Inter-city train dispatching method, device, computer equipment and storage medium

Abstract

The present invention discloses a shuttle bus scheduling method, which is applied to the field of intelligent transportation and is used to improve the efficiency of shuttle bus scheduling. The method provided by the present invention includes: based on the station set and time set corresponding to the shuttle bus to be scheduled, obtaining at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information; preprocessing all the historical passenger flow information to obtain preprocessing information corresponding to each of the historical passenger flow information; inputting all the preprocessing information and the time information corresponding to the historical passenger flow information into a scheduling prediction model for prediction calculation to obtain a prediction result; scheduling the shuttle bus to be scheduled based on the prediction result.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation, and in particular to a method, device, computer equipment and storage medium for scheduling inter-city buses. Background Art

[0002] In urban transportation, shuttle buses are a common flexible dispatching method for public transportation, such as bus dispatching, subway dispatching, and elevator dispatching. When shuttle buses are used in bus dispatching, they refer to vehicles that only run on part of the entire route in order to meet the passengers' riding needs. Shuttle buses can reasonably allocate capacity according to the passenger demand in different intervals, increase the departure frequency in intervals with higher demand, alleviate the problems of long waiting time and congestion caused by insufficient capacity supply in the interval, and improve the overall operation efficiency of the line.

[0003] At present, the scheduling decisions of shuttle buses are mostly based on the business experience of bus operators. Based on the understanding of the passenger flow of the route, the bus operators select a section of the route from the regular bus route as the route corresponding to the shuttle bus and choose the appropriate time to start the bus. In addition, with the development of advanced public transportation technologies such as IC cards (Integrated Circuit Cards) and automatic ticket vending and checking systems, it is also possible to obtain the passenger flow of the route and schedule it according to the passenger flow of the route. However, scheduling based on the passenger flow of the route is prone to the phenomenon of "bus stringing". Taking buses as an example, "bus stringing" refers to the phenomenon that two or more buses arrive at the same station at the same time in a short period of time. The "bus stringing" phenomenon easily causes multiple buses to appear at a certain station at the same time, resulting in no buses at other stations for a long time, which reduces the efficiency of shuttle bus scheduling. Therefore, in the routes corresponding to the shuttle buses, only relying on business experience to predict the passenger flow of the route and schedule the shuttle bus, or only relying on the passenger flow data of the route to schedule the shuttle bus, it is easy to lead to low efficiency and rationality of shuttle bus scheduling.

[0004] Therefore, the existing method has the problem of low efficiency in shuttle bus scheduling. Summary of the invention

[0005] The present invention provides a shuttle bus dispatching method, device, computer equipment and storage medium to improve the efficiency of shuttle bus dispatching.

[0006] A shuttle bus dispatching method, comprising:

[0007] Based on the station set and time set corresponding to the shuttle bus to be scheduled, obtaining at least two pieces of historical shuttle bus information corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information;

[0008] Preprocessing all the historical passenger flow information to obtain preprocessing information corresponding to each piece of historical passenger flow information;

[0009] Inputting the time information corresponding to all the pre-processing information and the historical passenger flow information into the scheduling prediction model for prediction calculation to obtain a prediction result;

[0010] Based on the prediction result, the shuttle bus to be scheduled is scheduled.

[0011] A shuttle bus dispatching device, comprising:

[0012] A historical shuttle bus information acquisition module, configured to acquire at least two pieces of historical shuttle bus information corresponding to the shuttle bus to be scheduled based on the station set and time set corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information;

[0013] A preprocessing module, used to preprocess all the historical passenger flow information to obtain preprocessing information corresponding to each of the historical passenger flow information;

[0014] A prediction module, used for inputting the time information corresponding to all the pre-processing information and the historical passenger flow information into a scheduling prediction model for prediction calculation to obtain a prediction result;

[0015] A scheduling module is used to schedule the shuttle buses to be scheduled based on the prediction results.

[0016] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned shuttle bus scheduling method when executing the computer program.

[0017] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned shuttle bus scheduling method are implemented.

[0018] The shuttle bus scheduling method, device, computer equipment and storage medium provided by the embodiments of the present invention obtain at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled based on the station set and time set corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information; pre-process all the historical passenger flow information to obtain pre-processed information corresponding to each of the historical passenger flow information; input all the pre-processed information and the time information corresponding to the historical passenger flow information into the scheduling prediction model for prediction calculation to obtain a prediction result; and schedule the shuttle bus to be scheduled based on the prediction result. By combining the historical passenger flow information of the historical shuttle bus corresponding to the shuttle bus to be scheduled and the time information corresponding to the historical passenger flow information, the passenger flow and running time of the shuttle bus to be scheduled are predicted, and the shuttle bus to be scheduled is scheduled according to the obtained prediction result, thereby improving the efficiency of shuttle bus scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0020] Figure 1 is a schematic diagram of an application environment of a shuttle bus scheduling method in an embodiment of the present invention;

[0021] Figure 2 is a flow chart of a shuttle bus dispatching method according to an embodiment of the present invention;

[0022] Figure 3 is an example diagram of a method for scheduling shuttle buses in one embodiment of the present invention.

