Intelligent driving dispatching method and system for rail transit construction line

Abstract

The present invention provides a method and system for intelligent driving scheduling of a rail transit construction line. First, the itinerary arrangement data of all construction driving tasks on the rail transit construction line are collected to construct a set of construction driving tasks to be scheduled; then, the construction driving tasks are prioritized according to the construction type and the construction starting point; finally, an optimization objective function of construction driving scheduling is constructed to iteratively optimize and generate a driving scheduling plan for the rail transit construction line; the present invention introduces a construction task priority division method, which can not only effectively reduce the search scale of the problem and improve the decision-making response speed of the method and the system, but also make the generated scheduling plan more in line with the requirements of actual construction driving, and further proposes an iterative optimization method, which only schedules part of the construction tasks in each optimization process to achieve rapid problem solving, thereby meeting the real-time scheduling requirements of the construction line driving operations and improving the practical application value of the present invention.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle dispatching, and in particular relates to an intelligent vehicle dispatching method and system for a rail transit construction line. Background Art

[0002] With the continuous development of high-speed railways, tasks such as new line construction and existing line reconstruction have become more arduous, and the arrangement of equipment, vehicles and personnel has become more compact. Especially for construction tasks that require the use of special track construction vehicles and equipment on the construction line to complete (referred to as construction driving tasks), how to formulate a reasonable and efficient construction driving task plan under the constraints of ensuring equipment and life safety is an important means to improve equipment utilization, shorten construction period and economic efficiency. High-speed railway construction line driving scheduling is a core work of intelligent construction in rail transit construction. Compared with the safety guarantee provided by the existing railway operation monitoring system for large-scale track maintenance machinery, most of the functions of the monitoring system cannot be realized due to the imperfect initial infrastructure of the new construction line, and the driving safety hazards are relatively large. At the same time, since a large number of construction tasks can only be completed with the help of driving (the driving used for construction tasks is referred to as construction driving), limited track resources are frequently occupied, and the construction site relies solely on manual construction line scheduling, which is arduous and inefficient. Therefore, it is necessary to carry out all-round and three-dimensional intelligent driving scheduling for the construction site, carry out safe transportation management, ensure the driving safety of the construction line, and improve the driving scheduling efficiency.

[0003] Establish a complete driving dispatch auxiliary decision-making system, design driving dispatch methods suitable for construction sites, and provide strong support for the management level of rail transit construction lines. For example, in response to complex working conditions such as long engineering line management intervals and cross-operation of multiple units, the Lianxu High-speed Railway has built a dispatching command system and a video monitoring system for unified operation dispatch and strengthened safety management of on-site construction.

[0004] At present, there are some patents in the field of rail transit traffic dispatching, such as "CN202011135474.9 (A high-speed railway intelligent traffic dispatching safety card control system based on cloud-edge collaboration)", "CN201821744971.7 (A rail transit traffic dispatching auxiliary system)", "CN202010097153.8 (High-speed railway intelligent traffic dispatching system and method)", "CN201010271149.5 (Intelligent processing method for traffic dispatching operation)". The above patents are about the traffic dispatching schemes for the railway operating lines that have been built and are in service. The line conditions, operating vehicles, technical equipment and service objects are quite different from those of the construction lines. The traffic dispatching schemes designed for the operating lines are difficult to be directly applied to the construction lines. At present, there are no relevant patents on traffic dispatching for high-speed rail construction lines. The existing construction line management information system can only detect and alarm traffic conflicts, but cannot eliminate traffic conflicts and automatically generate traffic dispatching schemes. Summary of the invention

[0005] Based on the above problems, the purpose of the present invention is to provide an intelligent driving scheduling method and scheduling system for rail transit construction lines, focusing on considering the levels of various construction driving tasks and heuristic intelligent driving in special or emergency situations. By designing a heuristic intelligent driving scheduling method for solution, it is possible to not only detect driving conflicts but also eliminate conflicts, thereby efficiently completing construction driving scheduling tasks.

[0006] The present invention provides an intelligent vehicle dispatching method for a rail transit construction line, comprising:

[0007] Step 1: Collect the schedule data of all construction driving tasks on the rail transit construction line and construct the set of construction driving tasks to be scheduled Ω;

[0008] Step 2: Prioritize construction driving tasks according to construction type and construction starting point;

[0009] Step 3: Construct the optimization objective function of construction traffic scheduling and iteratively optimize to generate the traffic scheduling plan for the rail transit construction line.

[0010] The step 1 comprises:

[0011] Step 1.1: Construct the construction task vector task according to the itinerary data of the i-th construction vehicle i :

[0012]

[0013] Among them, taskID i Represents the construction task number; taskType i is the construction task type; taskDes is the work content; s1i 、s 2i They represent the construction starting point and construction ending point respectively; Respectively represent the expected start time and expected end time; s 3i 、s 4i Respectively represent the departure position and the return position; T gi Indicates vehicle group information;

[0014] Step 1.2: Construct a set of construction driving tasks to be scheduled Ω, which is expressed as:

[0015]

[0016] Among them, TD 1 and TD 2 Respectively represent the start time and end time of construction scheduling, and It means construction driving task task i The expected start time and expected end time.

[0017] The step 2 comprises:

[0018] Step 2.1: Perform a preliminary priority classification of the construction driving tasks according to their construction types, and divide them into task sets at different levels;

[0019] Step 2.2: Construct a priority sorting rule. The farther the construction starting point of the construction driving task is, the higher the priority of the corresponding construction driving task is.

[0020] Step 2.3: Prioritize the construction driving tasks in each task set according to the sorting rules generated in step 2.2, and generate the corresponding construction driving task queue in descending order of priority;

[0021] Step 2.4: Generate a task queue Q after all construction driving tasks are prioritized according to the construction driving task queue 1 .

[0022] The step 3 comprises:

[0023] Step 3.1: Queue initialization, build and initialize the scheduled construction driving task queue Construction driving task queue to be scheduled and conflicting construction driving task queues Where Q 2 Used to store the completed scheduled construction driving tasks, Q 3 Used to store construction driving tasks that need to be scheduled. 4 Used to store construction driving tasks that have constraint conflicts with the construction tasks to be scheduled;

[0024] Step 3.2: Update the waiting queue Q 3 , in Q 1 The highest priority construction driving tasks are extracted from the queue in turn until Q 3 The number of tasks in the queue is N 3 N 3 Indicates Q 3 The capacity of the queue;

[0025] Step 3.3: Construct the optimization objective function of construction vehicle scheduling and determine Q 3 Driving time of construction driving tasks in the queue;

[0026] Step 3.4: Determine Q 1 Check whether there are still unscheduled trains in the queue. If yes, go to step 3.2. Otherwise, the construction driving task scheduling is completed.

[0027] The step 3.3 comprises:

[0028] Step 3.3.1: Determine Q 3 Construction driving tasks in the queue i The decision variables required for the driving time include the construction task start time t 1，j , end time t 2，j , departure time t 3，j and the pickup time t 4，j ;

[0029] Step 3.3.2: Establish the optimization objective function J of construction vehicle scheduling based on the decision variables:

[0030]

[0031] In the formula, Indicates Q 3 Construction driving tasks in the queue j′ The expected start time, Indicates Q 3 Construction driving tasks in the queue i′ The expected end time of

[0032] Step 3.3.3: Construct the feasibility constraint C of the driving time within the construction driving task in ;

[0033] Step 3.3.4: Determine and construct the feasibility constraint C of the driving time between construction driving tasks out ;

[0034] Step 3.3.5: According to constraint C in and C outSolve the objective function J. When there is a feasible solution to the problem, queue Q 3 and Q 4 The construction tasks in are added to the queue Q 2 In the above example, the decision variable is defined as the driving time of the construction vehicle to be scheduled. When the problem cannot be solved, the queue Q 4 The construction tasks in the queue are transferred to the waiting queue Q 3 middle.

[0035] The feasibility constraint C in step 3.3.3 in include:

[0036] Construction driving task departure time and start time constraints C 1 :

[0037] t 1，j >t 3，j j = 1, 2, 3, ..., N 3

[0038] Construction driving task start time and end time constraints C 2 :

[0039] t 2，j >t 1，j j = 1, 2, 3, ..., N 3

[0040] Construction driving task collection time and end time constraints C 3 :

[0041] t 4，j >t 2，j j = 1, 2, 3, ..., N 3

[0042] Job time constraints C 4 :

[0043]

[0044] The step 3.3.4 includes:

[0045] Traverse Q 3 The construction driving tasks to be arranged in the queue Q 3 Each construction driving task j Driving range [s 3j ,s 1j ] and the queue Q 2 Construction driving tasks have been arranged k Driving range [s 3k ,s 1k ] Is there a common part? If so, establish the feasibility constraint Cout , and Q 2 The corresponding construction driving task is moved to queue Q 4 Otherwise, the feasibility constraint C is not established. out ;

[0046] The feasibility constraint C out include:

[0047] Tracking interval time constraint C 5 :

[0048]

[0049] Overtaking restriction C 6 :

[0050] (t 3j -t 3k )×(t 1j -t 1k )>0, j≠k, j=1, 2, 3,..., N 3 , k = 1, 2, 3, ..., N 2

[0051] In the formula, Tz represents the minimum running interval time that needs to be met between construction vehicles, t 3j Indicates Q 3 Construction driving tasks in the queue j The departure time, t 4j Indicates Q 3 Construction driving tasks in the queue j The pickup time, t 3k Indicates Q 2 Construction driving tasks in the queue k The departure time, t 4k Indicates Q 2 Construction driving tasks in the queue k The pickup time, N 2 Represents queue Q 2 Capacity, N 3 Representation Queue Q 3 capacity.

[0052] An intelligent driving dispatching system for a rail transit construction line is implemented according to the intelligent driving dispatching method for a rail transit construction line, and the system comprises: a data preprocessing module, a heuristic driving sorting submodule, a heuristic driving time optimization submodule, and a visualization output module;

[0053] The data preprocessing module is used to generate a set of construction driving tasks to be scheduled based on the schedule data of all construction driving tasks on the rail transit construction line;

[0054] The heuristic driving sorting submodule is used to prioritize the construction driving tasks according to their construction types and construction starting points;

[0055] The heuristic driving time optimization submodule is used to construct the optimization objective function of construction driving scheduling and generate the driving scheduling plan for the rail transit construction line;

[0056] The visualization output module is used to visualize the output of the rail transit construction line driving scheduling plan, and the scheduling plan can be adjusted through human-computer interaction to meet the actual needs of construction driving.

[0057] The beneficial effects of the present invention are:

[0058] The present invention proposes an intelligent driving scheduling method and system for rail transit construction lines. Before determining the specific train construction plan, the present invention introduces a construction task priority division method, which can not only effectively reduce the search scale of the problem and improve the decision-making response speed of the method and system, but also make the generated scheduling plan more in line with the actual construction driving requirements. When optimizing the construction driving time, the present invention proposes an iterative optimization method, which only schedules part of the construction tasks in each optimization process to achieve rapid problem solving, thereby meeting the real-time scheduling requirements of the construction line driving operations and improving the practical application value of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a flow chart of the intelligent driving dispatching method for rail transit construction line in the present invention;

[0060] Figure 2 This is the architecture diagram for the intelligent driving dispatching system for the rail transit construction line in the present invention;

[0061] Figure 3 It is a diagram of the operation driving arrangement after the construction day plan reported by each construction unit in the present invention is reviewed and approved;

[0062] Figure 4 The diagram is a construction driving task arrangement diagram implemented according to the intelligent driving scheduling method for rail transit construction lines in the present invention. DETAILED DESCRIPTION

[0063] The invention is further described below with reference to the accompanying drawings and specific implementation examples. Figure 2As shown. The itinerary data received in this embodiment is transmitted from the existing "railway construction informationization" system, including each construction department at the construction site reporting the construction day plan, and then obtaining standardized itinerary data after review by the superior department, including locomotive number, construction task type, work content, construction starting point, construction end point, departure location, collection location, expected start time, expected end time, and vehicle group information. The received itinerary data is saved in a csv type task requirement description file in a tabular form. The format and definition of each field of the file are shown in Table 1. Table 2 is the actual construction driving task requirement table, which comes from the actual rail transit informationization system. It is used here as a specific case to describe the specific implementation process of this method in detail.

[0064] Table 1 Format and definition of each field in task requirements

[0065]

[0066]

[0067] Table 2 Actual construction driving task requirements

[0068]

[0069] like Figure 1 As shown, a method for intelligent vehicle dispatching for a rail transit construction line includes:

[0070] Step 1: Collect the schedule data of construction driving tasks on the rail transit construction line and construct the set of construction driving tasks to be scheduled Ω; specifically including:

[0071] Step 1.1: Extract the data information required for construction driving schedule, and construct the construction task vector task for each construction driving in turn i :

[0072]

[0073] Among them, taskID i Indicates the construction task number, which is the unique identifier of the construction driving task; taskType i It is the construction task type, which is numbered based on the actual construction demand priority. For example, the "track laying" task has a higher priority and is numbered 1. TaskDes is used to record the content of the construction work. 1i 、s 2i They represent the construction starting point and construction ending point respectively; Respectively represent the expected start time and expected end time; s 3i 、s 4i Respectively represent the departure position and the return position; Tgi It is the vehicle group information;

[0074] Step 1.2: Construct a set of construction driving tasks to be scheduled, based on the task i The expected start time t 1i and the expected end time t 2i Determine whether scheduling is needed. or When the task i Need to schedule and assign tasks i Add it to the set of construction driving tasks to be scheduled, otherwise it will not be scheduled. The final set Ω can be expressed as:

[0075]

[0076] Among them, TD 1 and TD 2 Respectively represent the start time and end time of construction scheduling;

[0077] Assume that the time range specified by the user for arranging construction driving tasks is:

[0078] TD 1 =2021 / 4 / 3 00:00, TD 2 =2021 / 4 / 5 00:00

[0079] According to step 1, the final set of construction driving tasks to be scheduled Ω can be expressed in a table, as shown in Table 3:

[0080] Table 3. Table of construction driving task set to be scheduled

[0081]

[0082] Step 2: Prioritize construction driving tasks according to construction type and construction starting point; including:

[0083] Step 2.1: Perform a preliminary priority sorting of the construction driving tasks according to their construction types, and define the tasks in the construction driving task set Ω. i The priority is p i To indicate that, in this embodiment, there are 9 tasks to be sorted in the task set Ω. i The value range of p is {1, 2, 3, ... 9}, i The smaller the value, the higher the priority. Traverse each driving task task in the construction driving task set Ω i , when task i Construction task type taskType iis 1 (i.e., “track laying” type), the task is classified into the high-priority driving task set Ω 1 ={task i |taskType i =1}, other types of driving tasks are divided into the low-priority driving task set Ω 2 ={task i |taskType i ≠1}. Specifically in this embodiment, Ω 1 ={task 28},Ω 2 ={task 27 , task 30 , task 31 , task 32 , task 33 , task 37 , task 34 , task 35}

[0084] Step 2.2: Construct a priority sorting rule. The farther the construction starting point of the construction driving task is, the higher the priority of the corresponding construction driving task is. Specifically, it can be expressed as:

[0085] If 1i <s 1j then i <p j

[0086] Among them, s 1i and 1j Indicates the construction driving task task i and construction driving tasks j The construction starting point, p i and p j They represent the construction driving tasks respectively. i and construction driving tasks j priority of tasks.

[0087] Step 2.3: Set the task set Ω 1 and Ω 2 The construction driving tasks in the task queue are prioritized according to the sorting rules generated in step 2.2, and the corresponding construction driving task queue Q is generated in descending order of priority. 11 and Q 12 In this embodiment, Q 11 ={task 28} and Q 12 ={task 37 , task 30 , task31 , task 32 , task 33 , task 34 , task 35 , task 27};

[0088] Step 2.4: Use the construction driving task queue Q 11 and Q 12 Generate a task queue Q after all construction driving tasks are prioritized 1 :

[0089] Q 1 =[Q 11 , Q 12 ]

[0090] According to step 2.4, the construction driving task queue Q in this embodiment 1 for:

[0091] {task 28 , task 37 , task 30 , task 31 , task 32 , task 33 , task 34 , task 35 , task 27}

[0092] Queue Q 1 The specific information is shown in the following table. Field p indicates the priority of the task, as shown in Table 4;

[0093] Table 4 Task priority table represented by field p

[0094]

[0095] Step 3: Construct the optimization objective function of construction traffic scheduling and iteratively optimize to generate the traffic scheduling plan for the rail transit construction line; including:

[0096] Step 3.1: Queue initialization, build and initialize the scheduled construction driving task queue Q 2 , Q 2 The initial value is empty, that is, initialized Construction driving task queue Q to be scheduled 3 , Q 3 The initial value is empty, that is, initialized Build and initialize the conflicting scheduled construction driving task queue Q 4 , Q 4 The initial value is empty, that is, initialized Where Q 2 Used to store the completed scheduled construction driving tasks, Q 3 Used to store construction driving tasks that need to be scheduled; Q 4 Used to store construction driving tasks after conflict constraint detection;

[0097] Step 3.2: Update the waiting queue Q 3 , extract Q 1 The first construction driving task to be scheduled in the queue arrives at Q 3 In the queue, specifically, the first construction driving task in queue Q1 is selected and put into queue Q3;

[0098] Q 1 =Q 1 -{task i}

[0099] Q 3 =Q 3 ∪{task i}

[0100] Repeat the above steps until the queue Q 3 The number of tasks in reaches N 3 So far.

[0101] In this embodiment, N is defined 3 =1, so queue Q 1 The first construction driving task of the team 28 Put it into queue Q 3 , at this time Q 3 ={task 28}, Q 1 ={task 37 , task 30 , task 31 , task 32 , task 33 , task 34 , task 35 , task 27};

[0102] Step 3.3: Construct the optimization objective function of construction vehicle scheduling and determine Q 3 The driving time of the construction driving tasks in the queue; including:

[0103] Step 3.3.1: Determine Q 3 Construction driving tasks in the queue i The decision variables required for the driving time include the construction task start time t 1，j , end time t 2，j , departure time t3，j and the pickup time t 4，j ;

[0104] According to the characteristics of the construction driving trajectory, following the basic process principles and safety principles, a "four-point three-line" solution approach was established, that is, by determining each construction task j The start time t 1，j , end time t 2，j , departure time t 3，j and the pickup time t 4，j Four time-space points are connected end to end to generate three running lines to complete the description of a single construction vehicle trajectory. 1，j , t 2，j , t 3，j , t 4，j |j=1,...,N 3 In this embodiment, the decision variable X is represented by {t 1，1 , t 2，1 , t 3，1 , t 4，1}.

[0105] Step 3.3.2: To ensure that the generated construction vehicle trajectory is as close to the actual construction plan requirements as possible, the optimization objective function J of construction vehicle scheduling is established based on the decision variables:

[0106]

[0107] In the formula, Indicates Q 3 Construction driving tasks in the queue j′ The expected start time, Indicates Q 3 Construction driving tasks in the queue j′ The expected end time of the construction; minimizing the objective function J represents that the generated construction driving trajectory should be as consistent as possible with the expected construction plan, while minimizing the total operation time of the train as much as possible to achieve the consideration of the energy consumption target.

[0108] Step 3.3.3: The construction driving tasks themselves have a fixed logical relationship in time. In order to ensure the feasibility of the construction driving trajectory, it is necessary to construct the driving time feasibility constraint C for each construction driving task. in , specifically including:

[0109] The same construction driving task departure time and start time constraints C 1 :

[0110] t 1，j >t 3，j j = 1, 2, 3, ..., N3

[0111] The start and end time constraints of the same construction driving task C 2 :

[0112] t 2，j >t 1，j j = 1, 2, 3, ..., N 3

[0113] Constraints C for the same construction driving task's closing time and end time 3 :

[0114] t 4，j >t 2，j j = 1, 2, 3, ..., N 3

[0115] Job time constraints C 4 :

[0116]

[0117] Step 3.3.4: Determine whether it is necessary to construct the feasibility constraint C of the driving time between construction driving tasks out ; Traverse Q 3 The construction driving tasks to be arranged in the queue Q 3 Each construction driving task j Driving range [s 3j ,s 1j ] and the queue Q 2 Construction driving tasks have been arranged k Driving range [s 3k ,s 1k ] Is there a common part? If so, establish the feasibility constraint C out ; and Q 2 The corresponding construction driving task is moved to queue Q 4 Otherwise, the feasibility constraint C is not established. out ;

[0118] The feasibility constraint C out include:

[0119] Tracking interval time constraint C 5 :

[0120]

[0121] Overtaking restriction C 6 :

[0122] (t 3j -t 3k )×(t 1j-t 1k )>0, j≠k, j=1, 2, 3,..., N 3 , k = 1, 2, 3, ..., N 2

[0123] In the formula, Tz represents the minimum running interval time that needs to be met between construction vehicles, t 3j Indicates Q 3 Construction driving tasks in the queue j The departure time, t 4j Indicates Q 3 Construction driving tasks in the queue j The pickup time, t 3k Indicates Q 2 Construction driving tasks in the queue k The departure time, t 4k Indicates Q 2 Construction driving tasks in the queue k The pickup time, N 2 Represents queue Q 2 Capacity, N 3 Represents queue Q 3 Capacity;

[0124] According to steps 3.3.2 to 3.3.4, the corresponding optimization problem of this embodiment can be expressed as:

[0125]

[0126]

[0127] Step 3.3.5: Use the optimization solver to solve the constructed optimization problem. When a feasible solution is obtained, queue Q 3 and Q 4 The construction tasks in are added to the queue Q 2 Middle, namely Q 2 =Q 2 ∪Q 3 ∪Q 4 , The obtained decision variable is defined as the driving time of the construction vehicle to be scheduled. When there is no feasible solution to the problem, the queue Q 4 The construction tasks in the queue are transferred to the waiting queue Q 3 In Chinese, that is: Q 3 =Q 3 ∪Q 4 , In this example, we use the Cplex optimizer to solve the problem and finally find that the problem has a feasible solution. The obtained decision variable X = [2021 / 4 / 4 0:00, 2021 / 4 / 4 8:00, 2021 / 4 / 4 20:00, 2021 / 4 / 5 01:00], the queue Q 2 ={tatsk 28}.

[0128] Step 3.4: Determine Q 1 Is there still an unscheduled train in the queue? If yes, go to step 3.2; otherwise, the construction driving task scheduling is completed. 1 There are still unscheduled trains in the queue, so it is necessary to repeat steps 3.2 to 3.4 until the termination condition is met.

[0129] The graphical display method is used to generate a scheduling plan, so that users can understand the possible conflicts in the driving scheduling process, so as to adjust the expected start time, expected end time parameters and construction driving task requirements through human-computer interaction, and further optimize the scheduling plan. According to the method of the present invention, the auxiliary decision-making plan for rail transit construction line driving is obtained, such as Figure 4 As shown. The horizontal axis in the figure represents the driving time, and the vertical axis represents the station corresponding to the construction driving track. The dotted line in the figure represents the driving track of a construction driving from the departure position to the construction starting point, the solid line represents the operation track of the construction driving from the construction starting point to the construction end point, and the dot-dash line represents the driving track of the construction driving from the construction end point to the collection position. It can be seen that after the system is optimized, each construction driving forms a basic pattern of "four points and three lines", which conforms to the basic idea of ​​system optimization solution. Figure 4 It also includes the locomotive number of a certain construction operation and the specific content of the construction operation.

[0130] An intelligent driving dispatching system for a rail transit construction line is implemented according to the intelligent driving dispatching method for a rail transit construction line, and the system comprises: a data preprocessing module, a heuristic driving sorting submodule, a heuristic driving time optimization submodule, and a visualization output module;

[0131] The data preprocessing module is used to generate a set of construction driving tasks to be scheduled based on the schedule data of all construction driving tasks on the rail transit construction line;

[0132] The heuristic driving sorting submodule is used to prioritize the construction driving tasks according to their construction types and construction starting points;

[0133] The heuristic driving time optimization submodule is used to construct the optimization objective function of construction driving scheduling and generate the driving scheduling plan for the rail transit construction line;

[0134] The visualization output module is used to visualize the output of the rail transit construction line driving scheduling plan, and the scheduling plan can be adjusted through human-computer interaction (such as adjusting the expected start time, expected end time parameters, and construction driving task requirements) to meet the actual needs of construction driving.

[0135] Figure 3 Report the operation and driving arrangement of the construction day plan to each construction unit after it is approved. Figure 3 and Figure 4 It is found that the present invention can fully solve the potential driving conflicts reported by various construction units and optimize the arrangements for various construction driving tasks, such as Figure 3 There is a conflict in track resource occupation between the driving tasks with taskID 30 and 31, and there is also a potential conflict between the driving tasks with taskID 28 and 32, 33 and 37. Figure 4 It can be seen that after the optimization solution of the present invention, there is no driving conflict in the construction driving task and the safety constraint C is satisfied. 1 , C 2 , C 3 , C 4 , C 5 and C 6 .

Claims

1. An intelligent driving dispatching method for a rail transit construction line, characterized in that: include: Step 1: Collect the schedule data of all construction driving tasks on the rail transit construction line and construct the set of construction driving tasks to be scheduled Ω; Step 1.1: Construct the construction task vector task according to the itinerary data of the i-th construction vehicle i : Among them, taskID i Represents the construction task number; taskType i is the construction task type; taskDes is the work content; s 1i 、s 2i They represent the construction starting point and construction ending point respectively; Respectively represent the expected start time and expected end time; s 3i 、s 4i Respectively represent the departure position and the return position; T gi Indicates vehicle group information; Step 1.2: Construct a set of construction driving tasks to be scheduled Ω, which is expressed as: Among them, TD1 and TD2 represent the start time and end time of construction scheduling respectively. and It means construction driving task task i The expected start time and expected end time of the Step 2: Prioritize construction driving tasks according to construction type and construction starting point; Step 2.1: Perform a preliminary priority classification of the construction driving tasks according to their construction types, and divide them into task sets at different levels; Step 2.2: Construct a priority sorting rule. The farther the construction starting point of the construction driving task is, the higher the priority of the corresponding construction driving task is. Step 2.3: Prioritize the construction driving tasks in each task set according to the sorting rules generated in step 2.2, and generate the corresponding construction driving task queue in descending order of priority; Step 2.4: Generate a task queue Q1 after all construction driving tasks are prioritized according to the construction driving task queue; Step 3: Construct the optimization objective function of construction traffic scheduling to generate the rail transit construction line traffic scheduling plan; Step 3.1: Queue initialization, build and initialize the scheduled construction driving task queue Construction driving task queue to be scheduled and conflicting construction driving task queues Q2 is used to store the construction driving tasks that have been scheduled, Q3 is used to store the construction driving tasks that need to be scheduled, and Q4 is used to store the construction driving tasks that have constraint conflicts with the construction tasks to be scheduled; Step 3.2: Update the waiting queue Q3, and extract the highest priority construction driving tasks in the Q1 queue in turn until the number of tasks in the Q3 queue reaches N3, where N3 represents the capacity of the Q3 queue; Step 3.3: Construct the optimization objective function of construction driving scheduling and determine the driving time of the construction driving tasks in the Q3 queue; Step 3.4: Determine whether there are still unscheduled trains in the Q1 queue. If yes, go to step 3.2; otherwise, the construction driving task scheduling is completed.

2. The intelligent driving dispatching method for rail transit construction line according to claim 1 is characterized in that: The step 3.3 comprises: Step 3.3.1: Determine the construction driving task in the Q3 queue i The decision variables required for the driving time include the construction task start time t 1,j , end time t 2,J , departure time t 3,J and the pickup time t 4,J ; Step 3.3.2: Establish the optimization objective function J of construction vehicle scheduling based on the decision variables: In the formula, Indicates the construction driving task in the Q3 queue j' The expected start time, Indicates the construction driving task in the Q3 queue j' The expected end time of Step 3.3.3: Construct the feasibility constraint C of the driving time within the construction driving task in ; Step 3.3.4: Determine and construct the feasibility constraint C of the driving time between construction driving tasks out ; Step 3.3.5: According to constraint C in and C out Solve the objective function J. When a feasible solution exists for the problem, the construction tasks in queues Q3 and Q4 are added to queue Q2, and the obtained decision variable is defined as the driving time of the construction vehicles to be scheduled. When a feasible solution cannot be found for the problem, the construction tasks in queue Q4 are transferred to queue Q3 to be scheduled.

3. The intelligent driving dispatching method for rail transit construction line according to claim 2 is characterized in that: The feasibility constraint C in step 3.3.3 in include: Construction driving task departure time and start time constraints C1: t 1,J >t 3,j j=1,2,3,…,N3 Construction driving task start and end time constraints C2: t 2,j >t 1,j j=1,2,3,…,N3 Construction driving task return time and end time constraint C3: t 4,j >t 2,j j=1,2,3,…,N3 Job time constraint C4:

4. The intelligent driving dispatching method for rail transit construction line according to claim 2 is characterized in that: The step 3.3.4 includes: traversing the construction driving tasks to be arranged in Q3, determining each construction driving task in the queue Q3 j Driving range [s 3j ,s 1j ] and the construction driving task that has been scheduled in queue Q2 k Driving range [s 3k ,s 1k ] Is there a common part? If so, establish the feasibility constraint C out , and move the corresponding construction driving task in Q2 to queue Q4; otherwise, the feasibility constraint C is not established. out ; The feasibility constraint C out include: Tracking interval time constraint C5: Override constraint C6: (t 3j -t 3k )×(t 1j -t 1k )>0,j≠k,j=1,2,3,…,N3,k=1,2,3,…,N2 In the formula, Tz represents the minimum running interval time that needs to be met between construction vehicles, t 3j Indicates the construction driving task in the Q3 queue j The departure time, t 4j Indicates the construction driving task in the Q3 queue j The pickup time, t 3k Indicates the construction driving task in the Q2 queue k The departure time, t 4k Indicates the construction driving task in the Q2 queue k The collection time of the queue Q2 is N2, and the capacity of the queue Q3 is N3.

5. An intelligent driving dispatching system for a rail transit construction line, implemented according to an intelligent driving dispatching method for a rail transit construction line according to any one of claims 1 to 4, characterized in that: The system includes: a data preprocessing module, a heuristic driving sorting submodule, a heuristic driving time optimization submodule, and a visualization output module; The data preprocessing module is used to generate a set of construction driving tasks to be scheduled based on the schedule data of all construction driving tasks on the rail transit construction line; The heuristic driving sorting submodule is used to prioritize the construction driving tasks according to their construction types and construction starting points; The heuristic driving time optimization submodule is used to construct the optimization objective function of construction driving scheduling and generate the driving scheduling plan for the rail transit construction line; The visualization output module is used to visualize the output of the rail transit construction line driving scheduling plan, and the scheduling plan can be adjusted through human-computer interaction to meet the actual needs of construction driving.

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