CN116187527B - Train running diagram rapid fluffing optimization method based on dynamic simulation - Google Patents
Train running diagram rapid fluffing optimization method based on dynamic simulation Download PDFInfo
- Publication number
- CN116187527B CN116187527B CN202211685159.2A CN202211685159A CN116187527B CN 116187527 B CN116187527 B CN 116187527B CN 202211685159 A CN202211685159 A CN 202211685159A CN 116187527 B CN116187527 B CN 116187527B
- Authority
- CN
- China
- Prior art keywords
- train
- time
- arrival
- departure
- station
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000010586 diagram Methods 0.000 title claims abstract description 40
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000005457 optimization Methods 0.000 title claims abstract description 16
- 238000005094 computer simulation Methods 0.000 title claims abstract description 12
- 238000004088 simulation Methods 0.000 claims abstract description 37
- 239000011159 matrix material Substances 0.000 claims description 15
- 230000001934 delay Effects 0.000 claims description 3
- 230000003111 delayed effect Effects 0.000 claims description 3
- 230000002441 reversible effect Effects 0.000 claims description 3
- 239000006185 dispersion Substances 0.000 abstract description 8
- 230000002068 genetic effect Effects 0.000 description 5
- 229910002056 binary alloy Inorganic materials 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/10—Operations, e.g. scheduling or time tables
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/10—Operations, e.g. scheduling or time tables
- B61L27/12—Preparing schedules
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06314—Calendaring for a resource
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G06Q50/40—
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
The invention provides a train running diagram quick untwining optimization method based on dynamic simulation. The method comprises the following steps: basic data and constraint conditions of train operation are obtained, wherein the basic data comprise: inputting simulation time period length, line application number, line station number, train starting station departure interval, train road traffic division, stop, starting train departure time and demand of customer flow starting point to destination OD; traversing time beats of all stations in the uplink and downlink directions according to the minimum time beats of a train operation diagram based on the basic data of train operation, and generating conflict-free train arrival and departure time meeting various constraint conditions and dynamic stop time; calculating and outputting key indexes of the running of the dredged train by utilizing the collision-free train arrival time. The invention provides a common support for conflict dispersion optimization of urban rail transit operation diagram establishment and train operation adjustment, provides technical conditions for scientific operation organizations, and improves the road network operation service level.
Description
Technical Field
The invention relates to the technical field of urban rail transit operation management, in particular to a train running diagram rapid untwining optimization method based on dynamic simulation.
Background
By the end of 2021, 50 cities in the continental region of China open urban rail transit operation lines 283, the total length of the operation lines is 9206.8 km, and 2021 finishes 236.9 hundred million people in total year, so that the national network and passenger flow scale jump is the first worldwide. With the networked development of urban rail transit, the demand of passenger flows is increased, and the urban rail travel is crowded due to limited transportation capacity. Meanwhile, due to the occupancy space characteristics of urban rail transit commuter passenger flows, the unbalanced and outstanding spatial and temporal distribution of the passenger flows is shown, and higher requirements are put forward for train running chart programming and adjustment.
In order to cope with dynamic unbalanced passenger flow, the existing running diagram generally considers constraints such as the number of bottoms, the capacity of trains, departure intervals and the like, and adopts a complex running scheme and a train running mode, including large and small road crossing, fast and slow vehicle crossing, dynamic stop and the like. The application of the complex running scheme and the train running mode naturally generates the problem that conflicts such as train turning back, running overtravel and the like are difficult to break.
Therefore, a train operation diagram simulation quick untwining optimization method under the condition of considering dynamic stop time caused by waiting passenger flow, meeting complex running schemes such as turning back and going out of the way of a large and small traffic routes, and the like needs to be provided, and feasibility of the operation diagram is met.
Disclosure of Invention
The embodiment of the invention provides a quick dispersion optimization method for a train running diagram based on dynamic simulation, which aims to solve the problem of difficulty in dispersion of train running diagram programming conflict under a complex running scheme.
