CN113935181A - Train simulation operation optimization system construction method based on matched passenger flow - Google Patents
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Abstract
The invention relates to a train simulation operation optimization system construction method based on matched passenger flow, which relates to the field of urban rail transit, aims to minimize the sum of passenger waiting time and urban rail transit operation cost, simulates train operation through a train simulation operation model, verifies the feasibility of a train scheduling operation scheme, obtains a feasible train scheduling operation scheme corresponding to a plurality of initial train number sequences, comprehensively evaluates the advantages and disadvantages of the train scheduling operation scheme through a plurality of analysis angles of passenger waiting time, urban rail transit operation cost, line section full load rate and train full load rate of each station, and selects an optimal train scheduling operation scheme, thereby realizing the feasibility of the train scheduling operation scheme and further optimizing the operation scheduling of rail transit lines.
Description
Technical Field
The invention relates to the field of urban rail transit, in particular to a method for constructing a train simulation operation optimization system based on passenger flow matching.
Background
The urban rail transit has the advantages of safety, high efficiency, convenience, reliability, environmental protection, low carbon and the like, and becomes an important transportation mode for the travel of urban residents. However, as the scale of the urban rail transit network is further and rapidly developed and expanded, various random factors and emergencies frequently interfere with train operation, and the problem of train operation safety faces challenges. In addition, since urban rail transit is generally characterized by simple routes, short headway, large passenger traffic volume, etc., the delay of any one train may become a large-scale delay, especially during peak hours, which may lead to a serious transportation capacity degradation problem. In addition, the detained passengers may enlarge the scale of delay spread, thereby disturbing the operation of the whole urban rail network and causing great trouble to passengers traveling on the rail. To avoid this, the operational schedule of the existing routes in rail traffic must be studied and optimized.
In addition, urban rail transit provides convenient trip mode for citizens, and has the characteristics of stable running speed and large transportation volume. With the continuous development of cities, the traffic demand increases, and urban rail transit also faces greater operation pressure. Train dispatching of rail transit directly influences the income of trip and operation of passengers, and is always the key point of expert research. The reasonable rail transit train dispatching scheme is made to be very important. In the related field of urban rail transit train scheduling problem research, scholars at home and abroad have obtained a lot of research achievements, and the achievements mostly aim at the minimum of passenger satisfaction or urban rail transit operation cost to further obtain an optimal scheme, often stay in a theoretical calculation stage, and cannot provide a relatively accurate decision basis for a train scheduling operation scheme.
Disclosure of Invention
The invention aims to provide a train simulation operation optimization system construction method based on matched passenger flow, which optimizes the operation scheduling of a rail transit line on the basis of considering the feasibility of a train scheduling operation scheme and provides an accurate decision basis for the train scheduling operation scheme.
In order to achieve the purpose, the invention provides the following scheme:
a train simulation operation optimization system construction method based on matched passenger flow comprises the following steps:
building a train simulation operation model;
presetting an initial train number sequence; the initial train number sequence comprises initial train numbers of different line intervals;
according to the initial train number sequence, aiming at minimizing the sum of passenger waiting time and urban rail transit operation cost, simulating train operation by using a train simulation operation model to generate a train dispatching operation scheme;
adjusting a train dispatching operation scheme until the line section full load rate of the adjusted train dispatching operation scheme is less than or equal to a line section full load rate threshold and the full load rate of each station train is less than or equal to a station train full load rate threshold, and taking the adjusted train dispatching operation scheme as a train dispatching operation feasible scheme corresponding to the initial train number sequence;
repeating the steps to obtain a train dispatching operation feasible scheme corresponding to a plurality of initial train number sequences, and the line section full load rate and each station train full load rate of each train dispatching operation feasible scheme;
calculating the passenger waiting time and urban rail transit operation cost of each train scheduling operation feasible scheme;
and taking the feasible train dispatching operation scheme with minimum passenger waiting time, urban rail transit operation cost, line section full load rate and train full load rate of each station as the optimal train dispatching operation scheme.
Optionally, the building of the train simulation operation model specifically includes:
constructing a train model, a track model and a line model;
defining basic parameters of train operation; the train operation basic parameters comprise station parameters, inter-train station operation parameters, line parameters, train parameters and inter-train operation parameters;
dividing the single-day operation of the train into a plurality of time intervals according to the characteristics of passenger flow;
and matching the passenger flow of each station in each time period according to the passenger number change curve of the urban rail transit in a single day.