[0023] Figure 4 is a flow chart of a shuttle bus dispatching method according to an embodiment of the present invention;

[0024] Figure 5 is a flow chart of a shuttle bus dispatching method according to an embodiment of the present invention;

[0025] Figure 6 is a flow chart of a shuttle bus dispatching method according to an embodiment of the present invention;

[0026] Figure 7 is a flow chart of a shuttle bus dispatching method according to an embodiment of the present invention;

[0027] Figure 8 is a flow chart of a shuttle bus dispatching method according to an embodiment of the present invention;

[0028] Fig. 9 It is a structural schematic diagram of a shuttle bus dispatching device in one embodiment of the present invention;

[0029] Fig.10 is a schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] The shuttle bus scheduling method provided by the embodiment of the present invention can be applied in the following aspects: Figure 1 In an application environment, a computer device communicates with a server via a network. The computer device may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices. The server may be implemented as an independent server or a server cluster consisting of multiple servers.

[0032] The system framework 100 may include a terminal device, a network and a server. The network is used to provide a medium for a communication link between the terminal device and the server. The network may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0033] Users can use terminal devices to interact with the server through the network to receive or send messages, etc.

[0034] Terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Eperts Group Audio Layer III), MP4 (Moving Picture Eperts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0035] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0036] It should be noted that the shuttle bus scheduling method provided in the embodiment of the present invention is executed by a server, and accordingly, the shuttle bus scheduling device is arranged in the server.

[0037] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only illustrative. According to the implementation requirements, there may be any number of terminal devices, networks and servers. The terminal devices in the embodiment of the present invention may specifically correspond to application systems in actual production.

[0038] The shuttle bus mentioned in the embodiment of the present invention refers to a common flexible dispatching mode of public transportation in urban transportation.

[0039] The shuttle buses include but are not limited to bus shuttle buses, subway shuttle buses, and elevator shuttle buses.

[0040] In order to facilitate the explanation of the following steps, the embodiment of the present invention is described by taking a bus shuttle bus as an example.

[0041] It should be understood that the following steps are also applicable to other types of shuttle buses.

[0042] When the shuttle bus is used on a bus, the information corresponding to the shuttle bus includes route information, shuttle bus information, GPS information, and passenger flow information.

[0043] The route information refers to the information on the route of the shuttle bus, including but not limited to the route name, the serial number of the stations along the route, the station name, and the longitude and latitude corresponding to the stations.

[0044] The shuttle bus information refers to the information related to the shuttle bus scheduling, including but not limited to the shuttle bus ID, shuttle bus license plate number, departure time, and end time.

[0045] GPS information refers to the GPS information obtained in real time during the shuttle bus process. The GPS information includes but is not limited to the shuttle bus license plate number, the arrival time of the shuttle bus at each station, and the time information of the shuttle bus leaving each station.

[0046] Passenger flow information refers to the passenger flow information corresponding to each station of the shuttle bus. The passenger flow information includes but is not limited to the line name, shuttle bus ID, passenger gathering volume and passenger evacuation volume corresponding to each station of the shuttle bus. The passenger gathering volume refers to the number of passengers getting on the bus at the current station, and the passenger evacuation volume refers to the number of passengers getting off the bus at the current station.

[0047] It should be understood that at different times of the day, the travel patterns and road conditions of passengers may change, so the embodiments of the present invention are closely related to time. Taking 00:00 as the starting point, the 24 hours of the day can be divided into small segments consistent with the preset time. For example, when the preset time is 10 minutes, T can be used to represent the index of each time segment. For example, T=39 represents the time period of 06:30-06:40. This is adjusted in combination with actual applications and is not limited.

[0048] By associating and integrating line information, historical shuttle bus information, GPS information, and passenger flow information, we can obtain the arrival time of each shuttle bus at each station on its corresponding line and the passenger gathering and passenger evacuation volume corresponding to each station.

[0049] In one embodiment, if Figure 2 As shown, a shuttle bus scheduling method is provided, which is applied in Figure 1 The server in the example is used as an example to illustrate, including the following steps S10 to S40:

[0050] S10. Based on the station set and time set corresponding to the shuttle bus to be scheduled, obtain at least two pieces of historical shuttle bus information corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information.

[0051] In step S10, the shuttle bus to be dispatched refers to a common flexible dispatching method of public transportation in urban transportation.

[0052] The above-mentioned shuttle trains to be dispatched include but are not limited to bus shuttle trains to be dispatched, subway shuttle trains to be dispatched, and elevator shuttle trains to be dispatched.

[0053] In order to facilitate the explanation of the steps, this application is explained using the bus shuttle bus to be dispatched as an example.

[0054] The above-mentioned station set refers to the set consisting of all stations of the shuttle buses to be dispatched.

[0055] The above time set refers to the set consisting of the time corresponding to each station in the interval train to be scheduled.

[0056] The time corresponding to each stop includes but is not limited to arrival time and departure time.

[0057] Taking the shuttle bus used in bus dispatch as an example, a shuttle bus refers to a vehicle that only runs on part of the entire bus route to meet the passengers' travel needs.

[0058] A bus route is usually divided into two roughly symmetrical operating directions: up and down.

[0059] It should be understood that the above two running directions of up and down are also applicable to other public transportation vehicles.

[0060] like Figure 3 As shown, there is a shuttle A. On the shuttle A, O1 is the up-going starting station, D1 is the up-going terminal station, O2 is the down-going starting station, D2 is the down-going terminal station, S' is the up-going station, and S" is the down-going station.

[0061] Among them, S' refers to the last station where the shuttle bus makes a U-turn in the upward bus route, and S" refers to the first station after the shuttle bus makes a U-turn from the upward bus route in the downward bus route.

