CN111695726A - Bus scheduling schedule updating method and device - Google Patents
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Abstract
The embodiment of the application discloses a method and a device for updating a schedule of a bus. According to the technical scheme provided by the embodiment of the application, the number of departure shifts and the time interval of the corresponding time period are calculated by obtaining the passenger flow data and the line scheduling parameters, and the update of the bus scheduling schedule is realized by combining the uplink and downlink departure time and the time interval.
Description
Technical Field
The embodiment of the application relates to the technical field of bus scheduling, in particular to a method and a device for updating a scheduling schedule of a bus.
Background
At present, the traditional bus shift scheduling comprises the following modes: firstly, automatically acquiring shift scheduling time of a vehicle at a time interval, and then controlling whether the vehicle runs on a bus line; secondly, the vehicle semi-automatically acquires time according to a preset scheduling schedule, namely, a corresponding scheduling schedule is set on the bus, and then the vehicle acquires information such as departure time in the scheduling schedule; and thirdly, the driver knows the departure time point on the driving line of the driver to control departure. However, the phenomena of large intervals, small intervals, overlong waiting time of passengers, no-load of vehicles, full load of vehicles and the like often occur in bus operation, and actually, the phenomena of insufficient or excessive transport capacity, low satisfaction degree of passengers and the like caused by unreasonable transport capacity resource allocation of buses are caused, and the bus scheduling needs to be configured through reasonable resource allocation. The design of the bus scheduling list depends on the experience of a dispatcher, and the scheduling result is difficult to ensure in the aspects of operation efficiency and the like. Therefore, designing a bus scheduling method capable of improving the operation efficiency becomes a technical problem to be solved urgently by technical personnel in the field.
Disclosure of Invention
The embodiment of the application provides a method and a device for updating a schedule of bus dispatching, which can calculate the number of departure shifts and time intervals in corresponding time periods by acquiring passenger flow data and line scheduling parameters, so as to update the schedule of bus dispatching.
In a first aspect, an embodiment of the present application provides a method for updating a schedule of a bus, including:
acquiring passenger flow data P (i) on a preset line and corresponding line scheduling parameters in a preset time period, wherein the line scheduling parameters comprise a maximum full load rate L, line vehicle allocation and vehicle checking number N (i) and uplink and downlink departure time; wherein i is a corresponding time period sequence number;
calculating the number of departure shifts in the preset time period according to a shift calculation formula, wherein the shift calculation formula comprises the following steps: ttip (i)/(n (i) × L), where ttip (i) takes an integer;
calculating the time interval between each departure shift in the preset time period according to a time interval calculation formula, wherein the time interval formula comprises the following steps: wherein, ttip (i) represents the number of required shifts in a preset time period, int (i) represents a time interval, and i (i) represents the ith preset time period;
and updating a bus scheduling schedule according to the uplink and downlink departure time and the time interval, and displaying the bus scheduling schedule.
Further, the line scheduling parameters further include a maximum shift interval maxi (i);
after the calculating the time interval between each departure shift in the preset time period according to the time interval calculation formula, the method further comprises the following steps:
judging whether the time interval is greater than the maximum shift interval or not, if so, taking the maximum shift interval as a corresponding time interval, and if not, updating a bus scheduling schedule according to the uplink and downlink departure time and the time interval;
if the remaining time of the corresponding preset time interval is greater than the maximum departure interval, performing an operation of adding one to the number of shift trip (i);
the predicted time interval is calculated according to a time interval calculation formula, wherein the time interval calculation formula comprises: i (i) '(i) ═ int (i) × trip (i), wherein i (i)' is the prediction period.
Further, the uplink and downlink departure time includes an uplink departure time start (i), and correspondingly, the updating of the bus shift schedule according to the uplink and downlink departure time and the time interval includes:
inputting the time of departure of the uplink and the downlink and the prediction time interval into a time calculation formula to update a bus scheduling schedule, wherein the time calculation formula comprises the following steps: starttime (i +1) ═ starttime (i) + i (i)'.