Optionally, according to the initial train number sequence, with the minimum sum of the passenger waiting time and the urban rail transit operation cost as a target, simulating train operation by using a train simulation operation model to generate a train dispatching operation scheme, specifically including:
determining a train operation objective function which aims at minimizing the sum of passenger waiting time and urban rail transit operation cost;
according to the initial train number sequence, solving the train operation objective function by adopting a simulated annealing algorithm to obtain a train timetable;
simulating train operation by using a train simulation operation model according to the train schedule to generate a train dispatching operation scheme; the train dispatching operation scheme comprises passenger flow matched with train simulated operation and the number of passengers getting on or off the train at each station in the train operation process.
Optionally, the determining a train operation objective function targeting that the sum of the passenger waiting time and the urban rail transit operation cost is minimum specifically includes:
establishing a passenger waiting time function of
Wherein, tRiding deviceTo representPassenger waiting time; b represents the train running direction; i represents a station at which the train stops; m represents the total number of sites; t represents the time when the train is in operation;
representing train operation time; k represents the train number of departure of the train;
a set of initial train numbers representing a train running direction b between the line sections; omegakibThe number of passengers which cannot get on the bus after the bus number k departs from the station i and the direction b is shown;
is shown in time period [ dkib,dk+1,i,b]i number of passengers arriving at station; dkibThe departure time of the train number k in the directions of the station i and the station b is shown; dk+1,i,bThe departure time of the train number k +1 in the i station and the b direction is shown;
is 1 or 0 when
When the number is equal to 1, the departure of the train number k in the direction of 1 station, t time and b is represented; when in use
When the value is equal to 0, the fact that the train number k does not depart in the 1 st station, t moment and b direction is shown; lambda [ alpha ]ibRepresenting the arrival rate of passengers at the ith station in the direction b; d1ibRepresenting the time interval of departure of the first train in the direction of the station i and the direction of the station b;
establishing an urban rail transit operation cost function as
Wherein m isBecome intoRepresenting the operation cost of urban rail transit; c represents the cost required by the train to finish the service in one direction of the line section;
according toA passenger waiting time function and an urban rail transit operation cost function, wherein the minimum sum of the passenger waiting time and the urban rail transit operation cost is taken as an optimization target, and a train operation objective function is determined as
Wherein minZ represents the minimum value of the sum of the passenger waiting time and the urban rail transit operation cost, and alpha and beta represent the weights of a passenger waiting time function and an urban rail transit operation cost function respectively;
determining constraint conditions of a train operation objective function; the constraint conditions comprise passenger flow distribution constraint, initial train number constraint on different line intervals, train passenger capacity constraint, minimum stopping distance constraint and passenger flow state balance constraint.
Optionally, the solving the train operation objective function by using a simulated annealing algorithm according to the initial train number sequence to obtain a train schedule specifically includes:
presetting an initial train timetable;
and taking a preset initial train schedule as an initial solution, and carrying out iterative solution on the train operation objective function by using a simulated annealing algorithm based on constraint conditions to obtain an optimal train schedule.
Optionally, the adjusting the train dispatching operation scheme until the line section full load rate of the adjusted train dispatching operation scheme is less than or equal to the line section full load rate threshold and the train full load rate of each station is less than or equal to the station train full load rate threshold, and taking the adjusted train dispatching operation scheme as a feasible train dispatching operation scheme corresponding to the initial train number sequence specifically includes:
according to the train dispatching operation scheme, calculating the line section full load rate and the train full load rate of each station, and judging whether the line section full load rate is smaller than or equal to a line section full load rate threshold value or not and whether the train full load rate of each station is smaller than or equal to a station train full load rate threshold value or not to obtain a judgment result;
if the judgment result shows no, updating the initial train number sequence, and returning to the step of presetting the initial train number sequence;
and if the judgment result shows that the train is in the acceptable state, outputting a train dispatching operation scheme as a train dispatching operation feasible scheme corresponding to the initial train number sequence.
