CN115339489B - Collaborative adjustment method for train running diagram and stop scheme - Google Patents
Collaborative adjustment method for train running diagram and stop scheme Download PDFInfo
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Abstract
A method for cooperatively adjusting a train operation diagram and a stop scheme comprises the following steps: s1, initializing basic parameters of a rolling time domain optimization framework, controlling the starting time of a time window and a predicted time window, and setting the starting time of a current time window; s2, updating a control time window range and a prediction time window; s3, judging whether an interference event occurs in the range of the predicted time window, if so, executing S4, otherwise, returning to S2; s4, searching all the occurrence events within the range of the prediction time window, and creating an event activity network; s5, fixing an operation diagram before the starting time of the current time window, establishing a collaborative adjustment model of the train operation diagram and the stop plan based on scene constraint, and solving to obtain an adjustment result; s6, executing the adjustment action of the current adjustment result in the control time window range, and updating the starting time of the current time window; s7, judging whether the adjustment is finished, and if not, executing S2. The method has high feasibility and robustness.
Description
Technical Field
The invention belongs to the technical field of train operation optimization, and particularly relates to a collaborative adjustment method for a train operation diagram and a stop scheme.
Background
As the total mileage and coverage area of high-speed railway operations increases, the operation environment of the train becomes more complex. The train delay is generated on the line due to the frequent occurrence of interference such as extreme weather, equipment faults and the like, and in order to ensure driving safety by taking long-time continuous strong wind as an example, the train needs to pass through the speed limiting section when the speed is reduced to the temporary speed limit, so that the running time of the train in an interval is prolonged to generate the delay, and the delay is spread to a larger range along with the increase of the density of a line network.
After the occurrence of the disturbance event, an adjustment to the train's operation plan is required. The contents of the adjustment are as follows: the schedule of the train and the stop plan of the train so as to realize the maximum utilization of line resources and complete the recovery of abnormal operation of the train.
In the actual scheduling process, the additional running time of the interval is relatively variable due to complex and multiple scenes of the interference event. However, at present, the train operation adjustment is mainly performed for an interference scene set in advance, that is, an additional interval operation time scene assumed in advance, which may cause that the obtained adjustment scheme may not guarantee collision-free and safe driving, has low feasibility, and cannot meet the actual field operation requirement and cope with changeable and complex emergencies.
Disclosure of Invention
Aiming at the problems of more availability, poor robustness, lower line resource utilization rate and the like of an adjustment result when a high-speed railway train operation scheduling plane is subjected to uncertain speed limitation, the invention provides a train operation diagram and stop scheme cooperative adjustment method under a rolling time domain optimization framework, and provides a train operation diagram and stop scheme adjustment strategy with higher feasibility and robustness for a dispatcher in train scheduling.
The technical scheme of the invention is as follows:
a method for cooperatively adjusting a train operation diagram and a stop scheme comprises the following steps:
s1, initiallyBasic parameters of the initialization rolling time domain optimization framework are controlled to be H with the starting time of a time window and a predicted time window i The length of the control time window is H c The predicted time window length is H p And sets the current time window start time beat=h i ；
S2, updating the control time window range to be [ H, H+H ] c ]And the prediction time window is [ H, H+H ] p ]；
S3, judging whether an interference event occurs in the range of the predicted time window, if so, executing S4, otherwise, returning to S2;
s4, searching all the occurrence events within the range of the prediction time window, and creating an event activity network;
s5, fixing an operation diagram before the starting time of the current time window, establishing a scene constraint-based train operation diagram and stop plan collaborative adjustment model, and solving to obtain an adjustment result R p ；
S6, executing the current adjustment result R p An adjustment operation within the control time window range, and updating the current time window start time to beat=beat+h c ；
S7, judging whether the adjustment is finished, and if not, executing S2.
Preferably, the specific step of creating an event-active network in S4 comprises:
s4.1, search event: searching in time window [ H, H+H ] p ]All planned departure events are planned, and all planned events are decomposed;
s4.2, creating an event activity network: and (3) obtaining a train activity set in a station, an interval train activity set, a station interval activity set, a turnout interval activity set and a stock track interval activity set according to all planned departure-arrival events obtained by searching in the S4.1 and all possible events obtained by decomposition, and finally obtaining an event activity network.
Preferably, the specific process of searching the event in S4.1 is:
defining the arrival event of a train i at a station as e a The departure event of a train i at a station is e d Will e a And e d Respectively into n events, i.e. the arrival event is divided intoDeparture event is divided into->Prescribed set->For event e a The resulting set of possible arrival events is decomposed, wherein the set { I, II,3,..n } represents the planned arrival event e for train I a The set of occupied tracks may be selected after the adjustment.