In order to achieve the above purpose, the present invention adopts the following technical scheme.
A train running diagram quick untwining optimization method based on dynamic simulation comprises the following steps:
basic data and constraint conditions of train operation are obtained, wherein the basic data comprise: inputting simulation time period length, line application number, line station number, train starting station departure interval, train road traffic division, stop, starting train departure time and demand of customer flow starting point to destination OD;
traversing time beats of all stations in the uplink and downlink directions according to the minimum time beats of a train operation diagram based on the basic data of train operation, and generating conflict-free train arrival and departure time meeting various constraint conditions and dynamic stop time;
and calculating and outputting key indexes of train operation after fluffing by utilizing the collision-free train arrival time.
Preferably, the acquiring basic data and constraint conditions of train operation includes: inputting simulation time period length, line application number of bottoms, number of line stations, train departure interval of a train departure station, train road traffic division, station stopping, departure time of the train and customer flow OD requirements, comprising:
setting the number of railway stations, departure time of the train and the number of train bottoms and departure interval constraint conditions of the train departure stations according to the actual conditions of railway lines;
according to the passenger flow space-time distribution characteristics of the railway line, a simulation period, a train crossing dividing mode and a stop mode are specified;
constructing a three-dimensional matrix for waiting for passengers according to the OD requirement of passenger flow, and representing the number of passengers waiting for the passengers to arrive at other stations of the line at each station and each moment by taking the minimum time beat as a unit;
and constructing a four-dimensional simulation data support matrix according to the departure time of the first-class train starting station, wherein the four-dimensional simulation data support matrix represents the occupancy state of the station in the up-down direction of the station and the station departure at each moment, and the moment, the station and the direction of the first-class train are 0 and the balance is-1.
Preferably, the step of traversing the time beats of all stations in the up-down direction according to the minimum time beat of the train operation chart by the basic data based on the train operation to generate the collision-free train arrival time meeting various constraint conditions and dynamic stop time comprises the following steps:
traversing time, stations, uplink and downlink and arrival states contained in the four-dimensional simulation data support matrix;
when traversing to the arrival state of 0, updating the arrival state of the new departure bottom sent by the starting station;
when traversing to reach the state as a positive integer, if the train stops at the station, simulating the passenger boarding process, generating dynamic stop time and preset departure time, and updating the departure state of the train; if the train does not stop at the station, generating a train departure time, and updating a train departure state;
when the traversing to the departure state is a positive integer, according to the running time or the turning time of the train section, the train forward collision is cleared, the train pre-arrival time is generated, and the train arrival state is updated.
Preferably, the updating the departure status of the train includes:
when the arrival state is 0, traversing forward from the current moment until the moment that the departure state of the station is a positive integer is found, recording the train bottom number of the front train, adjusting the arrival state moment of the new train bottom to meet the safety driving interval, traversing the departure moment of searching the train bottom of the front sequence from the arrival moment of the front sequence to the rear, and adjusting the arrival state moment of the new train bottom again to meet the arrival time interval; if the arrival time of the new vehicle bottom is not changed after adjustment, directly updating the arrival state 0 into the new vehicle bottom number; if the station direction arrival state is changed, the original arrival state 0 is recorded as-1, and the station direction arrival state is updated to be a new vehicle bottom number at the adjusted arrival time; after the new vehicle bottom arrival state is updated, according to the stop departure rule, searching for the moment meeting the new vehicle bottom departure interval backwards from the moment of determining the arrival state to record the next arrival state 0, and sequentially adjusting the subsequent arrival and pre-arrival states to meet the safe driving interval;
when traversing to the departure state as a positive integer, if the train does not carry out the turn-back operation at the departure station, generating the pre-arrival time reaching the next station according to the running time of the fixed interval; and moving the pre-arrival state to meet the time interval of the safe driving of the lead train and the time interval of the arrival, recording the arrival state as the train bottom number, and adjusting the arrival state of the train with the train bottom sequence to meet the time interval of the safe driving.
