CN112101751A - Public transport optimization method, system, device and storage medium - Google Patents
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Abstract
The invention discloses a public transport optimization method, a system, a device and a storage medium, wherein the method comprises the following steps: the method comprises the steps of obtaining bus travel demands of passengers in a preset time period, wherein the bus travel demands comprise getting-on stops, getting-off stops and the number of the passengers; acquiring an optimal scheduling strategy according to the collected bus travel demands, wherein the optimal scheduling strategy comprises the types of running vehicles, the departure frequency and a passenger transfer scheme of different road sections; and recombining and adjusting the carriages of the running vehicles on different road sections according to the optimal scheduling strategy. The invention can effectively reduce the waiting time of passengers and the bus operation cost by flexibly adjusting the vehicle capacity, overcomes the problems of low efficiency and resource waste of maintaining the traditional fixed bus service when the passenger demand is lower, has practical popularization value and can be widely applied to the technical field of intelligent transportation.
Description
Technical Field
The invention relates to the technical field of intelligent transportation, in particular to a public transportation optimization method, a public transportation optimization system, a public transportation optimization device and a public transportation optimization storage medium.
Background
Most of the existing public transport systems depend on vehicles with fixed capacity and cannot adapt to the space-time change of the traffic travel demand. This mismatch between vehicle capacity and passenger travel demand can lead to passenger's latency overlength, and public transit quality of service descends to and the phenomenon that the full load rate is too low and empty to drive appears, causes great operating cost, has wasted a large amount of resources.
The noun explains:
capsule type carriage: each carriage can independently run, and can also increase and decrease according to the actual demand condition of passenger flow, and when a plurality of capsule type carriages are spliced into a whole, the operation is synchronous, the operation energy consumption is lower than that of a plurality of single carriages in independent running, and the road occupation is smaller.
Capsule type public transport vehicle: according to the requirements, the number of the buses in the capsule type carriage can be increased or decreased.
Disclosure of Invention
In order to solve one of the above technical problems, the present invention aims to provide a flexible public transportation service optimization method, system, device and storage medium based on a capsule type carriage, which flexibly adjusts the vehicle capacity and departure frequency according to the actual travel demand of passengers, reduces the travel time of passengers, and saves the bus operation cost.
The technical scheme adopted by the invention is as follows:
a method of mass transit optimization comprising the steps of:
the method comprises the steps of obtaining bus travel demands of passengers in a preset time period, wherein the bus travel demands comprise getting-on stops, getting-off stops and the number of the passengers;
acquiring an optimal scheduling strategy according to the collected bus travel demands, wherein the optimal scheduling strategy comprises the types of running vehicles, the departure frequency and a passenger transfer scheme of different road sections;
carrying out recombination adjustment on the carriage of the running vehicle at different road sections according to the optimal scheduling strategy;
the optimal scheduling strategy is a scheduling strategy for realizing the minimum total system cost of the public transportation system.
Further, the public transit trip demand of obtaining passenger in the preset time quantum includes:
and aiming at the time period needing to be optimized, integrating and obtaining the travel traffic volume of the passengers between the stations in the time period so as to obtain the bus travel demand of the passengers.
Further, the obtaining of the optimal scheduling strategy according to the collected bus travel demands includes:
determining the total system cost according to the bus travel demand, wherein the total system cost comprises system operation cost and passenger travel time cost, and the passenger travel time cost comprises waiting time, riding time and getting on and off time;
determining a constraint condition that the total transport capacity of the running vehicles on each road section is not less than the travel demand;
determining a constraint condition of compartment quantity conservation;
determining a constraint condition that the bus travel demands of all passengers are served;
determining that only one type of the running vehicles exists in each road section, and the number of carriages of the running vehicles in each road section does not exceed a constraint condition of capacity limit;
and obtaining an optimal scheduling strategy according to the total system cost and all the constraint conditions.
Further, the calculation formula of the total cost of the system is as follows:
wherein, FMTSRepresents the total cost of the system;
a collection of sites is represented that is,
i, j, k, l denotes a site, i, j, k,
a set of the number of cars is represented,
s represents the number of cars
CsThe method comprises the following steps of (1) representing the operation cost of unit distance when a capsule type bus with the number of carriages being s is adopted; x is the number ofklsThe number of the vehicles driven by the capsule type public transport vehicle with the number of the carriages s from the station k to the station l is represented as a continuous variable; dklRepresents the distance between site k to site l; ctRepresents the time cost per hour of the passenger; y isijklThe number of passengers from the departure station i to the arrival station j who take the capsule type public transport vehicles from the station k to the station l is represented by a continuous variable; v represents the running speed of the capsule type bus; beta represents the cost of a single transfer of a single passenger.