Further, the passenger flow data includes predicted passenger flow data, and the predicted passenger flow data is obtained through the following steps:
acquiring historical passenger flow data of each operation bus number on a preset line at preset time, wherein the historical passenger flow data comprises the number of passengers getting on the bus;
and inputting the historical passenger flow data into the predicted passenger flow data obtained by calculation of the radial basis function neural network algorithm.
Further, after obtaining the historical passenger flow data of each operation bus number on the preset route at the preset time, the method further includes:
acquiring time information corresponding to historical passenger flow data, wherein the time information comprises working day information, holiday information and weekend day information;
acquiring weather information corresponding to time information, wherein the weather information comprises temperature information and humidity information, and is updated every 4 hours;
correspondingly, the step of inputting the historical passenger flow data into the predicted passenger flow data calculated by the radial basis function neural network algorithm includes:
and inputting the historical passenger flow data, the time information corresponding to the historical passenger flow data and the weather information corresponding to the time information into the predicted passenger flow data obtained by calculation of the radial basis function neural network algorithm.
Furthermore, a binocular depth sensor passenger flow instrument is arranged on the operation bus number and used for counting passenger flow data corresponding to the operation bus number.
Further, the time interval in the preset time period comprises half an hour; the passenger flow data P (i) comprises boarding passenger flow data P (up, i);
correspondingly, the shift calculation formula further includes: ttip (i) ═ P (up, i)/(n (i) × L).
In a second aspect, an embodiment of the present application provides a schedule updating apparatus for a bus, including:
an acquisition module: the system comprises a data acquisition module, a data acquisition module and a data transmission module, wherein the data acquisition module is used for acquiring passenger flow data P (i) on a preset line and corresponding line scheduling parameters in a preset time period, and the line scheduling parameters comprise a maximum full load rate L, line vehicle allocation checking number N (i) and uplink and downlink departure time; wherein i is a corresponding time period sequence number;
a first calculation module: the departure shift number in the preset time period is calculated according to a shift calculation formula, wherein the shift calculation formula comprises the following steps: ttip (i)/(n (i) × L), where ttip (i) takes an integer;
a second calculation module: the time interval calculation method is used for calculating the time interval between each departure shift in the preset time period according to a time interval calculation formula, and the time interval formula comprises the following steps: wherein, ttip (i) represents the number of required shifts in a preset time period, int (i) represents a time interval, and i (i) represents the ith preset time period;
an update module: and the bus scheduling system is used for updating the bus scheduling schedule according to the uplink and downlink departure time and the time interval and displaying the bus scheduling schedule.
In a third aspect, an embodiment of the present application provides an electronic device, including:
a memory and one or more processors;
the memory for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors implement the method for updating the schedule of buses according to the first aspect.
In a fourth aspect, embodiments of the present application provide a storage medium containing computer-executable instructions for performing the method for updating a schedule of a bus as described in the first aspect when executed by a computer processor.
According to the method and the device, the number of departure shifts and the time interval of the corresponding time period are calculated by obtaining the passenger flow data and the line scheduling parameters, and the update of the bus scheduling schedule is realized by combining the uplink and downlink departure times and the time interval.
Drawings
Fig. 1 is a flowchart of a method for updating a schedule of a bus according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating a process for obtaining predicted passenger flow data according to an embodiment of the present disclosure;
FIG. 3 is a schematic flow chart illustrating data acquisition of passenger flow influencing factors according to an embodiment of the present disclosure;
fig. 4 is a schematic flow chart illustrating the cumulative determination of the number of departure shifts according to the embodiment of the present application;
FIG. 5 is a schematic diagram of a display of an updated shift schedule provided by an embodiment of the present application;
fig. 6 is a schematic structural diagram of a schedule updating apparatus for buses according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
According to the bus scheduling schedule updating method, the number of departure shifts and the time interval of corresponding time periods are calculated by obtaining the passenger flow data and the line scheduling parameters, and the bus scheduling schedule is updated by combining the uplink and downlink departure times and the time interval. The prior art adopts a mode that the vehicle semi-automatically acquires time according to a preset scheduling schedule and acquires scheduling time according to preset bound time, and the mode easily causes the phenomena of large interval, small interval, overlong waiting time of passengers, no-load vehicle, full load vehicle and the like in bus operation, so that the transport capacity resources of the bus cannot be reasonably configured effectively, and the passenger satisfaction is low. Based on the method, the rationality of scheduling time arrangement is improved through the method for updating the scheduling schedule of the bus, and the rationality of bus transportation capacity resource allocation is also improved.