Preferably, the updating the train arrival state includes:
when the traversing state is a positive integer, if the arriving train bottom stops at the station, simulating passengers to get on or off the train and ensuring that the total number of passengers on the train does not exceed the capacity of the train, and recording the condition of the full load rate of the train and the accumulated waiting time of the passengers on the train; if the train does not move beyond the station, generating a pre-departure time directly according to the passenger flow of the on-off train, traversing the pre-departure time forward to find the departure time of the train in the front sequence, adjusting the pre-departure time to meet the safe driving time interval, and updating the departure state to be the arrival state train bottom number; if the train moves beyond the station, searching backward from the current moment whether the bottom of the train arrives in the safe running time interval, if so, generating the overtaking of the express train, updating the pre-departure time state of the bottom of the currently arrived state into the time state of meeting the distance from the arrival of the express train after the sending time of the express train, namely the number of the bottom of the arrived state; if the train does not stop at the station, updating the departure state to the train bottom number at the same time of the arrival time of the train;
after the current train departure state is updated, the arrival state of the subsequent train is updated in sequence to meet the arrival time interval.
Preferably, the performing the train positive line conflict fluffing includes:
when traversing to the departure state as a positive integer, if the train carries out turn-back operation at the departure station, generating the opposite direction pre-arrival time of the station according to the shortest turn-back time of the train, and carrying out forward line conflict fluffing on the middle turn-back station; if the returning train arrives at the reverse station in advance, the arrival time of the front train is delayed until the safe driving interval with the arrival of the returning train at the station is met; otherwise, the turning-back train increases turning-back operation time and delays to station time; the train which reaches the station first needs to ensure the safe driving interval and the arrival time interval with the preceding train.
Preferably, the calculating and outputting key indexes of the running of the untwined train by using the arrival time of the collision-free train includes:
generating a train schedule according to the four-dimensional simulation data support matrix after the traversal is finished;
calculating an overrun average value exceeding the full load rate limit according to the full load rate record of each passenger boarding simulation;
calculating average waiting time of passengers according to the number of passengers getting on, the waiting time of each arrival, the arrival time of passengers without getting on after simulation and the simulation ending time;
calculating the total travelling kilometers of the train according to the travelling of each section of the train in the simulation;
and outputting the overrun average value, the average waiting time of passengers, the total running kilometers of the train and the train schedule.
According to the technical scheme provided by the embodiment of the invention, the common support is provided for conflict and dispersion optimization of urban rail transit operation diagram programming and train operation adjustment, the technical conditions are provided for scientific operation organizations, and the road network operation service level is improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of 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 other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a process flow diagram of a train operation diagram quick untwining optimization method based on dynamic simulation provided by an embodiment of the invention;
fig. 2 is a schematic diagram of forward collision resolution for a train according to an embodiment of the present invention;
fig. 3 is a schematic diagram of updating an arrival status of a train according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a departure status update for a train according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a genetic algorithm call simulation running chart according to an embodiment of the present invention;
fig. 6 is a schematic diagram of an operation chart according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
For the purpose of facilitating an understanding of the embodiments of the invention, reference will now be made to the drawings of several specific embodiments illustrated in the drawings and in no way should be taken to limit the embodiments of the invention.
The process flow of the train operation diagram rapid fluffing optimization method based on dynamic simulation provided by the embodiment of the invention is shown in the figure 1, and comprises the following processing steps:
step S1, basic data and constraint conditions of train operation are obtained, wherein the basic data comprise: the simulation time period length, the line application number of bottoms, the number of line stations, the departure interval of a train starting station, the train road-passing division, stop, the departure time of the starting train and the demand of passenger flow OD (Origin to Destination, starting point to ending point) are input. The constraint conditions include: number of bottoms constraint, capacity constraint of train, departure interval time constraint, safe driving interval constraint, platform safe interval time constraint, stop time constraint, turn-back time constraint and study time range constraint.
