Vehicle scheduling method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a vehicle scheduling method and device, equipment and a storage medium. The method comprises the steps of firstly obtaining a to-be-dispatched departure train number, a to-be-dispatched departure train number, a to-be-dispatched receiving train number and a to-be-dispatched receiving station track, and then determining a vehicle dispatching strategy according to the to-be-dispatched departure train number, the to-be-dispatched receiving train number, the to-be-dispatched receiving station track and a preset dispatching rule, the preset scheduling rules comprise departure rules arranged according to a first priority sequence and receiving rules arranged according to a second priority sequence, the vehicle scheduling strategies comprise a vehicle departure strategy and a vehicle receiving strategy, the vehicle departure strategy is used for indicating a departure vehicle number corresponding to a to-be-scheduled departure vehicle number, and the vehicle receiving strategy is used for indicating a to-be-scheduled departure vehicle number; the vehicle receiving strategy is used for indicating the vehicle receiving station track corresponding to the to-be-dispatched vehicle receiving number. According to the method provided by the invention, rapid dispatching of departure and collection of the vehicles is realized, and the dispatching efficiency of the vehicles is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle dispatching technology, and in particular to a vehicle dispatching method, apparatus, equipment and storage medium. Background Technology

[0002] In urban rail transit systems, train arrival and departure are crucial for ensuring the safety and punctuality of mainline operations. Especially in depot (train yard) scheduling and management, the efficiency of these tasks directly impacts the overall operational efficiency of the rail transit network. In actual operation, train arrival and departure require consideration of various complex factors: for example, vehicle maintenance operations (such as daytime and evening inspections), car washing, lubrication, and other tasks. Different tasks place different demands on train readiness conditions, return time to the depot, and track allocation.

[0003] Traditionally, train dispatching and receiving tasks are mainly determined manually. Dispatchers rely on experience to determine the matching relationship between train numbers and car numbers, thereby carrying out vehicle dispatching operations such as track allocation for train dispatching and receiving.

[0004] However, traditional manual vehicle dispatching plans rely on experience and judgment, which cannot quickly respond to complex scenarios and result in low vehicle dispatching efficiency. Summary of the Invention

[0005] This application provides a vehicle scheduling method, apparatus, equipment, and storage medium to improve vehicle scheduling efficiency.

[0006] In a first aspect, embodiments of this application provide a vehicle dispatching method, comprising:

[0007] Obtain the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, and the track to be dispatched;

[0008] Based on the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, the train track to be dispatched, and preset dispatching rules, a vehicle dispatching strategy is determined. The preset dispatching rules include departure rules arranged in a first priority order and arrival rules arranged in a second priority order. The vehicle dispatching strategy includes a vehicle departure strategy and a vehicle arrival strategy. The vehicle departure strategy is used to indicate the departure number corresponding to the train number to be dispatched, and the vehicle arrival strategy is used to indicate the arrival track corresponding to the train number to be dispatched.

[0009] In one or more embodiments, determining the vehicle dispatching strategy based on the departure number to be dispatched, the departure number to be dispatched, the arrival number to be dispatched, the arrival track to be dispatched, and preset dispatching rules includes:

[0010] The vehicle departure strategy is determined based on the train number to be dispatched, the train number to be dispatched, and the departure rules in the preset dispatch rules.

[0011] The vehicle recall strategy is determined based on the vehicle number to be recalled, the track to be recalled, and the recall rules in the preset scheduling rules.

[0012] In one or more embodiments, determining the vehicle departure strategy based on the vehicle number to be dispatched, the vehicle number to be dispatched, and the departure rules in the preset dispatch rules includes:

[0013] S1, determine the highest priority departure rule from the preset scheduling rules;

[0014] S2, according to the highest priority departure rule, the departure number to be scheduled and the departure number to be scheduled are matched to obtain at least one first candidate departure combination, the candidate departure combination includes candidate departure number and corresponding candidate departure number;

[0015] S3, perform a first constraint verification on the at least one first candidate departure combination, and obtain at least one second candidate departure combination if the verification is successful. The first constraint verification is used to indicate the scheduling constraints of the candidate departure combination.

[0016] S4, perform a second constraint verification on the at least one second candidate departure combination to obtain a first score corresponding to the at least one second candidate departure combination. The second constraint verification is used to indicate the scheduling effect of the candidate departure combination.

[0017] S5, the third candidate departure combination corresponding to the maximum value in the first score corresponding to the at least one second candidate departure combination is determined as the highest priority candidate departure combination corresponding to the highest priority departure rule;

[0018] S6, take the next priority departure rule of the highest priority departure rule as the highest priority departure rule in the preset scheduling rules, repeat steps S1-S6 until all first candidate departure combinations are verified, and determine the vehicle departure strategy.

[0019] In one or more embodiments, the vehicle number to be dispatched carries a corresponding vehicle number attribute, and the track to be dispatched carries corresponding track status data.

[0020] Accordingly, determining the vehicle recall strategy based on the vehicle number to be recalled, the lane to be recalled, and the recall rules in the preset scheduling rules includes:

[0021] S7. Based on the current vehicle number in the vehicle number to be dispatched and the vehicle collection rule in the preset dispatch rules, determine the first vehicle collection rule corresponding to the vehicle number attribute corresponding to the current vehicle number.

[0022] S8. Based on the first vehicle retrieval rule, the vehicle retrieval track to be scheduled, and the track status data corresponding to the vehicle retrieval track to be scheduled, determine at least one candidate vehicle retrieval track and its corresponding track parameters.

[0023] S9. Determine the second score corresponding to the at least one candidate depot lane based on the at least one candidate depot lane and its corresponding lane parameters, as well as the first preset weight.

[0024] S10, the third candidate decommissioning lane corresponding to the maximum value of the second scores corresponding to the at least one candidate decommissioning lane is determined as the target decommissioning lane corresponding to the current decommissioning car number;

[0025] S11, take the next vehicle number of the current vehicle number as the current vehicle number in the vehicle numbers to be dispatched, repeat steps S7-S11 until all vehicle numbers to be dispatched have a corresponding vehicle lane, and determine the vehicle dispatching strategy.

[0026] In one or more embodiments, after determining the vehicle dispatching strategy based on the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, the train track to be dispatched, and preset dispatching rules, the method further includes:

[0027] Obtain the third score of the preset scheduling rule and historical vehicle scheduling data, wherein the historical vehicle scheduling data includes historical departure success rate and historical return success rate;

[0028] Based on the historical vehicle scheduling data, the third score of the preset scheduling rule is updated to obtain the updated fourth score;

[0029] Based on the fourth score and the preset threshold, the first priority order and the second priority order are adjusted.

