CN110826943A - Method and related equipment for judging whether bus allocation is needed or not and determining bus allocation number - Google Patents

Method and related equipment for judging whether bus allocation is needed or not and determining bus allocation number Download PDF

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CN110826943A
CN110826943A CN202010033980.0A CN202010033980A CN110826943A CN 110826943 A CN110826943 A CN 110826943A CN 202010033980 A CN202010033980 A CN 202010033980A CN 110826943 A CN110826943 A CN 110826943A
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CN110826943B (en
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李腾飞
孙熙
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Wuhan Yuanguang Technology Co Ltd
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Abstract

The embodiment of the application provides a method for judging whether bus allocation is needed and determining the bus allocation number, which is used for allocating the accurate bus allocation number for a target bus route after the target bus route is determined, so that the effect of reasonably utilizing bus resources is achieved. The method comprises the following steps: acquiring a passenger flow peak time of a target bus route; obtaining a first basic passenger flow Q1And a first actual passenger flow rate Q2(ii) a According to Q1And Q2Obtain the passenger flow demand △ Q12Judgment △ Q12Whether it is greater than the threshold value phi of vehicle allocation1When it is, △ Q12Calculating the corresponding departure interval duration of the passenger flow peak time period; and recommending the number of vehicle allocation; after the bus is allocated, acquiring a second basic passenger flow Q of a target bus line after the bus is allocated in the passenger flow peak period3(ii) a According to Q3And Q2To obtain an adjusted difference value △ Q32(ii) a If it is△Q32If greater than or equal to 0, the vehicle matching is successful, and if △ Q32If less than 0, △ Q is adjusted according to the following formula12To obtain new △ Q12 ‘’According to the specification △ Q12 ‘’And circularly executing vehicle matching verification.

Description

Method and related equipment for judging whether bus allocation is needed or not and determining bus allocation number
Technical Field
The application relates to the field of buses, in particular to a method and related equipment for judging whether bus allocation is needed or not and determining the bus allocation number.
Background
Under the background of continuous promotion of the purchasing power of residents and continuous development of science and technology, the travel mode of the online car reservation now becomes the daily travel mode of the residents. The network taxi booking, namely the short name of the network taxi booking operation service, refers to the operation activities of booking taxi service for non-tour by establishing a service platform based on the internet technology, accessing vehicles and drivers meeting the conditions and integrating supply and demand information.
The net car of making an appointment has the convenience of crossing time, crossing the region, however when net car of making an appointment occupies resident's a big mode of going on a journey, it also sees that, along with city population constantly rises, especially the hot city constantly flows in the external population, under the limited circumstances of traffic capacity, selects net car of making an appointment trip, especially in holiday peak period, still meets the condition of traffic jam easily, still brings inconvenience and relatively poor service experience for resident's trip.
Meanwhile, if the advantage of large passenger carrying capacity can be further exerted in the conventional public transport, the travel demand of residents can be better met, obviously, a larger feasible space still exists for improving the traffic jam condition, and higher resource utilization rate can be brought for the public transport resources, so that after the public transport route is determined, the reasonable distribution of the public transport resources of the public transport route is obviously an important link, and in the existing related technology, the condition of low accuracy still exists in the distribution mode of the public transport resources of the public transport route.
Disclosure of Invention
The embodiment of the application provides a method and related equipment for judging whether bus allocation is needed or not and determining the bus allocation number, and the method and the related equipment are used for allocating the accurate bus allocation number for a target bus route after the target bus route is determined, so that the effect of reasonably utilizing bus resources is achieved.
In a first aspect, the present invention provides a method for determining whether a bus mating is required and determining the number of bus assignments, the method comprising: s101, obtaining a passenger flow peak time of a target bus line; s102, respectively acquiring the destination bus routes in the passenger flow peak periodFirst base passenger flow rate Q1And a first actual passenger flow rate Q2(ii) a The first basic passenger flow is the passenger flow of a user who has taken a riding action, the first actual passenger flow is the passenger flow of the user who actually needs to take the riding action, and the first actual passenger flow is larger than the first basic passenger flow; the obtaining of the first basic passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining card swiping passenger flow data of the bus line, and obtaining the first basic passenger flow volume according to the card swiping passenger flow data; the obtaining of the first actual passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining line OD survey data, resident travel OD survey data and online user query data of the bus line; obtaining the first actual passenger flow of the target bus line in the passenger flow peak period according to the line OD survey data, the resident travel OD survey data and the online user query data; s103, according to the first basic passenger flow Q1And said first actual passenger flow rate Q2Obtain the passenger flow demand △ Q12△ Q12= Q2-Q1S104, judging the passenger flow demand △ Q12Whether the value is more than a threshold value phi of needing to allocate the vehicle1S105, if not, judging that the target bus line does not need to carry out public mating, S106, if so, judging that the target bus line needs to carry out public mating, and △ Q according to the passenger flow peak time and the passenger flow demand12Calculating the departure interval duration corresponding to the passenger flow peak time period; s107, calculating the recommended number of the buses in the target bus line in the passenger flow peak period according to the departure interval time and the single-shift operation time of the target bus line; s108, after the target bus line is allocated according to the recommended number of allocated buses, obtaining a second basic passenger flow Q of the allocated target bus line in the passenger flow peak period3(ii) a Wherein the second base passenger flow is the passenger flow of the user who has taken a ride; s109, according to the second basic passenger flow Q3And said first actual passenger flow rate Q2Obtaining an adjustmentDifference △ Q32△ Q32= Q3- Q2S110, if △ Q32If the value is more than or equal to 0, the vehicle matching is successful, S111, if the value is △ Q32Less than 0, the △ Q is adjusted according to the following formula12To obtain new △ Q12 ‘’Said △ Q12 ‘’=△Q12+△Q32S112 according to the △ Q12 ‘’And circularly executing the S106-S112.