Fig. 1 is a flowchart of a method for updating a schedule of a bus according to an embodiment of the present disclosure, where the method for updating a schedule of a bus according to the present disclosure may be executed by a schedule updating device of a bus, the schedule updating device of a bus may be implemented in a software and/or hardware manner, and the schedule updating device of a bus may be formed by two or more physical entities or may be formed by one physical entity. Generally speaking, the schedule updating device of the public transport vehicle can be a computer, a mobile phone, a tablet or a background server, etc.
The following description will be given taking the background server as an example of an apparatus for executing the schedule updating method for buses. Referring to fig. 1, the method for updating the schedule of the public transport vehicle specifically includes:
s101: acquiring passenger flow data P (i) on a preset line and corresponding line scheduling parameters in a preset time period, wherein the line scheduling parameters comprise a maximum full load rate L, line vehicle allocation and vehicle checking number N (i) and uplink and downlink departure time; where i is the corresponding time period number.
In this step, the passenger flow data in this embodiment may be historical passenger flow data, or passenger flow data in the current time period, or predicted passenger flow data, mainly for obtaining basic data for subsequent calculation; more preferably, in the present embodiment, the passenger flow prediction data is used, that is, the prediction of the passenger flow in a certain time is performed by an algorithm. The reference to the future shift schedule is realized by prediction data.
The method further comprises a data preprocessing step, wherein time intervals are sorted from small to large, the time interval data are clarified according to the first and last time of the uplink and downlink, the time intervals exceeding the first and last time are subjected to data extraction, and the number of people after the last shift is summarized to the last time. The first and last shift time is the time specified by the public transport company, but in actual operation, the bus can be dispatched beyond the time, the bus is in an operation state, and some data of the passengers on and off is generated, so that the data is processed.
Further, as shown in fig. 2, fig. 2 is a schematic flow chart of obtaining predicted passenger flow data according to an embodiment of the present application, where the passenger flow data includes predicted passenger flow data, and the predicted passenger flow data is obtained by the following steps:
s1011: the method comprises the steps of obtaining historical passenger flow data of each operation bus number on a preset line at preset time, wherein the historical passenger flow data comprises the number of passengers getting on the bus.
Specifically, the passenger flow data of 3 buses between 7 o 'clock and 7 o' clock in the morning of 4/month and 3 (friday) in 2020 is acquired, and the acquired data is mainly the getting-on data, that is, the data of all the 3 buses taken in the time period. The significance of obtaining the specific time interval is mainly to predict the passenger flow data in the same time interval.
Besides the influence factors of the time periods, external influence factors such as weather and weekend days need to be considered, and the accuracy and the scientificity of the model are increased by adding various factor influence settings.
Fig. 3 is a schematic flow chart of data acquisition of the passenger flow influencing factors according to the embodiment of the present application, and as shown in fig. 3, after step S1011, before step S1012, the following steps are further included:
s1011 a: and acquiring time information corresponding to the historical passenger flow data, wherein the time information comprises working day information, holiday information and weekend day information.
S1011 b: and acquiring weather information corresponding to the time information, wherein the weather information comprises temperature information and humidity information, and the weather information is updated every 4 hours.