Preferably, the event activity network created in S4.2 specifically includes:
a, train activity q= (e) in station a ，e d )∈A sta : the event e of planned arrival of such an event at a station by a train a And departure event e d Composition; in the adjustment, the activity q may be a stop activity or a pass-through no stop activity;
b, section train activity q= (e) a ，e d )∈A sec : such activities consist of a train of planned departure events at one station and its planned arrival events at the next station;
c, station interval movementSuch activities consist of planned arrival events (departure events) of two different trains at the same station in the same direction of travel;
d, switch interval activity q= (e) i ，e j )∈A sw : such an activity consists of planned arrival and departure events of two trains in different directions at the same station:
e, track interval movementThis type of activity is similar to the switch interval activity, but it is connected with two possible events e i，t And e j，t 。
The specific steps of establishing a train running diagram and stop plan collaborative adjustment model based on scene constraint and solving in S5 include:
s5.1, creating an objective function;
that is, the model is adjusted to minimize the sum of the deviation times between the actual occurrence times of all the scheduled events and the scheduled occurrence times;
where E represents a set comprising all of the scheduled events,representing event e t Time of occurrence, R e Representing a set of possible event components resulting from the decomposition of the planned event e, P e Representing the time of occurrence of the event e plan;
s5.2, creating constraint conditions; comprising the following steps: station stock selection constraint, schedule constraint, interference influence constraint on operation, shortest operation time constraint, train operation interval constraint and scene-based opportunity constraint;
s5.3, solving an objective function.
The invention has the beneficial effects that:
first: taking the internal structure of each station on the line into consideration, allowing the common stock way strategy of time adjustment, going over, additional parking, stock way replacement and opposite trains, adjusting the stop scheme of each train at each station while adjusting the train schedule, maximizing the utilization of line resources and improving the recovery capability;
second,: aiming at speed limit caused by strong wind, section additional running time uncertainty caused by wind speed variability is considered, scene-based constraint is established and converted into deterministic constraint, robustness of an adjustment result in the face of uncertain scene is improved, and the number of conflict constraint generated in the adjustment result due to section additional running time change in the dynamic adjustment process is reduced.
Drawings
FIG. 1 is a flow chart of a method for collaborative adjustment of a train operation diagram and a stop scheme provided by an embodiment of the invention;
fig. 2 is a schematic diagram illustrating the decomposition of a planned event when an event activity network is created in a collaborative adjustment method for a train operation diagram and a stop scheme according to an embodiment of the present invention;
fig. 3 is an operation diagram of a train after adjustment by the coordinated adjustment method of the train operation diagram and the stop scheme provided by the embodiment of the invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and specific examples so that those skilled in the art may better understand the present invention and practice it, and the embodiments of the present invention are not limited thereto.
As shown in fig. 1, a method for cooperatively adjusting a train operation diagram and a stop scheme includes the following steps:
s1, initializing basic parameters of a rolling time domain optimization framework, and controlling the starting time of a time window and a predicted time window to be H i The length of the control time window is H c The predicted time window length is H p And sets the current time window start time beat=h i ；
S2, updating the control time window range to be [ H, beating +H ] c ]And the prediction time window is [ beat, +H ] p ]；
S3, judging whether an interference event occurs in the range of the predicted time window, if so, executing S4, otherwise, returning to S2;
s4, searching all the occurrence events within the range of the prediction time window, and creating an event activity network;
s5, fixing an operation diagram before the starting time of the current time window, establishing a scene constraint-based train operation diagram and stop plan collaborative adjustment model, and solving to obtain an adjustment result R p ；
S6, executing current adjustmentResults R p An adjustment operation within the control time window range, and updating the current time window start time to beat=beat+h c ；
S7, judging whether the adjustment is finished, and if not, executing S2.
The step of establishing an event activity network in S4 specifically includes the following steps:
1. events:
in the present method, an event may refer to an arrival or departure event. In the planning chart, each arrival (departure) event has been planned. In the adjustment, the method divides each planned event into a plurality of possible events according to the available stock tracks.
As shown in fig. 2, event e a And e d For a planned arrival event of a train i at station i, in the model of the method, event e a Into n events, respectivelyLikewise, departure event e a Can also be decomposed intoHere, define the set->For event e a The resulting set of possible arrival events is decomposed. Accordingly, the set { I, II,3,., n } represents the planned arrival event e for train I a The set of occupied tracks may be selected after the adjustment.