Optionally, the obtaining of the first actual passenger flow volume of the target bus route at the passenger flow peak time period through the route OD survey, the resident travel OD survey and the online user query data includes: obtaining first actual passenger flow of the target bus line at different preset time periods according to the line OD survey, the resident travel OD survey, the card swiping passenger flow data and the online user query data;
solving for
Figure 388978DEST_PATH_IMAGE001
，
Figure 296760DEST_PATH_IMAGE002
The actual passenger flow of the target bus line during the peak time of passenger flow,
Figure 196583DEST_PATH_IMAGE003
the number of minutes involved in the peak hours of passenger flow,
Figure 231535DEST_PATH_IMAGE004
for the actual passenger flow for the different preset time periods,
Figure 533204DEST_PATH_IMAGE005
the unit of measurement of (a) is in minutes.
Optionally, the unit of the metering time of the different preset time periods is 15 minutes.
Optionally, the obtaining of the first actual passenger flow volume of the target bus route in the passenger flow peak period includes: and obtaining a first actual passenger flow of the target bus route in the passenger flow peak period through a passenger flow output model, wherein the passenger flow output model is obtained by a route OD survey of the bus route, a resident travel OD survey and an online user query data training initial model.
Optionally, the calculating, according to the passenger flow peak time and the passenger flow demand, the departure interval duration corresponding to the passenger flow peak time includes:
calculating the departure interval duration corresponding to the passenger flow peak time period according to a departure interval duration calculation formula, wherein the departure interval duration calculation formula comprises the following steps:
，
Figure 749739DEST_PATH_IMAGE007
for indicating the departure interval duration,
Figure 588382DEST_PATH_IMAGE008
the unit of measurement of (a) is in minutes,for indicating the number of minutes involved in the peak hours of traffic,
Figure 994141DEST_PATH_IMAGE010
for indicating the traffic demand of the target bus route during said peak traffic hours,
Figure 602977DEST_PATH_IMAGE011
and the system is used for indicating the rated bus carrying number of the target bus route.
Optionally, the calculating the recommended number of the buses in the target bus route during the passenger flow peak period according to the departure interval duration and the single-shift operation time of the target bus route includes:
calculating the recommended number of the buses of the target bus route in the passenger flow peak period according to a number of the buses calculation formula, wherein the number of the buses includes:
Figure 245311DEST_PATH_IMAGE012
，
Figure 255992DEST_PATH_IMAGE013
for indicating the recommended number of car assignments,
Figure 223948DEST_PATH_IMAGE014
for indicating the single shift operating time of the target bus route,for indicating the departure interval duration,
Figure 500526DEST_PATH_IMAGE014
and
Figure 834555DEST_PATH_IMAGE015
the unit of measurement of (a) is in minutes,
Figure 973412DEST_PATH_IMAGE016
for indicating the number of motor buses.
In a second aspect, the present invention further provides a device for determining the number of bus assignments, wherein the device comprises:
the acquisition unit is used for acquiring the passenger flow peak time of the target bus line;
the acquisition unit is further used for acquiring the passenger flow demand of the target bus route in the passenger flow peak period; respectively acquiring first basic passenger flow Q of the target bus line in the passenger flow peak period1And a first actual passenger flow rate Q2(ii) a The first basic passenger flow is the passenger flow of a user who has taken a riding action, the first actual passenger flow is the passenger flow of the user who actually needs to take the riding action, and the first actual passenger flow is larger than the first basic passenger flow; obtaining a first basic passenger flow measuring tool of the target bus route at the passenger flow peak timeThe body includes: obtaining card swiping passenger flow data of the bus line, and obtaining the first basic passenger flow volume according to the card swiping passenger flow data; the obtaining of the first actual passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining line OD survey data, resident travel OD survey data and online user query data of the bus line; obtaining the first actual passenger flow of the target bus line in the passenger flow peak period according to the line OD survey data, the resident travel OD survey data and the online user query data;
a processing unit for determining the first basic passenger flow Q1And said first actual passenger flow rate Q2Obtain the passenger flow demand △ Q12△ Q12= Q2- Q1；
The processing unit is further configured to determine the passenger flow demand △ Q12Whether the value is more than a threshold value phi of needing to allocate the vehicle1If not, judging that the target bus line does not need to carry out public mating, if so, judging that the target bus line needs to carry out public mating, and △ Q according to the passenger flow peak time period and the passenger flow demand12Calculating the departure interval duration corresponding to the passenger flow peak time period;
the processing unit is further used for calculating the recommended number of the buses in the passenger flow peak period according to the departure interval duration and the single-shift operation time of the target bus line;
the processing unit is further used for obtaining a second basic passenger flow Q of the target bus route in the passenger flow peak period after the target bus route is allocated according to the recommended number of allocated buses3(ii) a Wherein the second base passenger flow is the passenger flow of the user who has taken a ride;
the processing unit is also used for obtaining the second basic passenger flow quantity Q according to the second basic passenger flow quantity Q3And said first actual passenger flow rate Q2To obtain an adjusted difference value △ Q32△ Q32= Q3- Q2If △ Q32Is greater than or equal to 0, and is,the vehicle matching is successful;
the processing unit is also used for judging if the △ Q32Less than 0, the △ Q is adjusted according to the following formula12To obtain new △ Q12 ‘’Said △ Q12 ‘’=△Q12+△Q32；
The processing unit is further configured to rely on the △ Q12 ‘’And circularly executing the S106-S112 of claim 1.
In a third aspect, the present invention also provides a device for calculating the number of bus assignments, wherein the prediction device comprises a processor, and the processor is configured to implement the method according to any one of the above items when executing the computer program stored in the memory.
In a fourth aspect, the present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of any one of the above.
