Traffic flow prediction method and device, storage medium and electronic equipment

Abstract

The present disclosure relates to a traffic flow prediction method and device, a storage medium and an electronic device, and relates to the technical field of computers. The method comprises: obtaining historical traffic flow data of a target toll station, and extracting target traffic flow data from the historical traffic flow data; calculating a reference traffic flow of the target toll station in a platform closing time period according to the target traffic flow data; predicting a loss traffic flow of a currently closed toll station in the target toll station in the platform closing time period according to the reference traffic flow; and determining a fee loss amount of the currently closed toll station in the platform closing time period according to the loss traffic flow. The present disclosure realizes prediction of the loss traffic flow of a toll station in a closed state.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more specifically, to a method for predicting traffic flow, a device for predicting traffic flow, a computer-readable storage medium, and an electronic device. Background Technology

[0002] Existing traffic flow prediction methods can only predict traffic flow at toll stations under normal conditions, and cannot predict lost traffic flow at toll stations that are closed.

[0003] It should be noted that the information in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this disclosure is to provide a method, device, computer-readable storage medium, and electronic device for predicting traffic flow, thereby overcoming, to some extent, the problem of the inability to predict lost traffic flow at toll stations that are closed due to limitations and defects in related technologies.

[0005] According to one aspect of this disclosure, a method for predicting traffic flow is provided, comprising:

[0006] Obtain historical traffic flow data of the target toll station, and extract the target traffic flow data from the historical traffic flow data;

[0007] Based on the target traffic flow data, calculate the reference traffic flow for the target toll station during the platform closure period;

[0008] Based on the reference traffic flow, predict the lost traffic flow of the currently closed toll stations in the target toll stations during the period of station closure;

[0009] The amount of cost loss for the currently closed toll station during the time period of the station's closure is determined based on the lost traffic volume.

[0010] In one example embodiment of this disclosure, the target toll station includes at least one of a currently closed toll station, an upstream toll station corresponding to the currently closed toll station, and a downstream toll station corresponding to the currently closed toll station;

[0011] The historical traffic flow data includes at least one of the following: first historical traffic flow data corresponding to the currently closed toll station, second historical traffic flow data corresponding to the upstream toll station, and third historical traffic flow data corresponding to the downstream toll station;

[0012] The target traffic flow data includes at least one of the following: first target traffic flow data corresponding to the currently closed toll station, second target traffic flow data corresponding to the upstream toll station, and third target traffic flow data corresponding to the downstream toll station;

[0013] The reference traffic flow includes at least one of the following: a first reference traffic flow corresponding to a currently closed toll station, a second reference traffic flow corresponding to an upstream toll station, and a third reference traffic flow corresponding to a downstream toll station.

[0014] In one example embodiment of this disclosure, extracting target traffic flow data from the historical traffic flow data includes:

[0015] Obtain the start and end closing times of the currently closed toll stations, and calculate the station closure period based on the start and end closing times;

[0016] Based on the platform closure period, a data extraction interval for the historical traffic flow data is determined, and based on the data extraction interval, a first target traffic flow data is extracted from the first historical traffic flow data, and / or a second target traffic flow data is extracted from the second historical traffic flow data, and / or a third target traffic flow data is extracted from the third historical traffic flow data.

[0017] In one example embodiment of this disclosure, calculating the reference traffic flow of the target toll station during the platform closure period based on the target traffic flow data includes:

[0018] Based on the first target traffic flow data, calculate the first reference traffic flow for the currently closed toll stations during the platform closure period; and / or

[0019] Based on the second target traffic flow data, calculate the second reference traffic flow for the upstream toll station during the platform closure period; and / or

[0020] Based on the third target traffic flow data, calculate the third reference traffic flow for the downstream toll station during the platform closure period.

[0021] In one example embodiment of this disclosure, calculating a first reference traffic flow for the currently closed toll station during the platform closure period based on first target traffic flow data includes:

[0022] The first upper quartile and the first lower quartile are determined based on the first target traffic flow data, and the first quartile interval is determined based on the first upper quartile and the first lower quartile.

[0023] The first lower limit value is determined based on the first lower quartile and the first quartile interval, and the first upper limit value is determined based on the first upper quartile and the first quartile interval.

[0024] The first standard box area range is determined based on the first upper limit value and the first lower limit value, and the first target traffic flow data is mapped to the first standard box area range;

[0025] The first target traffic flow data outside the first standard box area is filtered, and the average value of the filtered first target traffic flow data is calculated to obtain the first reference traffic flow.

[0026] In one example embodiment of this disclosure, predicting the lost traffic flow of a currently closed toll station in the target toll station during the station closure period based on the reference traffic flow includes:

[0027] The number of first vehicles whose travel tasks are changed due to the closure of the currently closed toll station is determined based on the first reference traffic flow, and the number of second vehicles that detour around the currently closed toll station during the station closure period is determined based on the second reference traffic flow and the third reference traffic flow.

[0028] Based on the first number of vehicles and the second number of vehicles, determine the third number of vehicles whose travel missions are canceled due to the current closed toll station being closed.

[0029] Based on the number of third vehicles, determine the lost traffic volume of the currently closed toll stations in the target toll stations during the time the platforms are closed.

[0030] In one example embodiment of this disclosure, determining the number of first vehicles whose travel tasks are altered due to the closure of the currently closed toll station, based on a first reference traffic flow, includes:

[0031] The length of the traffic flow observation period for the currently closed toll station is determined based on the platform closure time period, before the start closure time and after the end closure time.

[0032] Based on the length of the traffic flow observation time and the start and end times, a first observation period before the start and end times of the currently closed toll station is determined, and a first increase in traffic flow is determined based on the first reference traffic flow and the first actual traffic flow of the target toll station within the first observation period.

[0033] Based on the traffic flow observation time and the termination closing time, a second observation period after the termination closing time is determined for the currently closed toll station, and a second traffic flow increase value is determined based on the first reference traffic flow and the second actual traffic flow of the target toll station within the second observation period.

[0034] Configure a first weight value and a second weight value for the first increase in traffic flow and the second increase in traffic flow, and perform a weighted summation of the first increase in traffic flow and the second increase in traffic flow based on the first weight value and the second weight value to obtain the first number of vehicles whose travel tasks have changed due to the current closed toll station being in a closed state.

[0035] In one example embodiment of this disclosure, determining the number of second vehicles that detour around the currently closed toll station during the station closure period based on a second reference traffic flow and a third reference traffic flow includes:

[0036] Obtain the third actual traffic flow of the upstream toll station during the platform closure period, and determine the third traffic flow increase value based on the third actual traffic flow and the second reference traffic flow;

[0037] Obtain the fourth actual traffic flow of the downstream toll station during the platform closure period, and determine the fourth traffic flow increase value based on the fourth actual traffic flow and the third reference traffic flow.

[0038] Configure a third weight value and a fourth weight value for the third and fourth vehicle flow increases, and perform a weighted sum of the third and fourth vehicle flow increases based on the third and fourth weight values ​​to determine the number of second vehicles that detour around the currently closed toll station during the station closure period.

[0039] In one example embodiment of this disclosure, determining the number of third vehicles whose travel tasks are cancelled due to the currently closed toll station being closed, based on the first number of vehicles and the second number of vehicles, includes:

[0040] Obtain the fifth actual traffic flow of the currently closed toll station during the time period of the station closure, and determine the reduction of traffic flow at the entrance of the currently closed toll station during the time period of the station closure based on the first reference traffic flow and the fifth actual traffic flow.

[0041] Based on the reduced traffic flow at the entrance, the number of the first vehicle, and the number of the second vehicle, determine the number of the third vehicle whose travel mission was canceled due to the currently closed toll station being in a closed state.

[0042] In one example embodiment of this disclosure, determining the number of third vehicles whose travel tasks are cancelled due to the currently closed toll station being closed, based on the reduced traffic flow at the entrance, the first number of vehicles, and the second number of vehicles, includes:

[0043] The sum of the first number of vehicles and the second number of vehicles is calculated, and the difference between the reduced traffic flow at the entrance and the sum is calculated to obtain the third number of vehicles whose travel tasks are canceled due to the current closed toll station being closed.

[0044] In one example embodiment of this disclosure, determining the amount of fee loss for the currently closed toll station during the time period of station closure based on the lost traffic flow includes:

[0045] Based on the number of second vehicles and the reduced traffic flow at the entrance, determine the cost for vehicles to detour from the currently closed toll station during the time period the station is closed.