Optionally, the train scheduling operation feasible scheme that the passenger waiting time, the urban rail transit operation cost, the line section full load rate, and the train full load rate of each station are all minimum is used as the optimal train scheduling operation scheme, and then the method further includes:
and respectively visualizing the passenger waiting time comparison result, the urban rail transit operation cost comparison result, the line section full-load rate comparison result and the train full-load rate comparison result of each station of the feasible scheduling and operating scheme of the plurality of trains.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses a train simulated operation optimization system construction method based on matched passenger flow, which aims at minimizing the sum of passenger waiting time and urban rail transit operation cost, simulates train operation through a train simulated operation model, verifies the feasibility of a train dispatching operation scheme, obtains a train dispatching operation feasible scheme corresponding to a plurality of initial train number sequences, comprehensively evaluates the quality of the train dispatching operation scheme through a plurality of analysis angles of passenger waiting time, urban rail transit operation cost, line section full load rate and train full load rate of each station, and selects an optimal train dispatching operation scheme, thereby realizing the feasibility of the train dispatching operation scheme and further optimizing the operation dispatching of rail transit lines.
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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 drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a method for constructing a train simulation operation optimization system based on matching passenger flow according to the present invention;
fig. 2 is a schematic diagram of a method for constructing a train simulation operation optimization system based on matching passenger flows according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 invention.
The invention aims to provide a train simulation operation optimization system construction method based on matched passenger flow, which optimizes the operation scheduling of a rail transit line on the basis of considering the feasibility of a train scheduling operation scheme and provides an accurate decision basis for the train scheduling operation scheme.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The invention provides a method for constructing a train simulation operation optimization system based on passenger flow matching, which comprises the following steps of:
and 101, constructing a train simulation operation model.
The method specifically comprises the following steps:
constructing a train model, a track model and a line model;
defining basic parameters of train operation; the train operation basic parameters comprise station parameters, inter-train station operation parameters, line parameters, train parameters and inter-train operation parameters;
dividing the single-day operation of the train into a plurality of time intervals according to the characteristics of passenger flow;
and matching the passenger flow of each station in each time period according to the passenger number change curve of the urban rail transit in a single day.
And 103, simulating train operation by using a train simulation operation model according to the initial train number sequence and aiming at minimizing the sum of passenger waiting time and urban rail transit operation cost, and generating a train dispatching operation scheme.
The method specifically comprises the following steps:
determining a train operation objective function which aims at minimizing the sum of passenger waiting time and urban rail transit operation cost;
according to the initial train number sequence, solving a train operation objective function by adopting a simulated annealing algorithm to obtain a train timetable;
simulating train operation by using a train simulation operation model according to a train schedule to generate a train dispatching operation scheme; the train dispatching operation scheme comprises passenger flow matched with train simulation operation and the number of passengers getting on or off the train at each station in the train operation process.
The method for determining the train operation objective function with the minimum sum of passenger waiting time and urban rail transit operation cost as the target specifically comprises the following steps:
establishing a passenger waiting time function of
Wherein, tRiding deviceRepresents passenger waiting time; b represents the train running direction; i represents a station at which the train stops; m represents the total number of sites; t represents the time when the train is in operation;
representing train operation time; k represents the train number of departure of the train;
a set of initial train numbers representing a train running direction b between the line sections; omegakibThe number of passengers which cannot get on the bus after the bus number k departs from the station i and the direction b is shown;
is shown in time period [ dkib,dk+1,i,b]i number of passengers arriving at station; dkibThe departure time of the train number k in the directions of the station i and the station b is shown; dk+1,i,bThe departure time of the train number k +1 in the i station and the b direction is shown;
is 1 or 0 when
When the number is equal to 1, the departure of the train number k in the direction of 1 station, t time and b is represented; when in use
When the value is equal to 0, the fact that the train number k does not depart in the 1 st station, t moment and b direction is shown; lambda [ alpha ]ibRepresenting the arrival rate of passengers at the ith station in the direction b; d1ibRepresenting the time interval of departure of the first train in the direction of the station i and the direction of the station b;
establishing an urban rail transit operation cost function as
Wherein m isBecome intoRepresenting the operation cost of urban rail transit; c represents the cost required by the train to finish the service in one direction of the line section;
according to the passenger waiting time function and the urban rail transit operation cost function, the minimum sum of the passenger waiting time and the urban rail transit operation cost is taken as an optimization target, and the train operation objective function is determined to be
Wherein minZ represents the minimum value of the sum of the passenger waiting time and the urban rail transit operation cost, and alpha and beta represent the weights of a passenger waiting time function and an urban rail transit operation cost function respectively;
determining constraint conditions of a train operation objective function; the constraint conditions comprise passenger flow distribution constraint, initial train number constraint on different line intervals, train passenger capacity constraint, minimum stopping distance constraint and passenger flow state balance constraint.