Step S2, traversing the time beats of all stations in the uplink and downlink directions according to the minimum time beat of the train running chart, and generating conflict-free train arrival time meeting the conditions of safe running, large and small traffic turn-back, overtravel and the like by considering various constraint conditions and dynamic stop time;
and step S3, calculating and outputting key indexes of the overrun average value of the train full rate, the average waiting time of passengers and the total running kilometers of the train of the running train after the untwining by utilizing the arrival time of the collision-free train.
Further, the S1 specifically includes:
s11, setting constraint conditions of the number of line stations, departure time of the originating train, the number of line application bases and departure intervals of the originating stations according to the actual conditions of the lines.
S12, according to the space-time distribution characteristics of the line passenger flow, defining a simulation period, a train crossing division and a stop mode;
s13, constructing a three-dimensional matrix for waiting passengers according to the demand of the passenger flow OD, and representing the number of waiting passengers arriving at each station and going to other stations of the line at each moment by taking the minimum time beat as a unit;
s14, constructing a four-dimensional simulation data support matrix according to the departure time of the first-class train from the departure station, wherein the four-dimensional simulation data support matrix represents the occupancy state of the arrival and departure of the train in the uplink and downlink directions of the station at each moment, the arrival time of the first-class train, the station, the direction are 0, and the balance is-1.
Further, the step S2 specifically includes:
s21, traversing time, station, uplink and downlink and arrival states of a four-dimensional simulation data support matrix based on basic data of train operation;
s22, when traversing to the arrival state of 0, updating the arrival state of the newly sent train;
s23, traversing to the state that the arrival state is a positive integer, simulating the passenger boarding process if the train parks at the station, generating dynamic stop time and pre-departure time, and updating the departure state of the train; if the train does not stop at the station, generating a train departure time, and updating a train departure state;
and S24, when the traversal is carried out until the departure state is a positive integer, according to the running time or the turn-back time of the train section, carrying out train positive line conflict and fluffing to generate train arrival time and train arrival state update.
Fig. 2 is a schematic diagram of forward collision resolution for a train according to an embodiment of the present invention. The conflict-solving method is as follows: when the traversing to the departure state is a positive integer, if the train carries out the turn-back operation at the departure station, generating the opposite direction pre-arrival time of the station according to the shortest turn-back time of the train, and carrying out the forward line conflict fluffing on the middle turn-back station. If the returning train arrives at the reverse station in advance, the arrival time of the front train is delayed until the safe driving interval with the arrival of the returning train at the station is met; otherwise, the turning-back train increases the turning-back operation time and delays the turning-back operation time to the station time. The train which reaches the station first needs to ensure the safe driving interval and the arrival time interval with the preceding train.
Fig. 3 is a schematic diagram of updating an arrival state of a train according to an embodiment of the present invention, where the method for updating the arrival state is as follows:
when the arrival state is 0, traversing forward from the current moment until the moment that the departure state of the station is a positive integer is found, recording the number of the train bottom of the front train, adjusting the arrival state moment of the new train bottom to meet the safety driving interval, traversing the departure moment of searching the train bottom of the front sequence from the arrival moment of the front sequence to the rear, and adjusting the arrival state moment of the new train bottom again to meet the arrival time interval. If the arrival time of the new vehicle bottom is not changed after adjustment, directly updating the arrival state 0 into the new vehicle bottom number; if the change occurs, the original arrival state 0 is marked as-1, and the arrival state of the station direction is updated to be the new bottom number at the adjusted arrival time. After the new vehicle bottom arrival state is updated, the next arrival state 0 is recorded at the moment of searching for meeting the new vehicle bottom departure interval from the moment of determining the arrival state according to the departure rule of the station, and the subsequent arrival and pre-arrival states are sequentially adjusted to meet the safe driving interval.