Further, the constraint condition that the total transport capacity of the running vehicles on each road section is not less than the travel demand is as follows:
the constraint conditions of the number conservation of the carriages are as follows:
wherein q isijRepresenting the passenger travel demand from station i to station j.
Further, the constraint condition that the bus travel demands of all the passengers are served is as follows:
wherein q isijRepresenting the passenger travel demand from station i to station j.
Further, the constraint condition that the number of cars of the running vehicle per road section does not exceed a capacity limit is as follows:
wherein e isklsIndicating whether the number of the carriages of the capsule type public transport from the station k to the station l is s, GklsAnd the maximum number of the trains which can be driven when the capsule type bus with the number of the carriages being s is adopted on the road section kl is represented.
The other technical scheme adopted by the invention is as follows:
a mass transit optimization system comprising:
the data acquisition module is used for acquiring bus travel demands of passengers in a preset time period, wherein the bus travel demands comprise getting-on stops, getting-off stops and the number of the passengers;
the scheduling strategy module is used for acquiring an optimal scheduling strategy according to the collected bus travel demands, wherein the optimal scheduling strategy comprises the types of running vehicles, the departure frequency and the passenger transfer schemes of different road sections;
carrying out recombination adjustment on the carriage of the running vehicle at different road sections according to the optimal scheduling strategy;
the optimal scheduling strategy is a scheduling strategy for realizing the minimum total system cost of the public transportation system.
The other technical scheme adopted by the invention is as follows:
a mass transit optimization device, comprising:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method described above.
The other technical scheme adopted by the invention is as follows:
a storage medium having stored therein processor-executable instructions for performing the method as described above when executed by a processor.
The invention has the beneficial effects that: the capsule type bus capacity adjusting device is based on the capsule type carriage, can flexibly adjust the capacity of the bus, effectively reduce the waiting time of passengers, reduce the bus operation cost, overcome the problems of low efficiency and resource waste of maintaining the traditional fixed bus service when the demand of the passengers is lower, and has practical popularization value.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description is made on the drawings of the embodiments of the present invention or the related technical solutions in the prior art, and it should be understood that the drawings in the following description are only for convenience and clarity of describing some embodiments in the technical solutions of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of a flexible optimization model operation mode of public transportation service based on capsule type carriages according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating the effect of a flexible optimization model for public transportation service based on capsule type carriages according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a bus stop distribution according to an embodiment of the present invention;
fig. 4 is a flow chart diagram of a public transportation optimization method according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
Referring to fig. 1 and 4, the embodiment provides a flexible public transportation service optimization method based on capsule type carriages, which can meet travel demands of different passenger flow rates by flexibly adjusting the number and departure frequency of the capsule type carriages. The capsule type bus runs in a public transport system according to a scheduling strategy, the minimum total system cost is taken as an optimization target, the types, departure frequency and passenger transfer strategies of the capsule type buses selected among different road sections are determined according to a model solving result, and the flexible bus operation steps include but are not limited to the following steps:
and S1, collecting the bus travel demands of the passengers in a preset time period (including information such as the number of passengers at all the boarding and alighting stations).
In the step, the passengers initiate bus travel demands, the bus travel demands comprise a starting station and a terminal station, and the total travel demands in the time interval, namely the travel traffic volume of the passengers between the stations, are integrated according to the specific time interval to be optimized.
In this embodiment, a mass transit system containing 10 critical bus stops was selected, as shown in fig. 2 and 3. The method comprises the steps of obtaining hour traffic travel demands OD of 10 stations by collecting passenger travel demand data of each station, and carrying out model solution by combining actual parameter data provided by a Goods map, a NEXT website, a Guangzhou third bus group and the like.
S2, according to the collected passenger travel demand data between the stations, the flexible public transport service optimization model determines the types of the running vehicles, the departure frequency and the passenger transfer schemes of the capsule type buses on different road sections, gives an optimal scheduling strategy and achieves the minimum total system cost of the bus system.
Wherein, the step S2 specifically includes steps S21-S25:
and S21, according to the travel demand of the passengers, determining that the aim is to minimize the total system cost, including the system operation cost and the travel time cost of the passengers, wherein the time cost of the passengers consists of three parts, namely waiting time, riding time and getting on and off time.
And S22, determining the constraint condition that the total transport capacity of the capsule type bus on each road section is not less than the travel demand.
And S23, determining the constraint condition of the conservation of the number of the carriages, namely that the number of the carriages leaving a certain station in unit time is equal to the number of the carriages arriving at the station in unit time.
And S24, determining the constraint condition that the requirements of all passengers are served.
And S25, determining that only one type of capsule type buses exist in each road section, and the number of capsule type bus rows in each road section does not exceed the constraint condition of capacity limit.