According to the initial train number sequence, a simulated annealing algorithm is adopted to solve a train operation objective function to obtain a train schedule, and the method specifically comprises the following steps:
presetting an initial train timetable;
and taking a preset initial train schedule as an initial solution, and carrying out iterative solution on the train operation objective function by using a simulated annealing algorithm based on constraint conditions to obtain an optimal train schedule.
And 104, adjusting the train dispatching operation scheme until the line section full load rate of the adjusted train dispatching operation scheme is less than or equal to the line section full load rate threshold and the train full load rate of each station is less than or equal to the station train full load rate threshold, and taking the adjusted train dispatching operation scheme as a train dispatching operation feasible scheme corresponding to the initial train number sequence.
The method specifically comprises the following steps:
according to the train dispatching operation scheme, calculating the line section full load rate and the train full load rate of each station, and judging whether the line section full load rate is smaller than or equal to a line section full load rate threshold value or not and whether the train full load rate of each station is smaller than or equal to a station train full load rate threshold value or not to obtain a judgment result;
if the judgment result shows no, updating the initial train number sequence, and returning to the step of 'the initial train number sequence';
and if the judgment result shows that the train is in the acceptable range, outputting a train dispatching operation scheme as a train dispatching operation feasible scheme corresponding to the initial train number sequence.
And 105, repeating the steps to obtain a train dispatching operation feasible scheme corresponding to the initial train number sequence, and the line section full load rate and each station train full load rate of each train dispatching operation feasible scheme.
And 106, calculating the passenger waiting time and urban rail transit operation cost of each train scheduling operation feasible scheme.
And 107, taking the feasible train dispatching operation scheme with the minimum passenger waiting time, the minimum urban rail transit operation cost, the minimum line section full load rate and the minimum train full load rate of each station as the optimal train dispatching operation scheme.
The invention can also respectively visualize the passenger waiting time comparison result, the urban rail transit operation cost comparison result, the line section full load ratio comparison result and the train full load ratio comparison result of each station of a plurality of feasible schemes for train dispatching operation.
The invention verifies whether the design of the train dispatching operation scheme is feasible or not through the simulated operation of the computer train model and the track model, and comprehensively evaluates the quality of the train dispatching operation scheme through a plurality of analysis angles of passenger waiting time, operation cost, line section full load rate and train full load rate of each station, provides scientific basis for the selection of the train dispatching operation scheme, and has important practical significance and application value.
Referring to fig. 2, the specific implementation process of the present invention is as follows:
step 1: and constructing a computer train model and a track model.
When a computer train model and a track model are constructed, the model construction is completed on the NET platform through a modeling tool. Wherein the simulation of the user-defined line model is implemented using a model layer. The model layer is a layer which is defined by the user and is used for virtualizing the user-defined simulation line model into a plurality of layers by taking the turns of the track model as a boundary. The introduction of the model layer enables simulation of arbitrary lines over arbitrary long distances on a limited track. The model layer is divided into a plurality of layers by taking a plurality of station images displayed by the computer train model when the computer train model runs for one circle as a layer. The method for dividing the layers is to store the sites belonging to the same circle in the same container, and the system automatically obtains images from the container for storing the image information of a plurality of sites in the next circle and calls a drawing function to draw on a window interface when the system runs to the last station of the current circle.
Step 2: and constructing a basic model definition module and automatically defining a model for train operation. The model definition comprises station definition, train station operation definition, line definition, train definition and inter-train operation definition.