[0046] Based on the number of third vehicles and the lost traffic flow, determine the cost of canceled vehicle trips during the time period when the currently closed toll station is closed;

[0047] Based on the cost of the vehicle detour and the cost of canceling the vehicle trip, determine the amount of cost loss incurred by the currently closed toll station during the period of station closure.

[0048] In one example embodiment of this disclosure, determining the cost for vehicles to detour from the currently closed toll station during the station's closure period, based on the second number of vehicles and the reduced traffic flow at the entrance, includes:

[0049] The detour ratio is determined based on the second number of vehicles and the reduced traffic flow at the entrance, and the number of detour vehicles is determined based on the detour ratio.

[0050] Calculate the first distance difference between the currently closed toll station and the upstream toll station, and calculate the second distance difference between the currently closed toll station and the downstream toll station;

[0051] The detour distance is determined based on the first distance difference and the second distance difference. The detour cost for vehicles traveling through the currently closed toll station during the station's closure period is determined based on the detour distance, the number of vehicles traveling through the detour, and the toll fee per unit distance.

[0052] In one example embodiment of this disclosure, the cost of canceled vehicle trips during the time period of the currently closed toll station is determined based on the number of third vehicles and the lost traffic flow, including:

[0053] The proportion of canceled vehicle trips is determined based on the number of third vehicles and the lost traffic flow, and the number of lost vehicles is determined based on the proportion of canceled vehicle trips and the first reference traffic flow.

[0054] The average vehicle loss amount is determined based on the toll fees of vehicles that entered from currently closed toll stations but exited from other toll stations.

[0055] Based on the average vehicle loss amount and the number of vehicles lost, the cost of canceled vehicle trips during the time period of the currently closed toll station is determined.

[0056] According to one aspect of this disclosure, a traffic flow prediction device is provided, comprising:

[0057] The target traffic flow data extraction module is used to obtain historical traffic flow data of the target toll station and extract target traffic flow data from the historical traffic flow data;

[0058] The reference traffic flow calculation module is used to calculate the reference traffic flow of the target toll station during the platform closure period based on the target traffic flow data.

[0059] The lost traffic flow prediction module is used to predict the lost traffic flow of the currently closed toll stations in the target toll station during the time the platform is closed, based on the reference traffic flow.

[0060] The cost loss quantity determination module is used to determine the cost loss quantity of the currently closed toll station during the time period of the station closure based on the lost traffic flow.

[0061] According to one aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the traffic flow prediction method described in any of the foregoing example embodiments.

[0062] According to one aspect of this disclosure, an electronic device is provided, comprising:

[0063] Processor; and

[0064] Memory for storing the executable instructions of the processor;

[0065] The processor is configured to execute the traffic flow prediction method described in any of the foregoing example embodiments by executing the executable instructions.

[0066] This disclosure provides a method for predicting traffic flow. Firstly, it acquires historical traffic flow data of a target toll station and extracts target traffic flow data from this data. Then, based on the target traffic flow data, it calculates a reference traffic flow for the toll station during its closure period. Next, it predicts the lost traffic flow for currently closed toll stations during their closure period based on the reference traffic flow. Finally, it determines the amount of cost loss for the currently closed toll station during its closure period based on the lost traffic flow. This method achieves the prediction of lost traffic flow for currently closed toll stations during their closure period, thereby solving the problem in the prior art of being unable to predict lost traffic flow for toll stations in a closed state.

[0067] On the other hand, since the reference traffic flow of the target toll station during the platform closure period can be calculated based on the target traffic flow data, and then the lost traffic flow of the currently closed toll station in the target toll station during the platform closure period can be predicted based on the reference traffic flow, the problem that the lost traffic flow can only be predicted by simulation in the existing technology is that the accuracy of the predicted lost traffic flow is low.

[0068] On the other hand, since the amount of toll revenue lost during the period of toll station closure can be determined based on the amount of lost traffic flow, corresponding toll station closure measures can be configured based on the amount of toll revenue lost, thereby further reducing the toll revenue loss caused by toll station closure.

[0069] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0070] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0071] Figure 1 The flowchart schematically illustrates a traffic flow prediction method according to an exemplary embodiment of the present disclosure.

[0072] Figure 2 An example diagram schematically illustrates a traffic flow prediction system according to an exemplary embodiment of the present disclosure.

[0073] Figure 3 This illustration shows a scenario where, according to an example embodiment of the present disclosure, a vehicle is traveling from east to west, with the upstream toll station, the currently closed toll station, and the downstream toll station in their respective locations.

[0074] Figure 4 This illustration shows a scenario where, according to an example embodiment of the present disclosure, a vehicle is traveling from west to east, and the upstream toll station, the currently closed toll station, and the downstream toll station are located.

[0075] Figure 5 An example diagram schematically illustrates a box diagram according to an exemplary embodiment of the present disclosure.

[0076] Figure 6 The flowchart illustrates a method for determining the amount of cost loss for a currently closed toll station during the platform closure period based on lost traffic flow, according to an example embodiment of the present disclosure.

[0077] Figure 7 The flowchart illustrates a method for determining the cost of vehicle detour during the closed period of a toll station, according to an example embodiment of the present disclosure.

[0078] Figure 8 This schematically illustrates a flowchart of a method for determining the cost of a vehicle trip cancellation during the time period of a currently closed toll station, according to an example embodiment of this disclosure.

[0079] Figure 9 A block diagram schematically illustrates a traffic flow prediction device according to an exemplary embodiment of the present disclosure.

[0080] Figure 10 An electronic device for implementing the traffic flow prediction method described above is illustrated according to an example embodiment of the present disclosure. Detailed Implementation

[0081] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this disclosure more comprehensive and complete, and to fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more of the specific details omitted, or other methods, components, apparatus, steps, etc., can be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0082] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0083] With economic development, my country's car ownership continues to grow, and highway traffic volume is also gradually increasing. In certain situations, such as excessive mainline traffic, serious traffic accidents, or toll station ramp construction, toll station entrances may be temporarily closed for a period. In these scenarios, highway management departments need to both implement appropriate toll station entrance closure plans and make a reasonable estimate of the resulting toll revenue losses to facilitate the development of overall traffic plans and minimize these losses. Therefore, estimating the toll revenue reduction caused by toll station entrance closures is a pressing issue that highway management departments need to address.

[0084] However, there is currently a lack of research on the impact of toll station entrance closures on toll fees. Some researchers use simulation methods to study toll station traffic flow prediction, but this method lacks real data support and does not consider the impact of entrance closures on traffic flow, resulting in low accuracy.

[0085] Based on this, this exemplary embodiment first provides a method for predicting traffic flow, which can run on a server, server cluster, or cloud server, etc. Of course, those skilled in the art can also run the method disclosed herein on other platforms as needed, and this exemplary embodiment does not impose any special limitations on this. Specifically, refer to... Figure 1 As shown, the traffic flow prediction method may include the following steps:

[0086] Step S110. Obtain historical traffic flow data of the target toll station, and extract target traffic flow data from the historical traffic flow data;

[0087] Step S120. Calculate the reference traffic flow of the target toll station during the platform closure period based on the target traffic flow data;

[0088] Step S130. Based on the reference traffic flow, predict the lost traffic flow of the currently closed toll stations in the target toll stations during the station closure period;

[0089] Step S140. Determine the amount of cost loss for the currently closed toll station during the time period of station closure based on the lost traffic flow.

[0090] The aforementioned traffic flow prediction method, on the one hand, acquires historical traffic flow data of the target toll station and extracts target traffic flow data from this data; then, based on the target traffic flow data, it calculates the reference traffic flow for the target toll station during the station closure period; next, it predicts the lost traffic flow for the currently closed toll station during the station closure period based on the reference traffic flow; finally, it determines the amount of fee loss for the currently closed toll station during the station closure period based on the lost traffic flow. This method achieves the prediction of the lost traffic flow for the currently closed toll station during the station closure period, thereby solving the problem that existing technologies cannot predict the lost traffic flow for toll stations that are in a closed state. On the one hand, the problem is that, since the reference traffic flow for the target toll station during the platform closure period can be calculated based on the target traffic flow data, and then the lost traffic flow for the currently closed toll station during the platform closure period can be predicted based on the reference traffic flow, this solves the problem that the existing technology can only predict lost traffic flow through simulation, resulting in low accuracy of the predicted lost traffic flow. On the other hand, since the amount of toll loss for the currently closed toll station during the platform closure period can be determined based on the lost traffic flow, and then corresponding platform closure measures can be configured based on the amount of toll loss, thereby further reducing the toll loss caused by toll station closure.

[0091] The method for predicting traffic flow described in the exemplary embodiments of this disclosure will be explained and described in detail below with reference to the accompanying drawings.