[0030] In one or more embodiments, updating the third score of the preset scheduling rule based on the historical vehicle scheduling data to obtain the updated fourth score includes:

[0031] Based on the historical vehicle scheduling data, the rule adaptation success rate, manual intervention rate, and execution stability data are determined. The rule adaptation success rate is used to indicate the ratio of the number of successful matches of the preset scheduling rule to the total number of matches. The manual intervention rate is used to indicate the ratio of the number of manual adjustments after the preset scheduling rule failed to match to the total number of matches. The execution stability data is used to indicate the quantitative value of the volatility of the preset scheduling rule matching.

[0032] Based on the rule adaptation success rate, the manual intervention rate, the execution stability data, and the second preset weight, the third score of the preset scheduling rule is updated to obtain the updated fourth score.

[0033] In one or more embodiments, after adjusting the first priority order and the second priority order according to the fourth score and a preset threshold, the method further includes:

[0034] Obtain real-time departure status information, real-time return status information, and return lane occupancy status information;

[0035] Based on the real-time departure status information, the real-time return status information, and the return lane occupancy status information, an abnormal scheduling type is determined, and the abnormal scheduling type includes at least one of vehicle status change, lane occupancy conflict, and abnormal lockout.

[0036] The first priority order and the second priority order are adjusted according to the abnormal scheduling type.

[0037] Secondly, embodiments of this application provide a vehicle dispatching device, comprising:

[0038] The acquisition module is used to acquire the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, and the track to be dispatched.

[0039] The processing module is used to determine a vehicle dispatching strategy based on the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, the train track to be dispatched, and preset dispatching rules. The preset dispatching rules include departure rules arranged in a first priority order and arrival rules arranged in a second priority order. The vehicle dispatching strategy includes a vehicle departure strategy and a vehicle arrival strategy. The vehicle departure strategy is used to indicate the departure number corresponding to the train number to be dispatched, and the vehicle arrival strategy is used to indicate the arrival track corresponding to the train number to be dispatched.

[0040] In one or more embodiments, the processing module is specifically used for:

[0041] The vehicle departure strategy is determined based on the train number to be dispatched, the train number to be dispatched, and the departure rules in the preset dispatch rules.

[0042] The vehicle recall strategy is determined based on the vehicle number to be recalled, the track to be recalled, and the recall rules in the preset scheduling rules.

[0043] In one or more embodiments, the processing module determines the vehicle departure strategy based on the train number to be scheduled, the train number to be scheduled, and the departure rules in the preset scheduling rules, specifically for:

[0044] S1, determine the highest priority departure rule from the preset scheduling rules;

[0045] S2, according to the highest priority departure rule, the departure number to be scheduled and the departure number to be scheduled are matched to obtain at least one first candidate departure combination, the candidate departure combination includes candidate departure number and corresponding candidate departure number;

[0046] S3, perform a first constraint verification on the at least one first candidate departure combination, and obtain at least one second candidate departure combination if the verification is successful. The first constraint verification is used to indicate the scheduling constraints of the candidate departure combination.

[0047] S4, perform a second constraint verification on the at least one second candidate departure combination to obtain a first score corresponding to the at least one second candidate departure combination. The second constraint verification is used to indicate the scheduling effect of the candidate departure combination.

[0048] S5, the third candidate departure combination corresponding to the maximum value in the first score corresponding to the at least one second candidate departure combination is determined as the highest priority candidate departure combination corresponding to the highest priority departure rule;

[0049] S6, take the next priority departure rule of the highest priority departure rule as the highest priority departure rule in the preset scheduling rules, repeat steps S1-S6 until all first candidate departure combinations are verified, and determine the vehicle departure strategy.

[0050] In one or more embodiments, the vehicle number to be dispatched carries a corresponding vehicle number attribute, and the track to be dispatched carries corresponding track status data.

[0051] Accordingly, the processing module determines the vehicle retrieval strategy based on the vehicle number to be dispatched, the track to be dispatched, and the retrieval rules in the preset dispatch rules, specifically for:

[0052] S7. Based on the current vehicle number in the vehicle number to be dispatched and the vehicle collection rule in the preset dispatch rules, determine the first vehicle collection rule corresponding to the vehicle number attribute corresponding to the current vehicle number.

[0053] S8. Based on the first vehicle retrieval rule, the vehicle retrieval track to be scheduled, and the track status data corresponding to the vehicle retrieval track to be scheduled, determine at least one candidate vehicle retrieval track and its corresponding track parameters.

[0054] S9. Determine the second score corresponding to the at least one candidate depot lane based on the at least one candidate depot lane and its corresponding lane parameters, as well as the first preset weight.

[0055] S10, the third candidate decommissioning lane corresponding to the maximum value of the second scores corresponding to the at least one candidate decommissioning lane is determined as the target decommissioning lane corresponding to the current decommissioning car number;

[0056] S11, take the next vehicle number of the current vehicle number as the current vehicle number in the vehicle numbers to be dispatched, repeat steps S7-S11 until all vehicle numbers to be dispatched have a corresponding vehicle lane, and determine the vehicle dispatching strategy.

[0057] In one or more embodiments, after determining the vehicle dispatching strategy based on the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, the train track to be dispatched, and the preset dispatching rules, the processing module is further configured to:

[0058] Obtain the third score of the preset scheduling rule and historical vehicle scheduling data, wherein the historical vehicle scheduling data includes historical departure success rate and historical return success rate;

[0059] Based on the historical vehicle scheduling data, the third score of the preset scheduling rule is updated to obtain the updated fourth score;

[0060] Based on the fourth score and the preset threshold, the first priority order and the second priority order are adjusted.

[0061] In one or more embodiments, the processing module updates the third score of the preset scheduling rule based on the historical vehicle scheduling data to obtain an updated fourth score, specifically for:

[0062] Based on the historical vehicle scheduling data, the rule adaptation success rate, manual intervention rate, and execution stability data are determined. The rule adaptation success rate is used to indicate the ratio of the number of successful matches of the preset scheduling rule to the total number of matches. The manual intervention rate is used to indicate the ratio of the number of manual adjustments after the preset scheduling rule failed to match to the total number of matches. The execution stability data is used to indicate the quantitative value of the volatility of the preset scheduling rule matching.

[0063] Based on the rule adaptation success rate, the manual intervention rate, the execution stability data, and the second preset weight, the third score of the preset scheduling rule is updated to obtain the updated fourth score.

[0064] In one or more embodiments, after adjusting the first priority order and the second priority order according to the fourth score and the preset threshold, the processing module is further configured to:

[0065] Obtain real-time departure status information, real-time return status information, and return lane occupancy status information;

[0066] Based on the real-time departure status information, the real-time return status information, and the return lane occupancy status information, an abnormal scheduling type is determined, and the abnormal scheduling type includes at least one of vehicle status change, lane occupancy conflict, and abnormal lockout.

[0067] The first priority order and the second priority order are adjusted according to the abnormal scheduling type.

[0068] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0069] The memory stores computer-executed instructions;

[0070] The processor executes computer execution instructions stored in the memory, such that the processor, when executed, is used to implement the method described in the first aspect and any of the embodiments above.