When a basic model definition module is constructed, station numbers, station names, positions, inter-station distances, station arrival time and station residence time can be defined in station definition; in the train inter-station operation definition, station stop time and inter-station operation time can be defined; in the line definition, the serial number of a line section, the train running direction of the line section, the line length and the departure cost of a single train number corresponding to the line section can be defined; in the train definition, the train passenger capacity, the number of passengers getting on the train in a saturated state and the passenger arrival rate of each station can be defined; in the inter-train operation definition, an inter-train minimum safe operation time interval and an inter-train operation time interval can be defined. In the invention, the parameters in the basic model definition module are acquired by relying on a Baidu map and a preset mode.
And step 3: matching passenger flow, and matching historical passenger flow data of each station under different scenes of working days and weekend days from the passenger flow database.
When passenger flow is matched, the passenger flow database matches the passenger flow volume of different scenes of working days and weekend days for each station of train operation. The passenger flow of working days and weekends has different characteristics, the passenger flow changes greatly in the working days and is mainly concentrated on the early peak and the late peak, wherein the passenger flow in the peak time period comprises the early peak and the late peak and even can account for 40% of the total number of people all day. On weekend days, the change of the passenger flow is relatively smooth, no obvious peak of the passenger flow exists, and the passenger flow is concentrated in the afternoon and the evening. According to the characteristics of passenger flow, the train operation time period is mainly divided into 6 parts of early/late low peak, secondary high peak, early/late high peak and normal peak, specifically divided into early/late low peak sections of 06:00-07:00 and 22:00-24:00, divided into secondary high peak sections of 09:00-10:00, divided into early/late high peak sections of 07:00-09:00 and 17:00-19:00, and divided into normal peak sections of 10:00-17:00 and 19:00-22: 00. And after the operation time period is divided, carrying out passenger flow distribution simulation on each station according to the passenger flow demand in each time period. The all-day passenger flow data in the passenger flow database is set according to a passenger number change curve of single-day urban rail transit provided by the Beijing urban traffic development research center.
And 4, step 4: and constructing a common parameter setting module, and setting the weight proportion of two objective functions of the total train bottom number of the trains, the passenger waiting time and the urban rail transit operation cost in different line intervals.
When a common parameter setting module is constructed, the waiting time of passengers and the urban rail transit operation cost need to be optimized at the same time, and the weight proportion of two objective functions of the waiting time of the passengers and the urban rail transit operation cost is selected according to the expectation of the waiting time of the passengers and the operation income. The two symbols alpha and beta are used for representing the weights of two objective functions of passenger waiting time and urban rail transit operation cost. If it is desired to reduce the waiting time of the passengers and improve the satisfaction of the passengers, α/β should be set to a larger value; if it is desired to reduce the urban rail transit operation cost and increase the operation income, a/beta should be set to a smaller value. The common parameter setting module is different from the basic model defining module, the parameters set in the common parameter setting module are the parameters which are changed most frequently among different train operation schemes, such as the weight proportion of two objective functions of passenger waiting time and urban rail transit operation cost and the number of initial trains in different line sections, and the parameters set in the basic model defining module are not changed in different train operation schemes. The common parameter setting module is constructed, so that the problem that all the train operation schemes need to be set every time is solved.
And 5: and calculating an optimal train schedule matched with the passenger flow demand through a simulated annealing algorithm based on the passenger waiting time and the urban rail transit operation cost.
When the optimal train schedule is calculated, the minimum passenger waiting time and the urban rail transit operation cost are taken as targets, wherein the waiting time of passengers is accumulated corresponding to the number of waiting persons of each node station at each time:
the measurement mode of the urban rail transit operation cost is that the cost caused by departure of each train is summed:
in summary, a synthetic target is formed by using two targets, and the target function is minimized to be the optimal target. As shown in the following formula:
besides the objective function, all aspects of elements are also considered fully, and constraint conditions, namely the distribution situation of passenger flow, the number of initial trains in different line sections, the passenger capacity of the trains, the minimum parking interval and the constraint of passenger flow state balance are determined, wherein the getting-off rate of passengers at the starting station is 0, and the getting-off rate at the terminal station is 100%. And then solving the optimal train schedule by using a simulated annealing algorithm.