According to the technical scheme, the embodiment of the application has the following advantages:
aiming at the peak time of passenger flow, the passenger flow demand at the peak time of passenger flow is obtained through the first basic passenger flow (the passenger flow of taking a riding action already occurs) and the first actual passenger flow (the passenger flow with the actual riding demand but not necessarily taking the riding action), the passenger flow demand at the peak time of passenger flow directly reflects the current riding demand of a target bus route, the passenger flow demand is compared with a distribution threshold, when the passenger flow demand is larger than the threshold, the riding demand of the target bus route is larger, at the moment, the recommended distribution number of the target bus route is obtained by taking the passenger flow demand as the center, and by additionally arranging a verification link after distribution, whether the difference value between the second basic passenger flow and the first actual passenger flow is larger than 0 is verified to determine whether the additionally arranged recommended distribution number solves the riding demand of the target bus route, if not, the method and the system are executed circularly until the bus allocation is successful, so that the accuracy of recommending the number of allocated buses is obviously improved by effectively combining historical passenger flow data and potential passenger flow demand, the number of allocated buses and bus resources can be reasonably allocated while the actual passenger flow is met, the win-win effect is achieved, and the method and the system have higher application value and popularization value for bus operation service.
Drawings
Fig. 1 is a schematic flow chart illustrating a method for determining whether bus allocation is required and determining the number of bus allocations in an embodiment of the present application;
fig. 2 is a schematic structural diagram of a device for determining the bus allocation number according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a device for determining the bus allocation number according to the embodiment of the present application.
Detailed Description
The embodiment of the application provides a method and related equipment for judging whether bus allocation is needed or not and determining the bus allocation number, and the method and the related equipment are used for allocating the accurate bus allocation number for a target bus route after the target bus route is determined, so that the effect of reasonably utilizing bus resources is achieved.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and in the claims of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Moreover, the terms "comprises," "comprising," and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus. The naming or numbering of the steps appearing in the present application does not mean that the steps in the method flow have to be executed in the chronological/logical order indicated by the naming or numbering, and the named or numbered process steps may be executed in a modified order depending on the technical purpose to be achieved, as long as the same or similar technical effects are achieved.
The division of the modules presented in this application is a logical division, and in practical applications, there may be another division, for example, multiple modules may be combined or integrated into another system, or some features may be omitted, or not executed, and in addition, the shown or discussed coupling or direct coupling or communication connection between each other may be through some interfaces, and the indirect coupling or communication connection between the modules may be in an electrical or other similar form, which is not limited in this application. The modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed in a plurality of circuit modules, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present disclosure.
Before the method for judging whether bus allocation is needed and determining the bus allocation number provided by the embodiment of the application is introduced, related background contents are introduced.
In the existing related technology in the bus field, when the number of bus allocations of a target bus route is determined, the corresponding number of bus allocations is often determined through historical bus card swiping data or real-time bus card swiping data, and influences brought by different special conditions are not considered, for example, sudden bad weather reasons, activity reasons of a network appointment platform and the like, so that the number of bus allocations distributed for the target bus route is caused, actual conditions of the bus allocations are not met, and the utilization rate of bus resources is low.
Based on the above defects in the prior art, the embodiment of the application provides a new method for judging whether bus allocation is needed and determining the bus allocation number, and the defects in the prior art can be overcome to a certain extent.
The execution main body of the method for judging whether bus allocation is needed and determining the bus allocation number in the embodiment of the present application may be the device for determining the bus allocation number provided in the embodiment of the present application, or the training device integrating the device for determining the bus allocation number in different types, such as a server device, a physical host, or a User Equipment (UE), and the like, where the device for determining the bus allocation number may be implemented in a hardware or software manner, and the UE may specifically be a terminal device such as a smart phone, a tablet computer, a notebook computer, a palm computer, a desktop computer, or a Personal Digital Assistant (PDA).
Next, a method for determining whether bus allocation is required and determining the bus allocation number provided in the embodiment of the present application is described.
Fig. 1 shows a schematic flow chart of a method for determining whether bus allocation is required and determining the number of bus allocations in an embodiment of the present application, and as shown in fig. 1, the method for determining whether bus allocation is required and determining the number of bus allocations in an embodiment of the present application may specifically include the following contents:
s101, obtaining a passenger flow peak time of a target bus line;
s102, respectively obtaining first basic passenger flow Q of the target bus line in the passenger flow peak period1And a first actual passenger flow rate Q2(ii) a The first basic passenger flow is the passenger flow of a user who has taken a riding action, the first actual passenger flow is the passenger flow of the user who actually needs to take the riding action, and the first actual passenger flow is larger than the first basic passenger flow; the obtaining of the first basic passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining card swiping passenger flow data of the bus line, and obtaining the first basic passenger flow volume according to the card swiping passenger flow data; the obtaining of the first actual passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining line OD survey data of the bus line and resident trip ODSurvey data and online user query data; obtaining the first actual passenger flow of the target bus line in the passenger flow peak period according to the line OD survey data, the resident travel OD survey data and the online user query data;
s103, according to the first basic passenger flow Q1And said first actual passenger flow rate Q2Obtain the passenger flow demand △ Q12△ Q12= Q2- Q1；
S104, judging the passenger flow demand △ Q12Whether the value is more than a threshold value phi of needing to allocate the vehicle1；
S105, if not, judging that the target bus line does not need to carry out bus mating;
s106, if yes, judging that the target bus line needs to carry out public mating, and △ Q according to the passenger flow peak time and the passenger flow demand12Calculating the departure interval duration corresponding to the passenger flow peak time period;
s107, calculating the recommended number of the buses in the target bus line in the passenger flow peak period according to the departure interval time and the single-shift operation time of the target bus line;
s108, after the target bus line is allocated according to the recommended number of allocated buses, obtaining a second basic passenger flow Q of the allocated target bus line in the passenger flow peak period3(ii) a Wherein the second base passenger flow is the passenger flow of the user who has taken a ride;
s109, according to the second basic passenger flow Q3And said first actual passenger flow rate Q2To obtain an adjusted difference value △ Q32△ Q32= Q3- Q2；
S110, if △ Q32If the vehicle speed is more than or equal to 0, the vehicle matching is successful;
s111, if △ Q32Less than 0, the △ Q is adjusted according to the following formula12To obtain new △ Q12 ‘’Said △ Q12 ‘’=△Q12+△Q32；
S112, according to the △ Q12 ‘’And circularly executing the S106-S112.