[0092] First, the inventive purpose of the exemplary embodiments of this disclosure will be explained and described. Specifically, the traffic flow prediction method provided in the exemplary embodiments of this disclosure first calculates a reference value for the traffic flow at the toll station entrance, then calculates the proportions of "waiting," "detouring," and "losing" caused by the closure of the toll station entrance. Next, based on the reference value of the traffic flow at the toll station entrance and the proportions of waiting, detouring, and losing, combined with the toll losses due to detouring and vehicle loss, the amount of toll affected by the closure of the toll station entrance is estimated. Furthermore, the exemplary embodiments of this disclosure are designed for highway scenarios, fully considering the actual conditions of highways, calculating the traffic flow characteristics of toll stations, and comprehensively estimating the impact of toll station entrance closure on tolls by combining the time periods before and after the toll station closure and the situation of upstream and downstream toll stations. This estimation is more accurate.

[0093] Secondly, the traffic flow prediction system involved in the exemplary embodiments of this disclosure will be explained and described. Specifically, the traffic flow prediction system may include a currently closed toll station 210, an upstream toll station 220 geographically adjacent to the currently closed toll station, and a downstream toll station 230; of course, the traffic flow prediction system may also include a toll station server 240; wherein, the toll station server can communicate with the currently closed toll station, the upstream toll station, and the downstream toll station through a wired network or a wireless network; of course, the various toll stations can also communicate with each other through a wired network or a wireless network. In practical applications, the currently closed toll station, the upstream toll station, and the downstream toll station can be used to collect corresponding traffic flow data, and the server can be used to implement the traffic flow prediction method described in the exemplary embodiments of this disclosure.

[0094] In one example embodiment, the upstream and downstream toll stations described in this exemplary embodiment of the present disclosure refer to toll stations that are geographically adjacent to the currently closed toll station in a specific direction; for example, referring to... Figure 3 As shown, if the travel direction is from east to west, then the upstream toll station could be toll station A, and the downstream toll station could be toll station C; of course, for reference... Figure 4 As shown, if the driving direction is from west to east, then the upstream toll station is toll station C, and the downstream toll station is toll station A. It should be noted that the driving direction here refers to determining the currently closed toll station as the inbound or outbound direction.

[0095] Furthermore, the application scenarios of the exemplary embodiments of this disclosure will be explained and described. Specifically, in practical applications, such as... Figure 3 As shown, assume that toll stations A, B, and C are adjacent toll stations on a highway traveling in the same direction (denoted as direction 1, and the opposite direction as direction 2). When the entrance to toll station B (currently closed) in direction 1 is closed, vehicles originally intending to enter the highway from toll station B in direction 1 have three possibilities: First, they may travel earlier or later (changing their travel plans due to the closed toll station), which can be simply referred to as "waiting"; second, they may enter the highway at the previous station (upstream toll station A in direction 1) / the next station (downstream toll station C in direction 1) (detouring around the currently closed toll station during the station closure period), which can be simply referred to as "detouring"; third, they may travel by other means or cancel their trip (canceling their travel plans due to the closed toll station), which can be simply referred to as "losing out".

[0096] In one example embodiment, for the first "etc." scenario, whether a vehicle departs early or late does not affect toll revenue. What needs to be determined in this case is the calculation range for early / late departures. The calculation range is determined by the closure duration; the longer the closure, the larger the calculation range for early / late departures. In reality, the proportion of late departures is much higher than early departures because toll station entrance closures are often temporary and without prior notice. Therefore, the calculation primarily considers the case of late departures.

[0097] In one example embodiment, for the second type of "detour," vehicles detour when the toll station entrance is closed, i.e., entering the highway at the previous station or the next station. Whether a vehicle chooses to detour depends on the distance between the toll station and the adjacent toll stations. Meanwhile, for the case of a single station closure, the toll will increase if a vehicle detours from the upstream station (e.g., station A) and decrease if it detours from the downstream station (e.g., station C). Therefore, the algorithm estimates the proportion of vehicles detouring from the upstream or downstream based on the distance from the upstream and downstream stations to the closed station, combined with historical data.

[0098] In one example embodiment, for the third "loss" scenario, the vehicle cancels its travel plans or chooses an alternative route, in which case the toll fee is completely lost.

[0099] It should be further noted that the content described in the example embodiments of this disclosure is only applicable to the scenario of a single toll station entrance being closed. If multiple toll station entrances are closed, the calculation can be performed on the basis of a single toll station entrance closure, and then the results can be accumulated to obtain the corresponding results. Furthermore, if a single toll station is closed in two directions (i.e., direction 1 and direction 2) at the same time, it can be split into two single toll station unidirectional entrance closure events, and the toll loss can still be calculated using the solution of this patent.

[0100] Furthermore, the data sources used in the exemplary embodiments of this disclosure will be explained and described. Specifically, in practical applications, the following data sources are required: toll station IDs (e.g., the ID of the first toll station that is currently closed, the ID of the second toll station upstream, and the ID of the third toll station downstream), toll station locations (the location of the first toll station that is currently closed, the location of the second toll station upstream, and the location of the third toll station downstream), the driving direction of the vehicle after entering the toll station (e.g., direction 1, direction 2, etc.), the first distance difference between the upstream toll station and the currently closed toll station, the second distance difference between the downstream toll station and the currently closed toll station, vehicle passage time, toll amount, the closing direction of the currently closed toll station, and the closing time of the currently closed toll station, etc. Of course, other data may also be used in practical applications, and this example does not impose any special restrictions on this.

[0101] The following will combine Figures 2-4 right Figure 1 The traffic flow prediction method shown will be further explained and illustrated. Specifically:

[0102] In step S110, historical traffic flow data of the target toll station is obtained, and target traffic flow data is extracted from the historical traffic flow data.

[0103] Specifically, taking direction 1 (from east to west) as the direction of travel, the target toll stations recorded here include currently closed toll stations (such as toll station B mentioned above), upstream toll stations corresponding to the currently closed toll stations (such as toll station A mentioned above), and downstream toll stations corresponding to the currently closed toll stations (such as toll station C mentioned above). Meanwhile, the historical traffic flow data recorded here may include first historical traffic flow data corresponding to the currently closed toll stations, second historical traffic flow data corresponding to the upstream toll stations, and third historical traffic flow data corresponding to the downstream toll stations, etc. Furthermore, the target traffic flow data recorded here may include first target traffic flow data corresponding to the currently closed toll stations, second target traffic flow data corresponding to the upstream toll stations, and third target traffic flow data corresponding to the downstream toll stations, etc.

[0104] In one example embodiment, historical traffic flow data of a target toll station can be obtained in the following ways: historical traffic flow data can be obtained from a corresponding database or from a corresponding cluster (such as Hive, Hadoop, etc.). This example does not impose any special restrictions on this. Furthermore, in the specific data acquisition process, it can be obtained directly through the corresponding toll station ID. For example, the first historical traffic flow data can be obtained through the first toll station identifier of the currently closed toll station B, the second historical traffic flow data can be obtained through the second toll station identifier of the upstream toll station A, and the third historical traffic flow data can be obtained through the third toll station identifier of the downstream toll station C.

[0105] In one example embodiment, after obtaining historical traffic flow data, target traffic flow data can be extracted from the historical traffic flow data. Specifically, this can be achieved as follows: obtain the start and end closing times of currently closed toll stations, and calculate the platform closure period of the currently closed toll stations based on the start and end closing times; determine the data extraction interval of the historical traffic flow data based on the platform closure period, and extract first target traffic flow data from the first historical traffic flow data, and / or extract second target traffic flow data from the second historical traffic flow data, and / or extract third target traffic flow data from the third historical traffic flow data based on the data extraction interval. That is, in practical applications, corresponding time data can be extracted from historical traffic flow data as target traffic flow data, and then a reference traffic flow can be determined based on the target traffic flow data, thereby improving the accuracy of the predicted traffic flow loss.

[0106] In step S120, the reference traffic flow of the target toll station during the platform closure period is calculated based on the target traffic flow data.

[0107] Specifically, the reference traffic flow recorded here includes a first reference traffic flow corresponding to the currently closed toll station, a second reference traffic flow corresponding to the upstream toll station, and a third reference traffic flow corresponding to the downstream toll station, etc. The calculation of the reference traffic flow for the target toll station during the platform closure period based on the target traffic flow data can be achieved in the following ways: calculating the first reference traffic flow for the currently closed toll station during the platform closure period based on the first target traffic flow data; and / or calculating the second reference traffic flow for the upstream toll station during the platform closure period based on the second target traffic flow data; and / or calculating the third reference traffic flow for the downstream toll station during the platform closure period based on the third target traffic flow data.