[0062] Generally, S' and S" are symmetrical sites, but the case where S' and S" are asymmetrical is not excluded.

[0063] The station set corresponding to the shuttle bus A is (O1, S', D1, D2, S", O2).

[0064] Among them, the time corresponding to O1 in the station set of the shuttle A is T O1 and T O1 The time corresponding to ';S' is T S’ and T S' '; The time corresponding to D1 is T D1 and T D1 '; The time corresponding to D2 is T D2 and T D2 The time corresponding to ';S" is T S” and T S” '; The time corresponding to O2 is T O2 and T O2 '.

[0065] Therefore, (T O1 , T S’ , T D1 , T D2 , T S” , T O2 ) are the arrival times of the scheduled shuttle buses corresponding to (O1, S', D1, D2, S", O2) at the station.

[0066] (T O1 ', T S' ', T D1 ', T D2 ', T S” , T O2 ') are the departure times of the scheduled shuttle buses corresponding to (O1, S', D1, D2, S", O2) at the station.

[0067] The above method for obtaining at least two pieces of historical train information corresponding to the train to be scheduled is keyword matching.

[0068] The keyword matching includes but is not limited to site information matching and time matching.

[0069] The above historical shuttle train information refers to all the information contained in the historical shuttle train. The historical shuttle train refers to the shuttle train that departs at the same time as the shuttle train to be scheduled and has the same uplink terminal station and the same downlink starting station.

[0070] The above historical passenger flow information refers to the passenger flow information corresponding to the historical shuttle bus.

[0071] The historical passenger flow information includes but is not limited to the route name corresponding to the historical shuttle bus, the route information corresponding to the historical shuttle bus, the historical shuttle bus dispatch ID, and the passenger gathering volume and passenger evacuation volume at each station on the route. The passenger gathering volume refers to the number of passengers getting on the bus at the current station, and the passenger evacuation volume refers to the number of passengers getting off the bus at the current station.

[0072] The time information corresponding to the above historical passenger flow information refers to the time information corresponding to the historical shuttle bus at each station.

[0073] The time information corresponding to the historical passenger flow information includes but is not limited to the departure time, the uplink arrival time, the arrival time and the departure time corresponding to each station, the downlink departure time, and the downlink arrival time.

[0074] Through the station set and time set corresponding to the shuttle bus to be scheduled, the historical passenger flow information of at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled and the time information corresponding to the historical passenger flow information are obtained, which is conducive to combining the time information and passenger flow information to predict the passenger flow and running time of the shuttle bus. Accurate passenger flow information and time information improve the accuracy of the prediction and further improve the efficiency of shuttle bus scheduling.

[0075] S20: pre-process all historical passenger flow information to obtain pre-processed information corresponding to each piece of historical passenger flow information.

[0076] In step S20, the above preprocessing includes but is not limited to data cleaning, normalization, and standardization.

[0077] The above data cleaning includes but is not limited to outlier cleaning and missing value cleaning. Due to the influence of the passenger flow information collection system or other factors, in practical applications, it is inevitable that there will be abnormal data, such as missing data, outliers, etc. Therefore, it is necessary to clean the historical passenger flow data to reduce data noise and improve the accuracy of the scheduling prediction model.

[0078] The above-mentioned normalization and standardization refers to mapping the historical passenger flow information to the same scale to ensure the convenience of subsequent data processing.

[0079] By preprocessing historical passenger flow information, data noise can be effectively reduced, the difficulty of subsequent data processing can be weakened, the accuracy of the scheduling prediction model can be improved, and the efficiency of inter-city vehicle scheduling can be improved.

[0080] S30: Input the time information corresponding to all pre-processing information and historical passenger flow information into the scheduling prediction model for prediction calculation to obtain a prediction result.

[0081] In step S30, the implementation method of the above-mentioned scheduling prediction model includes but is not limited to time series analysis method and machine learning prediction method.

[0082] Among them, the time series analysis method is to build a model by describing the past, analyzing the rules, and predicting the future. Machine learning prediction methods include but are not limited to decision trees and support vector machine regression.

[0083] Preferably, the present invention adopts time series analysis method to establish a scheduling prediction model.

[0084] The above-mentioned prediction calculation refers to a calculation method for predicting the time information corresponding to the corresponding pre-processing information and the historical passenger flow information.

[0085] The implementation methods of the above prediction calculation include but are not limited to weighted summation and average value.

[0086] The scheduling prediction model is used to predict the time information corresponding to the pre-processing information and the historical passenger flow information. Since the time information corresponding to the pre-processing information and the historical passenger flow information has high reliability, the accuracy of the prediction calculation is improved, thereby improving the efficiency of the inter-city bus scheduling.

[0087] S40. Based on the prediction result, the vehicles in the scheduled section are scheduled.

[0088] In step S40, the above prediction results include but are not limited to predicted passenger flow information and predicted running time.

[0089] The above-mentioned scheduling determination methods include but are not limited to optimal passenger flow scheduling and optimal shuttle bus scheduling.