2. Activity:
an activity includes and connects two events, in the method, the activity is divided into five categories:
a, train activity q= (e) in station a ，e d )∈A sta : the event e of planned arrival of such an event at a station by a train a And departure event e d Composition; in the adjustment, the activity q may be a stop activity or a pass-through no stop activity;
b, section train activity q= (e) a ，e d )∈A sec : such activities consist of a train of planned departure events at one station and its planned arrival events at the next station;
c, station interval movementSuch activities consist of planned arrival events (departure events) of two different trains at the same station in the same direction of travel;
d, switch interval activity q= (e) i ，e j )∈A sw : such an activity consists of planned arrival and departure events of two trains in different directions at the same station:
e, track interval movementThis type of activity is similar to the switch interval activity, but it is connected with two possible events e i，t And e j，t 。
The constructing a scene constraint-based train operation diagram and stop plan collaborative adjustment model in S5 specifically comprises the following steps:
1. objective function:
the objective function of the collaborative adjustment model is:
i.e. the model is tuned to minimize the sum of the deviation times between the actual occurrence times of all planned events and the planned occurrence times.
Where E represents a set comprising all of the scheduled events,representing event e t Time of occurrence, R e Representing a set of possible event components resulting from the decomposition of the planned event e, P e Representing the time of occurrence of event e-plan。
2. Constraint conditions
The constraints mainly include five classes:
2.1 station stock selection constraint:
constraint (2) in a set of possible events, some and only one can occur, 0-1 decision variablesRepresenting event e t Whether or not this happens, 1 if it happens and the scheduled event e will occur on track t after adjustment, otherwise 0.
In constraint (3), integer decision variablesRepresenting event e t The time of occurrence. Constraint (3) ensures that if a possible event occurs, it occurs for a time greater than or equal to 1, and if not, it is equal to 0. Constraint (4) ensures that the actual arrival event and actual departure event of a train at a station will occur on the same track.
If the train is planned to stop at the station, a 0-1 decision variable τ q =1 and still standing after adjustment, if passing through no stop, station activity may still be passing through no stop or stop after adjustment.
In general, the side line of the station is for the train to stop, and the constraint (6) ensures the requirement by passing the train without stopping directly from the main line of the station, wherein the combinationRepresenting event e t The decomposition results in a set of possible event compositions defined on the available positive line.
After adjustment, if the station activity is a stop activity, the stop time should be greater than or equal to the shortest stop time plus the additional travel time c caused by the occupied track t 。
2.2 schedule constraints:
constraint (8) ensures that the time that the scheduled event occurs after adjustment is greater than or equal to the time that the scheduled event occurs.
2.3 influence constraint of disturbances on operation:
in the method, the interference interval is regarded as a virtual station, and the difference from a common station is that the virtual station has only one station track and does not allow the overrun, and the running time of the train in the interference interval range is regarded as the stop time of the virtual station.And->Representing sets of arrival events and departure events at virtual stops, respectively. In the method, if the train overlaps with the disturbance in time and space in the parking process of the virtual station, the train is interfered by the disturbance event and is commanded to limit speed in the section represented by the virtual station, and the train needs multiple operation additional operation time in the section. Constraint (9) introduces the 0-1 decision variable +.>Representing the magnitude relation between the time when the train arrives at the virtual station and the interruption end time, if the train enters the virtual station before the end of the disturbance, +.>And vice versa is 0. Similarly, constraint (10) introduces a 0-1 decision variable +.>If the train starts from the virtual station after the start of the break +.>And vice versa is 0. Constraint (11) introduces a 0-1 decision variable gamma q For determining whether the train is being disturbed. Only when->When gamma is q =1, i.e. the train will not be dried only if it starts from the virtual station before the disturbance occurs or reaches the virtual station after the disturbance has endedThe other cases are disturbed.
2.4 shortest run time constraint:
to ensure the running safety of the train in the sections, the running time of the train in each section is more than or equal to the required running time, and the constraint (12) ensures that the requirements are met, wherein T is r Representing the shortest interval run time. The constraint (13) ensures that the train subjected to interference safely passes in the interference interval according to the speed limit requirement.
2.5 train operation interval constraint:
for the same train, the arrival (departure) interval of two different trains at the same station should be equal to or greater than the shortest interval, the parameter omega being in constraint (14) q For the shortest interval time between two events of an active q-connection, a 0-1 decision variable e q Representing the order in which two events of the active q-connection occur. In constraint (14), if E q =1, then represents e i The time taken to occur after adjustment is greater than or equal to e j The time after which the adjustment occurs.
Since the section has only one track in each direction, the train cannot be constrained in the section, constraint (15) ensures that the section does not go beyond, where v= (q) 1 ，q 2 ) Representing interval activity pairs consisting of two activities, q 1 Represents the departure activity of the station, q 2 Representing the arrival activity at the latter station. Psi s Is a set of all interval activity pairs.