In the technical solution provided in the embodiment shown in fig. 1, for a passenger flow peak period, the passenger flow demand in the passenger flow peak period is obtained through a first basic passenger flow (passenger flow in which a riding action has already occurred) and a first actual passenger flow (passenger flow in which an actual riding demand does not necessarily occur) in the passenger flow peak period, the passenger flow demand directly reflects the current riding demand for a target bus route, the passenger flow demand is compared with a distribution threshold, when the passenger flow demand is greater than the threshold, the riding demand for the target bus route is larger, at this time, the recommended distribution number of the target bus route is calculated with the passenger flow demand as a center, and by adding a verification link after distribution, checking whether a difference value between the second basic passenger flow and the first actual passenger flow is greater than 0, to determine whether the added recommended distribution number has solved the riding demand of the target bus route, if not, the method is executed circularly until the bus allocation is successful, so that the accuracy of recommending the number of allocated buses is obviously improved by effectively combining historical passenger flow data and potential passenger flow demand, the number of allocated buses and bus resources can be reasonably allocated while the actual passenger flow is met, the win-win effect is achieved, and the method has higher application value and popularization value for bus operation service.
Specific implementations of the various steps of the embodiment shown in FIG. 1 are described in detail below:
in the embodiment of the application, after the current target bus route is determined, according to historical passenger flow data of the target bus route and in combination with the threshold value of reference factors such as the passenger flow change rate and/or the number of people getting on or off the bus, the time period when the target value is higher than the threshold value is screened out and used as the passenger flow peak time period of the target bus route.
As a specific implementation manner of step S102 in the embodiment shown in fig. 1, the method may include:
obtaining a line OD survey, a resident trip OD survey and on-line user query data of a bus line;
it is understood that the OD survey is a traffic survey between the trip Origin location Origin and the trip Destination location Destination.
The survey content may specifically include information such as departure point distribution, destination point distribution, travel purpose, travel mode, travel time, travel distance, or travel times.
The line OD survey and the resident trip OD survey can be realized by survey modes such as a family visit survey, a roadside inquiry survey, a postcard survey, a work trip survey, a vehicle license plate survey, a transportation distribution point survey, a bus line passenger survey or a telephone inquiry survey and the like; or the data base corresponding to the input value is obtained through the mode of typing by the user.
And the card swiping passenger flow data and the online user inquiry data can be obtained by connecting with a data center of a public transport APP or a processing device of a public transport management center and calling.
After line OD survey, resident travel OD survey and online user query data are obtained, the first actual passenger flow of the target bus line at the passenger flow peak time can be obtained through analysis of big data.
For the first basic passenger flow, the processing equipment of the bus management center can be directly called to obtain the card swiping record of the real bus taking action, so that the first basic passenger flow is obtained. For the first actual passenger flow, as can be understood by those skilled in the art, it is a real reflection of the user vehicle quantity demand in the target bus route, and it includes both the taking action that has already occurred and the actual passenger flow in which the taking action should actually occur but the taking action does not occur due to insufficient number of buses. Thus according to said first base passenger flow Q1And said first actual passenger flow rate Q2Obtain the passenger flow demand △ Q12△ Q12= Q2- Q1And determining the passenger flow demand △ Q12Whether the value is more than a threshold value phi of needing to allocate the vehicle1To determine whether a vehicle needs to be matched, the threshold value phi1Can be preset according to the actual condition requirements (such as vehicle matching cost and the like); at the same time, it is required to say thatIt should be noted that the execution of step S101 and step S102 is not separately executed, for example, the determination of the peak time of the passenger flow in step S101 can be realized in the acquisition process of step S102, and if the number of occurrences, frequency, and occupancy of data in a certain time period are large in the line OD survey, the resident travel OD survey, and the online user query data, the peak time of the passenger flow can be extracted. Of course, step S101 may also be executed independently, that is, a certain bus route may be determined in daily life, and if the route has many complaints, or the time for waiting for a bus in the middle interval is long, or there are not many people in the seats during each riding, the bus route may be determined as the target bus route.
Further, as a specific implementation manner for obtaining the passenger flow demand, the passenger flow demand at the passenger flow peak time can be calculated by a sliding time window:
according to the line OD survey, the resident travel OD survey and the on-line user query data, obtaining passenger flow demand of the target bus line in different preset time periods;
solving for，
Figure 524665DEST_PATH_IMAGE018
For the traffic demand of the destination bus route during peak traffic hours,the number of minutes involved in the peak hours of passenger flow,
Figure 288539DEST_PATH_IMAGE020
for the passenger flow demand of different preset time periods,
Figure 828105DEST_PATH_IMAGE020
the unit of measurement of (a) is in minutes.
It can be understood that for the time windows corresponding to different preset time periods, the maximum solution of the passenger flow demand in the sliding time window can be solved in a sliding time window manner, and the maximum solution is used as the passenger flow demand at the passenger flow peak time period, or the highest cross-section passenger flow demand at the peak time period.
In the above-mentioned preset time period and the passenger flow peak time period, different metering time duration units are configured, and the metering time duration unit may indicate the granularity of the passenger flow demand, for example, 5 minutes, 10 minutes, 15 minutes, 20 minutes, 30 minutes, 45 minutes, 60 minutes, etc., and in further practical applications, it is found that the metering time duration unit of 15 minutes has a higher degree of distinction for the variation range of the passenger flow demand of the bus route in a short time, and can reflect the real passenger flow demand in a short time more clearly, so the metering time duration unit of the different preset time periods is preferably 15 minutes.
As another specific implementation manner for obtaining the passenger flow demand, the passenger flow demand at the time of the passenger flow peak may also be implemented by a neural network model, that is, the method may include:
and outputting the passenger flow demand of the target bus line at the passenger flow peak time period through a passenger flow output model, wherein the passenger flow output model is obtained by a line OD survey of the bus line, a resident travel OD survey and an initial model trained by historical passenger flow demand of online user query data at different preset time periods.
It can be understood that the neural network model can be trained and obtained by machine learning and combining training samples on the basis of an Artificial Intelligence (AI) technology, and has the characteristic of flexibly predicting the particle demand in peak passenger flow periods.