[0071] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods described in the first aspect and any of the embodiments above.

[0072] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, is used to implement a vehicle scheduling method as described in the first aspect and various possible implementations of the first aspect.

[0073] This application provides a vehicle scheduling method, apparatus, device, and storage medium. The method first obtains the train number to be scheduled for departure, the train number to be scheduled for departure, the train number to be scheduled for arrival, and the train track to be scheduled for arrival. Then, based on the train number to be scheduled for departure, the train number to be scheduled for departure, the train number to be scheduled for arrival, the train track to be scheduled for arrival, and preset scheduling rules, a vehicle scheduling strategy is determined. The preset scheduling rules include departure rules arranged in a first priority order and arrival rules arranged in a second priority order. The vehicle scheduling strategy includes a vehicle departure strategy and a vehicle arrival strategy. The vehicle departure strategy indicates the train number corresponding to the train number to be scheduled for departure, and the vehicle arrival strategy indicates the train track corresponding to the train number to be scheduled for arrival. In the above method, by acquiring information such as the departure number, vehicle number, arrival number, and arrival lane of the vehicles to be dispatched, dispatchers can quickly grasp all the information of vehicles to be dispatched, avoiding the tedious process of manual querying and judgment, and significantly improving dispatching efficiency. Combined with the departure and arrival rules in the preset dispatching rules, dispatching can be automated according to the priority of departure and arrival, thereby reducing human intervention and dispatching time. Dispatching according to the departure and arrival priority rules ensures that important trains and resources are given priority, avoiding conflicts or resource idleness. When multiple vehicles need to depart and arrive, the priority of the rules effectively ensures the orderly conduct of vehicle dispatching. Determining vehicle departure and arrival strategies according to preset dispatching rules effectively improves vehicle dispatching efficiency and can effectively avoid safety hazards caused by improper dispatching. Attached Figure Description

[0074] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0075] Figure 1 A flowchart illustrating the vehicle scheduling method provided in this application embodiment. Figure 1 ;

[0076] Figure 2 A flowchart illustrating the vehicle scheduling method provided in this application embodiment. Figure 2 ;

[0077] Figure 3 A flowchart illustrating the vehicle scheduling method provided in this application embodiment. Figure 3 ;

[0078] Figure 4 A flowchart illustrating the vehicle scheduling method provided in this application embodiment. Figure 4 ;

[0079] Figure 5 A schematic diagram of the structure of the vehicle dispatching device provided in the embodiments of this application;

[0080] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0081] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0082] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0083] Before introducing the embodiments of this application, the application background of the embodiments of this application will be explained first:

[0084] In urban rail transit systems, train arrival and departure are crucial for ensuring the safety and punctuality of mainline operations. Especially in depot (train yard) scheduling and management, the efficiency of these tasks directly impacts the overall operational efficiency of the rail transit network. In actual operation, train arrival and departure require consideration of various complex factors: for example, vehicle maintenance operations (such as daytime and evening inspections), car washing, lubrication, and other tasks. Different tasks place different demands on train readiness conditions, return time to the depot, and track allocation.

[0085] Traditionally, train dispatching and receiving tasks are mainly determined manually. Dispatchers rely on experience to determine the matching relationship between train numbers and car numbers, thereby carrying out vehicle dispatching operations such as track allocation for train dispatching and receiving.

[0086] However, traditional manual vehicle dispatching plans rely on experience and judgment, which cannot quickly respond to complex scenarios and result in low vehicle dispatching efficiency.

[0087] The vehicle dispatching method provided in this application aims to solve the aforementioned technical problems of the prior art. The technical concept of this application is as follows: An automated dispatching process can replace manual formulation of departure and arrival plans, thereby quickly determining departure and arrival dispatching strategies. First, information such as the departure number, departure vehicle number, arrival vehicle number, and arrival lane of the vehicle to be dispatched is obtained to provide a basis for subsequent decision-making. Next, considering that departure and arrival are the two core aspects of vehicle dispatching, rules need to be formulated separately, and there is a priority difference between the two. Therefore, a first-priority departure rule and a second-priority arrival rule are set as preset dispatching rules. Finally, based on the obtained basic information and preset rules, the corresponding vehicle departure strategy (clarifying the correspondence between departure numbers and vehicle numbers) and arrival strategy (clarifying the correspondence between arrival vehicle numbers and lanes) are naturally derived, forming a complete vehicle dispatching logic.

[0088] The execution subject of this application embodiment is an electronic device, which can be a terminal device, such as a laptop, desktop computer, or tablet computer, or a server. In practical applications, whether the electronic device is a terminal device or a server can be determined according to the actual situation, and no specific limitation is imposed on it.

[0089] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0090] Figure 1 A flowchart illustrating the vehicle scheduling method provided in this application embodiment. Figure 1 .like Figure 1 As shown, the vehicle dispatching method includes the following steps:

[0091] S110: Obtain the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, and the track to be dispatched.

[0092] In this step, in order to efficiently dispatch vehicles, we can first obtain the departure number, departure number, arrival number, and arrival track of the vehicles to be dispatched, so as to provide accurate and complete data for subsequent vehicle departure and arrival dispatch.

[0093] For example, the vehicle number to be dispatched is used to uniquely identify the vehicle to be dispatched, and the vehicle number to be dispatched for return is used to uniquely identify the vehicle to be dispatched for return.

[0094] In one possible implementation, the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, and the track to be dispatched can be extracted synchronously from the rail vehicle operation management system (such as the depot integrated monitoring platform).

[0095] For trains awaiting dispatch, obtain attribute information such as departure time, departure direction, and vehicle type requirements. For train numbers awaiting dispatch, filter available train numbers that are not under maintenance, not faulty, and not stored, including information such as the corresponding vehicle type and current location. For train numbers awaiting return, obtain a list of train numbers planned for return to the depot and information on maintenance requirements, washing / wheel turning, and other tasks after the vehicles return to the depot. For tracks awaiting return, collect the real-time status of all tracks within the depot, including whether they are occupied, maintenance function configuration, and electrical section availability.

[0096] S120. Determine the vehicle dispatching strategy based on the departure number to be dispatched, the departure number to be dispatched, the arrival number to be dispatched, the arrival track to be dispatched, and the preset dispatching rules.

[0097] The preset scheduling rules include departure rules arranged in the first priority order and return rules arranged in the second priority order. The vehicle scheduling strategy includes a vehicle departure strategy and a vehicle return strategy. The vehicle departure strategy is used to indicate the departure car number corresponding to the departure number to be scheduled, and the vehicle return strategy is used to indicate the return track corresponding to the return car number to be scheduled.

[0098] In this step, the train number to be dispatched, the train number to be dispatched, and the dispatch rules arranged in the first priority order are matched to obtain a vehicle dispatch strategy for indicating the departure number corresponding to the train number to be dispatched. In addition, the vehicle return strategy for indicating the return lane corresponding to the return number to be dispatched is obtained based on the return number to be dispatched, the return lane to be dispatched, and the return rules arranged in the second priority order.