[0108] In one example embodiment, calculating the first reference traffic flow for the currently closed toll station during the platform closure period based on the first target traffic flow data can be achieved as follows: First, determine the first upper quartile and the first lower quartile based on the first target traffic flow data, and determine the first quartile interval based on the first upper quartile and the first lower quartile; second, determine the first lower limit value based on the first lower quartile and the first quartile interval, and determine the first upper limit value based on the first upper quartile and the first quartile interval; then, determine the range of the first standard box area based on the first upper limit value and the first lower limit value, and map the first target traffic flow data into the range of the first standard box area; finally, filter the first target traffic flow data outside the range of the first standard box area, and calculate the average value of the filtered first target traffic flow data to obtain the first reference traffic flow.

[0109] In one example embodiment, calculating the second reference traffic flow during the platform closure period of the upstream toll station based on the second target traffic flow data can be achieved as follows: First, determine the second upper quartile and the second lower quartile based on the second target traffic flow data, and determine the second quartile interval based on the second upper quartile and the second lower quartile; second, determine the second lower limit value based on the second lower quartile and the second quartile interval, and determine the second upper limit value based on the second upper quartile and the second quartile interval; then, determine the range of the second standard box area based on the second upper limit value and the second lower limit value, and map the second target traffic flow data into the range of the second standard box area; finally, filter the second target traffic flow data outside the range of the second standard box area, and calculate the average value of the filtered second target traffic flow data to obtain the second reference traffic flow.

[0110] In one example embodiment, calculating the third reference traffic flow for the downstream toll station during the platform closure period based on the third target traffic flow data can be achieved as follows: First, determine the third upper quartile and the third lower quartile based on the third target traffic flow data, and determine the third quartile interval based on the third upper quartile and the third lower quartile; second, determine the third lower limit based on the third lower quartile and the third quartile interval, and determine the third upper limit based on the third upper quartile and the third quartile interval; then, determine the third standard box area range based on the third upper limit and the third lower limit, and map the third target traffic flow data into the third standard box area range; finally, filter the third target traffic flow data outside the third standard box area range, and calculate the average value of the filtered third target traffic flow data to obtain the third reference traffic flow.

[0111] The following section uses the specific calculation process of the first reference traffic flow as an example, combined with... Figure 5 The specific calculation process for the first reference traffic flow is explained and illustrated. Specifically, assuming the initial closure time is T0, the final closure time is T1, the vehicle travel direction is direction 1, and the currently closed toll station is toll station B; in calculating the first reference traffic flow, firstly, the traffic flow data for direction 1 at toll station B entrance during the time interval T0 to T1 within the same week of the previous eight weeks is taken (excluding holidays, construction, and other abnormal situations); secondly, outlier processing is performed on the data; here, box plots are used to identify outlier data; where the vast majority of data lies within a fixed box, points exceeding the upper and lower edges of the box are removed as outliers. Let the first upper quartile of the data be Q1, and the first lower quartile be Q3; then:

[0112] The first quartile interval (IQR) is calculated as Q3 - Q1; the first lower limit is Q1 - 1.5 * IQR; the first upper limit is Q3 + 1.5 * IQR. Data above the upper limit or below the lower limit is considered outlier. Further, based on the data obtained after removing outliers, the average value is taken as the first reference traffic flow for entrance B of toll station 1. The calculation processes for the second and third reference traffic flows are similar and will not be elaborated further here.

[0113] In step S130, the lost traffic flow of the currently closed toll stations in the target toll station is predicted during the time period of station closure based on the reference traffic flow.

[0114] Specifically, predicting the lost traffic volume of the currently closed toll station in the target toll station during the platform closure period based on the reference traffic volume can be achieved as follows: First, determine the number of vehicles changing their travel plans due to the currently closed toll station being closed based on the first reference traffic volume; second, determine the number of vehicles detouring around the currently closed toll station during the platform closure period based on the second and third reference traffic volumes; third, determine the number of vehicles canceling their travel plans due to the currently closed toll station being closed based on the first and second vehicle numbers; and finally, determine the lost traffic volume of the currently closed toll station in the target toll station during the platform closure period based on the third vehicle number.

[0115] The first reference traffic flow recorded here includes the first sub-reference traffic flow during the time the toll station is currently closed, the second sub-reference traffic flow during the period before the toll station begins to close (the first observation period), and the third sub-reference traffic flow during the period after the toll station ends to close (the second observation period). The first target traffic flow data used to calculate the first sub-reference traffic flow is the traffic flow data within the historical time period corresponding to the toll station closure time period; the first target traffic flow data used to calculate the second sub-reference traffic flow is the traffic flow data within the historical time period corresponding to the first observation period; and the first target traffic flow data used to calculate the third sub-reference traffic flow is the traffic flow data within the historical time period corresponding to the second observation period. The specific calculation process for each sub-reference traffic flow is similar to the aforementioned calculation process for the reference traffic flow, and will not be elaborated further here.

[0116] In one example embodiment, determining the number of vehicles whose travel tasks have changed due to the closure of the currently closed toll station, based on a first reference traffic flow, can be achieved as follows: First, determine the length of the traffic flow observation period before and after the start and end times of the closure of the currently closed toll station, based on the toll station closure time period; second, determine a first observation period before the start and end times of the closure of the currently closed toll station, based on the traffic flow observation period and the start and end times of the closure, and determine a first traffic flow increase value based on the first reference traffic flow and the first actual traffic flow of the target toll station within the first observation period; then, determine a second observation period after the end times of the closure of the currently closed toll station, based on the traffic flow observation period and the end times of the closure, and determine a second traffic flow increase value based on the first reference traffic flow and the second actual traffic flow of the target toll station within the second observation period; finally, configure a first weight value and a second weight value for the first and second traffic flow increase values, and perform a weighted summation of the first and second traffic flow increase values ​​based on the first and second weight values ​​to obtain the number of vehicles whose travel tasks have changed due to the closure of the currently closed toll station.

[0117] The following will further explain and illustrate the specific calculation process for the first vehicle count. Specifically, firstly, assuming T1 is the starting closure time of the entrance to the currently closed toll station, and T2 is the ending closure time of the entrance to the currently closed toll station, then the length of the traffic flow observation time... The unit is hours; based on this, we can draw the following conclusions: the observation period before the closing time (first observation period) = T1-T~T1; the observation period after the closing time (second observation period) = T2~T2+T; where T1-T~T1 means that the first observation period is the starting observation time node obtained by subtracting T hours from the starting closing time T1 (that is, T1-T can be used to obtain the starting observation time node), and it can be inferred that the value of the first observation period is [T1-T, T1]; similarly, T2~T2+T means that the second observation period is the ending observation time node obtained by subtracting T hours from the ending closing time T2 (that is, T2+T can be used to obtain the ending observation time node); it can be inferred that the value of the second observation period is [T2, T2+T].

[0118] For example, suppose the tollbooth entrance will be closed from 8:00 AM to 10:30 AM on May 6, 2023, for a total closure time of 2.5 hours. Therefore, the observation period before the toll station closure is from 7:00 AM to 8:00 AM on May 6, 2023, and the observation period after the closure is from 10:30 AM to 11:30 AM on May 6, 2023. Furthermore, the increase in traffic flow before the toll station closure (i.e., the first increase in traffic flow) = the actual traffic flow at the entrance during the observation period before the toll station closure (first actual traffic flow) - the reference traffic flow at the entrance during the observation period before the toll station closure (first reference traffic flow). Simultaneously, the increase in traffic flow after the toll station closure (i.e., the second increase in traffic flow) = the actual traffic flow at the entrance during the observation period after the toll station closure (second actual traffic flow) - the reference traffic flow at the entrance during the observation period after the toll station closure (first reference traffic flow). The minimum value for both the first and second increase in traffic flow is 0; that is, if the first actual traffic flow is less than the first reference traffic flow, the minimum value of 0 is directly taken.

[0119] Finally, after obtaining the first and second increases in traffic flow, the number of the first vehicle can be calculated based on these values. The specific calculation process for the number of the first vehicle is as follows:

[0120] The first number of vehicles = [max(cd,0)*w1+max(ef,0)*w2];

[0121] Where c is the first actual traffic flow, d is the second sub-reference traffic flow, e is the second actual traffic flow, and f is the third sub-reference traffic flow; w1 is the first weight value, which can also be called the early departure weighting coefficient, and w2 is the second weight value, which can also be called the late departure weighting coefficient; the specific values ​​of w1 and w2 are in the range of 0 to 1; at the same time, the specific values ​​of the first weight value and the second weight value can be achieved by empirical methods or by network model prediction methods, and this example does not impose special restrictions on this.