The method comprises the steps that an initialized neural network model can be obtained as an initial model, the passenger flow demand of a passenger flow peak time period is output as a target, and the line OD survey of a bus line, the resident travel OD survey, the on-line user query data and the historical passenger flow demand of the target bus line in different preset time periods are input to carry out forward propagation; and calculating a loss function according to the output passenger flow demand at the passenger flow peak time, performing back propagation, and optimizing parameters of the model so as to improve the prediction effect of the model. And continuously optimizing and adjusting the model through repeated propagation, wherein the trained model can be used as a passenger flow output model and put into practical application.
The model can specifically adopt a time sequence model, such as a Prophet model, and the time sequence model has higher learning capability and prediction accuracy for time sequence prediction, so that the model is more suitable for prediction of passenger flow demand in a passenger flow peak period related to the embodiment of the application.
As a specific implementation manner of the embodiment corresponding to fig. 1, the calculating of the departure interval duration may include:
calculating the departure interval duration corresponding to the passenger flow peak time period according to a departure interval duration calculation formula, wherein the departure interval duration calculation formula comprises the following steps:
Figure 881511DEST_PATH_IMAGE021
，
Figure 190133DEST_PATH_IMAGE022
for indicating the number of minutes involved in peak hours of passenger flow,
Figure 670793DEST_PATH_IMAGE023
for indicating the traffic demand of the destination bus route during peak traffic hours,
Figure 681343DEST_PATH_IMAGE024
the bus station is used for indicating the rated bus carrying number of the target bus line.
The number of the rated carrying persons of the bus can be determined by combining a bus policy and a bus product.
After the departure interval duration is obtained, the obtained single-shift operation time of the target bus route can be combined, and the ratio of the two operation times is used as the recommended number of bus allocations.
In yet another exemplary implementation, a mobility bus may also be introduced. That is, step S104 in the embodiment corresponding to fig. 1 may specifically include:
calculating the recommended number of the buses of the target bus line in the passenger flow peak period according to a number of the buses calculation formula, wherein the number of the buses comprises the following formula:
Figure 538441DEST_PATH_IMAGE025
，
Figure 232727DEST_PATH_IMAGE026
for indicating the recommended number of car assignments,
Figure 353130DEST_PATH_IMAGE027
for indicating the single shift operating time of the target bus route,
Figure 867288DEST_PATH_IMAGE028
is used for indicating the time length of the departure interval,
Figure 262497DEST_PATH_IMAGE016
for indicating the number of motor buses.
It can be understood that by introducing the mobile buses, the mobile buses can be flexibly distributed by combining multiple bus lines on the whole layer, so that the bus resources are flexibly configured, and the utilization rate of the bus resources is further improved. Meanwhile, after the target bus route is allocated according to the recommended allocation number, whether the target bus route is successfully allocated or whether the problem of passenger flow demand is solved3(ii) a The second basic passenger flow is the passenger flow of a user who takes a riding action after the user is allocated with a vehicle; according to the second basic passenger flow Q3And said first actual passenger flow rate Q2To obtain an adjusted difference value △ Q32△ Q32= Q3- Q2If △ Q32If the value is more than or equal to 0, the vehicle matching is successful, and if the value is △ Q32Less than 0, the △ Q is adjusted according to the following formula12To obtain new △ Q12 ‘’Said △ Q12 ‘’=△Q12+△Q32According to said △ Q12 ‘’And circularly verifying and matching the vehicle. Can be used forUnderstanding, △ Q12 ‘’And continuing to perform vehicle allocation verification through the steps S106-S112 of the invention according to the updated passenger flow demand after the vehicle is allocated for the first time until the vehicle allocation is successful.
In order to better implement the method for judging whether bus allocation is needed and determining the bus allocation number provided by the embodiment of the application, the embodiment of the application also provides a device for determining the bus allocation number.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a training device for an order quantity prediction model according to an embodiment of the present application, in the embodiment of the present application, a device 300 for determining a bus allocation number may specifically include the following structure:
an obtaining unit 301, configured to obtain a passenger flow peak time of a target bus route;
the obtaining unit 301 is further configured to obtain a passenger flow demand of the target bus route in the passenger flow peak time period; respectively acquiring first basic passenger flow Q of the target bus line in the passenger flow peak period1And a first actual passenger flow rate Q2(ii) a The first basic passenger flow is the passenger flow of a user who has taken a riding action, the first actual passenger flow is the passenger flow of the user who actually needs to take the riding action, and the first actual passenger flow is larger than the first basic passenger flow; the obtaining of the first basic passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining card swiping passenger flow data of the bus line, and obtaining the first basic passenger flow volume according to the card swiping passenger flow data; the obtaining of the first actual passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining line OD survey data, resident travel OD survey data and online user query data of the bus line; obtaining the first actual passenger flow of the target bus line in the passenger flow peak period according to the line OD survey data, the resident travel OD survey data and the online user query data;
a processing unit 302 for determining the first base passenger flow Q1And said first actual passenger flow rate Q2Obtained byObtain the passenger flow demand △ Q12△ Q12= Q2- Q1The processing unit is also used for judging the passenger flow demand △ Q12Whether the value is more than a threshold value phi of needing to allocate the vehicle1If not, judging that the target bus line does not need to carry out public mating, if so, judging that the target bus line needs to carry out public mating, and △ Q according to the passenger flow peak time period and the passenger flow demand12Calculating the departure interval duration corresponding to the passenger flow peak time period; the processing unit is further used for calculating the recommended number of the buses in the passenger flow peak period according to the departure interval duration and the single-shift operation time of the target bus line; the processing unit is further used for obtaining a second basic passenger flow Q of the target bus route in the passenger flow peak period after the target bus route is allocated according to the recommended number of allocated buses3(ii) a Wherein the second base passenger flow is the passenger flow of the user who has taken a ride; the processing unit is also used for obtaining the second basic passenger flow quantity Q according to the second basic passenger flow quantity Q3And said first actual passenger flow rate Q2To obtain an adjusted difference value △ Q32△ Q32= Q3- Q2If △ Q32If the value is more than or equal to 0, the vehicle matching is successful, and the processing unit is also used for judging that the vehicle is matched with the △ Q32Less than 0, the △ Q is adjusted according to the following formula12To obtain new △ Q12 ‘’Said △ Q12 ‘’=△Q12+△Q32The processing unit is also used for processing the △ Q12 ‘’And circularly executing the S106-S112 of claim 1.