[0099] For example, the departure rules are sorted by first priority: peak-hour trains are given priority in matching available trains, trains of the same model are given priority in allocation, and trains with the shortest shunting distance are given priority; the return rules are sorted by second priority: maintenance trains are given priority in matching maintenance tracks, trains with functional requirements are given priority in matching dedicated tracks, and trains with the lowest track occupancy rate are given priority.

[0100] In one possible implementation, after step S120 described above, the vehicle dispatching method further includes the following steps:

[0101] S131. Obtain the third score and historical vehicle scheduling data of the preset scheduling rules;

[0102] Historical vehicle dispatch data includes historical departure success rate and historical return success rate;

[0103] For example, the third score of the preset scheduling rule is an initially set quantitative indicator of the rule's effectiveness (such as a maximum score of 100 points, with initial scores assigned to departure / return rules based on human experience), used to initially determine the priority of departure and return rules in the preset scheduling rules.

[0104] Historical departure success rate represents the proportion of trains successfully departing in the past when the train number-car number combination matched by the rules is matched. Historical arrival success rate represents the proportion of trains arriving without conflict when the train number-track combination assigned by the rules is matched. Both types of data are extracted from the historical database of the dispatching system to ensure data authenticity and relevance.

[0105] In addition, historical vehicle dispatching data also includes records of manual intervention and results of anomaly handling. The records of manual intervention are obtained by converting every manual intervention in the system plan recorded by the rail vehicle operation management system into feedback data.

[0106] S132. Based on historical vehicle dispatch data, update the third score of the preset dispatch rules to obtain the updated fourth score.

[0107] In one possible implementation, step S132 may further include the following steps:

[0108] Step 1: Based on historical vehicle dispatch data, determine the rule adaptation success rate, manual intervention rate, and execution stability data;

[0109] Among them, the rule adaptation success rate is used to indicate the ratio of the number of successful matches of the preset scheduling rule to the total number of matches; the manual intervention rate is used to indicate the ratio of the number of manual adjustments after the preset scheduling rule failed to match to the total number of matches; and the execution stability data is used to indicate the quantitative value of the volatility of the preset scheduling rule matching.

[0110] For example, historical vehicle scheduling data includes the process of determining historical departure and arrival strategies. During this process, the execution results of preset scheduling rules are recorded, including: rule matching success / failure, rule matching time, occurrence / absence of human intervention, and occurrence / absence of delays, thereby determining the rule adaptation success rate, human intervention rate, time efficiency, and execution stability data.

[0111] Step 2: Based on the rule adaptation success rate, manual intervention rate, execution stability data, and the second preset weight, update the third score of the preset scheduling rule to obtain the updated fourth score.

[0112] For example, for each rule in the preset scheduling rules, its fourth score Score4 = w1 × rule adaptation success rate + w2 × (1 − human intervention rate) + w3 × time efficiency + w4 × execution stability data, where w1, w2, w3, and w4 represent weight parameters, which can be dynamically adjusted according to scheduling requirements.

[0113] S133. Adjust the first priority order and the second priority order according to the fourth score and the preset threshold.

[0114] For example, the fourth score is compared with a preset threshold. If the fourth score is greater than the preset threshold, the priority of the rule corresponding to the fourth score in the preset scheduling rules is increased; if the fourth score is equal to the preset threshold, the priority of the rule corresponding to the fourth score in the preset scheduling rules remains unchanged; if the fourth score is less than the preset threshold, the priority of the rule corresponding to the fourth score in the preset scheduling rules is decreased or the rule is marked as "to be deleted".

[0115] In addition, in one possible implementation, the vehicle scheduling method can also use a large language model to analyze historical scheduling data based on natural language processing technology, generate rule templates, and optimize preset scheduling rules.

[0116] For example, the system will convert manual correction behavior (such as "a certain train number has excessive energy consumption due to excessive shunting distance") into "shunting distance limit rule" and automatically add it to the preset scheduling rules.

[0117] In one possible implementation, after step S133 described above, the vehicle dispatching method further includes the following steps:

[0118] Step 1: Obtain real-time departure status information, real-time return status information, and return lane occupancy status information;

[0119] For example, key status data during vehicle dispatching can be collected in real time to provide a real-time and accurate data source for anomaly identification.

[0120] Real-time departure status information includes the current status of the car number corresponding to the train to be dispatched (such as whether there is a sudden failure or whether it is delayed), departure preparation progress, etc.; real-time return status information includes the actual return progress of the car number to be dispatched, sudden vehicle failure, etc.; return track occupancy status information includes the real-time occupancy status of all tracks in the depot (such as whether it is temporarily occupied, the duration of occupation, and whether it has been unlocked). All data is dynamically obtained through the depot real-time monitoring system interface in the rail vehicle operation management system to ensure timeliness.

[0121] For example, train number 108 of train G105, which is scheduled to depart, suddenly experiences a braking failure (real-time departure status). Train number 125, which is scheduled to return to the depot, is delayed due to line congestion (real-time return status). The track 006 originally allocated to train 125 is occupied by a temporary maintenance vehicle (return track occupied status), while track 008 is in a normal idle state.

[0122] Step 2: Determine the type of abnormal dispatch based on real-time departure status information, real-time arrival status information, and arrival lane occupancy status information;

[0123] Among them, abnormal scheduling types include at least one of vehicle status changes, lane occupancy conflicts, and abnormal locking;

[0124] For example, vehicle status change refers to the inconsistency between the actual status and the planned status of the dispatched departure train number and the dispatched arrival train number (such as sudden failure or delay); lane occupancy conflict refers to the planned arrival lane being occupied by unplanned vehicles, which conflicts with the parking needs of the arrival train number; abnormal locking refers to the lane or train number being unexpectedly locked by an external system and unable to be used as planned. The specific abnormal type can be identified by comparing the status and matching the rules.

[0125] For example, the sudden malfunction of vehicle number 108 is an anomaly of "vehicle status change"; track 006 is occupied by a vehicle undergoing temporary maintenance, which conflicts with the parking plan of vehicle number 125 waiting to be picked up, and is an anomaly of "track occupancy conflict"; there is no track or the vehicle number is unexpectedly locked, so the anomaly dispatch type this time is two categories: vehicle status change and track occupancy conflict.

[0126] Step 3: Adjust the first priority order and the second priority order according to the abnormal scheduling type.

[0127] For example, based on the determined abnormal scheduling type, the first priority order of the departure rules and the second priority order of the return rules are adjusted accordingly to ensure that the rules are adapted to abnormal scenarios.

[0128] The processing logic has been adjusted to prioritize rules that can resolve the current anomaly, increase their priority, and ensure that anomaly-handling rules are executed first in subsequent scheduling and matching, thereby quickly generating a scheduling scheme that adapts to the anomaly.