If two different trains select the same track, the arrival time of the following train and the departure time of the preceding train need to be equal to or greater than a minimum separation time, such as described in the context of the bundle (16).
The constraint (17) specifies that the train cannot travel further on the track.
In the constraint (18), only when∈ q =1, i.e. ensuring the outgoing interval of trains on a track only makes sense if two trains select the same track. Otherwise E q ＝0。
∑ R ∈ q In fact represents the planned arrival event e i And departure event e j The order of occurrence after adjustment, wherein R represents event e i And e j Commonly available tracks. If sigma R ∈ q =0, then both the arrival and departure events of train i are after train j, a constraint can be derived (19).
Since the method allows the subtended trains to share the track in the station, the constraint of the subtended trains on the turnout needs to be considered separately.
Constraints (20) and (21) ensure the departure-to-departure interval of the opposite train at the switch, wherein in constraint (20) event e represents activity q= (e) i ，e j ) Is used to determine the departure event of the vehicle,the event e representing the definition plan defines a set of possible events in the reverse track. If->The trains associated with the departure event occupy the opposite track, and constraints (20) and (21) ensure that the arrival time of the opposing trains is spaced more than a minimum spacing. If->Meaning that the departure-related train does not select the opposite track, so that the two trains do not interfere with each other,/->Constraints (20) and (21) do not impose practical constraints on the departure to departure intervals between the trains.
Constraint (22) is similar to constraint (19),can represent the arrival and departure sequence of two opposite trains at the station switch.
From the objective function and constraints described above, an adjustment model can be obtained, as shown in (23):
2.6 scenario-based opportunity constraints:
t in constraint (13) a The interval is added with running time for representing wind speed, the constraint (13) is rewritten as a scene-based opportunity constraint according to the formula (24) for uncertain parameters, and the obtained opportunity constraint is converted into a deterministic constraint according to linearization, wherein the deterministic constraint is shown as the constraint (25).
In equation (24), phi is the set of all possible scene components, phi is a specific scene,for uncertain parameters +.>Uncertain parameter value of representative decision variable vector x under phi scene is +.>Make->The result of (2) is 0 or less, so that formula (24) represents that a part of +.>Is not true butThe probability of establishment is equal to or greater than α. In formula (25), a new decision variable +.>I.e. representing the scene phi->If so, the constraint represented by the formula (25) can be obtained.
The line data of all trains on all lines of the high-speed rail in jinghu and the day are selected as an example for display, and 23 stations (except for lines) are all arranged in 117 columns of the ascending and descending train. 4 winds were set as interference events all day on the kynghu high-speed rail, as shown in table 1.
| Sequence number | The interval of occurrence | Average additional run time | Start time | End time |
| 1 | 6 | 15 | 7:30 | 9:10 |
| 2 | 7 | 20 | 10:00 | 13:20 |
| 3 | 11 | 20 | 10:50 | 14:10 |
| 4 | 18 | 10 | 7:30 | 10:00 |
TABLE 1 interference event information
According to the rolling time domain optimization framework, the train operation diagram and the stop scheme collaborative adjustment model, the problem that four high wind events shown in table 1 interfere with a normal operation plan is solved, normal operation of a train is recovered as much as possible, the arrival time of the train and the corresponding stop scheme are obtained, and due to the fact that uncertainty of the high wind events is considered, the probability constraint added in the model also enables an adjustment result to have certain robustness, and feasibility of the adjustment scheme in the face of changing wind speed can be improved.
Those of ordinary skill in the art will appreciate that: the drawings are schematic representations of one embodiment only and the flow in the drawings is not necessarily required to practice the invention.