The simulated annealing algorithm is used for solving the combinatorial optimization problem and is composed of an initial solution iSolution (II)And starting with the initial value n of the control parameter, repeatedly generating a new solution for the current solution, then calculating the iteration of the target function difference which is finally accepted or abandoned, gradually attenuating the value n, and obtaining the approximate optimal solution for the current solution when the algorithm is terminated. The initial solution input by the simulated annealing algorithm is an initial train schedule which is automatically set according to the total passenger flow demand condition, and the optimal train schedule which can minimize the passenger waiting time and the urban rail transit operation cost is finally obtained after continuous iteration through a target function and constraint conditions, so that the train-starting time interval between trains in different operation periods is determined.
Step 6: and setting train workshop operation time intervals according to the train timetable obtained by calculation, and performing train simulation operation.
And according to the optimal train schedule, setting train workshop operation time intervals in the inter-train operation definition, and performing train simulation operation. And generating a train dispatching operation scheme after the simulated operation is finished, and storing the train dispatching operation scheme into a database, wherein the train dispatching operation scheme comprises basic parameters set by a basic model definition module, common parameters set by a common parameter setting module, passenger flow matched with the train simulated operation and the number of passengers getting on or off the train at each station in the train operation process.
And 7: and constructing a single train dispatching operation scheme result analysis in a train operation scheme evaluation module. The waiting time of passengers, the operation cost of urban rail transit, the line section full load rate and the train full load rate of each station are analyzed, the analysis result is displayed by utilizing a visualization technology, whether the line section full load rate and the train full load rate of each station meet the requirements or not is judged, and then whether the train dispatching operation scheme is feasible or not is judged.
When the result of the single train dispatching operation scheme is analyzed, the passenger waiting time, the urban rail transit operation cost, the line section full load rate and the train full load rate of each station of the scheme are analyzed, and whether the operation scheme is feasible or not is judged according to whether the requirements on the line section full load rate and the train full load rate of each station are met or not. The line section full load rate refers to the proportion of the actual passenger carrying capacity of the vehicle passing through the maximum passenger flow section in unit time (generally calculated according to the early peak hour) to the designed passenger carrying capacity, and can embody the service level of the urban rail transit system. According to relevant regulations, if the maximum line section full-load rate exceeds 120% in the peak hour normalization of the train scheduling operation scheme in the analysis process, adjusting the initial train number in different line intervals in a common parameter setting module to optimize the train operation scheduling scheme; the train full load rate of each station refers to the proportion of the number of passengers actually carried by the train at each station to the passenger capacity of the train during the running process of the train. According to relevant regulations, if the station peak hour maximum saturation normalization of one line exceeding 40% in quantity exceeds 100% in the research process, the number of initial trains in different line intervals is adjusted in a common parameter setting module, and a train operation scheduling scheme is optimized. And judging that the train dispatching operation scheme is feasible until the line section full load rate and the train full load rate of each station meet the requirements.
And 8: and constructing a result comparison analysis of a plurality of times of train dispatching operation schemes in the train operation scheme evaluation module. The passenger waiting time, the operation cost, the line section full load rate and the train full load rate of each station of each scheme are compared, the comparison result is displayed in the forms of a line chart, a scatter diagram, a bar chart and the like by using a visualization technology, the train dispatching operation scheme which is more matched with the passenger flow demand, namely the train dispatching operation scheme which is relatively small in each parameter through comparison is searched, and the train dispatching scheme is optimized.
And when the results of the train dispatching operation schemes are compared and analyzed for multiple times, the analysis results of the feasible single train simulation operation scheme are called, the passenger waiting time, the operation cost, the line section full load rate and the train full load rate of each station of each scheme are compared by using a visualization technology, and the results are displayed in the forms of a broken line graph, a scatter diagram, a bar chart and the like. And comparing and judging the advantages and disadvantages of the simulated operation schemes of different trains. The number of the initial trains in different line intervals is increased in the common parameter setting module, so that a train dispatching operation scheme is feasible, but if the number of the initial trains in different line intervals is too large, the urban rail transit operation cost is increased, and meanwhile, the waste of train resources is caused. Therefore, the results of the multiple train dispatching operation scheme are compared and analyzed, parameters of passenger waiting time, urban rail transit operation cost, line section full load rate and train full load rate of each station are compared and displayed one by one on the basis of feasible scheme, the initial train number in different line intervals which is more matched with passenger flow demands, namely, the initial train number is relatively smaller through comparison of all parameters, the reasonable departure number is determined, and the train dispatching scheme is optimized. Reasonable departure number can reduce waiting time of passengers, reduce operation cost of urban rail transit and reduce waste of train resources.