All the above steps are to obtain the factor conditions affecting the passenger flow, and in the actual operation, the size of the passenger flow is affected by the factors such as weather and date. When different factors can have different influences on the passenger flow, in particular implementation, when the number of people going out on a sunny day is reduced in rainy days, the number of corresponding passenger flows is also reduced. During working days, the number of people going out on duty peak periods is greatly increased compared with the number of people going out on weekends and holidays, so that the future passenger flow can be accurately predicted by designing more detailed passenger flow influence factors. In addition to the above factors, other factors affecting passenger flow may be set, and all the factors are provided to the station operator for the convenience of the station operator in the train number route planning and the vehicle dispatch.
More preferably, the weather information is updated every 4 hours. There is some inaccuracy in weather measurements in units of days, and when the conditions of a certain day are shown to be clear throughout the day, but when it is raining for a certain period of time, such weather conditions are usually shown to be clear. Sometimes the traffic data will cause the operators to be questioned if the condition of intermediate rain is not reflected in the result, because the traffic volume will suddenly decrease in a certain period of time. Therefore, in the present embodiment, the weather information update is set to be performed every 4 hours to ensure the accuracy of the information.
More preferably, a binocular depth sensor passenger flow instrument is arranged on the operation bus number and used for counting passenger flow data of the corresponding operation bus number. By adopting the binocular passenger flow instrument, the constraint of the data integrity by the equipment accuracy is reduced, the data monitoring accuracy is improved, and a more accurate prediction result is obtained in an auxiliary manner.
S1012: and inputting the historical passenger flow data, the time information corresponding to the historical passenger flow data and the weather information corresponding to the time information into the predicted passenger flow data obtained by calculation of the radial basis function neural network algorithm.
And cleaning, complementing and converting the above mentioned features to form a feature set, and establishing an RBF algorithm model to realize the prediction of passenger flow data of the next several days. The radial basis function neural network algorithm in this embodiment is also an RBF algorithm, and the RBF neural network is a three-layer neural network including an input layer, a hidden layer, and an output layer. The transformation from the input space to the hidden layer space is non-linear, while the transformation from the hidden layer space to the output layer space is linear. The acquired historical passenger flow data, the time information corresponding to the historical passenger flow data and the weather information corresponding to the time information are sent to the constructed radial basis function neural network for learning, and then the passenger flow data on a certain day in the future can be predicted.
S102: calculating the number of departure shifts in the preset time period according to a shift calculation formula, wherein the shift calculation formula comprises the following steps: ttip (i)/(n (i) × L), where ttip (i) takes an integer.
S103: calculating the time interval between each departure shift in the preset time period according to a time interval calculation formula, wherein the time interval formula comprises the following steps: wherein, ttip (i) represents the number of required shifts within a preset time period, int (i) represents a time interval, and i (i) represents the ith preset time period.
The number of departure shifts and the time interval of each departure shift time within a preset time period are calculated through the steps S102 and S103, and the departure shifts and the departure time intervals are calculated by combining actual line scheduling parameters, so that the scheduling schedule is dynamically adjusted.
S104: and updating a bus scheduling schedule according to the uplink and downlink departure time and the time interval, and displaying the bus scheduling schedule.
Updating the existing scheduling data according to the data obtained by calculation in the step S102 and the step S103, so as to obtain a more optimized scheduling schedule which better meets the actual requirements.
In this embodiment, the line scheduling parameter further includes a maximum shift interval maxi (i).
As shown in fig. 4, fig. 4 is a schematic flowchart of the process of accumulating and judging the number of departure shifts provided in the embodiment of the present application, and after the calculating the time interval between departure shifts in the preset time period according to the time interval calculation formula, that is, after step S103, the method further includes:
s103 a: and judging whether the time interval is greater than the maximum shift interval or not, if so, taking the maximum shift interval as a corresponding time interval, and if not, updating the bus scheduling schedule according to the uplink and downlink departure time and the time interval.
S103 b: and if the remaining time of the corresponding preset time interval is greater than the maximum departure interval, adding one to the number of shift trip (i).
S103 c: the predicted time interval is calculated according to a time interval calculation formula, wherein the time interval calculation formula comprises: i (i) '(i) ═ int (i) × trip (i), wherein i (i)' is the prediction period.