[0129] In one possible implementation, the exception priority score corresponding to the exception scheduling type is determined based on the exception urgency level (e.g., whether the impact immediately blocks departure), the exception impact range (e.g., single vehicle / single track / entire section), and the exception occurrence frequency (statistical value, normalized).

[0130] If the abnormal priority score is greater than 0.7, the vehicle dispatching strategy will be immediately re-arranged; if the abnormal priority score is greater than 0.4 and less than or equal to 0.7, the vehicle dispatching strategy will be partially adjusted and manual confirmation will be requested; if the abnormal priority score is less than 0.4, only the log will be recorded and no immediate action will be triggered.

[0131] The vehicle dispatching method provided in this application first obtains the departure number, departure number, arrival number, and arrival lane to be dispatched. Then, based on the departure number, departure number, arrival number, arrival lane, and preset dispatching rules, a vehicle dispatching strategy is determined. The preset dispatching rules include departure rules arranged in a first priority order and arrival rules arranged in a second priority order. The vehicle dispatching strategy includes a vehicle departure strategy and a vehicle arrival strategy. The vehicle departure strategy is used to indicate the departure number corresponding to the departure number to be dispatched, and the vehicle arrival strategy is used to indicate the arrival lane corresponding to the arrival number to be dispatched. In this embodiment, by acquiring information such as the departure number, vehicle number, arrival number, and arrival lane of the vehicles to be dispatched, dispatchers can quickly grasp all information on vehicles to be dispatched, avoiding the tedious process of manual querying and judgment, and significantly improving dispatching efficiency. Combined with the departure and arrival rules in the preset dispatching rules, dispatching can be automated based on departure and arrival priorities, thereby reducing human intervention and dispatching time. Dispatching according to the departure and arrival priority rules ensures that important trains and resources are prioritized, avoiding conflicts or resource idleness. When multiple vehicles need to depart and arrive, the priority of the rules effectively ensures the orderly conduct of vehicle dispatching. Determining vehicle departure and arrival strategies based on preset dispatching rules effectively improves vehicle dispatching efficiency and can effectively avoid safety hazards caused by improper dispatching.

[0132] Based on the above embodiments, Figure 2 A flowchart illustrating the vehicle scheduling method provided in this application embodiment. Figure 2 .like Figure 2 As shown, a possible implementation of step S120 above also includes the following steps:

[0133] S210. Determine the vehicle departure strategy based on the train number to be dispatched, the train number to be dispatched, and the departure rules in the preset dispatch rules.

[0134] In this step, the train number to be scheduled, the train number to be scheduled, and the departure rules arranged in the first priority order are matched to obtain the vehicle departure strategy used to indicate the departure number corresponding to the train number to be scheduled.

[0135] In one possible implementation, Figure 3 A flowchart illustrating the vehicle scheduling method provided in this application embodiment. Figure 3 .like Figure 3 As shown, one possible implementation of step S210 above includes the following steps:

[0136] S1, determine the highest priority departure rule from the preset scheduling rules;

[0137] For example, the rule with the highest priority is selected from the departure rules of the preset scheduling rules and used as the core basis for matching train number and vehicle number.

[0138] The preset departure rules are arranged in order of first priority (such as priority for peak-hour trains, priority for trains of the same type, and priority for trains with the shortest shunting distance). The priority can be determined by the third score of the preset dispatching rule. The higher the score, the higher the priority, ensuring that the departure rule with the best adaptability and effectiveness is used first.

[0139] S2, according to the highest priority departure rule, match the departure number to be scheduled with the departure number to be scheduled to obtain at least one first candidate departure combination;

[0140] Among them, the candidate departure combinations include candidate departure train numbers and corresponding candidate departure car numbers;

[0141] For example, based on the highest priority departure rule, suitable targets are selected from the departure numbers and departure vehicle numbers to be scheduled, to obtain at least one first candidate departure combination.

[0142] S3, perform first constraint verification on at least one first candidate departure combination, and if the verification is successful, obtain at least one second candidate departure combination;

[0143] The first constraint verification is used to indicate the scheduling constraints of the candidate departure combinations;

[0144] For example, the first constraint verification (hard constraint) is performed on the first candidate departure combination, eliminating combinations that do not meet the mandatory scheduling constraint and retaining the legal candidates.

[0145] The first constraint verification is a prerequisite that must be met, including vehicle type matching constraint (the vehicle type required for the train number must be consistent with the vehicle number's vehicle type), vehicle number availability status constraint (not under maintenance, not stored, not faulty), location constraint (the track or garage where the vehicle number is located should be physically accessible from the train's departure point), and operational safety constraint (blocking constraint: if the candidate vehicle number is occupied by a preceding train or its location is blocked, it is unavailable; power supply area constraint: power supply for two consecutive train departures cannot exceed the power supply area threshold), to ensure that the combination is feasible to execute.

[0146] In one possible implementation, if all first candidate departure combinations fail the first constraint verification, the departure rule with the highest current priority is marked as "adaptation failed", and the departure rule with the next lower priority is selected to re-execute step S1.

[0147] S4, perform second constraint verification on at least one second candidate departure combination to obtain the first score corresponding to at least one second candidate departure combination;

[0148] The second constraint verification is used to indicate the scheduling effect of candidate departure combinations;

[0149] For example, a second constraint verification (soft constraint) is performed on at least one second candidate departure combination, and the scheduling effect is reflected by quantitative scoring, providing a basis for combination selection.

[0150] The second constraint verification focuses on optimization objectives such as efficiency, energy saving, and resource balance. The first score is calculated according to a preset scoring formula, and the higher the score, the better the scheduling effect.

[0151] The preset scoring formula is expressed as follows:

[0152]

[0153] in, This indicates the second candidate starting combination. This indicates the degree to which the second candidate departure combination meets the highest pre-priority rule (such as vehicle type priority or time priority). This indicates the shunting distance for the second candidate departure combination (the shorter the distance, the higher the score). This indicates the frequency of use of the train number in the second candidate departure combination. This indicates the energy-saving factor data for the second candidate train combination.

[0154] In one possible implementation, a multi-objective optimization algorithm is used to search for the Pareto optimal solution. This algorithm includes at least one of genetic algorithms and particle swarm optimization. Based on the generation of the Pareto optimal solution, a balance can be found between shunting distance and the frequency of vehicle usage, avoiding suboptimal solutions under single-objective rules and ensuring the global optimality of the scheduling strategy under multiple constraints.

[0155] S5, determine the third candidate departure combination corresponding to the maximum value in the first score corresponding to at least one second candidate departure combination as the highest priority candidate departure combination corresponding to the highest priority departure rule;

[0156] For example, from at least one second candidate departure combination, the combination with the highest score in the first score is selected as the optimal candidate departure combination corresponding to the highest priority departure rule.