In one exemplary implementation, the method further includes:
obtaining a line OD survey, a resident trip OD survey and on-line user query data of a bus line;
and deducing the passenger flow demand of the target bus line at the passenger flow peak time period through line OD survey, resident travel OD survey and on-line user query data.
In yet another exemplary implementation manner, in a second possible implementation manner of the second aspect of the embodiment of the present application:
predicting passenger flow demand of a target bus line in different preset time periods according to line OD survey, resident travel OD survey and on-line user query data;
solving for，
Figure 368173DEST_PATH_IMAGE030
For the traffic demand of the destination bus route during peak traffic hours,
Figure 353316DEST_PATH_IMAGE031
the number of minutes involved in the peak hours of passenger flow,
Figure 552216DEST_PATH_IMAGE032
for the passenger flow demand of different preset time periods,
Figure 424357DEST_PATH_IMAGE032
the unit of measurement of (a) is in minutes.
In yet another exemplary implementation, the metered time period units for the different preset periods are 15 minutes.
In yet another exemplary implementation, the passenger flow demand of the target bus line in the peak time period of the passenger flow is obtained through a passenger flow output model, wherein the passenger flow output model is obtained by a bus line OD survey of the bus line, a resident travel OD survey and an online user query data training initial model.
In another exemplary implementation manner, the departure interval duration corresponding to the peak time of passenger flow is calculated according to a departure interval duration calculation formula, where the departure interval duration calculation formula includes:
Figure 683300DEST_PATH_IMAGE033
，
Figure 906471DEST_PATH_IMAGE034
is used for indicating the time length of the departure interval,
Figure 112324DEST_PATH_IMAGE035
the unit of measurement of (a) is in minutes,
Figure 635710DEST_PATH_IMAGE036
for indicating the number of minutes involved in peak hours of passenger flow,
Figure 783663DEST_PATH_IMAGE037
for indicating the traffic demand of the destination bus route during peak traffic hours,
Figure 759709DEST_PATH_IMAGE038
the bus station is used for indicating the rated bus carrying number of the target bus line.
In yet another exemplary implementation, the recommended number of bus assignments for the target bus route during peak hours of passenger flow is calculated according to a number of bus assignments calculation formula, which includes:
，for indicating the recommended number of car assignments,
Figure 216733DEST_PATH_IMAGE041
for indicating the single shift operating time of the target bus route,
Figure 945654DEST_PATH_IMAGE042
is used for indicating the time length of the departure interval,
Figure 24469DEST_PATH_IMAGE043
and
Figure 991288DEST_PATH_IMAGE042
the unit of measurement of (a) is in minutes,
Figure 497355DEST_PATH_IMAGE044
for indicating the number of motor buses.
Referring to fig. 3, fig. 3 shows a schematic structural diagram of a device for determining the number of bus assignments provided in the embodiment of the present application, specifically, the device for determining the number of bus assignments provided in the embodiment of the present application includes a processor 401, and when the processor 401 is used to execute a computer program stored in a memory 402, each step of the method for determining whether bus assignment is needed and determining the number of bus assignments in any embodiment corresponding to fig. 1 or fig. 1 is implemented; alternatively, the processor 401 is configured to implement the functions of the units in the corresponding embodiment of fig. 1 when executing the computer program stored in the memory 402.
Illustratively, a computer program may be partitioned into one or more modules/units, which are stored in memory 402 and executed by processor 401 to accomplish the present application. One or more modules/units may be a series of computer program instruction segments capable of performing certain functions, the instruction segments being used to describe the execution of a computer program in a computer device.
The bus allocation number determination device may include, but is not limited to, the processor 401 and the memory 402. It will be understood by those skilled in the art that the illustration is merely an example of the device for determining the number of bus assignments, and does not constitute a limitation of the device for determining the number of bus assignments, and may include more or less components than those illustrated, or may combine some components, or different components, for example, the determination of the number of bus assignments may further include an input-output device, a network access device, a bus, etc., and the processor 401, the memory 402, the input-output device, and the network access device, etc., are connected by the bus.
The Processor 401 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center for the bus distribution number determining device, with various interfaces and lines connecting the various parts of the overall device.
The memory 402 may be used to store computer programs and/or modules, and the processor 401 may implement various functions of the computer device by running or executing the computer programs and/or modules stored in the memory 402 and invoking data stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the stored data area may store data (such as audio data, video data, etc.) created according to the use of the bus allocation determination device, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The application also provides a computer readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for determining whether bus allocation is needed and determining the bus allocation number in any embodiment corresponding to fig. 1 or fig. 2 is implemented.
It will be appreciated that the integrated unit, if implemented as a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the device, the equipment and the units for determining the number of bus assignments described above may refer to the description of the method for determining whether the bus assignment is required and determining the number of bus assignments in the embodiment corresponding to fig. 1 or fig. 2, and details are not described herein again.
In summary, the method and the related device for judging whether bus allocation is needed and determining the number of bus allocations provided by the embodiment of the application calculate the recommended number of bus allocations of the target bus route by acquiring the passenger flow demand at the passenger flow peak time and taking the passenger flow demand as a center, thereby combining the historical passenger flow data with the potential passenger flow demand, obviously improving the accuracy of the recommended number of bus allocations, satisfying the actual passenger flow, reasonably allocating the number of bus allocations and the bus resources thereof, achieving the win-win effect, and having higher application value and popularization value for the bus operation service.