[0122] In one example embodiment, a third actual traffic flow at the upstream toll station during the toll station closure period is determined based on a second reference traffic flow and a third reference traffic flow. A third traffic flow increase is then determined based on the third actual traffic flow and the second reference traffic flow. Next, a fourth actual traffic flow at the downstream toll station during the toll station closure period is obtained, and a fourth traffic flow increase is determined based on the fourth actual traffic flow and the third reference traffic flow. Then, a third weight value and a fourth weight value are configured for the third and fourth traffic flow increase values, and a weighted sum is performed on the third and fourth traffic flow increase values ​​to determine the second number of vehicles bypassing the currently closed toll station during the toll station closure period.

[0123] The following will explain and illustrate the specific calculation process for the number of the second vehicle. Specifically, the second number of vehicles recorded here refers to the additional traffic flow at the entrances before and after the closed toll station. The entrance before the closed toll station refers to the upstream toll station entrance on the same road and in the same direction (toll station A in the diagram), and the entrance after the closed toll station refers to the downstream toll station entrance on the same road and in the same direction (toll station C in the diagram). In practical application, the increase in traffic flow at the entrance before the closed toll station (third increase in traffic flow) = the actual traffic flow at the entrance before the closed toll station (third actual traffic flow) - the reference traffic flow at the entrance before the closed toll station (second reference traffic flow); the increase in traffic flow at the entrance after the closed toll station (fourth increase in traffic flow) = the actual traffic flow at the entrance after the closed toll station (fourth actual traffic flow) - the reference traffic flow at the entrance after the closed toll station (third reference traffic flow); the minimum value for both the third and fourth increase in traffic flow is 0; that is, if the third actual traffic flow is less than the second reference traffic flow, the minimum value of 0 is directly taken.

[0124] Finally, after obtaining the third and fourth traffic flow increases, the number of the second vehicle can be calculated based on these increases. The specific calculation process for the number of the second vehicle is as follows:

[0125] The second vehicle quantity = [max(gh,0)*w3+max(ij,0)*w4];

[0126] Where g is the third actual traffic flow, h is the second reference traffic flow, i is the fourth actual traffic flow, j is the third reference traffic flow, w3 is the third weight value, which can also be called the upstream detour weighting coefficient, and w4 is the fourth weight value, which can also be called the downstream detour weighting coefficient. The specific values ​​of w3 and w4 are in the range of 0 to 1. At the same time, the specific values ​​of the third and fourth weight values ​​can be achieved through empirical methods or through network model prediction. This example does not impose any special restrictions on this.

[0127] In one example embodiment, determining the number of third vehicles whose travel tasks are cancelled due to the closure of the currently closed toll station, based on the first number of vehicles and the second number of vehicles, can be achieved as follows: First, obtain the fifth actual traffic flow of the currently closed toll station during the station closure period, and determine the reduced traffic flow at the entrance of the currently closed toll station during the station closure period based on the first reference traffic flow and the fifth actual traffic flow; second, determine the number of third vehicles whose travel tasks are cancelled due to the closure of the currently closed toll station based on the reduced traffic flow at the entrance, the first number of vehicles, and the second number of vehicles.

[0128] In one example embodiment, the number of third vehicles whose travel tasks are cancelled due to the current closed toll station being closed can be determined based on the reduced traffic flow at the entrance, the first number of vehicles, and the second number of vehicles. This can be achieved by calculating the sum of the first number of vehicles and the second number of vehicles, and then calculating the difference between the reduced traffic flow at the entrance and the sum, to obtain the number of third vehicles whose travel tasks are cancelled due to the current closed toll station being closed.

[0129] The following will explain the specific calculation process for the third vehicle quantity. Specifically, the calculation process for the third vehicle quantity begins by determining the reduction in entrance traffic flow during the toll station closure period. The specific calculation process for this reduction is as follows: Entrance traffic flow reduction during toll station closure (entrance traffic flow reduction during toll station closure period) = Reference value of entrance traffic flow during toll station closure (first sub-reference traffic flow) - Actual value of entrance traffic flow during toll station closure (fifth actual traffic flow). Secondly, the "loss" of traffic flow due to toll station entrance closure (third vehicle quantity) = Entrance traffic flow reduction during toll station closure (entrance traffic flow reduction) - Increase in entrance traffic flow before and after the closure (first vehicle quantity) - Increase in entrance traffic flow before and after the toll station closure (second vehicle quantity).

[0130] For example, in practical applications, the following table 1 exists:

[0131] Table 1

[0132]

[0133] In Table 1 above, "historical" represents reference traffic flow, and "current" represents actual traffic flow. Based on Table 1, the specific calculation formula for the third traffic flow can be deduced as follows:

[0134] (ba)-[max(cd,0)*w1+max(ef,0)*w2]-[max(gh,0)*w3+max(ij,0)*w4];

[0135] Where 'b' represents the first sub-reference traffic flow and 'a' represents the fifth actual traffic flow, the actual meanings of the other parameters are consistent with those shown above, and will not be elaborated further here. Furthermore, in practical application, a, b, c, d, e, f, g, h, i, and j in Table 1 represent the traffic flow at toll stations in closed directions. During statistics, vehicle types are statistically analyzed separately for cars (Class I passenger vehicles, Class II passenger vehicles, and Class I freight vehicles) and large vehicles (vehicles other than cars). Of course, the specific classification of large and small vehicles can be adaptively adjusted according to actual circumstances; this example does not impose special restrictions on this.

[0136] Finally, after obtaining the number of the third vehicle, the final lost traffic flow can be determined. In determining the lost traffic flow, the number of the third vehicle can be directly used as the final lost traffic flow, or a corresponding weight value can be configured based on the number of the third vehicle to obtain the lost traffic flow. In practical applications, the method can be determined according to actual needs; this example does not impose any special restrictions.

[0137] In step S140, the amount of cost loss for the currently closed toll station during the time period of station closure is determined based on the lost traffic flow.

[0138] For details, please refer to Figure 6 As shown, determining the amount of fee loss for the currently closed toll station during the time the platform is closed, based on the lost traffic flow, may include the following steps:

[0139] Step S610: Based on the second number of vehicles and the reduced traffic flow at the entrance, determine the cost for vehicles to detour through the currently closed toll station during the station's closure period.

[0140] For details, please refer to Figure 7 As shown, determining the cost for vehicles to detour from the currently closed toll station during the station's closure period, based on the second number of vehicles and the reduced traffic flow at the entrance, may include the following steps:

[0141] Step S710: Determine the vehicle detour ratio based on the second number of vehicles and the reduced traffic flow at the entrance, and determine the number of detour vehicles based on the vehicle detour ratio.

[0142] Step S720: Calculate the first distance difference between the currently closed toll station and the upstream toll station, and calculate the second distance difference between the currently closed toll station and the downstream toll station.

[0143] Step S730: Determine the vehicle detour distance based on the first distance difference and the second distance difference, and determine the vehicle detour fee for the currently closed toll station during the station closure period based on the vehicle detour distance, the number of detour vehicles, and the toll fee per unit distance.

[0144] The following will explain and illustrate steps S710-S730. Specifically, to obtain the cost of vehicle detour, it is first necessary to calculate the proportion of the first, second, and third vehicle numbers in the reduction of traffic flow at the entrance. Specifically, in the proportion calculation, vehicles can be divided into two different categories: cars and large vehicles; the specific vehicle classification is determined based on the per-kilometer toll for each type of vehicle. For example:

[0145] The proportion of cars waiting = the number of cars waiting / the reduction in car traffic at the entrance during the toll station closure period;

[0146] The proportion of cars "going around" = the number of cars "going around" / the reduction in car traffic at the entrance during the toll station closure period;

[0147] The percentage of cars "lost" = the number of cars "lost" / the reduction in car traffic at the entrance during the toll station closure period;

[0148] The proportion of large vehicles waiting = the number of large vehicles waiting / the reduction in large vehicle traffic at the entrance during the toll station closure period;

[0149] The proportion of large vehicles "going around" = the number of large vehicles "going around" / the reduction in large vehicle traffic at the entrance during the toll station closure period;

[0150] The percentage of large vehicles "lost" = the number of large vehicles "lost" / the reduction in large vehicle traffic at the entrance during the toll station closure period.

[0151] Furthermore, in practical applications, all historical toll station entrance closure events can be statistically analyzed periodically (e.g., every Monday) and compiled into Table 2 below; where all proportions in Table 2 are percentages.