[0090] Among them, the optimal passenger flow scheduling refers to the method of scheduling to meet the maximum passenger flow information. Among them, the process of optimal passenger flow scheduling is: obtain the predicted passenger flow information of each station, arrange the predicted passenger flow information of each station in order from large to small, obtain the predicted passenger flow information set, select the predicted passenger flow information equal to the preset number from the predicted passenger flow information set in order from large to small as the scheduling passenger flow information, calculate the scheduling number of the shuttle buses to be scheduled according to all the scheduling passenger flow information, and schedule the shuttle buses to be scheduled according to the scheduling number and the time points corresponding to all the scheduling passenger flow information. For example, when the shuttle bus to be scheduled can accommodate 10 people, the scheduling passenger flow information is 45 people, and the time point corresponding to the scheduling passenger flow information is 9 am, then the number of people in the scheduling passenger flow information 45 is divided by the number of people that the shuttle bus to be scheduled can accommodate 10, and the scheduling number of the shuttle bus to be scheduled is 5, then at 9 am, 5 shuttle buses to be scheduled are scheduled.

[0091] The optimal dispatching of shuttle buses refers to a dispatching method that satisfies the best of all prediction results at the same time. For example, when the prediction results are predicted passenger flow information and predicted running time, the optimal dispatching process of shuttle buses is as follows: obtain the predicted passenger flow information and predicted running time of each station, assign different weights to the predicted passenger flow information and predicted running time according to the preset weight assignment method, and perform weighted summation of the predicted passenger flow information and predicted running time corresponding to each station assigned with different weights to obtain the predicted weighted information, arrange the predicted weighted information of each station in order from large to small, and obtain the predicted weighted information set, select the predicted weighted information equal to the preset number from the predicted weighted information set in order from large to small as the dispatching information, calculate the dispatching quantity of the shuttle buses to be dispatched according to all the dispatching information, and dispatch the shuttle buses to be dispatched according to the dispatching quantity and the time points corresponding to all the dispatching information. For example, when the number of people that the shuttle bus to be dispatched can accommodate is 20, the dispatch information is 40, and the time point corresponding to the dispatch information is 9 a.m., then divide the number of people in the dispatch information 40 by the number of people that the shuttle bus to be dispatched can accommodate 20, and the dispatch number of shuttle buses to be dispatched is 2. At 9 a.m., 2 shuttle buses to be dispatched are dispatched.

[0092] It should be understood that the scheduling method adopted should be selected in combination with the actual application scenario and is not specifically limited here.

[0093] The prediction results are used to schedule the shuttle buses to be scheduled. Since the accuracy of the prediction results is high, the efficiency of shuttle bus scheduling is improved.

[0094] The shuttle bus scheduling method, device, computer equipment and storage medium provided by the embodiments of the present invention obtain at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled based on the station set and time set corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information; pre-process all the historical passenger flow information to obtain pre-processed information corresponding to each of the historical passenger flow information; input all the pre-processed information and the time information corresponding to the historical passenger flow information into the scheduling prediction model for prediction calculation to obtain a prediction result; and schedule the shuttle bus to be scheduled based on the prediction result. By combining the historical passenger flow information of the historical shuttle bus corresponding to the shuttle bus to be scheduled and the time information corresponding to the historical passenger flow information, the passenger flow and running time of the shuttle bus to be scheduled are predicted, and the shuttle bus to be scheduled is scheduled according to the obtained prediction result, thereby improving the efficiency of shuttle bus scheduling.

[0095] In this embodiment, if Figure 4 As shown, as a preferred implementation, in step S10, based on the station set and time set corresponding to the shuttle bus to be scheduled, the step of obtaining at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information, comprises:

[0096] S101. Obtain the uplink station, downlink station, and departure time corresponding to the shuttle bus to be scheduled, wherein the uplink station is the terminal station of the outbound trip of the shuttle bus to be scheduled, and the downlink station is the starting station of the return trip of the shuttle bus to be scheduled.

[0097] S102, performing matching processing according to the departure time, the uplink station, and the downlink station to determine at least two pieces of historical shuttle bus information corresponding to the shuttle bus to be scheduled.

[0098] S103. Based on the historical inter-city train information, obtain historical passenger flow information corresponding to the historical inter-city train information and time information corresponding to the historical passenger flow information.

[0099] In step S101, specifically, the up-going station, down-going station and departure time corresponding to the shuttle bus to be scheduled are obtained from the shuttle bus information corresponding to the shuttle bus to be scheduled.

[0100] For example, Figure 3 For the shuttle bus departing from the upward route shown, S' is the upward station, S" is the downward station, and the departure time corresponding to O1 is the departure time.

[0101] It should be understood that the information obtained from the shuttle bus information corresponding to the shuttle bus to be scheduled includes but is not limited to the uplink station, downlink station, and departure time corresponding to the shuttle bus to be scheduled. The information obtained here can be selected in combination with the specific application scenario.

[0102] For example, in a shuttle bus used in public transportation scheduling, the arrival time or departure time corresponding to each station can be obtained from the shuttle bus information corresponding to the shuttle bus.

[0103] In step S102, the matching process is to match the historical shuttle bus database according to the departure time, the upstream station and the downstream station to obtain the historical shuttle bus information corresponding to the shuttle bus to be scheduled. It should be noted that the data in the historical shuttle bus database is the historical shuttle bus information corresponding to the shuttle bus to be scheduled only if and only if the data in the historical shuttle bus database has the same departure time, the same upstream station and the same downstream station as the shuttle bus to be scheduled.