In this embodiment, the maximum shift interval is maximum time interval data set by the government to ensure city operation, and is unreasonable if the departure time interval set by the bus operation company exceeds the maximum shift interval; for example, the maximum time interval for bus departure set by the guangzhou city government is 12 minutes, but it is known from the calculated data that the reasonable time interval for departure in a specific time period on the corresponding line is 20 minutes, and it can be known that the time interval for departure exceeds the maximum time interval, then the calculation cannot be performed according to the calculated time interval for departure, because the company should operate according to the specifications of the local government. Therefore, in the embodiment, whether the time strategy is reasonable or not is judged by setting the maximum time interval. Government strategy information is added to the strategy at the shift interval to increase the rationality of the strategy.
Further, the uplink and downlink departure time includes an uplink departure time start (i), and correspondingly, the updating of the bus shift schedule according to the uplink and downlink departure time and the time interval includes:
inputting the time of departure of the uplink and the downlink and the prediction time interval into a time calculation formula to update a bus scheduling schedule, wherein the time calculation formula comprises the following steps: starttime (i +1) ═ starttime (i) + i (i)'.
FIG. 5 is a schematic diagram of a display of an updated shift schedule provided by an embodiment of the present application; as shown in fig. 5, time-no refers to the period number, pre-passers refers to the predicted passenger flow number, pre-timeintenterval refers to the time interval, and recimmend-tris refers to the departure times. The data in fig. 5 is the result of the updated data, and the start time before updating is … points 6, 6 and a half points 6, 7 and 7, and after updating, the data is adaptively adjusted, which can better meet the actual requirement; more reasonable bus transport capacity arrangement is carried out.
According to the method and the device, the number of departure shifts and the time interval of the corresponding time period are calculated by obtaining the passenger flow data and the line scheduling parameters, and the update of the bus scheduling schedule is realized by combining the uplink and downlink departure times and the time interval.
On the basis of the foregoing embodiment, fig. 6 is a schematic structural diagram of a schedule updating apparatus for buses according to an embodiment of the present application. Referring to fig. 6, the schedule updating apparatus for buses provided in this embodiment specifically includes:
the acquisition module 21: the system comprises a data acquisition module, a data acquisition module and a data transmission module, wherein the data acquisition module is used for acquiring passenger flow data P (i) on a preset line and corresponding line scheduling parameters in a preset time period, and the line scheduling parameters comprise a maximum full load rate L, line vehicle allocation checking number N (i) and uplink and downlink departure time; wherein i is a corresponding time period sequence number;
the first calculation module 22: the departure shift number in the preset time period is calculated according to a shift calculation formula, wherein the shift calculation formula comprises the following steps: ttip (i)/(n (i) × L), where ttip (i) takes an integer;
the second calculation module 23: the time interval calculation method is used for calculating the time interval between each departure shift in the preset time period according to a time interval calculation formula, and the time interval formula comprises the following steps: wherein, ttip (i) represents the number of required shifts in a preset time period, int (i) represents a time interval, and i (i) represents the ith preset time period;
the update module 24: and the bus scheduling system is used for updating the bus scheduling schedule according to the uplink and downlink departure time and the time interval and displaying the bus scheduling schedule.
The bus scheduling schedule updating device provided by the embodiment of the application can be used for executing the bus scheduling schedule updating method provided by the embodiment, and has corresponding functions and beneficial effects.
According to the method and the device, the number of departure shifts and the time interval of the corresponding time period are calculated by obtaining the passenger flow data and the line scheduling parameters, and the update of the bus scheduling schedule is realized by combining the uplink and downlink departure times and the time interval.
Fig. 7 is a schematic structural diagram of an electronic device provided in an embodiment of the present application, and referring to fig. 7, the electronic device includes: a processor 31, a memory 32, a communication module 33, an input device 34, and an output device 35. The number of processors 31 in the electronic device may be one or more, and the number of memories 32 in the electronic device may be one or more. The processor 31, the memory 32, the communication module 33, the input device 34 and the output device 35 of the electronic apparatus may be connected by a bus or other means.