When the traversing to the departure state is a positive integer, if the train does not carry out the turn-back operation at the departure station, generating the pre-arrival time reaching the next station according to the fixed interval running time. And moving the pre-arrival state to meet the time interval of the safe driving of the lead train and the time interval of the arrival, recording the arrival state as the train bottom number, and adjusting the arrival state of the train with the train bottom sequence to meet the time interval of the safe driving.
Fig. 4 is a schematic diagram of a departure status update of a train according to an embodiment of the present invention, where the departure status update method is as follows:
when the traversing state is a positive integer, if the arriving train bottom stops at the station, simulating passengers to get on and off the train and ensuring that the total number of passengers on the train does not exceed the capacity of the train, and recording the condition of the full load rate of the train and the accumulated waiting time of the passengers on the train.
If the train does not move beyond the station, the pre-departure time is directly generated according to the passenger flow of the on-off train, the pre-departure time is traversed forward to find the departure time of the train in the front sequence, the pre-departure time is adjusted to meet the safe driving time interval, and the departure state is updated to be the arrival state train bottom number.
If the train moves beyond the station, whether the bottom of the train arrives in the safe running time interval is searched backwards from the current moment, if so, the running of the train is generated, the pre-departure moment state of the bottom of the train in the current arrival state is updated to be the moment state of meeting the interval with the arrival of the train after the sending moment of the train, namely the number of the bottom of the train in the arrival state.
If the train does not stop at the station, the departure state is updated to the bottom number at the same time of the arrival time of the train.
After the current train departure state is updated, the arrival state of the subsequent train is updated in sequence to meet the arrival time interval.
FIG. 5 is a schematic diagram of a genetic algorithm call simulation running chart according to an embodiment of the present invention, where the genetic algorithm call simulation running chart according to the present invention includes the following steps:
(1) Performing individual coding by adopting real number coding;
(2) Generating an initial population according to the vehicle bottom number constraint, the express vehicle bottom number constraint and the departure time interval constraint, wherein the step is applied to the step S1;
(3) Setting reasonable adaptability for evaluating the quality of the running diagram, and calculating the adaptability by applying a dynamic simulation train running diagram rapid fluffing optimization method, wherein the step is applied to the step S2;
(4) Selecting individuals with high fitness to enter the next generation through a tournament method;
(5) Converting the genes into binary system to perform single-point cross operation;
(6) The heterogeneous mutation operation is adopted to increase population diversity, so that the genetic algorithm is prevented from falling into local optimum;
(7) And finishing iteration after the algorithm iterates for a certain number of times, and outputting the population optimal individuals of the last iteration. The optimal individual of the iteration not only meets conflict fluffing, namely, the time of arrival of the conflict-free train meeting the conditions of safe operation, turn-back of the large and small traffic routes, going beyond the line and the like is obtained, but also is an optimal solution in all feasible solutions meeting the conflict fluffing.
Further, the step S3 specifically includes:
s31, generating a train schedule according to the four-dimensional simulation data support matrix after the traversal is finished;
s32, calculating an overrun average value exceeding the full load rate limit according to the full load rate record of each passenger boarding simulation;
s33, calculating average waiting time of passengers according to the number of passengers getting on, the waiting time and boarding time of each arrival, the arrival time and the ending time of the simulation ending non-boarding passengers;
s34, calculating the total travelling kilometers of the train according to the travelling of each section of the train in the simulation;
and S35, outputting an overrun average value of the full load rate, an average waiting time of passengers, a total kilometer of the train and a train schedule.
Fig. 6 is a schematic diagram of a train running chart compiling result according to an embodiment of the invention. Referring to fig. 6, the method for optimizing quick untwining of the train operation diagram based on dynamic simulation realizes the untwining of the train positive line conflict of the train operation diagram at the foldback stations 0, 9, 15, 24 and 31 and the untwisting of the fast and slow train conflict of the overtravel station 23. Wherein the express travel occurs in the 7:50-8:00 period.