[0104] In step S103, specifically, based on the historical shuttle bus information, the shuttle bus ID, the shuttle bus license plate number, and the departure time corresponding to the historical shuttle bus are obtained, and the passenger flow information corresponding to the shuttle bus ID and the shuttle bus license plate number at the departure time and the time information corresponding to the passenger flow information are obtained.

[0105] It should be noted here that the historical shuttle bus information is first obtained, and then the passenger flow information corresponding to the historical shuttle bus information is obtained, and based on the passenger flow information, the time information corresponding to each station passed by the historical shuttle bus is obtained.

[0106] By going through the above steps, the historical passenger flow information corresponding to the historical shuttle bus and the time information corresponding to the historical passenger flow information are obtained, which is conducive to combining the time information and passenger flow information to predict the passenger flow and running time of the shuttle bus. Accurate passenger flow information and time information improve the accuracy of the prediction and further improve the efficiency of shuttle bus scheduling.

[0107] In this embodiment, if Figure 5 As shown, as a preferred implementation, in step S102, the step of performing matching processing according to the departure time, the uplink station, and the downlink station to determine at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled includes:

[0108] S1021. Determine at least two historical shuttle buses corresponding to the shuttle bus to be scheduled based on the departure time, the uplink station, and the downlink station.

[0109] S1022. For each historical shuttle bus, obtain GPS information and passenger flow information corresponding to the historical shuttle bus, wherein the GPS information is the time collection of the historical shuttle bus at different stations, and the passenger flow information is the passenger gathering volume and passenger evacuation volume corresponding to different stations of the historical shuttle bus.

[0110] S1023. Determine historical shuttle bus information corresponding to the historical shuttle bus based on the GPS information and the passenger flow information, wherein the historical shuttle bus information includes operating time, U-turn time, passenger gathering volume, and passenger evacuation volume.

[0111] In step S1021, specifically, at least two historical shuttle buses are obtained by matching the departure time, the uplink station, and the downlink station in the historical shuttle bus data.

[0112] In step S1022, specifically, the GPS information and passenger flow information corresponding to each historical shuttle bus are determined according to the shuttle bus ID, the shuttle bus license plate number, and the departure time corresponding to each historical shuttle bus.

[0113] It should be noted here that the GPS information obtains the longitude and latitude between the travel position of the shuttle bus and different stations in real time through GPS to determine the time when the shuttle bus arrives at or leaves a certain station.

[0114] The above-mentioned methods for obtaining passenger flow information include but are not limited to obtaining from IC cards and obtaining data from automatic ticket vending and checking systems.

[0115] In step S1023, the running time refers to the time taken by the historical local train to complete the journey.

[0116] The above-mentioned U-turn time refers to the time taken by the historical shuttle train to switch from the up route to the down route.

[0117] Through the above steps, the running time, U-turn time, passenger assembly volume and passenger evacuation volume are obtained, so that the running time, U-turn time, passenger assembly volume and passenger evacuation volume can be analyzed later to predict the scheduled shuttle bus. Since the data reliability of the running time, U-turn time, passenger assembly volume and passenger evacuation volume is high, the accuracy of the prediction result obtained based on the high reliability data analysis is improved, thereby improving the scheduling accuracy of the scheduled shuttle bus.

[0118] In this embodiment, if Figure 6 As shown, as a preferred implementation, in step S20, the step of preprocessing all the historical passenger flow information to obtain preprocessed information corresponding to each of the historical passenger flow information includes:

[0119] S201: Perform abnormal identification on all historical passenger flow information to obtain an identification result corresponding to each historical passenger flow information.

[0120] S202: When the recognition result is abnormal, data cleaning is performed on the historical passenger flow information corresponding to the recognition result to obtain preprocessing information corresponding to the historical passenger flow information.

[0121] In step S201, the above-mentioned abnormality identification includes but is not limited to missing value identification and abnormal value identification.

[0122] The above recognition results include normal and abnormal.

[0123] For example, when there is a piece of historical passenger flow information that is null, the recognition result corresponding to the historical passenger flow information is abnormal.

[0124] In step S202, specifically, when the recognition result is abnormal, the corresponding historical passenger flow information and the time information corresponding to the historical passenger flow information are deleted.

[0125] By identifying anomalies in historical passenger flow information and deleting the identified anomalies, errors caused by abnormal data can be prevented, the accuracy of predictions can be improved, and the accuracy and efficiency of scheduling can be further improved.

[0126] In this embodiment, if Figure 7 As shown, as a preferred implementation, in step S30, the time information corresponding to all the pre-processing information and the historical passenger flow information is input into the scheduling prediction model for prediction calculation, and the step of obtaining the prediction result includes:

[0127] S301. Input the time information corresponding to all pre-processing information and historical passenger flow information into the scheduling prediction model, wherein the pre-processing information includes the passenger assembly volume and the passenger evacuation volume, and the time information corresponding to the historical passenger flow information includes the running time and the U-turn time.

[0128] S302, predict and calculate the passenger gathering volume, passenger evacuation volume, operating time and U-turn time respectively to obtain the predicted passenger gathering volume, predicted passenger evacuation volume, predicted operating time and predicted U-turn time.

[0129] S303: Obtain predicted passenger flow based on the predicted passenger gathering volume and the predicted passenger evacuation volume.

[0130] S304: Obtain the predicted running time based on the predicted running time and the predicted U-turn time.

[0131] S305: Taking the predicted passenger flow and the predicted running time as the prediction result.

[0132] In step S302, the above prediction calculation includes but is not limited to average value prediction calculation and weighted sum prediction calculation.