[0157] S6. Take the next priority departure rule of the highest priority departure rule as the highest priority departure rule in the preset scheduling rules, and repeat steps S1-S6 until all first candidate departure combinations are verified and the vehicle departure strategy is determined.

[0158] For example, delete the highest priority departure rule that has been adapted, update the preset scheduling rule, and repeat steps S1-S6 until all departures to be scheduled are matched with a vehicle number, thus generating a complete vehicle departure strategy.

[0159] In one possible implementation, once all the first candidate departure combinations have been verified, a vehicle departure strategy is obtained. The number of times the departure strategy is optimized is set, and the vehicle departure strategy is then optimized and updated.

[0160] For the departure combinations in the vehicle departure strategy, the combination score for each departure combination is determined based on the availability of vehicles in the combination, the time difference between the estimated arrival time and the departure time, the matching degree of vehicle attributes (including vehicle type, maintenance time, and departure lane), and the conflict risk estimation data. The calculation formula is: Combination score = ωA × vehicle availability + ωT × exp (-time difference / time decay constant τ) + ωR × vehicle attribute matching degree - ωC × conflict risk estimation data, where ωA, ωT, ωR, and ωC are all weighting coefficients.

[0161] The initial strategy score for the vehicle departure strategy is determined based on the sum of the combination scores corresponding to each departure combination. If the score of each combination is positive, the departure combination is adjusted and optimized within the number of departure strategy optimization attempts. Each time the departure strategy optimization is completed, the sum of the combination scores corresponding to each departure combination is recalculated. When the sum is greater than the initial strategy score, the departure combination is adjusted and optimized again until the number of departure strategy optimization attempts is reached.

[0162] S220. Determine the vehicle recall strategy based on the vehicle number to be recalled, the track to be recalled, and the recall rules in the preset dispatch rules.

[0163] In this step, a vehicle recall strategy is obtained based on the vehicle number to be recalled, the lane to be recalled, and the recall rules arranged in the second priority order to indicate the recall lane corresponding to the vehicle number to be recalled.

[0164] In one possible implementation, Figure 4 A flowchart illustrating the vehicle scheduling method provided in this application embodiment. Figure 4 .like Figure 4 As shown, the car number to be dispatched carries the corresponding car number attribute, and the track to be dispatched carries the corresponding track status data.

[0165] Accordingly, one possible implementation of step S220 above includes the following steps:

[0166] S7. Based on the current vehicle number in the vehicle number to be dispatched and the vehicle dispatching rules in the preset dispatching rules, determine the first vehicle dispatching rule corresponding to the vehicle number attribute corresponding to the current vehicle number.

[0167] For example, the vehicle acceptance rules are sorted by second priority (such as vehicle model compatibility, repair process requirements, function-specific, etc.). The vehicle number attribute includes key information such as vehicle model, repair process task, and whether a car wash / wheel turning is required. Based on the precise matching between the vehicle number attribute and the vehicle acceptance rule requirements, it is ensured that the vehicle acceptance rules can adapt to the vehicle acceptance needs.

[0168] For example, the current vehicle number is 120, and its vehicle number attribute is "Type A vehicle, requiring M2 maintenance". In the preset vehicle acceptance rules, "Type A vehicles are given priority to be matched with tracks 1-5" and "Vehicles under maintenance are given priority to be assigned to dedicated maintenance tracks" are both compatible with the vehicle number attribute corresponding to the current vehicle number. Therefore, these two rules are determined to be the first vehicle acceptance rules.

[0169] S8. Based on the first train retrieval rule, the train retrieval track to be scheduled, and the track status data corresponding to the train retrieval track to be scheduled, determine at least one candidate train retrieval track and its corresponding track parameters.

[0170] For example, based on the first train retrieval rule, combined with the train retrieval track to be scheduled and track status data, candidate train retrieval tracks that meet the requirements are selected, and the corresponding track parameters are extracted.

[0171] Track status data includes whether it is occupied, functional configuration (such as whether it is for maintenance), and power section availability. Track parameters include migration time, current track occupancy rate, and subsequent obstruction costs, ensuring that candidate tracks are feasible for use.

[0172] For example, the tracks to be dispatched for vehicle return are numbered 1-5. The track status data shows that track 1 is for maintenance only and is available, track 3 is for regular parking and is available, and track 5 is occupied. According to the first vehicle return rule, the candidate tracks for vehicle return are track 1 and track 3; the corresponding track parameters are: track 1 has a migration time of 10 minutes and an occupancy rate of 0%, and track 3 has a migration time of 15 minutes and an occupancy rate of 10%.

[0173] S9. Determine the second score corresponding to at least one candidate de-stationing track based on at least one candidate de-stationing track and its corresponding track parameters, as well as the first preset weight.

[0174] For example, the lane parameters of the candidate lanes are quantified into a second score by using a first preset weight, and the score reflects the lane adaptation effect.

[0175] The first preset weight is set according to scheduling requirements (such as migration time weight 0.4, occupancy rate weight 0.3, and subsequent obstacle cost weight 0.3), and a comprehensive evaluation of multi-dimensional parameters is achieved through weighted calculation.

[0176] For example, for each candidate lane, its second score Score2 = αD × migration time + αU × current lane occupancy rate + αL × subsequent obstruction cost + αS × safety penalty, where αD, αU, αL, and αS represent the first preset weights.

[0177] S10, determine the third candidate decommissioning lane corresponding to the maximum value of the second score of at least one candidate decommissioning lane as the target decommissioning lane corresponding to the current decommissioning car number;

[0178] In one possible implementation, if the third candidate return lane is occupied, the return lane corresponding to the next maximum score corresponding to the maximum score in the second score is designated as the target return lane corresponding to the current return car number.

[0179] In addition, if all candidate return lanes are occupied, manual intervention will be implemented for scheduling.

[0180] S11, take the next receiving car number of the current receiving car number as the current receiving car number in the waiting car numbers, repeat steps S7-S11 until all waiting car numbers have their corresponding receiving tracks determined, and determine the vehicle receiving strategy.

[0181] For example, redundant vehicle numbers to be dispatched and their corresponding dispatch lanes are integrated to obtain a vehicle dispatch strategy.

[0182] The vehicle dispatching method provided in this application first determines the vehicle departure strategy based on the departure number to be dispatched, the vehicle number to be dispatched, and the departure rules in the preset dispatching rules. Then, it determines the vehicle arrival strategy based on the arrival number to be dispatched, the arrival lane to be dispatched, and the arrival rules in the preset dispatching rules. In this embodiment, based on the departure number and vehicle number to be dispatched, combined with the departure rules in the preset dispatching rules, it is possible to quickly determine which vehicles should be dispatched first, how to allocate vehicle numbers to the departure numbers to be dispatched, and how to ensure a smooth departure process, thereby effectively reducing delays and inaccuracies that occur during manual dispatching. During the arrival process, the arrival lane allocation can be automatically performed based on the arrival number, the arrival lane to be dispatched, and the arrival rules, reducing tedious manual judgment and improving arrival efficiency.

[0183] Based on the above embodiments, the following is a vehicle dispatching device provided in the embodiments of this application, which can execute the methods provided in the above method embodiments.

[0184] Figure 5This is a schematic diagram of the structure of a vehicle dispatching device provided in an embodiment of this application. Figure 5 As shown, the vehicle dispatching device 500 includes:

[0185] The acquisition module 510 is used to acquire the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, and the train track to be dispatched.

[0186] The processing module 520 is used to determine a vehicle dispatching strategy based on the train number to be dispatched, the train number to be dispatched, the train number to be dispatched, the train track to be dispatched, and preset dispatching rules. The preset dispatching rules include departure rules arranged in a first priority order and arrival rules arranged in a second priority order. The vehicle dispatching strategy includes a vehicle departure strategy and a vehicle arrival strategy. The vehicle departure strategy is used to indicate the departure number corresponding to the train number to be dispatched, and the vehicle arrival strategy is used to indicate the arrival track corresponding to the arrival number to be dispatched.

[0187] In one or more embodiments, the processing module 520 is specifically used for:

[0188] The vehicle departure strategy is determined based on the train number to be dispatched, the train number to be dispatched, and the departure rules in the preset dispatch rules.

[0189] The vehicle recall strategy is determined based on the vehicle number to be recalled, the track to be recalled, and the recall rules in the preset dispatch rules.

[0190] In one or more embodiments, the processing module 520 determines a vehicle departure strategy based on the train number to be scheduled, the train number to be scheduled, and the departure rules in the preset scheduling rules, specifically for:

[0191] S1, determine the highest priority departure rule from the preset scheduling rules;

[0192] S2, according to the departure rule with the highest priority, match the departure number to be scheduled and the departure number to be scheduled to obtain at least one first candidate departure combination, wherein the candidate departure combination includes the candidate departure number and the corresponding candidate departure number;

[0193] S3, perform a first constraint verification on at least one first candidate departure combination, and obtain at least one second candidate departure combination if the verification is successful, wherein the first constraint verification is used to indicate the scheduling constraints of the candidate departure combination;

[0194] S4, perform a second constraint verification on at least one second candidate departure combination to obtain a first score corresponding to at least one second candidate departure combination, wherein the second constraint verification is used to indicate the scheduling effect of the candidate departure combination;

[0195] S5, determine the third candidate departure combination corresponding to the maximum value in the first score corresponding to at least one second candidate departure combination as the highest priority candidate departure combination corresponding to the highest priority departure rule;

[0196] S6. Take the next priority departure rule of the highest priority departure rule as the highest priority departure rule in the preset scheduling rules, and repeat steps S1-S6 until all first candidate departure combinations are verified and the vehicle departure strategy is determined.

[0197] In one or more embodiments, the vehicle number to be dispatched carries a corresponding vehicle number attribute, and the track to be dispatched carries corresponding track status data.

[0198] Correspondingly, the processing module 520 determines the vehicle recall strategy based on the vehicle number to be recalled, the lane to be recalled, and the recall rules in the preset scheduling rules. Specifically, it is used for:

[0199] S7. Based on the current vehicle number in the vehicle number to be dispatched and the vehicle dispatching rules in the preset dispatching rules, determine the first vehicle dispatching rule corresponding to the vehicle number attribute corresponding to the current vehicle number.

[0200] S8. Based on the first train retrieval rule, the train retrieval track to be scheduled, and the track status data corresponding to the train retrieval track to be scheduled, determine at least one candidate train retrieval track and its corresponding track parameters.

[0201] S9. Determine the second score corresponding to at least one candidate de-stationing track based on at least one candidate de-stationing track and its corresponding track parameters, as well as the first preset weight.

[0202] S10, determine the third candidate decommissioning lane corresponding to the maximum value of the second score of at least one candidate decommissioning lane as the target decommissioning lane corresponding to the current decommissioning car number;

[0203] S11, take the next receiving car number of the current receiving car number as the current receiving car number in the waiting car numbers, repeat steps S7-S11 until all waiting car numbers have their corresponding receiving tracks determined, and determine the vehicle receiving strategy.

[0204] In one or more embodiments, after determining the vehicle dispatching strategy based on the departure number to be dispatched, the departure vehicle number to be dispatched, the arrival vehicle number to be dispatched, the arrival track to be dispatched, and preset dispatching rules, the processing module 520 is further configured to:

[0205] Obtain the third score of the preset scheduling rules and historical vehicle scheduling data, including historical departure success rate and historical return success rate.

[0206] Based on historical vehicle dispatch data, the third score of the preset dispatch rules is updated to obtain the updated fourth score;

[0207] Based on the fourth score and the preset threshold, the first priority order and the second priority order are adjusted.

[0208] In one or more embodiments, the processing module 520 updates the third score of the preset scheduling rules based on historical vehicle scheduling data to obtain an updated fourth score, specifically for:

[0209] Based on historical vehicle dispatching data, rule adaptation success rate, manual intervention rate, and execution stability data are determined. The rule adaptation success rate is used to indicate the ratio of the number of successful matches of the preset dispatching rule to the total number of matches. The manual intervention rate is used to indicate the ratio of the number of manual adjustments after the preset dispatching rule failed to match to the total number of matches. The execution stability data is used to indicate the quantitative value of the volatility of the preset dispatching rule matching.

[0210] Based on the rule adaptation success rate, manual intervention rate, execution stability data, and the second preset weight, the third score of the preset scheduling rule is updated to obtain the updated fourth score.

[0211] In one or more embodiments, after adjusting the first priority order and the second priority order according to the fourth score and the preset threshold, the processing module 520 is further configured to:

[0212] Obtain real-time departure status information, real-time return status information, and return lane occupancy status information;

[0213] Based on real-time departure status information, real-time return status information, and return lane occupancy status information, the abnormal scheduling type is determined. The abnormal scheduling type includes at least one of the following: vehicle status change, lane occupancy conflict, and abnormal lockout.

[0214] The first priority order and the second priority order are adjusted according to the abnormal scheduling type.

[0215] The vehicle dispatching device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0216] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 6 As shown, the electronic device 600 includes: a processor 610, a memory 620, and a bus 630;

[0217] The memory 620 is used to store the computer-executed instructions of the processor 610;

[0218] The processor 610 is configured to execute the technical solutions of any of the foregoing method embodiments by executing computer execution instructions.

[0219] The specific implementation process of processor 610 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0220] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0221] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0222] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0223] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0224] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0225] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0226] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0227] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0228] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0229] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0230] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory (RAM), magnetic disks, or optical disks.

[0231] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0232] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A dispatching method of a vehicle, characterized by, The method comprises the following steps: acquiring a to-be-scheduled departure train number, a to-be-scheduled departure train number, a to-be-scheduled arrival train number, and a to-be-scheduled arrival track; determining a vehicle scheduling strategy according to the to-be-scheduled departure train number, the to-be-scheduled departure train number, the to-be-scheduled arrival train number, the to-be-scheduled arrival track, and a preset scheduling rule, wherein the preset scheduling rule comprises departure rules arranged in a first priority order and arrival rules arranged in a second priority order, and the vehicle scheduling strategy comprises a vehicle departure strategy and a vehicle arrival strategy, wherein the vehicle departure strategy is used to indicate a departure train number corresponding to the to-be-scheduled departure train number, and the vehicle arrival strategy is used to indicate an arrival track corresponding to the to-be-scheduled arrival train number.

2. The method of claim 1, wherein, The step of determining the vehicle scheduling strategy according to the to-be-scheduled departure train number, the to-be-scheduled departure train number, the to-be-scheduled arrival train number, the to-be-scheduled arrival track, and the preset scheduling rule comprises the following steps: determining the vehicle departure strategy according to the to-be-scheduled departure train number, the to-be-scheduled departure train number, and the departure rules in the preset scheduling rule; determining the vehicle arrival strategy according to the to-be-scheduled arrival train number, the to-be-scheduled arrival track, and the arrival rules in the preset scheduling rule.

3. The method of claim 2, wherein, The step of determining the vehicle departure strategy according to the to-be-scheduled departure train number, the to-be-scheduled departure train number, and the departure rules in the preset scheduling rule comprises the following steps: S1, determining a departure rule with the highest priority in the preset scheduling rule; S2, performing matching processing on the to-be-scheduled departure train number and the to-be-scheduled departure train number according to the departure rule with the highest priority to obtain at least one first candidate departure combination, wherein the candidate departure combination comprises a candidate departure train number and a corresponding candidate departure train number; S3, performing first constraint verification on the at least one first candidate departure combination to obtain at least one second candidate departure combination, wherein the first constraint verification is used to indicate a scheduling constraint condition of the candidate departure combination; S4, performing second constraint verification on the at least one second candidate departure combination to obtain a first score corresponding to the at least one second candidate departure combination, wherein the second constraint verification is used to indicate a scheduling effect of the candidate departure combination; S5, determining a third candidate departure combination corresponding to a maximum value in the first scores corresponding to the at least one second candidate departure combination as a candidate departure combination with the highest priority corresponding to the departure rule with the highest priority; S6, taking a departure rule corresponding to a next priority of the departure rule with the highest priority as the departure rule with the highest priority in the preset scheduling rule, and repeating steps S1-S6 until all the first candidate departure combinations are verified to obtain the vehicle departure strategy.

4. The method of claim 2, wherein, The to-be-scheduled arrival train number carries corresponding train number attributes, and the to-be-scheduled arrival track carries corresponding track state data. Correspondingly, the step of determining the vehicle arrival strategy according to the to-be-scheduled arrival train number, the to-be-scheduled arrival track, and the arrival rules in the preset scheduling rule comprises the following steps: S7, determining a first parking rule corresponding to a vehicle attribute corresponding to the current parking vehicle number according to the current parking vehicle number in the to-be-scheduled parking vehicle number and a parking rule in the preset scheduling rule; S8, determining at least one candidate parking track and a corresponding track parameter according to the first parking rule, the to-be-scheduled parking track, and the track state data corresponding to the to-be-scheduled parking track; S9, determining a second score corresponding to the at least one candidate parking track according to the at least one candidate parking track and the corresponding track parameter and a first preset weight; S10, determining a third candidate parking track corresponding to a maximum value in the second score corresponding to the at least one candidate parking track as a target parking track corresponding to the current parking vehicle number; S11, taking a next parking vehicle number of the current parking vehicle number as a current parking vehicle number in the to-be-scheduled parking vehicle number, and repeating steps S7-S11 until all to-be-scheduled parking vehicle numbers are determined to correspond to a parking track, and determining the vehicle parking strategy.

5. The method according to claim 1 or 2, characterized in that, After the vehicle scheduling strategy is determined according to the to-be-scheduled departure vehicle number, the to-be-scheduled departure vehicle number, the to-be-scheduled parking vehicle number, the to-be-scheduled parking track, and the preset scheduling rule, the method further comprises: obtaining a third score of the preset scheduling rule and historical vehicle scheduling data, the historical vehicle scheduling data including historical departure success rate and historical parking success rate; updating the third score of the preset scheduling rule according to the historical vehicle scheduling data to obtain an updated fourth score; adjusting the first priority order and the second priority order according to the fourth score and a preset threshold.

6. The method of claim 5, wherein, The updating of the third score of the preset scheduling rule according to the historical vehicle scheduling data to obtain an updated fourth score comprises: determining a rule adaptation success rate, an artificial intervention rate, and an execution stability data according to the historical vehicle scheduling data, the rule adaptation success rate being used to indicate a ratio of a matching success number of the preset scheduling rule to a total matching number, the artificial intervention rate being used to indicate a ratio of an artificial adjustment number after a matching failure of the preset scheduling rule to the total matching number, and the execution stability data being used to indicate a quantization value of volatility of the matching of the preset scheduling rule; updating the third score of the preset scheduling rule according to the rule adaptation success rate, the artificial intervention rate, the execution stability data, and a second preset weight to obtain the updated fourth score.

7. The method of claim 5, wherein, After the adjusting of the first priority order and the second priority order according to the fourth score and a preset threshold, the method further comprises: obtaining real-time departure state information, real-time parking state information, and parking track occupation state information; determining an abnormal scheduling type according to the real-time departure state information, the real-time parking state information, and the parking track occupation state information, the abnormal scheduling type including at least one of vehicle state change, track occupation conflict, and abnormal locking. The first priority order and the second priority order are adjusted according to the abnormal scheduling type.

8. A dispatching device of a vehicle, characterized by comprising: The method comprises the steps of: An acquisition module is configured to acquire a to-be-scheduled departure train number, a to-be-scheduled departure train number, a to-be-scheduled arrival train number, and a to-be-scheduled arrival track; A processing module is configured to determine a vehicle scheduling strategy according to the to-be-scheduled departure train number, the to-be-scheduled departure train number, the to-be-scheduled arrival train number, the to-be-scheduled arrival track, and a preset scheduling rule, wherein the preset scheduling rule comprises a departure rule arranged in a first priority order and an arrival rule arranged in a second priority order, and the vehicle scheduling strategy comprises a vehicle departure strategy and a vehicle arrival strategy, the vehicle departure strategy is used to indicate a departure train number corresponding to the to-be-scheduled departure train number, and the vehicle arrival strategy is used to indicate an arrival track corresponding to the to-be-scheduled arrival train number.

9. An electronic device, comprising: The method comprises the steps of: A memory and a processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by the processor to implement the method according to any one of claims 1-7.

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