Compared with the prior art, the invention has the following advantages:
the invention provides a train simulated operation optimization system construction method based on matching passenger flow, which is characterized in that an optimal train operation timetable which aims at minimum passenger waiting time and operation cost and is matched with the passenger flow is generated by utilizing a simulated annealing algorithm, then train operation simulation operation is carried out on a train model and a track model which are constructed by a computer by utilizing the generated optimal train operation timetable, and further the train operation scheme is comprehensively analyzed, so that a scientific basis is provided for evaluating the advantages and disadvantages of the train dispatching operation scheme and selecting the train dispatching operation scheme. At present, the research in the related field of urban rail transit train scheduling problems generally aims at the minimum of passenger satisfaction or urban rail transit operation cost, so that an optimal scheme is obtained, and the optimal scheme often stays in a theoretical calculation stage. Compared with the prior art, the method can simulate the operation through the computer train model and the track model, verify whether the design of the train dispatching operation scheme is feasible, comprehensively evaluate the quality of the train dispatching operation scheme through a plurality of analysis angles of passenger waiting time, operation cost, line section full load rate and train full load rate of each station, and provide scientific basis for the selection of the train dispatching operation scheme. In addition, the invention utilizes the visualization technology to compare and display the train dispatching operation schemes for multiple times, thereby judging the quality between the train dispatching operation schemes more intuitively.
In the invention, passenger flows in different scenes are matched from step 3, the optimal train operation schedule is obtained from step 5 with the aim of minimum passenger waiting time and operation cost, the train operation scheduling scheme is verified to be from step 1, step 2, step 3 and step 4, and the advantages and disadvantages of the train scheduling operation scheme are comprehensively evaluated from multiple analysis angles from steps 7 and 8.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (7)
1. A train simulation operation optimization system construction method based on matched passenger flow is characterized by comprising the following steps:
building a train simulation operation model;
presetting an initial train number sequence; the initial train number sequence comprises initial train numbers of different line intervals;
according to the initial train number sequence, aiming at minimizing the sum of passenger waiting time and urban rail transit operation cost, simulating train operation by using a train simulation operation model to generate a train dispatching operation scheme;
adjusting a train dispatching operation scheme until the line section full load rate of the adjusted train dispatching operation scheme is less than or equal to a line section full load rate threshold and the full load rate of each station train is less than or equal to a station train full load rate threshold, and taking the adjusted train dispatching operation scheme as a train dispatching operation feasible scheme corresponding to the initial train number sequence;
repeating the steps to obtain a train dispatching operation feasible scheme corresponding to a plurality of initial train number sequences, and the line section full load rate and each station train full load rate of each train dispatching operation feasible scheme;
calculating the passenger waiting time and urban rail transit operation cost of each train scheduling operation feasible scheme;
and taking the feasible train dispatching operation scheme with minimum passenger waiting time, urban rail transit operation cost, line section full load rate and train full load rate of each station as the optimal train dispatching operation scheme.
2. The method for constructing the train simulation operation optimization system based on the matched passenger flow according to claim 1, wherein the constructing of the train simulation operation model specifically comprises:
constructing a train model, a track model and a line model;
defining basic parameters of train operation; the train operation basic parameters comprise station parameters, inter-train station operation parameters, line parameters, train parameters and inter-train operation parameters;
dividing the single-day operation of the train into a plurality of time intervals according to the characteristics of passenger flow;
and matching the passenger flow of each station in each time period according to the passenger number change curve of the urban rail transit in a single day.
3. The method for constructing the train simulation operation optimization system based on the matched passenger flow according to claim 1, wherein a train operation is simulated by using a train simulation operation model to generate a train dispatching operation scheme by aiming at the minimum sum of passenger waiting time and urban rail transit operation cost according to the initial train number sequence, and the method specifically comprises the following steps:
determining a train operation objective function which aims at minimizing the sum of passenger waiting time and urban rail transit operation cost;
according to the initial train number sequence, solving the train operation objective function by adopting a simulated annealing algorithm to obtain a train timetable;
simulating train operation by using a train simulation operation model according to the train schedule to generate a train dispatching operation scheme; the train dispatching operation scheme comprises passenger flow matched with train simulated operation and the number of passengers getting on or off the train at each station in the train operation process.