[0133] Preferably, the present invention adopts average value prediction calculation.

[0134] In this embodiment, if Figure 8As shown, as a preferred implementation, in step S302, the steps of respectively predicting and calculating the passenger assembly volume, the passenger evacuation volume, the running time, and the U-turn time to obtain the predicted passenger assembly volume, the predicted passenger evacuation volume, the predicted running time, and the predicted U-turn time include:

[0135] S3021. Calculate the average values ​​of the passenger gathering volume, passenger evacuation volume, operating time and U-turn time respectively to obtain the predicted passenger gathering volume, predicted passenger evacuation volume, predicted operating time and predicted U-turn time.

[0136] In step S3021, the predicted passenger gathering volume is calculated according to the following formula (1):

[0137]

[0138] in, It refers to the predicted passenger gathering quantity with departure time T, uplink station S' and downlink station S", N refers to the number of historical shuttle buses obtained, and the value range of i is (1, N).

[0139] The predicted passenger evacuation volume is calculated according to the following formula (2):

[0140]

[0141] in, It refers to the predicted passenger evacuation volume with departure time T, uplink station S', and downlink station S", N refers to the number of historical shuttle buses obtained, and the value range of i is (1, N).

[0142] The predicted running time is calculated according to the following formula (3):

[0143]

[0144] in, It refers to the predicted running time with departure time T, uplink starting station i, and downlink terminal station j. N refers to the number of historical shuttle buses obtained. The value range of i is (1, N), and the value range of j is (1, N).

[0145] The predicted U-turn time is calculated according to the following formula (4):

[0146]

[0147] in, It refers to the predicted U-turn time with departure time T, uplink station S', and downlink station S", N refers to the number of historical interval vehicles obtained, the value range of i is (1, N), and the value range of j is (1, N).

[0148] In step S303, the predicted passenger flow is calculated according to the following formula (5):

[0149]

[0150] Among them, p(T,S',S") refers to the predicted passenger flow with departure time T, upstream station S', and downstream station S". It refers to the predicted passenger evacuation volume. It refers to the predicted passenger gathering volume.

[0151] In step S304, the predicted running time is calculated according to the following formula (6):

[0152]

[0153] Among them, t(T,S',S") refers to the predicted running time with departure time T, uplink station S', and downlink station S". It refers to the predicted outbound travel time with departure time T, uplink starting station O1, and uplink ending station S' It refers to the predicted turn-around time when the departure time is T, the uplink station is S', and the downlink station is S' It refers to the predicted return trip time with the departure time being T, the downlink starting station being S', and the uplink ending station being D2.

[0154] The scheduling prediction model is used to predict the time information corresponding to the pre-processing information and the historical passenger flow information. Since the time information corresponding to the pre-processing information and the historical passenger flow information has high reliability, the accuracy of the prediction calculation is improved, thereby improving the efficiency of the inter-city bus scheduling.

[0155] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0156] In one embodiment, a shuttle bus dispatching device is provided, and the shuttle bus dispatching device corresponds to the shuttle bus dispatching method in the above embodiment. Fig. 9 As shown, the shuttle bus dispatching device includes a historical shuttle bus information acquisition module 11, a preprocessing module 12, a prediction module 13 and a dispatching module 14. The functional modules are described in detail as follows:

[0157] The historical shuttle train information acquisition module 11 is used to acquire at least two historical shuttle train information corresponding to the shuttle train to be scheduled based on the station set and time set corresponding to the shuttle train to be scheduled, wherein the historical shuttle train information includes historical passenger flow information and time information corresponding to the historical passenger flow information.

[0158] The preprocessing module 12 is used to preprocess all historical passenger flow information to obtain preprocessing information corresponding to each piece of historical passenger flow information.

[0159] The prediction module 13 is used to input the time information corresponding to all pre-processing information and historical passenger flow information into the scheduling prediction model to perform prediction calculation and obtain the prediction result.

[0160] The dispatching module 14 is used to dispatch the vehicles to be dispatched based on the prediction results.

[0161] In this embodiment, the historical inter-city train information acquisition module 11 further includes the following units:

[0162] The prediction information acquisition unit is used to obtain the up-station, down-station and departure time corresponding to the shuttle bus to be scheduled, wherein the up-station is the terminal station of the outbound trip of the shuttle bus to be scheduled, and the down-station is the starting station of the return trip of the shuttle bus to be scheduled.

[0163] The historical shuttle bus information acquisition unit is used to perform matching processing according to the departure time, the uplink station, and the downlink station to determine at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled.

[0164] The historical passenger flow information and time information acquisition unit is used to acquire the historical passenger flow information corresponding to the historical shuttle bus information and the time information corresponding to the historical passenger flow information based on the historical shuttle bus information.

[0165] Furthermore, the historical inter-city train information acquisition unit includes the following subunits:

[0166] The historical shuttle bus acquisition unit is used to determine at least two historical shuttle buses corresponding to the shuttle bus to be scheduled based on the departure time, the upstream station, and the downstream station.

[0167] The GPS information and passenger flow information acquisition unit is used to acquire the GPS information and passenger flow information corresponding to each historical shuttle bus, wherein the GPS information is the time collection of the historical shuttle bus at different stations, and the passenger flow information is the passenger gathering volume and passenger evacuation volume corresponding to different stations of the historical shuttle bus.