[0152] Table 2

[0153]

[0154] Furthermore, by averaging the proportions in Table 2 above, the final proportion can be obtained. For example, the specific averaging process can be as follows: Average proportion of cars at toll stations = Σ n Cars proportionally / n; Average car detour ratio at toll stations = ∑ n Car detour ratio / n; Average car loss ratio at toll stations = ∑ n The proportion of small cars lost per n; the average proportion of large vehicles lost per toll station = ∑ m Large vehicles are proportionally deflected per meter; the average deflection ratio of large vehicles at toll stations = ∑ m Large vehicle detour ratio / m; Average large vehicle loss ratio at toll stations = Σ m The percentage of vehicles lost is expressed as / m; where n and m represent the decrease in traffic flow at the entrance for large vehicles and small vehicles during the toll station closure period, respectively. Furthermore, for Table 2 above, by aggregating other data based on toll station and direction and taking the average, the percentage values ​​shown in Table 3 below can be obtained.

[0155] Table 3

[0156]

[0157] Additionally, if the table does not contain data for a particular toll station in a certain direction, the default value will be used to fill the data (the default value is the average value). This table can also be updated periodically (e.g., every Monday).

[0158] Furthermore, if Tables 2 and 3 exist, the cost of vehicles detouring through the toll station can be calculated, which is the amount of loss caused by vehicles detouring through the currently closed toll station. Taking toll station B as an example, in direction 1, the distance from toll station B to upstream toll station A is d1 (first distance difference), and the distance to downstream toll station C is d2 (second distance difference). Therefore, the toll loss due to vehicle detours caused by the toll station entrance closure is calculated as follows: Toll station vehicle detour loss = Number of cars detouring * (w4 * d2 - w3 * d1) * Average toll per kilometer for cars on the highway + Number of large vehicles detouring * (w4 * d2 - w3 * d1) * Average toll per kilometer for large vehicles on the highway; Number of cars detouring = Reference value of car traffic flow during toll station closure * Car detour ratio; Number of large vehicles detouring = Reference value of large vehicle traffic flow during toll station closure * Large vehicle detour ratio; Referring to the highway toll standards of a certain province, the calculation is based on an average toll of 0.4 yuan per kilometer for cars and 1.2 yuan per kilometer for large vehicles on the highway. Where (w4*d2-w3*d1) is the detour distance of the vehicle, w4 is the fourth weight value, and w3 is the third weight value.

[0159] Step S620: Based on the number of third vehicles and the lost traffic flow, determine the cost of canceled vehicle trips during the time period when the currently closed toll station is closed.

[0160] For details, please refer to Figure 8 As shown, determining the cost of canceled trips for vehicles at the currently closed toll station during the station's closure period, based on the number of third vehicles and the lost traffic flow, may include the following steps:

[0161] Step S810: Determine the proportion of canceled vehicle trips based on the number of third vehicles and the lost traffic flow, and determine the number of lost vehicles based on the proportion of canceled vehicle trips and the first reference traffic flow.

[0162] Step S820: Determine the average vehicle loss amount based on the toll fees of vehicles that entered from the currently closed toll station but exited from other toll stations.

[0163] Step S830: Based on the average vehicle loss amount and the number of vehicles lost, determine the cost of vehicle trip cancellations during the time period when the currently closed toll station is closed.

[0164] The following will explain and illustrate steps S810-S830. Specifically, if Tables 2 and 3 exist, the toll fees for canceled vehicle trips can be calculated; that is, the toll fee loss amount of the currently closed toll station due to canceled vehicle trips. For example, taking toll station B as an example, for toll station B, the travel direction is direction 1, and the average vehicle loss amount is calculated as follows: Average vehicle loss amount for cars = ∑(toll fee for cars entering from toll station B, traveling in direction 1, and then exiting from other toll stations) / j; Average vehicle loss amount for trucks = ∑(toll fee for trucks entering from toll station B, traveling in direction 1, and then exiting from other toll stations) / k; where j and k represent the number of car trips and truck trips calculated, respectively. One trip by a vehicle that generates a toll fee is counted as one trip. Meanwhile, the amount of vehicle loss at toll stations = number of cars lost at toll stations * average amount of cars lost + number of large vehicles lost at toll stations * average amount of large vehicles lost; the number of cars lost at toll stations = reference value of car traffic during toll station closure time * car loss ratio; the number of large vehicles lost at toll stations = reference value of large vehicle traffic during toll station closure time * large vehicle loss ratio.

[0165] Step S630: Determine the amount of cost loss incurred by the currently closed toll station during the time period of station closure, based on the cost of the vehicle detour and the cost of canceling the vehicle trip.

[0166] Specifically, after obtaining the costs of vehicle detours and trip cancellations, these costs can be added together to obtain the total amount of financial loss. Furthermore, the amount of financial loss can be displayed so that relevant personnel can view it.

[0167] Thus far, the traffic flow prediction method described in the exemplary embodiments of this disclosure has been fully implemented. Based on the foregoing description, it can be understood that the traffic flow prediction method described in the exemplary embodiments of this disclosure can use only highway toll station data and toll station entrance closure event data, without the need for additional equipment installation or the introduction of external data, thereby reducing the calculation cost of the amount of toll loss.

[0168] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0169] This disclosure also provides an example embodiment of a traffic flow prediction device. Specifically, refer to... Figure 9As shown, the traffic flow prediction device may include a target traffic flow data extraction module 910, a reference traffic flow calculation module 920, a loss traffic flow prediction module 930, and a cost loss quantity determination module 940. Wherein:

[0170] The target traffic flow data extraction module 910 can be used to obtain historical traffic flow data of the target toll station and extract target traffic flow data from the historical traffic flow data;

[0171] The reference traffic flow calculation module 920 can be used to calculate the reference traffic flow of the target toll station during the platform closure period based on the target traffic flow data.

[0172] The lost traffic flow prediction module 930 can be used to predict the lost traffic flow of the currently closed toll station in the target toll station during the time the platform is closed, based on the reference traffic flow.

[0173] The cost loss quantity determination module 940 can be used to determine the cost loss quantity of the currently closed toll station during the time period of the station closure based on the lost traffic flow.

[0174] In one example embodiment of this disclosure, the target toll station includes at least one of a currently closed toll station, an upstream toll station corresponding to the currently closed toll station, and a downstream toll station corresponding to the currently closed toll station; the historical traffic flow data includes at least one of a first historical traffic flow data corresponding to the currently closed toll station, a second historical traffic flow data corresponding to the upstream toll station, and a third historical traffic flow data corresponding to the downstream toll station; the target traffic flow data includes at least one of a first target traffic flow data corresponding to the currently closed toll station, a second target traffic flow data corresponding to the upstream toll station, and a third target traffic flow data corresponding to the downstream toll station; the reference traffic flow includes at least one of a first reference traffic flow corresponding to the currently closed toll station, a second reference traffic flow corresponding to the upstream toll station, and a third reference traffic flow corresponding to the downstream toll station.

[0175] In one example embodiment of this disclosure, extracting target traffic flow data from the historical traffic flow data includes: obtaining the start and end closing times of currently closed toll stations, and calculating the platform closure period of the currently closed toll stations based on the start and end closing times; determining the data extraction interval of the historical traffic flow data based on the platform closure period, and extracting first target traffic flow data from the first historical traffic flow data, and / or extracting second target traffic flow data from the second historical traffic flow data, and / or extracting third target traffic flow data from the third historical traffic flow data based on the data extraction interval.

[0176] In one example embodiment of this disclosure, calculating the reference traffic flow of the target toll station during the platform closure period based on the target traffic flow data includes: calculating the first reference traffic flow of the currently closed toll station during the platform closure period based on the first target traffic flow data; and / or calculating the second reference traffic flow of the upstream toll station during the platform closure period based on the second target traffic flow data; and / or calculating the third reference traffic flow of the downstream toll station during the platform closure period based on the third target traffic flow data.

[0177] In one example embodiment of this disclosure, calculating a first reference traffic flow for a currently closed toll station during its platform closure period based on first target traffic flow data includes: determining a first upper quartile and a first lower quartile based on the first target traffic flow data, and determining a first quartile interval based on the first upper quartile and the first lower quartile; determining a first lower limit based on the first lower quartile and the first quartile interval, and determining a first upper limit based on the first upper quartile and the first quartile interval; determining a first standard box area range based on the first upper limit and the first lower limit, and mapping the first target traffic flow data to the first standard box area range; filtering the first target traffic flow data outside the first standard box area range, and calculating the average value of the filtered first target traffic flow data to obtain the first reference traffic flow.