The goal of minimizing the total system cost in step S21 is:
the constraint condition that the total transport capacity of the capsule type bus on each road section is not less than the travel demand in the step S22 is as follows:
the constraint conditions for the conservation of the number of cars in step S23 are:
the constraint in step S24 that all passenger requirements are serviced is:
in the step S25, only one type of capsule type bus exists in each road segment, and the constraint condition that the number of capsule type bus columns in each road segment does not exceed the capacity limit is as follows:
in the above series of computational equations, the relevant parameters define: fMTSRepresents the system cost;
a collection of sites is represented that is,
i, j, k, l denotes a site, i, j, k,
a set of the number of cars is represented,
s represents the number of cars
CsThe method comprises the following steps of (1) representing the operation cost of unit distance when a capsule type bus with the number of carriages being s is adopted; x is the number ofklsThe number of vehicles driven by the capsule type bus with the number of cars s from the station k to the station l is represented as a continuous variable; dklRepresents the distance between site k to site l; ctRepresents the time cost per hour of the passenger; y isijklThe number of passengers from the departure station i to the arrival station j taking the capsule type public transport from the station k to the station l is represented by a continuous variable; v represents the running speed of the capsule type bus; beta represents the cost of a single transfer of a single passenger; q. q.siiRepresenting passenger travel demand from station i to station j; e.g. of the typeklsIndicating whether the number of the carriages of the capsule type bus which is started from the station k to the station l is s; gklsAnd the maximum number of the trains which can be driven when the capsule type bus with the number of the carriages being s is adopted on the road section kl is represented.
And S3, the system issues the obtained optimal scheduling strategy to the capsule type public transportation system. The capsule type bus stops at bus stations according to a scheduling strategy, passengers get on or off the bus, and the carriages are separated or recombined automatically at each station according to a scheduling instruction so as to respond to the traveling demands of the passengers.
Compared with the traditional fixed-capacity bus system and the private car system, the flexible public transportation service optimization mode based on the capsule type carriage has obvious advantages. Wherein, the optimization effect is shown in the following table 1, which significantly reduces the operation cost of the system and the time cost of passengers.
TABLE 1 comparison of the optimization results of several operating systems in the examples
Where the revised system cost deducts the fixed free stream travel time (equal to the ride time cost of the private car system), which is independent of the optimal decision.
In summary, compared with the prior art, the traffic optimization method of the embodiment has the following beneficial effects:
(1) compare with traditional public transit mode, this embodiment can reassemble fast and adjust the carriage quantity of capsule type bus to adjustment vehicle capacity satisfies different passenger's trip demands. Through flexible adjustment of the vehicle capacity, the invention can effectively reduce the waiting time of passengers, reduce the bus operation cost and overcome the problems of low efficiency and resource waste of maintaining the traditional fixed bus service when the passenger demand is lower.
(2) Because each capsule type carriage is provided with an independent power system, compared with a private car, the capsule type car has higher flexibility, when a plurality of capsule type carriages are connected to form a capsule car fleet, the average running cost of each carriage is reduced, the road occupancy rate is lower, and the capsule type car is more suitable for running in urban congestion areas and expressway congestion areas, so that the energy utilization rate is improved, and traffic congestion is reduced.
The embodiment also provides a public transportation optimization system, including:
the data acquisition module is used for acquiring bus travel demands of passengers in a preset time period, wherein the bus travel demands comprise getting-on stops, getting-off stops and the number of the passengers;
the scheduling strategy module is used for acquiring an optimal scheduling strategy according to the collected bus travel demands, wherein the optimal scheduling strategy comprises the types of running vehicles, the departure frequency and the passenger transfer schemes of different road sections;
carrying out recombination adjustment on the carriage of the running vehicle at different road sections according to the optimal scheduling strategy;
the optimal scheduling strategy is a scheduling strategy for realizing the minimum total system cost of the public transportation system.
The public transportation optimization system of the embodiment can execute the public transportation optimization method provided by the method embodiment of the invention, can execute any combination implementation steps of the method embodiment, and has corresponding functions and beneficial effects of the method.
The embodiment also provides a public transportation optimization device, which comprises:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method described above.
The public transportation optimization device of the embodiment can execute the public transportation optimization method provided by the method embodiment of the invention, can execute any combination implementation steps of the method embodiment, and has corresponding functions and beneficial effects of the method.
The present embodiments also provide a storage medium having stored therein processor-executable instructions, which when executed by a processor, are configured to perform the method as described above.
The embodiment also provides a storage medium, which stores instructions or programs capable of executing the public transportation optimization method provided by the embodiment of the method of the invention, and when the instructions or the programs are run, the steps can be implemented in any combination of the embodiment of the method, and the corresponding functions and the beneficial effects of the method are achieved.