In the several embodiments provided in the present application, it should be understood that the disclosed device, apparatus and units for determining the number of bus assignments may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims (9)

1. A method of determining whether a bus mating is required and determining the number of bus assignments, the method comprising:
s101, obtaining a passenger flow peak time of a target bus line;
s102, respectively obtaining first basic passenger flow Q of the target bus line in the passenger flow peak period1And a first actual passenger flow rate Q2(ii) a The first basic passenger flow is the passenger flow of a user who has taken a riding action, the first actual passenger flow is the passenger flow of the user who actually needs to take the riding action, and the first actual passenger flow is larger than the first basic passenger flow; the obtaining of the first basic passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining card swiping passenger flow data of the bus line, and obtaining the first basic passenger flow volume according to the card swiping passenger flow data;the obtaining of the first actual passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining line OD survey data, resident travel OD survey data and online user query data of the bus line; obtaining the first actual passenger flow of the target bus line in the passenger flow peak period according to the line OD survey data, the resident travel OD survey data and the online user query data;
s103, according to the first basic passenger flow Q1And said first actual passenger flow rate Q2Obtain the passenger flow demand △ Q12△ Q12= Q2- Q1；
S104, judging the passenger flow demand △ Q12Whether the value is more than a threshold value phi of needing to allocate the vehicle1；
S105, if not, judging that the target bus line does not need to carry out bus mating;
s106, if yes, judging that the target bus line needs to carry out public mating, and △ Q according to the passenger flow peak time and the passenger flow demand12Calculating the departure interval duration corresponding to the passenger flow peak time period;
s107, calculating the recommended number of the buses in the target bus line in the passenger flow peak period according to the departure interval time and the single-shift operation time of the target bus line;
s108, after the target bus line is allocated according to the recommended number of allocated buses, obtaining a second basic passenger flow Q of the allocated target bus line in the passenger flow peak period3(ii) a Wherein the second base passenger flow is the passenger flow of the user who has taken a ride;
s109, according to the second basic passenger flow Q3And said first actual passenger flow rate Q2To obtain an adjusted difference value △ Q32△ Q32= Q3- Q2；
S110, if △ Q32If the vehicle speed is more than or equal to 0, the vehicle matching is successful;
s111, if △ Q32Less than 0, then according toThe △ Q is adjusted by the following formula12To obtain new △ Q12 ‘’Said △ Q12 ‘’=△Q12+△Q32；
S112, according to the △ Q12 ‘’And circularly executing the S106-S112.
2. The method of claim 1, wherein the obtaining of the first actual passenger flow volume of the target bus line during the peak passenger flow period through the line OD survey, the resident travel OD survey, and the online user query data comprises:
obtaining first actual passenger flow of the target bus line at different preset time periods according to the line OD survey, the resident travel OD survey, the card swiping passenger flow data and the online user query data;
solving for，
Figure 349096DEST_PATH_IMAGE002
The actual passenger flow of the target bus line during the peak time of passenger flow,
Figure 847073DEST_PATH_IMAGE003
the number of minutes involved in the peak hours of passenger flow,
Figure 87561DEST_PATH_IMAGE004
for the actual passenger flow for the different preset time periods,
Figure 38200DEST_PATH_IMAGE004
the unit of measurement of (a) is in minutes.
3. The method according to claim 2, wherein the metering duration of the different preset time periods is in units of 15 minutes.
4. The method of claim 1, wherein said obtaining a first actual passenger flow volume of said target bus route during said rush hour of passenger flow comprises:
and obtaining a first actual passenger flow of the target bus route in the passenger flow peak period through a passenger flow output model, wherein the passenger flow output model is obtained by a route OD survey of the bus route, a resident travel OD survey and an online user query data training initial model.
5. The method of claim 1, wherein calculating an departure interval duration corresponding to the peak traffic hour based on the peak traffic hour and the traffic demand comprises:
calculating the departure interval duration corresponding to the passenger flow peak time period according to a departure interval duration calculation formula, wherein the departure interval duration calculation formula comprises the following steps:
Figure 389547DEST_PATH_IMAGE005
，
Figure 742031DEST_PATH_IMAGE006
for indicating the departure interval duration,
Figure 402688DEST_PATH_IMAGE007
the unit of measurement of (a) is in minutes,
Figure 309464DEST_PATH_IMAGE008
for indicating the number of minutes involved in the peak hours of traffic,
Figure 730081DEST_PATH_IMAGE009
for indicating the traffic demand of the target bus route during said peak traffic hours,
Figure 671493DEST_PATH_IMAGE010
and the system is used for indicating the rated bus carrying number of the target bus route.
6. The method of claim 1, wherein calculating the recommended number of bus assignments for the target bus route during the peak traffic hours based on the departure interval duration and the single-shift operating time of the target bus route comprises:
calculating the recommended number of the buses of the target bus route in the passenger flow peak period according to a number of the buses calculation formula, wherein the number of the buses includes:
Figure 784942DEST_PATH_IMAGE011
，
Figure 179014DEST_PATH_IMAGE012
for indicating the recommended number of car assignments,
Figure 403322DEST_PATH_IMAGE013
for indicating the single shift operating time of the target bus route,
Figure 182928DEST_PATH_IMAGE014
for indicating the departure interval duration,
Figure 936121DEST_PATH_IMAGE013
and
Figure 348647DEST_PATH_IMAGE014
the unit of measurement of (a) is in minutes,
Figure 845488DEST_PATH_IMAGE015
for indicating the number of motor buses.