In summary, the embodiment of the invention provides a common support for conflict and dispersion optimization of urban rail transit operation map programming and train operation adjustment, provides technical conditions for scientific operation organizations, and improves the road network operation service level.
The invention utilizes a simulation mode to carry out quick dispersion of the train operation diagram, can simulate the arrival time conflict of the train operation diagram under the conditions of complex running schemes such as dynamic stop time, large and small traffic turn-back, going-over and the like under the loading of passenger flow, automatically adjusts and dispersion the conflict time, and can replace manual conflict adjustment for the complex operation diagram.
The quick dispersion method of the train running diagram based on dynamic simulation can be used for calling optimization algorithms such as genetic algorithm, can meet complex constraint conditions, can obtain the required fitness of the algorithm, achieves the effect of optimizing the train running diagram under the complex conditions, and obtains the train running diagram after conflict-free optimization.
Those of ordinary skill in the art will appreciate that: the drawing is a schematic diagram of one embodiment and the modules or flows in the drawing are not necessarily required to practice the invention.
From the above description of embodiments, it will be apparent to those skilled in the art that the present invention may be implemented in software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the embodiments or some parts of the embodiments of the present invention.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus or system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, with reference to the description of method embodiments in part. The apparatus and system embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (6)
1. A train running diagram quick untwining optimization method based on dynamic simulation is characterized by comprising the following steps:
basic data and constraint conditions of train operation are obtained, wherein the basic data comprise: inputting simulation time period length, line application number, line station number, train starting station departure interval, train road traffic division, stop, starting train departure time and demand of customer flow starting point to destination OD;
traversing time beats of all stations in the uplink and downlink directions according to the minimum time beats of a train operation diagram based on the basic data of train operation, and generating conflict-free train arrival and departure time meeting various constraint conditions and dynamic stop time;
calculating and outputting key indexes of train operation after fluffing by utilizing the collision-free train arrival time; the basic data and constraint conditions of train operation are obtained, and the basic data comprise: inputting simulation time period length, line application number of bottoms, number of line stations, train departure interval of a train departure station, train road traffic division, station stopping, departure time of the train and customer flow OD requirements, comprising:
setting the number of railway stations, departure time of the train and the number of train bottoms and departure interval constraint conditions of the train departure stations according to the actual conditions of railway lines;
according to the passenger flow space-time distribution characteristics of the railway line, a simulation period, a train crossing dividing mode and a stop mode are specified;
constructing a three-dimensional matrix for waiting for passengers according to the OD requirement of passenger flow, and representing the number of passengers waiting for the passengers to arrive at other stations of the line at each station and each moment by taking the minimum time beat as a unit;
and constructing a four-dimensional simulation data support matrix according to the departure time of the first-class train starting station, wherein the four-dimensional simulation data support matrix represents the occupancy state of the station in the up-down direction of the station and the station departure at each moment, and the moment, the station and the direction of the first-class train are 0 and the balance is-1.
2. The method according to claim 1, wherein the step of traversing the time beats of all stations in the up-down direction according to the minimum time beat of the train operation graph based on the basic data of the train operation to generate collision-free train arrival/departure time satisfying various constraint conditions and dynamic stop time comprises the steps of:
traversing time, stations, uplink and downlink and arrival states contained in the four-dimensional simulation data support matrix;
when traversing to the arrival state of 0, updating the arrival state of the new departure bottom sent by the starting station;
when traversing to reach the state as a positive integer, if the train stops at the station, simulating the passenger boarding process, generating dynamic stop time and preset departure time, and updating the departure state of the train; if the train does not stop at the station, generating a train departure time, and updating a train departure state;
when the traversing to the departure state is a positive integer, according to the running time or the turning time of the train section, the train forward collision is cleared, the train pre-arrival time is generated, and the train arrival state is updated.