The memory 32 is a computer-readable storage medium, and can be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the schedule updating method for buses according to any embodiment of the present application (for example, the obtaining module 21, the first calculating module 22, the second calculating module 23, and the updating module 24 in the schedule updating apparatus for buses). The memory 32 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 for at least one function; the storage data area may store data created according to use of the device, and the like. Further, the memory 32 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory may further include memory located remotely from the processor, and these remote memories may be connected to the device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The communication module 33 is used for data transmission.
The processor 31 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 32, that is, the method for updating the schedule of the public transportation vehicles is realized.
The input device 34 may be used to receive entered numeric or character information and to generate key signal inputs relating to user settings and function controls of the apparatus. The output device 35 may include a display device such as a display screen.
The electronic equipment can be used for executing the method for updating the schedule of the bus, and has corresponding functions and beneficial effects.
The embodiment of the present application further provides a storage medium containing computer executable instructions, which when executed by the computer processor 31, is configured to execute a schedule updating method for a bus, where the schedule updating method for a bus includes:
acquiring passenger flow data P (i) on a preset line and corresponding line scheduling parameters in a preset time period, wherein the line scheduling parameters comprise a maximum full load rate L, line vehicle allocation and vehicle checking number N (i) and uplink and downlink departure time; wherein i is a corresponding time period sequence number;
calculating the number of departure shifts in the preset time period according to a shift calculation formula, wherein the shift calculation formula comprises the following steps: ttip (i)/(n (i) × L), where ttip (i) takes an integer;
calculating the time interval between each departure shift in the preset time period according to a time interval calculation formula, wherein the time interval formula comprises the following steps: wherein, ttip (i) represents the number of required shifts in a preset time period, int (i) represents a time interval, and i (i) represents the ith preset time period;
and updating a bus scheduling schedule according to the uplink and downlink departure time and the time interval, and displaying the bus scheduling schedule.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in a first computer system in which the program is executed, or may be located in a different second computer system connected to the first computer system through a network (such as the internet). The second computer system may provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media residing in different locations, e.g., in different computer systems connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors 31.
Of course, the storage medium containing the computer-executable instructions provided in the embodiments of the present application is not limited to the above-mentioned method for updating the schedule of buses, and may also perform the relevant operations in the method for updating the schedule of buses provided in any embodiments of the present application.
The bus schedule updating device, the storage medium and the electronic device provided in the above embodiments may execute the bus schedule updating method provided in any embodiment of the present application, and refer to the bus schedule updating method provided in any embodiment of the present application without detailed technical details in the above embodiments.
The foregoing is considered as illustrative of the preferred embodiments of the invention and the technical principles employed. The present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.
Claims (10)
1. A method for updating a schedule of a bus is characterized by comprising the following steps:
acquiring passenger flow data P (i) on a preset line and corresponding line scheduling parameters in a preset time period, wherein the line scheduling parameters comprise a maximum full load rate L, line vehicle allocation and vehicle checking number N (i) and uplink and downlink departure time; wherein i is a corresponding time period sequence number;
calculating the number of departure shifts in the preset time period according to a shift calculation formula, wherein the shift calculation formula comprises the following steps: ttip (i)/(n (i) × L), where ttip (i) takes an integer;
calculating the time interval between each departure shift in the preset time period according to a time interval calculation formula, wherein the time interval formula comprises the following steps: wherein, ttip (i) represents the number of required shifts in a preset time period, int (i) represents a time interval, and i (i) represents the ith preset time period;
and updating a bus scheduling schedule according to the uplink and downlink departure time and the time interval, and displaying the bus scheduling schedule.