[0168] The information determination unit is used to determine the historical shuttle bus information corresponding to the historical shuttle bus based on the GPS information and the passenger flow information, wherein the historical shuttle bus information includes the running time, the U-turn time, the passenger gathering amount and the passenger evacuation amount.

[0169] In this embodiment, the preprocessing module 12 further includes the following units:

[0170] The anomaly recognition unit is used to perform anomaly recognition on all historical passenger flow information and obtain the recognition result corresponding to each historical passenger flow information.

[0171] The preprocessing unit is used to perform data cleaning on the historical passenger flow information corresponding to the recognition result when the recognition result is abnormal, so as to obtain preprocessing information corresponding to the historical passenger flow information.

[0172] In this embodiment, the prediction module 13 further includes the following units:

[0173] The data input unit is used to input the time information corresponding to all pre-processing information and historical passenger flow information into the scheduling prediction model, wherein the pre-processing information includes the passenger assembly volume and the passenger evacuation volume, and the time information corresponding to the historical passenger flow information includes the running time and the U-turn time.

[0174] The prediction unit is used to predict and calculate the passenger gathering volume, passenger evacuation volume, running time and U-turn time respectively, and obtain the predicted passenger gathering volume, predicted passenger evacuation volume, predicted running time and predicted U-turn time.

[0175] The predicted passenger flow acquisition unit is used to obtain the predicted passenger flow based on the predicted passenger gathering volume and the predicted passenger evacuation volume.

[0176] The predicted running time acquisition unit is used to obtain the predicted running time based on the predicted running time and the predicted U-turn time.

[0177] The prediction result acquisition unit is used to take the predicted passenger flow and the predicted running time as the prediction result.

[0178] Furthermore, the prediction unit includes the following subunits:

[0179] The average value prediction unit is used to calculate the average values ​​of the passenger assembly volume, the passenger evacuation volume, the running time and the U-turn time respectively, and obtain the predicted passenger assembly volume, the predicted passenger evacuation volume, the predicted running time and the predicted U-turn time.

[0180] The meaning of "first" and "second" in the above modules / units is only to distinguish different modules / units, and is not used to define which module / unit has a higher priority or other limiting meanings. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The division of modules in this application is only a logical division, and there may be other division methods when implemented in actual applications.

[0181] The specific definition of the shuttle bus dispatching device can be found in the definition of the shuttle bus dispatching method above, which will not be repeated here. Each module in the above-mentioned shuttle bus dispatching device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0182] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data involved in the inter-city bus scheduling method. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for scheduling inter-city buses is implemented.

[0183] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the shuttle bus scheduling method in the above embodiment are implemented, such as Figure 2 Steps S10 to S40 and other extensions of the method and related steps are shown. Alternatively, when the processor executes the computer program, the functions of each module / unit of the shuttle bus dispatching device in the above embodiment are realized, for example Fig. 9 The functions of modules 11 to 14 are shown in Figure 1. To avoid repetition, they will not be described here.

[0184] The processor may be a central processing unit (CPU), or 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. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the computer device, and various interfaces and lines are used to connect various parts of the entire computer device.

[0185] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the computer device by running or executing the computer program and / or module 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 a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, video data, etc.), etc.

[0186] The memory may be integrated into the processor or may be arranged separately from the processor.

[0187] In one embodiment, a computer-readable storage medium is provided on which a computer program is stored. When the computer program is executed by a processor, the steps of the shuttle bus scheduling method in the above embodiment are implemented, such as Figure 2 Steps S10 to S40 and other extensions of the method and related steps are shown. Alternatively, when the computer program is executed by the processor, the functions of each module / unit of the shuttle bus dispatching device in the above embodiment are realized, for example Fig. 9 The functions of modules 11 to 14 are shown in Figure 1. To avoid repetition, they will not be described here.

[0188] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0189] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0190] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A shuttle bus dispatching method, characterized in that: include: Based on the station set and time set corresponding to the shuttle bus to be scheduled, obtaining at least two pieces of historical shuttle bus information corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information; Preprocessing all the historical passenger flow information to obtain preprocessing information corresponding to each piece of historical passenger flow information; Inputting the time information corresponding to all the pre-processing information and the historical passenger flow information into the scheduling prediction model for prediction calculation to obtain a prediction result; Based on the prediction result, dispatching the shuttle bus to be dispatched; The method includes: obtaining predicted passenger flow information and predicted running time of each station; and According to a preset weight assignment method, different weights are assigned to the predicted passenger flow information and the predicted operating time, and the predicted passenger flow information and the predicted operating time corresponding to each station assigned with different weights are weighted and summed to obtain predicted weighted information; The prediction weighted information of each station is arranged in order from large to small to obtain a prediction weighted information set, and prediction weighted information equal to a preset number is selected from the prediction weighted information set in order from large to small as scheduling information; The dispatch quantity of the to-be-dispatched inter-section vehicles is calculated according to all the dispatch information, and the to-be-dispatched inter-section vehicles are dispatched according to the dispatch quantity and the time points corresponding to all the dispatch information.

2. The method according to claim 1, characterized in that The step of acquiring at least two pieces of historical shuttle bus information corresponding to the shuttle bus to be scheduled based on the station set and time set corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information comprises: Obtaining the uplink station, downlink station, and departure time corresponding to the shuttle bus to be scheduled, wherein the uplink station is the terminal station of the outbound trip of the shuttle bus to be scheduled, and the downlink station is the starting station of the return trip of the shuttle bus to be scheduled; Perform matching processing according to the departure time, the uplink station, and the downlink station to determine at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled; Based on the historical inter-city train information, historical passenger flow information corresponding to the historical inter-city train information and time information corresponding to the historical passenger flow information are acquired.