3. The method of claim 2, wherein said performing a train departure status update comprises:
when the arrival state is 0, traversing forward from the current moment until the moment that the departure state of the station is a positive integer is found, recording the train bottom number of the front train, adjusting the arrival state moment of the new train bottom to meet the safety driving interval, traversing the departure moment of searching the train bottom of the front sequence from the arrival moment of the front sequence to the rear, and adjusting the arrival state moment of the new train bottom again to meet the arrival time interval; if the arrival time of the new vehicle bottom is not changed after adjustment, directly updating the arrival state 0 into the new vehicle bottom number; if the station direction arrival state is changed, the original arrival state 0 is recorded as-1, and the station direction arrival state is updated to be a new vehicle bottom number at the adjusted arrival time; after the new vehicle bottom arrival state is updated, according to the stop departure rule, searching for the moment meeting the new vehicle bottom departure interval backwards from the moment of determining the arrival state to record the next arrival state 0, and sequentially adjusting the subsequent arrival and pre-arrival states to meet the safe driving interval;
when traversing to the departure state as a positive integer, if the train does not carry out the turn-back operation at the departure station, generating the pre-arrival time reaching the next station according to the running time of the fixed interval; and moving the pre-arrival state to meet the time interval of the safe driving of the lead train and the time interval of the arrival, recording the arrival state as the train bottom number, and adjusting the arrival state of the train with the train bottom sequence to meet the time interval of the safe driving.
4. The method of claim 2, wherein said performing a train arrival status update comprises:
when the traversing state is a positive integer, if the arriving train bottom stops at the station, simulating passengers to get on or off the train and ensuring that the total number of passengers on the train does not exceed the capacity of the train, and recording the condition of the full load rate of the train and the accumulated waiting time of the passengers on the train; if the train does not move beyond the station, generating a pre-departure time directly according to the passenger flow of the on-off train, traversing the pre-departure time forward to find the departure time of the train in the front sequence, adjusting the pre-departure time to meet the safe driving time interval, and updating the departure state to be the arrival state train bottom number; if the train moves beyond the station, searching backward from the current moment whether the bottom of the train arrives in the safe running time interval, if so, generating the overtaking of the express train, updating the pre-departure time state of the bottom of the currently arrived state into the time state of meeting the distance from the arrival of the express train after the sending time of the express train, namely the number of the bottom of the arrived state; if the train does not stop at the station, updating the departure state to the train bottom number at the same time of the arrival time of the train;
after the current train departure state is updated, the arrival state of the subsequent train is updated in sequence to meet the arrival time interval.
5. The method of claim 2, wherein said performing a train positive line collision solution comprises:
when traversing to the departure state as a positive integer, if the train carries out turn-back operation at the departure station, generating the opposite direction pre-arrival time of the station according to the shortest turn-back time of the train, and carrying out forward line conflict fluffing on the middle turn-back station; if the returning train arrives at the reverse station in advance, the arrival time of the front train is delayed until the safe driving interval with the arrival of the returning train at the station is met; otherwise, the turning-back train increases turning-back operation time and delays to station time; the train which reaches the station first needs to ensure the safe driving interval and the arrival time interval with the preceding train.