Claims (3)
1. A method for cooperatively adjusting a train operation diagram and a stop scheme is characterized by comprising the following steps:
s1, initializing basic parameters of a rolling time domain optimization framework, and controlling the starting time of a time window and a predicted time window to beControl of the power supplyThe length of the time window is->The prediction time window length is +.>And sets the current time window start time +.>；
S2, updating the control time window range to beIs +.>；
3, judging whether an interference event occurs in the range of the predicted time window, if so, executing S4, otherwise, returning to S2;
s4, searching all the occurrence events within the range of the prediction time window, and creating an event activity network;
the specific steps of creating the event activity network in S4 include:
s4.1, search event: searching in time windowAll planned departure events are planned, and all planned events are decomposed; the specific process of searching the event in S4.1 is as follows:
defining the arrival event of a train i at a station asThe departure event of a train i at the station is +.>Will->And->Respectively into n events, i.e. the arrival event is divided into +.>Departure event is classified as->,/>,...,/>The method comprises the steps of carrying out a first treatment on the surface of the Prescribed set->For event->Decomposing the resulting set of possible arrival events, wherein the set +.>Planned arrival event representing train i>The occupied track set can be selected after adjustment;
s4.2, creating an event activity network: obtaining a train activity set in a station, an interval train activity set, a station interval activity set, a turnout interval activity set and a stock track interval activity set according to all planned departure-arrival events obtained by searching in the S4.1 and all possible events obtained by decomposition, and finally obtaining an event activity network;
s5, fixing an operation diagram before the starting time of the current time window, establishing a scene constraint-based train operation diagram and stop plan collaborative adjustment model, and solving to obtain adjustmentResults；
S6, executing the current adjustment resultAn adjusting action within the control time window range and updating the current time window start time to +.>;
S7, judging whether the adjustment is finished, and if not, executing S2.
2. The method for collaborative adjustment of a train operation diagram and a stop solution according to claim 1, wherein the event activity network created in S4.2 specifically comprises:
a, train movement in station: such activities are planned arrival events at a station by a train>And departure event->Composition; in the adjustment, the activity q may be a stop activity or a pass-through no stop activity;
b, section train activity: such activities consist of a train of planned departure events at one station and its planned arrival events at the next station;
c, station interval movement: such activities consisting of two in the same direction of travelThe planned arrival event and departure event of different trains at the same station are formed;
d, switch interval movement: such an activity consists of planned arrival and departure events of two trains in different directions at the same station:
e, track interval movement: this type of activity is similar to the switch interval activity, but it is connected by two possible events +.>And->。
3. The method for collaborative adjustment of a train operation diagram and a stop plan according to claim 1, wherein the specific steps of establishing a scene constraint-based collaborative adjustment model for the train operation diagram and the stop plan in S5 and solving the model include:
s5.1, creating an objective function;
that is, the model is adjusted to minimize the sum of the deviation times between the actual occurrence times of all the scheduled events and the scheduled occurrence times;
wherein the method comprises the steps ofRepresenting a set comprising all planned events, +.>Representing event->Time of occurrence, < >>Representing events planned->Decomposing the resulting set of possible event components, < ->Representing event->Scheduled occurrence time;
s5.2, creating constraint conditions; comprising the following steps: station stock selection constraint, schedule constraint, interference influence constraint on operation, shortest operation time constraint, train operation interval constraint and scene-based opportunity constraint;
s5.3, solving an objective function.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103440422A (en) * | 2013-09-02 | 2013-12-11 | 东南大学 | Bus behind-schedule recovering method based on arrival time predication with time window |
| CN104875774A (en) * | 2015-06-16 | 2015-09-02 | 北京交通大学 | Train delay adjusting method and system based on urban rail transit working diagram |
| CN110775109A (en) * | 2019-11-06 | 2020-02-11 | 中国铁道科学研究院集团有限公司通信信号研究所 | High-speed railway train arrival time prediction method based on dispatching command system |
| CN113291356A (en) * | 2021-06-24 | 2021-08-24 | 北京交通大学 | Dynamic train tracking interval calculation method |
| CN113715875A (en) * | 2021-08-26 | 2021-11-30 | 北京交通大学 | Train operation regulation and control method and system for initial delay and interval speed limit |
-
2022
- 2022-07-13 CN CN202210821364.0A patent/CN115339489B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103440422A (en) * | 2013-09-02 | 2013-12-11 | 东南大学 | Bus behind-schedule recovering method based on arrival time predication with time window |
| CN104875774A (en) * | 2015-06-16 | 2015-09-02 | 北京交通大学 | Train delay adjusting method and system based on urban rail transit working diagram |
| CN110775109A (en) * | 2019-11-06 | 2020-02-11 | 中国铁道科学研究院集团有限公司通信信号研究所 | High-speed railway train arrival time prediction method based on dispatching command system |
| CN113291356A (en) * | 2021-06-24 | 2021-08-24 | 北京交通大学 | Dynamic train tracking interval calculation method |
| CN113715875A (en) * | 2021-08-26 | 2021-11-30 | 北京交通大学 | Train operation regulation and control method and system for initial delay and interval speed limit |
Non-Patent Citations (2)
| Title |
|---|
| 基于高铁快运的城市配送需求预测及选址路径优化研究;彭军等;《中国优秀硕士学位论文全文数据库 基础科学辑》(第01期);第A002-890页 * |
| 考虑旅游效用提升的高铁列车运行方案优化研究;马振国;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》(第02期);第C033-539页 * |
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