It will be understood that all or some of the steps, systems of methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (10)
1. A method of mass transit optimization, comprising the steps of:
the method comprises the steps of obtaining bus travel demands of passengers in a preset time period, wherein the bus travel demands comprise getting-on stops, getting-off stops and the number of the passengers;
acquiring an optimal scheduling strategy according to the collected bus travel demands, wherein the optimal scheduling strategy comprises the types of running vehicles, the departure frequency and a passenger transfer scheme of different road sections;
carrying out recombination adjustment on the carriage of the running vehicle at different road sections according to the optimal scheduling strategy;
the optimal scheduling strategy is a scheduling strategy for realizing the minimum total system cost of the public transportation system.
2. The method for optimizing public transportation according to claim 1, wherein the obtaining of the bus travel demand of the passenger in the preset time period comprises:
and aiming at the time period needing to be optimized, integrating and obtaining the travel traffic volume of the passengers between the stations in the time period so as to obtain the bus travel demand of the passengers.
3. The method of claim 1, wherein the obtaining of the optimal scheduling strategy according to the collected bus travel demands comprises:
determining the total system cost according to the bus travel demand, wherein the total system cost comprises system operation cost and passenger travel time cost, and the passenger travel time cost comprises waiting time, riding time and getting on and off time;
determining a constraint condition that the total transport capacity of the running vehicles on each road section is not less than the travel demand;
determining a constraint condition of compartment quantity conservation;
determining a constraint condition that the bus travel demands of all passengers are served;
determining that only one type of the running vehicles exists in each road section, and the number of carriages of the running vehicles in each road section does not exceed a constraint condition of capacity limit;
and obtaining an optimal scheduling strategy according to the total system cost and all the constraint conditions.
4. A method as claimed in claim 3, wherein the total cost of the system is calculated by the formula:
wherein, FMTSRepresents the total cost of the system;
a collection of sites is represented that is,
i, j, k, l denote sites,
a set of the number of cars is represented,
s represents the number of cars
CsThe method comprises the following steps of (1) representing the operation cost of unit distance when a capsule type bus with the number of carriages being s is adopted; x is the number ofklsThe capsule type public transport vehicle with the number of cars s represents the driving vehicle from the station k to the station l as a continuous variableCounting; dklRepresents the distance between site k to site l; ctRepresents the time cost per hour of the passenger; y isijklThe number of passengers from the departure station i to the arrival station j who take the capsule type public transport vehicles from the station k to the station l is represented by a continuous variable; v represents the running speed of the capsule type bus; beta represents the cost of a single transfer of a single passenger.
5. The method for optimizing public transportation according to claim 4, wherein the constraint condition that the total capacity of the running vehicles on each road section is not less than the travel demand is as follows:
the constraint conditions of the number conservation of the carriages are as follows:
wherein q isijRepresenting the passenger travel demand from station i to station j.
6. The method of claim 4, wherein the constraint condition that the bus travel demand of all passengers is served is as follows:
wherein q isijRepresenting the passenger travel demand from station i to station j.
7. A mass transit optimization method as claimed in claim 4, wherein the constraint that the number of cars in the moving vehicle per road segment does not exceed a capacity limit is:
wherein e isklsIndicating whether the number of the carriages of the capsule type public transport from the station k to the station l is s, GklsAnd the maximum number of the trains which can be driven when the capsule type bus with the number of the carriages being s is adopted on the road section kl is represented.
8. A mass transit optimization system, comprising:
the data acquisition module is used for acquiring bus travel demands of passengers in a preset time period, wherein the bus travel demands comprise getting-on stops, getting-off stops and the number of the passengers;
the scheduling strategy module is used for acquiring an optimal scheduling strategy according to the collected bus travel demands, wherein the optimal scheduling strategy comprises the types of running vehicles, the departure frequency and the passenger transfer schemes of different road sections;
carrying out recombination adjustment on the carriage of the running vehicle at different road sections according to the optimal scheduling strategy;
the optimal scheduling strategy is a scheduling strategy for realizing the minimum total system cost of the public transportation system.
9. A mass transit optimization device, comprising:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement a method of mass transit optimization as claimed in any one of claims 1 to 7.
10. A storage medium having stored therein a program executable by a processor, wherein the program executable by the processor is adapted to perform the method of any one of claims 1-7 when executed by the processor.
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| CN113284361A (en) * | 2021-04-09 | 2021-08-20 | 中国二十冶集团有限公司 | Modular combined public transportation system |
| CN117217397A (en) * | 2023-10-26 | 2023-12-12 | 淮阴工学院 | Cloud data capsule type intelligent interaction device for buses and subways |
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