2. The method of updating a schedule of buses according to claim 1, where the line scheduling parameters further include the maximum shift interval maxi (i);
after the calculating the time interval between each departure shift in the preset time period according to the time interval calculation formula, the method further comprises the following steps:
judging whether the time interval is greater than the maximum shift interval or not, if so, taking the maximum shift interval as a corresponding time interval, and if not, updating a bus scheduling schedule according to the uplink and downlink departure time and the time interval;
if the remaining time of the corresponding preset time interval is greater than the maximum departure interval, performing an operation of adding one to the number of shift trip (i);
the predicted time interval is calculated according to a time interval calculation formula, wherein the time interval calculation formula comprises: i (i) '(i) ═ int (i) × trip (i), wherein i (i)' is the prediction period.
3. The method as claimed in claim 2, wherein the uplink and downlink departure time includes an uplink departure time start (i), and correspondingly, the updating the bus schedule according to the uplink and downlink departure time and the time interval includes:
inputting the time of departure of the uplink and the downlink and the prediction time interval into a time calculation formula to update a bus scheduling schedule, wherein the time calculation formula comprises the following steps: starttime (i +1) ═ starttime (i) + i (i)'.
4. The method for updating a schedule of buses according to claim 1, where the traffic data includes predicted traffic data, which is obtained by the steps of:
acquiring historical passenger flow data of each operation bus number on a preset line at preset time, wherein the historical passenger flow data comprises the number of passengers getting on the bus;
and inputting the historical passenger flow data into the predicted passenger flow data obtained by calculation of the radial basis function neural network algorithm.
5. The method for updating the schedule of buses according to claim 4, wherein after obtaining the historical passenger flow data of each bus operating time on the preset route at the preset time, the method further comprises:
acquiring time information corresponding to historical passenger flow data, wherein the time information comprises working day information, holiday information and weekend day information;
acquiring weather information corresponding to time information, wherein the weather information comprises temperature information and humidity information, and is updated every 4 hours;
correspondingly, the step of inputting the historical passenger flow data into the predicted passenger flow data calculated by the radial basis function neural network algorithm includes:
and inputting the historical passenger flow data, the time information corresponding to the historical passenger flow data and the weather information corresponding to the time information into the predicted passenger flow data obtained by calculation of the radial basis function neural network algorithm.
6. The method for updating the schedule of buses according to claim 4, wherein the operating bus number is provided with a binocular depth sensor passenger flow instrument, and the binocular depth sensor passenger flow instrument is used for counting the passenger flow data of the corresponding operating bus number.
7. The method for updating the schedule of buses according to any of the claims 1-6, characterized in that the time interval in the preset time period comprises half an hour; the passenger flow data P (i) comprises boarding passenger flow data P (up, i);
correspondingly, the shift calculation formula further includes: ttip (i) ═ P (up, i)/(n (i) × L).
8. The utility model provides a schedule updating device of public transit vehicle which characterized in that includes:
an acquisition module: the system comprises a data acquisition module, a data acquisition module and a data transmission module, wherein the data acquisition module is used for acquiring passenger flow data P (i) on a preset line and corresponding line scheduling parameters in a preset time period, and the line scheduling parameters comprise a maximum full load rate L, line vehicle allocation checking number N (i) and uplink and downlink departure time; wherein i is a corresponding time period sequence number;
a first calculation module: the departure shift number in the preset time period is calculated according to a shift calculation formula, wherein the shift calculation formula comprises the following steps: ttip (i)/(n (i) × L), where ttip (i) takes an integer;
a second calculation module: the time interval calculation method is used for calculating the time interval between each departure shift in the preset time period according to a time interval calculation formula, and the time interval formula comprises the following steps: wherein, ttip (i) represents the number of required shifts in a preset time period, int (i) represents a time interval, and i (i) represents the ith preset time period;
an update module: and the bus scheduling system is used for updating the bus scheduling schedule according to the uplink and downlink departure time and the time interval and displaying the bus scheduling schedule.
9. An electronic device, comprising:
a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method for updating a schedule for a bus as set forth in any of claims 1-7.
10. A storage medium containing computer-executable instructions for performing the method for updating a schedule of a bus as set forth in any of claims 1-7 when executed by a computer processor.
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Application publication date: 20200922 |