6. The method of claim 1, wherein calculating and outputting key indicators of the untwined train operation using the collision-free train arrival time comprises:
generating a train schedule according to the four-dimensional simulation data support matrix after the traversal is finished;
calculating an overrun average value exceeding the full load rate limit according to the full load rate record of each passenger boarding simulation;
calculating average waiting time of passengers according to the number of passengers getting on, the waiting time of each arrival, the arrival time of passengers without getting on after simulation and the simulation ending time;
calculating the total travelling kilometers of the train according to the travelling of each section of the train in the simulation;
and outputting the overrun average value, the average waiting time of passengers, the total running kilometers of the train and the train schedule.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211685159.2A CN116187527B (en) | 2022-12-27 | 2022-12-27 | Train running diagram rapid fluffing optimization method based on dynamic simulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211685159.2A CN116187527B (en) | 2022-12-27 | 2022-12-27 | Train running diagram rapid fluffing optimization method based on dynamic simulation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116187527A CN116187527A (en) | 2023-05-30 |
| CN116187527B true CN116187527B (en) | 2023-08-18 |
Family
ID=86435596
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211685159.2A Active CN116187527B (en) | 2022-12-27 | 2022-12-27 | Train running diagram rapid fluffing optimization method based on dynamic simulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116187527B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114386310A (en) * | 2021-12-02 | 2022-04-22 | 南京理工大学 | Subway train energy-saving schedule optimization method under time-space passenger flow network distribution |
| CN114662778A (en) * | 2022-04-06 | 2022-06-24 | 西南交通大学 | Urban rail transit line network train operation interval cooperative decision method |
| CN114925909A (en) * | 2022-05-18 | 2022-08-19 | 北京交通大学 | Urban rail transit passenger flow and traffic flow coupling optimization method and system |
-
2022
- 2022-12-27 CN CN202211685159.2A patent/CN116187527B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114386310A (en) * | 2021-12-02 | 2022-04-22 | 南京理工大学 | Subway train energy-saving schedule optimization method under time-space passenger flow network distribution |
| CN114662778A (en) * | 2022-04-06 | 2022-06-24 | 西南交通大学 | Urban rail transit line network train operation interval cooperative decision method |
| CN114925909A (en) * | 2022-05-18 | 2022-08-19 | 北京交通大学 | Urban rail transit passenger flow and traffic flow coupling optimization method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116187527A (en) | 2023-05-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8612071B2 (en) | Synchronized express and local trains for urban commuter rail systems | |
| Cats et al. | Effect of real-time transit information on dynamic path choice of passengers | |
| Altazin et al. | Rescheduling through stop-skipping in dense railway systems | |
| Kang et al. | A case study on the coordination of last trains for the Beijing subway network | |
| CN106485912B (en) | A kind of common bus dynamic dispatching method based on bus station informationization | |
| CN110162931B (en) | Large-scale road network rapid simulation system for urban rail transit | |
| CN107464005B (en) | Expanded path planning method for vehicle reservation | |
| Yuan et al. | Integrated optimization of train timetable, rolling stock assignment and short-turning strategy for a metro line | |
| CN110599760B (en) | Travel behavior simulation method under multi-mode traffic network | |
| CN105279955B (en) | A kind of share-car method and apparatus | |
| Hassannayebi et al. | Variable and adaptive neighbourhood search algorithms for rail rapid transit timetabling problem | |
| CN110390421B (en) | Space-time network-based method for coordinating and controlling passenger flow of congested subway line | |
| KR20150127429A (en) | Method of intelligent train scheduling | |
| CN113276915B (en) | Subway departure scheduling method and system | |
| Cats et al. | Effect of real-time transit information on dynamic passenger path choice | |
| CN111311002B (en) | Bus trip planning method considering active transfer of passengers in transit | |
| CN114662778A (en) | Urban rail transit line network train operation interval cooperative decision method | |
| CN112085641A (en) | High-speed railway passenger flow distribution method based on train operation scheme | |
| D’Acierno et al. | Assumptions and simulation of passenger behaviour on rail platforms | |
| CN116187527B (en) | Train running diagram rapid fluffing optimization method based on dynamic simulation | |
| CN111723991A (en) | Method for predicting and evaluating impact influence of large-scale movable scattered field passenger flow on subway station | |
| CN109523064B (en) | Intelligent micro-hub based on multi-network fusion | |
| Yao et al. | Circle line optimization of shuttle bus in central business district without transit hub | |
| CN115675584A (en) | Urban area line driving scheme optimization method for urban rail transit | |
| Uehara et al. | Evaluation of a hierarchical cooperative transport system using demand responsive bus on a dynamic simulation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |