with the actual movement needs of the passengers, so as to realize the diversion under the overall planning, and improve the passenger load rate, and the subsequent first vehicle can connect with more passengers on the first route, which is conducive to improving the diversion efficiency of the passengers on the main route.

[0075] It should be noted that when the actual docking point does not include a common docking point, the first vehicle is dispatched to dock all passengers before the common route. This situation is relatively simple and will not be described in detail here. Please refer to the relevant statements on passenger docking in subsequent embodiments.

[0076] like Figure 2 As shown, as an optional embodiment of the present invention, the step of obtaining passenger flow data on a sub-section of the main route before a common section with the intersecting route includes:

[0077] Step S101: Counting the passenger data that takes the first destination or the second destination as the target arrival point at a preset statistical time interval, wherein the passenger data includes the passenger data that makes a remote reservation based on the sub-segment and the passenger data that makes an on-site reservation;

[0078] Specifically, passenger data is summarized once at a preset statistical time interval. The sources of the summary include remote reservations (such as reservations through APP or reporting through other network ports), or on-site reservations through the main route, where a reservation client is set up on the main route, or reported after manual statistics on the main route.

[0079] Step S102: determining valid passenger data for the remote reservation according to the passenger data for the remote reservation;

[0080] Specifically, valid passenger data indicates that there is theoretically a demand to go to the first destination or the second destination, and the passenger can reach the corresponding connecting point as soon as possible. Otherwise, this indicates that the remote reservation is invalid and it is impossible to facilitate timely transportation by vehicle.

[0081] Step S103: Summarize the valid passenger data of remote reservations and the passenger data of on-site reservations to generate the passenger flow data.

[0082] Specifically, the passenger data itself includes the number of passengers going to each destination, so the passenger flow data has two attributes: passenger attributes and destination attributes.

[0083] Wherein, determining the valid passenger data of the remote reservation according to the passenger data of the remote reservation comprises:

[0084] Step: obtaining the passenger location corresponding to the remotely booked passenger data;

[0085] Specifically, the passenger location includes the location of the terminal where the passenger is registered, or the location reflected by a third-party location software on the terminal.

[0086] Step: screening passenger locations within a preset distance range from the connecting point of the sub-section to obtain screening results;

[0087] Specifically, the preset distance range can be determined based on the product of the average travel speed of passengers (such as the average travel speed of adults) and the allowed travel time. The allowed travel time is the time to reach the main route in time, which can be set based on experience, such as 10 minutes; of course, the preset distance range can also be set directly, and the preset distance range can be the distance between two connecting points.

[0088] It should be noted that the preset value or set value or set threshold in the present invention can be set according to actual needs and experience, and will not be explained later.

[0089] Step: taking the remotely booked passenger data corresponding to the screening result as the valid passenger data.

[0090] Specifically, the screening result is the passenger data of passengers who have made remote reservations and are within a preset distance range from the connecting point of the sub-section.

[0091] In summary, the above can comprehensively determine the passenger flow data based on the effective passenger data of remote reservations and the passenger data of on-site reservations, avoiding the problem of inaccurate passenger flow in future time periods caused by single on-site statistics, and at the same time enriching the passenger connection access channels.

[0092] like Figure 3 As shown, as an optional embodiment of the present invention, the first estimated time for the first vehicle on the main route to arrive at the common connecting point on the common road section includes:

[0093] Step S111: obtaining currently dispatchable vehicles for passenger diversion at the connecting point;

[0094] Specifically, currently dispatchable vehicles are directly given, representing vehicles that can be dispatched in a relatively short time.

[0095] Step S112: determining an estimated travel time according to the vehicle location of the currently dispatchable vehicle and the distance between the common docking point and the travel speed of the currently dispatchable vehicle;

[0096] Specifically, the vehicle is generally located at the starting point of the main route, and its distance from the connecting point is also determined. The driving speed is based on the set recommended speed, and the ratio of the two is the estimated driving time.

[0097] Step S113: Obtaining the waiting time for boarding at the connecting point;

[0098] Specifically, the longest waiting time for boarding is the product of the time spent at a single docking point and the number of docking points. The number of docking points is determined by the ratio of the maximum passenger capacity of the vehicle to the number of people limited at the docking points, and the number of docking points generally does not exceed the preset number to avoid multiple stops. For example, the maximum passenger capacity of the vehicle is 30, and the number of people limited at the docking point is 15. Therefore, the number of docking points can be determined as 2 times. The longest waiting time for boarding is amin, and the longest waiting time for boarding is 2amin. Under normal circumstances, the waiting time for boarding of the first vehicle with the same passenger capacity is not much different. Therefore, the average value determined by the waiting time for boarding at multiple docking points can also be taken as the waiting time for boarding at the docking point. If the estimated driving time is long, the waiting time for boarding can be ignored, such as when the difference between the two is 20 times.

[0099] Step S114: Determine the first estimated time according to the estimated travel time and the waiting time for boarding the vehicle.

[0100] Specifically, the sum of the two times (superimposed starting time) is the first estimated time. The first estimated time is also the theoretical time for the first vehicle to arrive at the common docking point from the starting point to pick up passengers. This time can be used as a reference for determining the second estimated time of the actual docking point.

[0101] This embodiment can make a more accurate estimate based on the distance and estimated travel time of the currently dispatchable vehicles, and even the waiting time for boarding the vehicle, and finally obtain a first estimated time, so that the subsequent determination of the actual docking point can be more accurate.

[0102] As an optional embodiment of the present invention, the acquiring, based on the real-time driving data of the intersecting routes, the available driving data of the second vehicle passing through the common docking point before the first estimated time comprises:

[0103] Step: obtaining the fixed-point arrival time of the second vehicle before the common section of the intersecting route and the number of the second vehicles that can be dispatched;

[0104] Specifically, in this case, the second vehicle is of covering type, that is, there are sufficient vehicles, each of which has a large passenger capacity. The passenger flow demand of the intersecting routes can be met by setting fixed-point arrivals (at fixed intervals). Since the intersecting routes are not main routes and the increase in the number of people is limited, this condition is easier to meet.

[0105] Step: determining the number of people to be assigned to each second vehicle according to the number of dispatchable second vehicles, the maximum number of passengers of the second vehicles, and the total number of passengers before the common section of the intersecting routes;

[0106] Specifically, the total number of passengers before the common section of the intersecting routes is the total number of people counted again at a certain interval after one connection. For example, the number of dispatchable vehicles is 8, the maximum number of passengers is 20, and the total number of passengers is 50. Therefore, at least 3 vehicles can be dispatched, and the number of people assigned is 20, 20 and 10 (between 10 and 20). Alternatively, the integer N obtained by total number of passengers / maximum number of passengers can be obtained. If it is not an integer, the smallest integer larger than it is taken to obtain the integer N. At least N-1 vehicles can be set to be close to full, and then 1 vehicle can be vacant to obtain the classified number of people in each second vehicle, and then the next judgment is made.

[0107] Step: screening the second vehicle in which there is a preset difference between the maximum number of passengers and the allocated number of passengers;

[0108] Specifically, the second vehicle to be screened is a vehicle that is not fully occupied and has sufficient vacancies, such as at least 3 vacancies, so as to obtain the second vehicle to be screened.

[0109] Step: determining the second vehicle among the screened second vehicles that passes through the common docking point before the first estimated time, and obtaining a first determination result;

[0110] Specifically, to filter the second vehicle that passes the common docking point before the first estimated time, it is only necessary to select the second vehicle whose fixed-point arrival time is closest to the first estimated time and is before the first estimate. The previous step has been filtered once, and the target second vehicle can be obtained by superimposing the time filtering. Since the number of available passengers and vehicles of the target second vehicle are determined, it is easy to count the available driving data.

[0111] Step: According to the first determination result, the available driving data is obtained.

[0112] It can be understood that, in this embodiment, based on the fact that there are sufficient vehicles, the vehicles can be planned to arrive at a fixed time, and combined with the plan, it can be determined whether it is possible to pick up passengers at a common docking point.

[0113] The present invention further provides an embodiment parallel to the above embodiment, wherein the step of obtaining the available driving data of the second vehicle passing through the common docking point before the first estimated time based on the real-time driving data of the intersecting routes comprises:

[0114] Step: determining the required vehicle passenger capacity according to the passenger flow before the common section of the intersecting routes and a preset floating ratio, wherein the preset floating ratio is greater than 1;

[0115] Specifically, the passenger flow is the total number of passengers in a period of time, and the preset floating ratio is pre-set. The product of the two is the required vehicle passenger capacity. For example, if the total number of passengers is 40 and the preset floating ratio is 1.25, the vehicle passenger capacity is 50.

[0116] Step: determining a second vehicle that meets the passenger diversion demand according to the required vehicle passenger capacity and the single vehicle passenger capacity;

[0117] The ratio of the required vehicle passenger capacity to the single-vehicle passenger capacity is the number of second vehicles required. For example, if the vehicle passenger capacity is 50 people and the single-vehicle passenger capacity is 15 people, at least 4 vehicles are needed to meet the demand for diversion and riding.

[0118] Step: according to the determined second vehicle that meets the diversion riding demand, determine the vehicle that passes the common docking point before the first estimated time, and obtain a second determination result;

[0119] The second vehicle has been determined. Considering the time limit requirement for diversion and the fact that passenger flow may be gradually increasing, and the passenger flow on the intersecting routes is small, the second vehicles can be dispatched almost at the same time. For example, if the growth rate is about 40 people / h and the second vehicle carries 12 passengers / vehicle, 4 vehicles can be dispatched each time, and the vehicles are dispatched every 50 minutes. Alternatively, the data on the change in the number of people and the number of connecting vehicles are substituted into a trained deep learning model (such as a recurrent neural network RNN, a long short-term memory network LSTM or a convolutional neural network CNN). This allows the calculation of the interval departure time and the number of departures of the second vehicle. The departure time and the time to the common connecting point are set to be fixed (driving at a constant speed). Therefore, the vehicles that passed the common connecting point before the first estimated time (arrival at the estimated time at the latest) can be inferred to obtain the second result.

[0120] Step: According to the second determination result, the available driving data is obtained.

[0121] When determining the second vehicle, each vehicle is generally equipped with a margin, and combined with the actual passenger flow, if the passenger flow decreases, the margin will increase accordingly. If the passenger flow increases accordingly, the margin can meet the demand. The vacant passenger capacity of each vehicle can be determined, and the vacant driving data of the second vehicle can be obtained.

[0122] This embodiment provides another embodiment for obtaining the vacant vehicle data, which can plan the departure time interval of the second vehicle, and then determine the remaining number of vehicles that pass through the common docking point before meeting the estimated time, and then reasonably obtain the vacant passenger capacity of each vehicle, that is, obtain the vacant vehicle data, which is relatively accurate.

[0123] like Figure 4 As shown, as an optional embodiment of the present invention, determining the mobile distribution information of the gathered passengers according to the passenger flow data, and determining the positions and number of actual connecting points on the main route before the second estimated time according to the mobile distribution information and the limited number of people at each connecting point includes:

[0124] Step S131: sending the passenger flow data to the terminal where the guide on the main route is located, and waiting for a confirmation signal from the terminal;

[0125] Specifically, the guide guides the passengers to the docking point (each docking point can be configured with one or more docking points), and after sending the passenger flow data to the terminal carried by the guide, the guide is prompted to confirm the passenger flow data. The guide only needs to make a rough estimate of the number of people. After confirmation, the guide takes the real-time image information of the passengers he guides (the face can be hidden to ensure privacy) and then reports it to (the server).

[0126] Step S132: if the confirmation signal is detected, it is determined whether there are any gathered passengers arriving at the common docking point before the second estimated time according to the movement information of the terminal, and the confirmation signal is generated after confirming the passenger flow data and obtaining a live image of the gathered passengers;

[0127] Specifically, when the confirmation signal is detected, since the positioning of each guide's terminal is always on, the average moving speed (the ratio of the moving distance to the time, or directly obtained through the terminal speed measurement software) and the moving direction can be determined according to the terminal's movement information (the guide prompts the restricted personnel at the docking point when starting the guidance to select a docking point to which they are heading through the terminal, and it is necessary to comprehensively determine the actual docking point, that is, the preset priority, in combination with the distance between the gathered passengers and the common docking point and the location distribution of the docking point). For example, before the common section, there are docking points 1, 2, 3, and 4 (close to the common docking point or as the common docking point) along the direction from the starting point to the end point of the first vehicle. When the distance between a part of the gathered passengers and the common docking point is less than the threshold distance (the distance of the other part is greater than the threshold distance), the docking points are preset according to the priority from both sides to the middle, and their selection order can be determined as follows: No. 1 (No. 4) → No. 2 No. (No. 3); the distance between all the gathered passengers and the common connecting point is less than the threshold distance, and the actual connecting point is determined in order from near to far from the common connecting point, such as No. 4 → No. 3 → No. 2 → No. 1; this ensures that the moving passengers can arrive at the common connecting point nearby or according to their own needs. Of course, if the gathered passengers are all more than the threshold distance away from the common connecting point, the connecting point can be determined arbitrarily (such as No. 1 → No. 2 → No. 3). The common connecting point is generally determined by the guide of the gathered passengers who are relatively close to it. After the common connecting point is determined, the distance between the terminal and the common connecting point is determined, and the distance is divided by the duration of the second estimated time of the current distance to determine a target speed. When the target speed is greater than or equal to the average moving speed (or the difference between the target speed and the average speed is within the preset speed difference), it is determined that there are gathered passengers who arrive at the common connecting point before the second estimated time, and the subsequent travel speed is prompted according to the target speed.

[0128] Step S133: If yes, then determine the location and number of the actual docking points according to the aggregated passengers arriving at the common docking point before the second estimated time and the distribution of the remaining aggregated passengers corresponding to the passenger flow data;

[0129] The gathered passengers arrive at the common docking point before the second estimated time, so the actual docking points include the common docking points, and the number of each docking point is generally greater than or equal to the guided single group of gathered passengers (there are one or more groups of gathered passengers in total). The selection of the docking points has been described in detail in the previous step, and the distribution of the remaining gathered passengers can also be combined with the distance of the gathered passengers from the common docking point and the location distribution of the docking points to comprehensively determine the preset priority, which will not be described here.

[0130] Step S134: If not, directly determine the location and number of the actual docking points based on the distribution of the aggregated passengers corresponding to the passenger flow data.

[0131] When there are no gathered passengers arriving at the common connecting point before the second estimated time, the actual connecting point can be determined according to a preset order, for example, according to the order of the connecting point numbers from small to large (first separate multiple groups of gathered passengers, and then correspond to the connecting point numbers in turn after separation, which indicates that the group of gathered passengers corresponds to the corresponding connecting point), and the next connecting point is determined after the previous connecting point is full, that is, the order of the actual connecting points is determined.

[0132] It should be noted that when all the connecting points are full at the same time and there are still passengers who have not been assigned a connecting point, the recommendation information for adding the first vehicle or the second vehicle should be reported.

[0133] It should be understood that by combining passenger flow data with the mobile distribution information of mobile aggregated passengers, fully considering the passengers' nearby movement or actual movement (such as movement speed), the passengers under the passenger flow data can be reasonably guided and quickly assigned to the corresponding docking points, thereby ensuring the stability of the aggregated passengers. Especially when the actual docking points include common docking points, in theory, docking can be achieved preferentially and the docking pressure of the first vehicle can be reduced, or the first vehicle can be used to dock the increased number of passengers on the first line, effectively improving the efficiency of the diversion.

[0134] As another optional embodiment of the present invention, if the actual docking point includes at least a common docking point, determining the dispatch quantity of the first vehicle on the main route according to the vacant vehicle data and the passenger flow data so as to achieve docking of all passengers under the passenger flow data by the first vehicle and the second vehicle comprises:

[0135] Step: determining the total number of passengers in the passenger flow data, and determining the number of remaining passengers based on the total number of passengers and the total available passenger capacity in the available vehicle data;

[0136] Specifically, the total number of passengers in the passenger flow data is equal to the total number of passengers in the passenger flow data, which can be directly counted through valid passenger data and passenger data of on-site reservations; it can also be obtained by aggregating passengers, etc.; the difference between the total number of passengers and the total vacant passenger capacity, that is, the remaining number of passengers, means that the second vehicle will pick up the same number of passengers as the total vacant passenger capacity in the common transfer point, and the remaining passengers can all be picked up by the first vehicle.

[0137] Step: Determine the dispatch quantity of the first vehicle on the main route according to the number of remaining passengers and the preset passenger capacity of the first vehicle, generate an additional connection instruction according to the second estimated time and the total available passenger capacity, and send the additional connection instruction to the second vehicle with available passenger capacity.

[0138] Specifically, the preset passenger capacity can be close to full load, such as 90-100% of the full load capacity, and more passengers can be carried. In one case, the ratio of the remaining number of passengers to the preset passenger capacity is used to obtain the dispatch number of the first vehicle. The information of the second vehicle's connecting capacity should also be sent to the first vehicle. In the case that the second vehicle has additional connecting capacity, it will not pick up all the passengers on the main route.

[0139] Of course, since the passenger flow data has taken into account the number of people who have made remote reservations, and the preset passenger capacity may not be full, it can meet the demand for increased passenger flow to a certain extent and improve the stability of connection.

[0140] It should be noted that, since the first destination and the second destination may be the same or different destinations, when the first destination and the second destination are different destinations, or the two are far apart, there are passengers on the first route who are heading to the second destination by the second vehicle but are picked up at the common docking point, and their destination may be the first destination. At this time, the additional docking instruction should also include releasing passengers with different destinations at the terminal docking point of the common section (only the common docking point and the terminal docking point facing the first vehicle and the second vehicle are set on the common section). These released passengers send a terminal docking instruction to the second vehicle or the first vehicle heading to the first destination to wait for the subsequent second vehicle or the first vehicle heading to the first destination. Because these vehicles may not be fully loaded, the docking demand can be met. In addition, the method also includes: counting the passengers temporarily stranded at the terminal docking point, and when the number of stranded passengers reaches the first threshold and the stranded time reaches the preset duration, generating a third instruction to dispatch another first vehicle for docking. These first vehicles are empty from the starting point to the terminal docking point and can quickly reach the terminal docking point.

[0141] For example, before the first estimated time, there are 2 second vehicles arriving at the common docking point, and the total available passenger capacity is 10 people. One of the second vehicles A has an available passenger capacity of 8 and goes to the first destination, and the other second vehicle B has an available passenger capacity of 6 and goes to the second destination. At this time, the second vehicles A and B jointly pick up these 10 people, and the second vehicle B releases 2 people at the terminal docking point, waiting for the subsequent first vehicle or second vehicle. Therefore, since the second vehicle arrives before the first time, at least 8 people can arrive at the first destination first, and the passenger load rate is increased. Moreover, these 8 people arrive at the common docking point based on their own mobility needs and do not need to be picked up by the second vehicle; the total number of passengers is 50, so the remaining number of passengers is 42, and the preset passenger capacity is 14 (a vehicle with a full load of 15 people, such as a commercial vehicle), so 3 first vehicles can be dispatched.

[0142] The above can connect passengers under the total available passenger capacity in combination with the actual mobility needs of the passengers. These passengers can even arrive at the first destination in advance, and the passenger load factor is increased. The subsequent first vehicle can connect more passengers on the first route, which is conducive to improving the efficiency of passenger diversion on the main route.

[0143] like Figure 5 As shown, based on the passenger flow diversion method based on big data proposed in the above embodiment, on the other hand, a passenger flow diversion system based on big data includes:

[0144] A passenger flow acquisition module 100 is used to acquire passenger flow data on a sub-section of the main route before a common section with the intersecting route;

[0145] A time determination module 200, for determining a first estimated time for a first vehicle on the main route to arrive at a common connecting point on the common road section;

[0146] The driving data acquisition module 300 is used to acquire the available driving data of the second vehicles passing through the common docking point before the first estimated time according to the real-time driving data of the intersecting route, wherein the available driving data includes the available passenger capacity of each of the second vehicles and the destination to be reached, wherein the destination includes the first end point of the main route or the second end point of the bifurcated route;

[0147] The docking point determination module 400 is used to determine the movement distribution information of the gathered passengers according to the passenger flow data, and determine the position and number of the actual docking points on the main route before the second estimated time according to the movement distribution information and the limited number of people at each docking point, wherein the second estimated time and the first estimated time are within a preset time difference range, and the docking points are selected as the actual docking points according to the priority including from both sides to the middle before the common road section;

[0148] The dispatch determination module 500 is used to determine the dispatch quantity of the first vehicle on the main route according to the vacant vehicle data and the passenger flow data if the actual docking point includes at least a common docking point, so as to realize the docking of all passengers under the passenger flow data by the first vehicle and the second vehicle.

[0149] It should be noted that, referring to the specific implementation description of a passenger flow diversion method based on big data in the aforementioned embodiment, this system completely corresponds to the implementation method of the method and will not be described again here.

[0150] The above-mentioned embodiment of the present invention provides a passenger flow diversion method based on big data, and based on the passenger flow diversion method based on big data, provides a passenger flow diversion system based on big data. By fully considering the aggregation of passengers on the main route, the aggregated passengers (multiple passengers in groups) can be predicted and guided, for example, based on the actual movement distribution information of the passengers, and the actual environmental impact of the docking point can be considered to avoid excessive aggregation during diversion, and finally the position and number of actual docking points on the main route are formed, that is, the pre-set docking point is selected as the actual passenger pick-up point when the subsequent vehicle picks up passengers, and the determination of the actual docking point uses the second estimated time as the reference time. Its purpose is to refer to the time when the first vehicle arrives at the common docking point, so that it can be used for the first The vehicle and / or the second vehicle provide a relatively accurate time reference for the connection at the actual connecting point, ensuring that the passengers at the connecting point are ready or about to be ready when the connection is made; further, if the actual connecting point includes at least a common connecting point, the dispatch quantity of the first vehicle on the main route is determined according to the spare driving data and the passenger flow data, so as to realize the connection of all passengers under the passenger flow data by the first vehicle and the second vehicle. In combination with the actual movement needs of the passengers, the spare passenger capacity of the second vehicle on the forked route can be fully utilized to realize the guidance under the overall planning and improve the passenger load factor. The subsequent first vehicle can connect more passengers on the first route, which is conducive to improving the guidance efficiency of the passengers on the main route.

[0151] It should be noted that big data can be structured data and unstructured data from different sources. The present invention combines data from multiple sources to comprehensively consider passenger flow diversion on the main route, and can provide reliable data support or reference for actual passenger flow diversion.

[0152] In order to load the above-mentioned method and system and enable it to run smoothly, the system, in addition to the various modules mentioned above, may also include more or fewer components than described above, or a combination of certain components, or different components, for example, it may include input and output devices, network access devices, buses, processors and memories, etc.

[0153] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the system, and various interfaces and lines are used to connect various parts.

[0154] The above-mentioned memory can be used to store computer and system programs and / or modules, and the above-mentioned processor realizes the above-mentioned various functions by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as an information collection template display function, a product information release function, etc.). In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0155] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0156] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0157] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A passenger flow diversion method based on big data, characterized in that: include: Obtain passenger flow data on a sub-section of the main route before a common section with the intersecting route; Determine a first estimated time for a first vehicle on the main route to arrive at a common connecting point on the common road segment; Acquire, based on the real-time driving data of the intersecting route, the available driving data of the second vehicles that pass through the common docking point before the first estimated time, the available driving data including the available passenger capacity of each of the second vehicles and the destination to be reached, the destination including the first end point of the main route or the second end point of the intersecting route; Determine the movement distribution information of the gathered passengers according to the passenger flow data, and determine the positions and number of actual docking points on the main route before the second estimated time according to the movement distribution information and the number of people limited at each docking point, wherein the second estimated time and the first estimated time are within a preset time difference range, and the docking point is selected as the actual docking point according to a preset priority; If the actual docking point includes at least a common docking point, the dispatch quantity of the first vehicle on the main route is determined according to the vacant vehicle data and the passenger flow data, so as to dock all passengers under the passenger flow data by the first vehicle and the second vehicle.

2. The passenger flow diversion method based on big data according to claim 1 is characterized in that: The step of obtaining passenger flow data on a sub-section of the main route before the common section with the intersecting route includes: According to a preset statistical time interval, counting the passenger data that takes the first terminal or the second terminal as the target arrival point, the passenger data includes the passenger data that makes a remote reservation based on the sub-segment and the passenger data that makes an on-site reservation; Determine valid passenger data for the remote reservation based on the passenger data for the remote reservation; The valid passenger data of remote reservations and the passenger data of on-site reservations are aggregated to generate the passenger flow data.

3. The passenger flow diversion method based on big data according to claim 2 is characterized in that: Determining the valid passenger data of the remote reservation according to the passenger data of the remote reservation comprises: Obtaining the passenger location corresponding to the remotely booked passenger data; Filtering the passenger locations within a preset distance range from the connecting point of the sub-section to obtain a filtering result; The passenger data of the remote reservation corresponding to the screening result is used as the valid passenger data.

4. The passenger flow diversion method based on big data according to claim 3 is characterized in that: The first estimated time for the first vehicle on the main route to arrive at the common connecting point on the common road section includes: Obtaining currently dispatchable vehicles for passenger diversion at the connecting point; Determining an estimated travel time according to the vehicle location of the currently dispatchable vehicle and the distance between the common docking point and the travel speed of the currently dispatchable vehicle; Obtain the boarding waiting time at the connecting point; The first estimated time is determined according to the estimated travel time and the waiting time for boarding.

5. The passenger flow diversion method based on big data according to claim 4 is characterized in that: The acquiring, based on the real-time driving data of the intersecting routes, the available driving data of the second vehicle passing through the common docking point before the first estimated time comprises: Obtaining the fixed-point arrival time of the second vehicle before the common section of the intersecting route and the number of the second vehicles that can be dispatched; determining the number of persons to be assigned to each second vehicle according to the number of dispatchable second vehicles, the maximum number of passengers of the second vehicles, and the total number of passengers before the common section of the intersecting routes; Selecting the second vehicle for which there is a preset difference between the maximum number of passengers and the allocated number of passengers; Determine the second vehicle among the screened second vehicles that passes through the common docking point before the first estimated time, and obtain a first determination result; The available driving data is obtained according to the first determination result.

6. The passenger flow diversion method based on big data according to claim 1 or 5, characterized in that: The acquiring, based on the real-time driving data of the intersecting routes, the available driving data of the second vehicle passing through the common docking point before the first estimated time comprises: Determine the required vehicle passenger capacity according to the passenger flow before the common section of the intersecting routes and a preset floating ratio, wherein the preset floating ratio is greater than 1; Determining a second vehicle that meets the passenger diversion demand based on the required vehicle passenger capacity and the single-vehicle passenger capacity; According to the determined second vehicle that meets the diversion riding demand, determine a vehicle that passes through the common docking point before the first estimated time, and obtain a second determination result; The available driving data is obtained according to the second determination result.

7. The passenger flow diversion method based on big data according to claim 1, 4 or 5, characterized in that: Determining the movement distribution information of the gathered passengers according to the passenger flow data, and determining the positions and number of actual connecting points on the main route before the second estimated time according to the movement distribution information and the limited number of people at each connecting point, comprises: Sending the passenger flow data to the terminal where the guide is located on the main route, and waiting for a confirmation signal from the terminal; If the confirmation signal is detected, determining whether there are gathered passengers arriving at the common docking point before the second estimated time according to the movement information of the terminal, the confirmation signal being generated after confirming the passenger flow data and obtaining a live image of the gathered passengers; If yes, determining the location and number of the actual docking points according to the aggregated passengers arriving at the common docking point before the second estimated time and the distribution of the remaining aggregated passengers corresponding to the passenger flow data; If not, the location and number of the actual connecting points are determined directly based on the distribution of the aggregated passengers corresponding to the passenger flow data.

8. The passenger flow diversion method based on big data according to claim 1, 4 or 5, characterized in that: If the actual docking point includes at least a common docking point, determining the dispatch quantity of the first vehicle on the main route according to the vacant vehicle data and the passenger flow data, so as to achieve docking of all passengers under the passenger flow data by the first vehicle and the second vehicle comprises: Determine the total number of passengers in the passenger flow data, and determine the number of remaining passengers based on the total number of passengers and the total available passenger capacity in the available vehicle data; The number of first vehicles to be dispatched on the main route is determined according to the number of remaining passengers and the preset passenger capacity of the first vehicle.

9. The passenger flow diversion method based on big data according to claim 8, characterized in that: If the actual docking point includes at least a common docking point, determining the dispatch quantity of the first vehicle on the main route according to the vacant vehicle data and the passenger flow data, so as to achieve docking of all passengers under the passenger flow data by the first vehicle and the second vehicle, further includes: An additional connection instruction is generated according to the second estimated time and the total available empty passenger capacity, and the additional connection instruction is sent to a second vehicle with available passenger capacity.

10. A passenger flow management system based on big data, characterized in that: The method for directing passenger flow based on big data as claimed in any one of claims 1 to 9 is applied, comprising: A passenger flow acquisition module, used to acquire passenger flow data on a sub-section of the main route before a common section with the intersecting route; A classification module, configured to determine a first estimated time for a first vehicle on the main route to arrive at a common connecting point on the common road segment; a driving data acquisition module, configured to acquire, based on the real-time driving data of the intersecting route, the available driving data of the second vehicles passing through the common docking point before the first estimated time, wherein the available driving data includes the available passenger capacity of each of the second vehicles and the destination to be reached, wherein the destination includes the first end point of the main route or the second end point of the intersecting route; A docking point determination module, configured to determine the movement distribution information of the gathered passengers according to the passenger flow data, and determine the position and number of the actual docking points on the main route before the second estimated time according to the movement distribution information and the limited number of people at each docking point, wherein the second estimated time and the first estimated time are within a preset time difference range, and the docking point is selected as the actual docking point according to a preset priority; The dispatch determination module is used to determine the dispatch quantity of the first vehicle on the main route according to the vacant vehicle data and the passenger flow data if the actual docking point includes at least a common docking point, so as to realize the docking of all passengers under the passenger flow data by the first vehicle and the second vehicle.

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