[0178] In one example embodiment of this disclosure, predicting the lost traffic flow of a currently closed toll station in the target toll station during the station closure period based on the reference traffic flow includes: determining, based on a first reference traffic flow, the number of first vehicles changing their travel plans due to the currently closed toll station being closed; and determining, based on a second reference traffic flow and a third reference traffic flow, the number of second vehicles detouring around the currently closed toll station during the station closure period; determining, based on the first and second vehicle numbers, the number of third vehicles canceling their travel plans due to the currently closed toll station being closed; and determining, based on the third vehicle number, the lost traffic flow of the currently closed toll station in the target toll station during the station closure period.

[0179] In one example embodiment of this disclosure, determining the number of vehicles whose travel tasks have changed due to the closure of the currently closed toll station based on a first reference traffic flow includes: determining the length of the traffic flow observation period before and after the start and end times of the closure of the currently closed toll station based on the toll station closure time period; determining a first observation period before the start and end times of the closure of the currently closed toll station based on the traffic flow observation period and the start and end times of the closure, and determining a first traffic flow increase value based on the first reference traffic flow and the first actual traffic flow of the target toll station within the first observation period; determining a second observation period after the end and end times of the closure of the currently closed toll station based on the traffic flow observation period and the end and end times of the closure, and determining a second traffic flow increase value based on the first reference traffic flow and the second actual traffic flow of the target toll station within the second observation period; configuring a first weight value and a second weight value for the first and second traffic flow increase values, and performing a weighted summation of the first and second traffic flow increase values ​​based on the first and second weight values ​​to obtain the number of vehicles whose travel tasks have changed due to the closure of the currently closed toll station.

[0180] In one example embodiment of this disclosure, determining the number of second vehicles bypassing the currently closed toll station during the station closure period based on a second reference traffic flow and a third reference traffic flow includes: obtaining the third actual traffic flow of the upstream toll station during the station closure period, and determining a third traffic flow increase value based on the third actual traffic flow and the second reference traffic flow; obtaining the fourth actual traffic flow of the downstream toll station during the station closure period, and determining a fourth traffic flow increase value based on the fourth actual traffic flow and the third reference traffic flow; configuring a third weight value and a fourth weight value for the third traffic flow increase value and the fourth traffic flow increase value, and performing a weighted summation of the third traffic flow increase value and the fourth traffic flow increase value based on the third weight value and the fourth weight value to determine the number of second vehicles bypassing the currently closed toll station during the station closure period.

[0181] In one example embodiment of this disclosure, determining the number of third vehicles whose travel tasks are cancelled due to the closure of the currently closed toll station, based on the first number of vehicles and the second number of vehicles, includes: obtaining the fifth actual traffic flow of the currently closed toll station during the station closure period, and determining the reduced traffic flow at the entrance of the currently closed toll station during the station closure period based on the first reference traffic flow and the fifth actual traffic flow; and determining the number of third vehicles whose travel tasks are cancelled due to the closure of the currently closed toll station based on the reduced traffic flow at the entrance, the first number of vehicles, and the second number of vehicles.

[0182] In one example embodiment of this disclosure, determining the number of third vehicles whose travel tasks are cancelled due to the current closed toll station being closed, based on the reduced traffic flow at the entrance, the first number of vehicles, and the second number of vehicles, includes: calculating the sum of the first number of vehicles and the second number of vehicles, and calculating the difference between the reduced traffic flow at the entrance and the sum of the two numbers, to obtain the number of third vehicles whose travel tasks are cancelled due to the current closed toll station being closed.

[0183] In one example embodiment of this disclosure, determining the amount of cost loss for the currently closed toll station during the station closure period based on the lost traffic flow includes: determining the cost of vehicle detours during the station closure period based on a second number of vehicles and reduced traffic flow at the entrance; determining the cost of canceled trips during the station closure period based on a third number of vehicles and lost traffic flow; and determining the amount of cost loss for the currently closed toll station during the station closure period based on the cost of vehicle detours and the cost of canceled trips.

[0184] In one example embodiment of this disclosure, determining the cost of vehicle detour during the platform closure period of the currently closed toll station based on the second number of vehicles and the reduced traffic flow at the entrance includes: determining the vehicle detour ratio based on the second number of vehicles and the reduced traffic flow at the entrance, and determining the number of detour vehicles based on the vehicle detour ratio; calculating a first distance difference between the currently closed toll station and the upstream toll station, and calculating a second distance difference between the currently closed toll station and the downstream toll station; determining the vehicle detour distance based on the first distance difference and the second distance difference, and determining the cost of vehicle detour during the platform closure period of the currently closed toll station based on the vehicle detour distance, the number of detour vehicles, and the toll per unit distance.

[0185] In one example embodiment of this disclosure, determining the cost of canceled vehicle trips during the time period of the currently closed toll station based on the number of third vehicles and the lost traffic flow includes: determining the proportion of canceled vehicle trips based on the number of third vehicles and the lost traffic flow, and determining the number of lost vehicles based on the proportion of canceled vehicle trips and a first reference traffic flow; determining the average vehicle loss amount based on the toll fees of vehicles entering from the currently closed toll station but exiting from other toll stations; and determining the cost of canceled vehicle trips during the time period of the currently closed toll station based on the average vehicle loss amount and the number of lost vehicles.

[0186] The specific details of each module in the aforementioned traffic flow prediction device have been described in detail in the corresponding traffic flow prediction method, so they will not be repeated here.

[0187] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0188] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0189] In an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described method is also provided.

[0190] Those skilled in the art will understand that various aspects of this disclosure can be implemented as a system, method, or program product. Therefore, various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "system."

[0191] The following reference Figure 10 To describe an electronic device 1000 according to such an embodiment of the present disclosure. Figure 10 The electronic device 1000 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0192] like Figure 10 As shown, the electronic device 1000 is manifested in the form of a general-purpose computing device. The components of the electronic device 1000 may include, but are not limited to: at least one processing unit 1010, at least one storage unit 1020, a bus 1030 connecting different system components (including storage unit 1020 and processing unit 1010), and a display unit 1040.

[0193] The storage unit stores program code that can be executed by the processing unit 1010, causing the processing unit 1010 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure. For example, the processing unit 1010 can perform actions such as... Figure 1 Step S110: Obtain historical traffic flow data of the target toll station and extract target traffic flow data from the historical traffic flow data; Step S120: Calculate the reference traffic flow of the target toll station during the station closure period based on the target traffic flow data; Step S130: Predict the lost traffic flow of the currently closed toll station in the target toll station during the station closure period based on the reference traffic flow; Step S140: Determine the amount of cost loss of the currently closed toll station during the station closure period based on the lost traffic flow.

[0194] Storage unit 1020 may include readable media in the form of volatile storage units, such as random access memory (RAM) 10201 and / or cache memory 10202, and may further include read-only memory (ROM) 10203.

[0195] Storage unit 1020 may also include a program / utility 10204 having a set (at least one) program module 10205, such program module 10205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0196] Bus 1030 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0197] Electronic device 1000 can also communicate with one or more external devices 1100 (e.g., keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with electronic device 1000, and / or any device that enables electronic device 1000 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 1050. Furthermore, electronic device 1000 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 1060. As shown, network adapter 1060 communicates with other modules of electronic device 1000 via bus 1030. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 1000, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0198] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0199] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible implementations, various aspects of this disclosure may also be implemented as a program product including program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of this disclosure described in the "Exemplary Methods" section above.

[0200] The program product for implementing the above-described method according to embodiments of the present disclosure may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0201] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0202] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0203] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0204] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing devices can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0205] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0206] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention described herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not invented by this disclosure. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. A method for predicting traffic flow, characterized in that, include: Obtain historical traffic flow data of the target toll station, and extract the target traffic flow data from the historical traffic flow data; Based on the target traffic flow data, calculate the reference traffic flow for the target toll station during the platform closure period; Based on the reference traffic flow, predict the lost traffic flow of the currently closed toll stations in the target toll stations during the period when the stations are closed; Determining the cost loss of the currently closed toll station during the platform closure period based on the lost traffic flow includes: determining the cost of vehicle detours during the platform closure period based on the second vehicle number and reduced traffic flow at the entrance; determining the cost of canceled trips during the platform closure period based on the third vehicle number and lost traffic flow; and determining the cost loss of the currently closed toll station during the platform closure period based on the cost of vehicle detours and the cost of canceled trips. The cost of vehicle detour is determined as follows: The detour ratio is determined based on the second number of vehicles and the reduced traffic flow at the entrance; the number of detour vehicles is determined based on the detour ratio; a first distance difference is calculated between the currently closed toll station and the upstream toll station; a second distance difference is calculated between the currently closed toll station and the downstream toll station; the detour distance is determined based on the first and second distance differences; and the detour cost for vehicles traveling from the currently closed toll station during the station closure period is determined based on the detour distance, the number of detour vehicles, and the toll per unit distance.

2. The traffic flow prediction method according to claim 1, characterized in that, The target toll station includes at least one of the following: a currently closed toll station, an upstream toll station corresponding to the currently closed toll station, and a downstream toll station corresponding to the currently closed toll station; The historical traffic flow data includes at least one of the following: first historical traffic flow data corresponding to the currently closed toll station, second historical traffic flow data corresponding to the upstream toll station, and third historical traffic flow data corresponding to the downstream toll station; The target traffic flow data includes at least one of the following: first target traffic flow data corresponding to the currently closed toll station, second target traffic flow data corresponding to the upstream toll station, and third target traffic flow data corresponding to the downstream toll station; The reference traffic flow includes at least one of the following: a first reference traffic flow corresponding to a currently closed toll station, a second reference traffic flow corresponding to an upstream toll station, and a third reference traffic flow corresponding to a downstream toll station.

3. The traffic flow prediction method according to claim 2, characterized in that, Extracting target traffic flow data from the historical traffic flow data includes: Obtain the start and end closing times of the currently closed toll stations, and calculate the station closure period based on the start and end closing times; Based on the platform closure period, a data extraction interval for the historical traffic flow data is determined, and based on the data extraction interval, a first target traffic flow data is extracted from the first historical traffic flow data, and / or a second target traffic flow data is extracted from the second historical traffic flow data, and / or a third target traffic flow data is extracted from the third historical traffic flow data.

4. The traffic flow prediction method according to claim 3, characterized in that, Based on the target traffic flow data, calculate the reference traffic flow for the target toll station during the platform closure period, including: Based on the first target traffic flow data, calculate the first reference traffic flow for the currently closed toll stations during the platform closure period; and / or Based on the second target traffic flow data, calculate the second reference traffic flow for the upstream toll station during the platform closure period; and / or Based on the third target traffic flow data, calculate the third reference traffic flow for the downstream toll station during the platform closure period.

5. The traffic flow prediction method according to claim 4, characterized in that, Based on the primary target traffic flow data, calculate the primary reference traffic flow for the currently closed toll stations during the platform closure period, including: The first upper quartile and the first lower quartile are determined based on the first target traffic flow data, and the first quartile interval is determined based on the first upper quartile and the first lower quartile. The first lower limit value is determined based on the first lower quartile and the first quartile interval, and the first upper limit value is determined based on the first upper quartile and the first quartile interval. The first standard box area range is determined based on the first upper limit value and the first lower limit value, and the first target traffic flow data is mapped to the first standard box area range; The first target traffic flow data outside the first standard box area is filtered, and the average value of the filtered first target traffic flow data is calculated to obtain the first reference traffic flow.

6. The traffic flow prediction method according to claim 1, characterized in that, Based on the reference traffic flow, predict the lost traffic flow of the currently closed toll stations in the target toll station during the station closure period, including: The number of first vehicles whose travel tasks are changed due to the closure of the currently closed toll station is determined based on the first reference traffic flow, and the number of second vehicles that detour around the currently closed toll station during the station closure period is determined based on the second reference traffic flow and the third reference traffic flow. Based on the first number of vehicles and the second number of vehicles, determine the third number of vehicles whose travel missions are canceled due to the current closed toll station being closed. Based on the number of third vehicles, determine the lost traffic volume of the currently closed toll stations in the target toll stations during the time the platforms are closed.

7. The traffic flow prediction method according to claim 6, characterized in that, The number of vehicles whose travel tasks are changed due to the closure of the currently closed toll station is determined based on the first reference traffic flow, including: The length of the traffic flow observation period for the currently closed toll station is determined based on the platform closure time period, before the start closure time and after the end closure time. Based on the length of the traffic flow observation time and the start and end times, a first observation period before the start and end times of the currently closed toll station is determined, and a first increase in traffic flow is determined based on the first reference traffic flow and the first actual traffic flow of the target toll station within the first observation period. Based on the traffic flow observation time and the termination closing time, a second observation period after the termination closing time is determined for the currently closed toll station, and a second traffic flow increase value is determined based on the first reference traffic flow and the second actual traffic flow of the target toll station within the second observation period. Configure a first weight value and a second weight value for the first increase in traffic flow and the second increase in traffic flow, and perform a weighted summation of the first increase in traffic flow and the second increase in traffic flow based on the first weight value and the second weight value to obtain the first number of vehicles whose travel tasks have changed due to the current closed toll station being in a closed state.

8. The traffic flow prediction method according to claim 6, characterized in that, The number of second vehicles that detour around the currently closed toll station during the station closure period is determined based on the second and third reference traffic volumes, including: Obtain the third actual traffic flow of the upstream toll station during the platform closure period, and determine the third traffic flow increase value based on the third actual traffic flow and the second reference traffic flow; Obtain the fourth actual traffic flow of the downstream toll station during the platform closure period, and determine the fourth traffic flow increase value based on the fourth actual traffic flow and the third reference traffic flow. Configure a third weight value and a fourth weight value for the third and fourth vehicle flow increases, and perform a weighted sum of the third and fourth vehicle flow increases based on the third and fourth weight values ​​to determine the number of second vehicles that detour through the currently closed toll station during the station closure period.

9. The traffic flow prediction method according to claim 6, characterized in that, Based on the first number of vehicles and the second number of vehicles, determine the third number of vehicles whose travel missions are canceled due to the currently closed toll station being closed, including: Obtain the fifth actual traffic flow of the currently closed toll station during the time period of the station closure, and determine the reduction of traffic flow at the entrance of the currently closed toll station during the time period of the station closure based on the first reference traffic flow and the fifth actual traffic flow. Based on the reduced traffic flow at the entrance, the number of the first vehicle, and the number of the second vehicle, determine the number of the third vehicle whose travel mission was canceled due to the currently closed toll station being in a closed state.

10. The traffic flow prediction method according to claim 9, characterized in that, Based on the reduced traffic flow at the entrance, the first number of vehicles, and the second number of vehicles, determine the third number of vehicles whose travel plans are cancelled due to the currently closed toll station being closed, including: The sum of the first number of vehicles and the second number of vehicles is calculated, and the difference between the reduced traffic flow at the entrance and the sum is calculated to obtain the third number of vehicles whose travel tasks are canceled due to the current closed toll station being closed.

11. The traffic flow prediction method according to claim 1, characterized in that, Based on the number of third-party vehicles and the lost traffic flow, determine the cost of canceled vehicle trips during the time period when the currently closed toll station is closed, including: The proportion of canceled vehicle trips is determined based on the number of third vehicles and the lost traffic flow, and the number of lost vehicles is determined based on the proportion of canceled vehicle trips and the first reference traffic flow. The average vehicle loss amount is determined based on the toll fees of vehicles that entered from currently closed toll stations but exited from other toll stations. Based on the average vehicle loss amount and the number of vehicles lost, the cost of canceled vehicle trips during the time period of the currently closed toll station is determined.

12. A traffic flow prediction device, characterized in that, include: The target traffic flow data extraction module is used to obtain historical traffic flow data of the target toll station and extract target traffic flow data from the historical traffic flow data; The reference traffic flow calculation module is used to calculate the reference traffic flow of the target toll station during the platform closure period based on the target traffic flow data. The lost traffic flow prediction module is used to predict the lost traffic flow of the currently closed toll stations in the target toll station during the time the platform is closed, based on the reference traffic flow. The cost loss quantity determination module is used to determine the cost loss quantity of the currently closed toll station during the platform closure period based on the lost traffic flow, including: determining the cost of vehicle detours during the platform closure period based on the second vehicle number and reduced traffic flow at the entrance; determining the cost of canceled trips during the platform closure period based on the third vehicle number and lost traffic flow; and determining the cost loss quantity of the currently closed toll station during the platform closure period based on the vehicle detour cost and the vehicle trip cancellation cost. The cost of vehicle detour is determined as follows: The detour ratio is determined based on the second number of vehicles and the reduced traffic flow at the entrance; the number of detour vehicles is determined based on the detour ratio; a first distance difference is calculated between the currently closed toll station and the upstream toll station; a second distance difference is calculated between the currently closed toll station and the downstream toll station; the detour distance is determined based on the first and second distance differences; and the detour cost for vehicles traveling from the currently closed toll station during the station closure period is determined based on the detour distance, the number of detour vehicles, and the toll per unit distance.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the traffic flow prediction method according to any one of claims 1-11.

14. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to execute the traffic flow prediction method according to any one of claims 1-11 by executing the executable instructions.

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