4. The method for constructing the train simulation operation optimization system based on the matched passenger flow according to claim 3, wherein the step of determining the train operation objective function with the minimum sum of the passenger waiting time and the urban rail transit operation cost as the target specifically comprises the following steps:
establishing a passenger waiting time function of
Wherein, tRiding deviceRepresents passenger waiting time; b represents the train running direction; i represents a station at which the train stops; m represents the total number of sites; t represents the time when the train is in operation;
representing train operation time; k represents the train number of departure of the train;
a set of initial train numbers representing a train running direction b between the line sections; omegakibThe number of passengers which cannot get on the bus after the bus number k departs from the station i and the direction b is shown;
is shown in time period [ dkib,dk+1,i,b]i number of passengers arriving at station; dkibThe departure time of the train number k in the directions of the station i and the station b is shown; dk+1,i,bThe departure time of the train number k +1 in the i station and the b direction is shown;
is 1 or 0 when
When the number is equal to 1, the departure of the train number k in the direction of 1 station, t time and b is represented; when in use
When the value is equal to 0, the fact that the train number k does not depart in the 1 st station, t moment and b direction is shown; lambda [ alpha ]ibRepresenting the arrival rate of passengers at the ith station in the direction b; d1ibRepresenting the time interval of departure of the first train in the direction of the station i and the direction of the station b;
establishing an urban rail transit operation cost function as
Wherein m isBecome intoRepresenting the operation cost of urban rail transit; c represents the cost required by the train to finish the service in one direction of the line section;
according to the passenger waiting time function and the urban rail transit operation cost function, the minimum sum of the passenger waiting time and the urban rail transit operation cost is taken as an optimization target, and the train operation objective function is determined to be
determining constraint conditions of a train operation objective function; the constraint conditions comprise passenger flow distribution constraint, initial train number constraint on different line intervals, train passenger capacity constraint, minimum stopping distance constraint and passenger flow state balance constraint.
5. The method for constructing the train simulation operation optimization system based on the matched passenger flow according to claim 4, wherein the train operation objective function is solved by adopting a simulated annealing algorithm according to the initial train number sequence to obtain a train schedule, and the method specifically comprises the following steps:
presetting an initial train timetable;
and taking a preset initial train schedule as an initial solution, and carrying out iterative solution on the train operation objective function by using a simulated annealing algorithm based on constraint conditions to obtain an optimal train schedule.
6. The method for constructing the train simulation operation optimization system based on the matched passenger flow according to claim 1, wherein the train dispatching operation scheme is adjusted until a line section full load rate of the adjusted train dispatching operation scheme is less than or equal to a line section full load rate threshold and a train full load rate of each station is less than or equal to a station train full load rate threshold, and the adjusted train dispatching operation scheme is used as a train dispatching operation feasible scheme corresponding to an initial train number sequence, and specifically comprises:
according to the train dispatching operation scheme, calculating the line section full load rate and the train full load rate of each station, and judging whether the line section full load rate is smaller than or equal to a line section full load rate threshold value or not and whether the train full load rate of each station is smaller than or equal to a station train full load rate threshold value or not to obtain a judgment result;
if the judgment result shows no, updating the initial train number sequence, and returning to the step of presetting the initial train number sequence;
and if the judgment result shows that the train is in the acceptable state, outputting a train dispatching operation scheme as a train dispatching operation feasible scheme corresponding to the initial train number sequence.
7. The method for constructing the train simulation operation optimization system based on the matched passenger flow according to claim 1, wherein a feasible train dispatching operation scheme that the passenger waiting time, the urban rail transit operation cost, the line section full load rate and the train full load rate of each station are all minimum is used as an optimal train dispatching operation scheme, and then the method further comprises the following steps:
and respectively visualizing the passenger waiting time comparison result, the urban rail transit operation cost comparison result, the line section full-load rate comparison result and the train full-load rate comparison result of each station of the feasible scheduling and operating scheme of the plurality of trains.
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