3. The method according to claim 2, characterized in that The step of performing matching processing according to the departure time, the uplink station, and the downlink station to determine at least two pieces of historical shuttle bus information corresponding to the shuttle bus to be scheduled comprises: Determine at least two historical shuttle buses corresponding to the shuttle bus to be scheduled based on the departure time, the uplink station, and the downlink station; For each of the historical shuttle buses, obtain GPS information and passenger flow information corresponding to the historical shuttle bus, wherein the GPS information is a time set of the historical shuttle bus at different stations, and the passenger flow information is a passenger gathering volume and a passenger evacuation volume corresponding to different stations of the historical shuttle bus; Based on the GPS information and the passenger flow information, historical shuttle bus information corresponding to the historical shuttle bus is determined, wherein the historical shuttle bus information includes operating time, U-turn time, passenger gathering volume, and passenger evacuation volume.

4. The method according to claim 1, characterized in that: The step of preprocessing all the historical passenger flow information to obtain preprocessing information corresponding to each of the historical passenger flow information comprises: Performing abnormal identification on all the historical passenger flow information to obtain an identification result corresponding to each of the historical passenger flow information; When the recognition result is abnormal, data cleaning is performed on the historical passenger flow information corresponding to the recognition result to obtain preprocessing information corresponding to the historical passenger flow information.

5. The method according to any one of claims 2 to 4, characterized in that: The step of inputting all the pre-processing information and the time information corresponding to the historical passenger flow information into the scheduling prediction model for prediction calculation to obtain the prediction result includes: Inputting the time information corresponding to all the pre-processing information and the historical passenger flow information into the dispatch prediction model, wherein the pre-processing information includes the passenger assembly volume and the passenger evacuation volume, and the time information corresponding to the historical passenger flow information includes the running time and the U-turn time; Predict and calculate the passenger gathering volume, the passenger evacuation volume, the running time and the U-turn time respectively to obtain the predicted passenger gathering volume, the predicted passenger evacuation volume, the predicted running time and the predicted U-turn time; Based on the predicted passenger gathering volume and the predicted passenger evacuation volume, a predicted passenger flow is obtained; Obtaining a predicted running time based on the predicted running time and the predicted U-turn time; The predicted passenger flow and the predicted running time are taken as prediction results.

6. The method according to claim 5, characterized in that The step of respectively predicting and calculating the passenger gathering amount, the passenger evacuation amount, the running time and the U-turn time to obtain the predicted passenger gathering amount, the predicted passenger evacuation amount, the predicted running time and the predicted U-turn time comprises: The average values ​​of the passenger gathering volume, the passenger evacuation volume, the running time and the U-turn time are calculated respectively to obtain the predicted passenger gathering volume, the predicted passenger evacuation volume, the predicted running time and the predicted U-turn time.

7. A shuttle bus dispatching device, characterized in that: include: A historical shuttle bus information acquisition module, configured to acquire at least two pieces of historical shuttle bus information corresponding to the shuttle bus to be scheduled based on a station set and a time set corresponding to the shuttle bus to be scheduled, wherein the historical shuttle bus information includes historical passenger flow information and time information corresponding to the historical passenger flow information; A preprocessing module, used to preprocess all the historical passenger flow information to obtain preprocessing information corresponding to each of the historical passenger flow information; A prediction module, used for inputting the time information corresponding to all the pre-processing information and the historical passenger flow information into a scheduling prediction model for prediction calculation to obtain a prediction result; A scheduling module, used for scheduling the shuttle bus to be scheduled based on the prediction result; The method includes: obtaining predicted passenger flow information and predicted running time of each station; and According to a preset weight assignment method, different weights are assigned to the predicted passenger flow information and the predicted operating time, and the predicted passenger flow information and the predicted operating time corresponding to each station assigned with different weights are weighted and summed to obtain predicted weighted information; The prediction weighted information of each station is arranged in order from large to small to obtain a prediction weighted information set, and prediction weighted information equal to a preset number is selected from the prediction weighted information set in order from large to small as scheduling information; The dispatch quantity of the to-be-dispatched inter-section vehicles is calculated according to all the dispatch information, and the to-be-dispatched inter-section vehicles are dispatched according to the dispatch quantity and the time points corresponding to all the dispatch information.

8. The device according to claim 7, characterized in that The historical inter-city train information acquisition module includes: A prediction information acquisition unit, used to acquire the up-station, down-station, and departure time corresponding to the shuttle bus to be scheduled, wherein the up-station is the terminal station of the shuttle bus to be scheduled, and the down-station is the starting station of the shuttle bus to be scheduled; A historical shuttle bus information acquisition unit, configured to perform matching processing according to the departure time, the uplink station, and the downlink station, and determine at least two historical shuttle bus information corresponding to the shuttle bus to be scheduled; The historical passenger flow information and time information acquisition unit is used to acquire the historical passenger flow information corresponding to the historical inter-city train information and the time information corresponding to the historical passenger flow information based on the historical inter-city train information.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the shuttle bus scheduling method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the shuttle bus scheduling method according to any one of claims 1 to 6 are implemented.

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