7. A device for determining the number of bus assignments, comprising:
the acquisition unit is used for acquiring the passenger flow peak time of the target bus line;
the acquisition unit is further used for acquiring the passenger flow demand of the target bus route in the passenger flow peak period; respectively acquiring first basic passenger flow Q of the target bus line in the passenger flow peak period1And a first actual passenger flow rate Q2(ii) a The first basic passenger flow is the passenger flow of a user who has taken a riding action, the first actual passenger flow is the passenger flow of the user who actually needs to take the riding action, and the first actual passenger flow is larger than the first basic passenger flow; the obtaining of the first basic passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining card swiping passenger flow data of the bus line, and obtaining the first basic passenger flow volume according to the card swiping passenger flow data; the obtaining of the first actual passenger flow volume of the target bus route at the passenger flow peak time specifically includes: obtaining line OD survey data, resident travel OD survey data and online user query data of the bus line; obtaining the first actual passenger flow of the target bus line in the passenger flow peak period according to the line OD survey data, the resident travel OD survey data and the online user query data;
a processing unit for determining the first basic passenger flow Q1And said first actual passenger flow rate Q2Obtain the passenger flow demand △ Q12△ Q12= Q2- Q1；
The processing unit is further configured to determine the passenger flow demand △ Q12Whether the value is more than a threshold value phi of needing to allocate the vehicle1If not, judging that the target bus line does not need to carry out public mating, if so, judging that the target bus line needs to carry out public mating, and △ Q according to the passenger flow peak time period and the passenger flow demand12Calculating the departure interval duration corresponding to the passenger flow peak time period;
the processing unit is further used for calculating the recommended number of the buses in the passenger flow peak period according to the departure interval duration and the single-shift operation time of the target bus line;
the processing unit is further used for obtaining a second basic passenger flow Q of the target bus route in the passenger flow peak period after the target bus route is allocated according to the recommended number of allocated buses3(ii) a Wherein the second base passenger flow is the passenger flow of the user who has taken a ride;
the processing unit is also used for obtaining the second basic passenger flow quantity Q according to the second basic passenger flow quantity Q3And said first actual passenger flow rate Q2To obtain an adjusted difference value △ Q32△ Q32= Q3- Q2If △ Q32If the vehicle speed is more than or equal to 0, the vehicle matching is successful;
the processing unit is also used for judging if the △ Q32Less than 0, the △ Q is adjusted according to the following formula12To obtain new △ Q12 ‘’Said △ Q12 ‘’=△Q12+△Q32；
The processing unit is further configured to rely on the △ Q12 ‘’And circularly executing the S106-S112 of claim 1.
8. A device for calculating the number of bus assignments, wherein the prediction device comprises a processor for implementing the method according to any one of claims 1 to 6 when executing a computer program stored in a memory.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 6.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112070372A (en) * 2020-08-25 2020-12-11 长沙理工大学 Bus passenger flow distribution method, system and storage medium based on interval uncertainty
CN113673803A (en) * 2020-05-13 2021-11-19 丰田自动车株式会社 Vehicle distribution device, vehicle and terminal
CN113673803B (en) * 2020-05-13 2024-05-28 丰田自动车株式会社 Car distribution device, car and terminal

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102024206A (en) * 2010-12-20 2011-04-20 江苏省交通科学研究院股份有限公司 Method for predicting suburban rail transit passenger flow
CN102156732A (en) * 2011-04-11 2011-08-17 北京工业大学 Bus IC card data stop matching method based on characteristic stop
CN104318081A (en) * 2014-10-10 2015-01-28 东南大学 Method for allocating bicycles at public bicycle rental stations with urgent demand in city
CN107766969A (en) * 2017-09-28 2018-03-06 东南大学 A kind of major station cable release distribution method based on the identification of subway service ability bottleneck section
CN109859459A (en) * 2019-02-22 2019-06-07 北京航空航天大学 A kind of automatic Pilot bus dispatching optimization method
CN109886491A (en) * 2019-02-26 2019-06-14 北京工业大学 A kind of routine bus system two stages Optimization Scheduling of magnanimity operation data driving
CN109905845A (en) * 2018-12-10 2019-06-18 华南理工大学 A kind of bus passenger flow OD acquisition methods based on mobile phone signaling
CN110222893A (en) * 2019-06-06 2019-09-10 武汉元光科技有限公司 Dispensing location recommendation method, device and the electronic equipment of shared traffic resource
CN110334867A (en) * 2019-07-05 2019-10-15 河海大学常州校区 A kind of intelligent public transportation system and operation method of passenger-vehicle-cloud interaction
CN110428096A (en) * 2019-07-26 2019-11-08 西南交通大学 The more cross-channel Transportation Organization optimization methods of urban track traffic based on ticket information
CN110657817A (en) * 2019-09-29 2020-01-07 武汉元光科技有限公司 Method and device for recommending travel route

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102024206A (en) * 2010-12-20 2011-04-20 江苏省交通科学研究院股份有限公司 Method for predicting suburban rail transit passenger flow
CN102156732A (en) * 2011-04-11 2011-08-17 北京工业大学 Bus IC card data stop matching method based on characteristic stop
CN104318081A (en) * 2014-10-10 2015-01-28 东南大学 Method for allocating bicycles at public bicycle rental stations with urgent demand in city
CN107766969A (en) * 2017-09-28 2018-03-06 东南大学 A kind of major station cable release distribution method based on the identification of subway service ability bottleneck section
CN109905845A (en) * 2018-12-10 2019-06-18 华南理工大学 A kind of bus passenger flow OD acquisition methods based on mobile phone signaling
CN109859459A (en) * 2019-02-22 2019-06-07 北京航空航天大学 A kind of automatic Pilot bus dispatching optimization method
CN109886491A (en) * 2019-02-26 2019-06-14 北京工业大学 A kind of routine bus system two stages Optimization Scheduling of magnanimity operation data driving
CN110222893A (en) * 2019-06-06 2019-09-10 武汉元光科技有限公司 Dispensing location recommendation method, device and the electronic equipment of shared traffic resource
CN110334867A (en) * 2019-07-05 2019-10-15 河海大学常州校区 A kind of intelligent public transportation system and operation method of passenger-vehicle-cloud interaction
CN110428096A (en) * 2019-07-26 2019-11-08 西南交通大学 The more cross-channel Transportation Organization optimization methods of urban track traffic based on ticket information
CN110657817A (en) * 2019-09-29 2020-01-07 武汉元光科技有限公司 Method and device for recommending travel route

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113673803A (en) * 2020-05-13 2021-11-19 丰田自动车株式会社 Vehicle distribution device, vehicle and terminal
CN113673803B (en) * 2020-05-13 2024-05-28 丰田自动车株式会社 Car distribution device, car and terminal
CN112070372A (en) * 2020-08-25 2020-12-11 长沙理工大学 Bus passenger flow distribution method, system and storage medium based on interval uncertainty
CN112070372B (en) * 2020-08-25 2022-11-18 长沙理工大学 Bus passenger flow distribution method, system and storage medium based on interval uncertainty

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