Operation interruption driving adjustment method based on hybrid intersection

Abstract

The invention discloses an operation interruption driving adjustment method based on a mixed route, and belongs to the technical field of rail transit. Comprising the following steps: S1, on the basis of a small intersection driving adjustment strategy and a single-line two-way driving adjustment strategy, providing a'single-line two-way + small intersection 'mixed intersection driving adjustment strategy under the condition of one-way interruption of a track line; s2, measuring the influence of the driving adjustment scheme on the passengers based on the total passenger travel time; s3, establishing a driving adjustment model based on S1 and S2: establishing an optimization model with the minimum total passenger travel time as a target by taking a train traffic plan as a decision variable; and S4, solving the model by adopting a BFS optimal priority search algorithm, and evaluating the traversed scheme according to a heuristic evaluation function so as to save the calculation time and obtain an optimal driving adjustment scheme. According to the invention, the problem of driving adjustment under interruption of rail transit operation is solved.

Description

Technical Field

[0001] The invention relates to a method for adjusting train operation interruption based on mixed routes, belonging to the technical field of rail transportation. Background Art

[0002] As urban rail transit occupies an increasingly large proportion in public transportation, the city's travel system is increasingly dependent on rail transit. If the rail transit system is suddenly disturbed, resulting in delays or even interruptions, the scope of impact will also expand, which will in turn cause serious losses to social and economic development. At present, the main deficiencies in the research on the traffic adjustment method under rail transit operation interruption at home and abroad are: only a single traffic adjustment strategy is targeted, such as small-route traffic adjustment and single-line two-way traffic adjustment, and both adjustment methods have their own limitations and defects. The use of small-route traffic adjustment alone cannot guarantee the traffic connectivity on both sides of the interruption, and the use of single-line two-way traffic adjustment alone will reduce the transportation capacity of the entire line due to shared tracks; the traffic adjustment optimization model itself is a mixed integer optimization model. In most studies, for such optimization problems with complex variables and many constraints, heuristic algorithms are usually used. Such algorithms may not guarantee the global optimal solution when facing different interruption scenarios, and may even lead to poor solution quality in some cases.

[0003] The BFS best-first search algorithm uses a heuristic evaluation function to evaluate the solutions to be traversed under the premise of a global search. The biggest difference between it and the traditional search algorithm is that before formally calculating the target value of a solution, a simple valuation calculation is performed to directly exclude solutions that do not meet the valuation conditions, narrow the invalid solution range, and thus speed up the calculation process. Therefore, in the complex environment of operational interruption, the BFS best-first search algorithm solves the driving adjustment model, speeds up the model solution speed, and overcomes the shortcoming of the general traversal search algorithm that the number of calculations increases exponentially. Summary of the invention

[0004] The purpose of the present invention is to reduce the negative impact of interruptions on passengers and ensure efficient operation of trains. Under the condition of one-way interruption of the track line and simultaneous adjustment of small routes and single-line two-way driving, a method for adjusting driving during operation interruptions based on mixed routes is provided, which can solve the problem of driving adjustment in operation interruption scenarios.

[0005] In order to solve the above technical problems, a method for adjusting traffic during operation interruption based on mixed routes is provided in the present invention, which models a traffic adjustment model and includes the following steps:

[0006] S1. Based on the small-route traffic adjustment strategy and the single-track two-way traffic adjustment strategy, a mixed-route traffic adjustment strategy of "single-track two-way + small-route" is proposed in the case of one-way interruption of the track line;

[0007] S2, measure the impact of traffic adjustment schemes on passengers based on total passenger travel time;

[0008] S3, establish a traffic adjustment model based on S1 and S2: take the train route plan as the decision variable and establish an optimization model with the minimum total passenger travel time as the goal;

[0009] S4. Use the BFS best-first search algorithm to solve the model, evaluate the traversed solutions according to the heuristic evaluation function to save computing time and obtain the best driving adjustment plan.

[0010] Furthermore, S1 specifically includes the following steps:

[0011] S101. The research object is defined as an operational interruption scenario in which a one-way interruption occurs on a two-way urban rail line. Some stations on the line have conditions such as crossovers, which allow trains to operate in short routes at stations where they can turn back, and also allow trains to use crossovers to borrow the opposite track to organize single-line two-way operation. Except for the trains that are affected by the interruption and are trapped, no train service is allowed to be suspended.

[0012] Furthermore, S2 specifically includes the following steps:

[0013] S201,t p_total represents the total passenger travel time during the optimization period, as follows:

[0014] t p_total =α w t w_total +t c_total

[0015] Where: t p_total is the total passenger travel time within the optimization period; α w is the platform waiting time penalty coefficient; t w_total is the total passenger platform waiting time; t c_total is the total passenger time on board;

[0016] The total passenger platform waiting time and the total passenger on-board time can be obtained by integrating the number of people on the platform and on the train over time, as follows:

[0017]

[0018] Where: T c is the starting time of the interruption duration phase; T p is the end time of the interruption duration phase; p_w s is the number of passengers waiting at the platform of station s; p_c j is the number of passengers on train No. j;

[0019] The passengers waiting on the platform and on the train are composed of passengers going to different destinations, as follows:

[0020]

[0021] Where: p_w s,s' is the number of passengers waiting at platform s to go to station s′; p_c j，s′ is the number of passengers on train number j who will get off at station s′;

[0022] Passengers enter the platform at a fixed arrival rate, so the number of passengers waiting on the platform increases continuously. Passengers waiting on the platform will only board the train when it leaves the station, so the decrease in the number of passengers waiting on the platform is discrete. c , T p ], the number of passengers waiting at station s and intending to go to station s′ varies with time, as follows:

[0023]

[0024] Where: α(s, s′) is the passenger arrival rate from station s to station s′; is the number of passengers who board train j at station s and go to station s′; is the time when train number j arrives at node n;

[0025] The number of passengers in the carriage changes discretely. For passengers who need to go to a certain station, they will get off the train after the train arrives at the target station. Therefore, any number that satisfies T∈[T c , T p ], the number of passengers on train number j who will get off at station s′ is as follows:

[0026]

[0027] Furthermore, S3 specifically includes the following steps:

[0028] S301. In order to make the model feasible, it is necessary to simplify the actual situation and make the following assumptions;

[0029] S302, taking the train route plan as a decision variable;

[0030] S303. During the interruption period, the main purpose of the train adjustment is to restore some capacity as much as possible, reduce the number of passengers stranded in the station, and complete the passenger transfer task under limited conditions. The objective function is to minimize the total passenger travel time, as follows:

[0031] MinZ=t p_total

[0032] Furthermore, S4 specifically includes the following steps:

[0033] S401, initializing the intersection combination i=0; initial optimal solution and target value [0, Z min =+∞];

[0034] S402, simplifying the calculation of the valuation function H of the intersection combination i, requiring the valuation function H ≤ the actual target value Z, so as not to miss the nearest solution due to estimation errors, and the valuation function H is as close to the actual target value Z as possible under the premise of convenient calculation;

[0035] S403. Compare the valuation function value of a certain plan with the actual value of the currently calculated best plan. If the valuation of the plan is higher than the current best plan, it is considered that the actual value of the plan cannot be better than the current result. There is no need to calculate this plan, which saves calculation time and ultimately finds the optimal driving adjustment plan.

[0036] Furthermore, in order to make the model feasible, S301 needs to simplify the actual situation, combine existing research, and make assumptions, which specifically include the following steps:

[0037] (1) For single-track bidirectional trains, if there are trains waiting on both sides of the interruption area, the routes are arranged in order of priority.

[0038] (2) Trains running on the same platform shall adopt the same route plan.

[0039] (3) Trains should be dispatched as much as possible while satisfying the constraints.

[0040] (4) Passengers enter the station at a fixed arrival rate, and the OD of passengers arriving at different stations is known.

[0041] (5) Assume that the time it takes for a train to pass through the station section is the same as before the interruption.

[0042] (6) Passenger boarding is subject to train capacity restrictions. Passengers who are unable to board will continue to wait for the next available train.

[0043] (7) Assuming that passengers get on and off the train instantly, in order to make the calculation clear, it is stipulated that passengers get off when the train enters the station and get on when the train leaves the station.

[0044] Furthermore, S302 uses the train route plan as a decision variable, and specifically includes the following steps:

[0045] 1) Train reachable node constraint: The node reached by a certain train must be reachable by the route plan selected by the train. The route plan that the train can choose is related to its initial position;

[0046]

[0047] 2) Tracking train safety constraints: According to the model assumptions, the automatic station-to-station blocking method is used to control the train block after the interruption. The tracking train safety constraints comply with the automatic station-to-station blocking, and the time when the train arrives at the exit node must meet the constraints;

[0048] Or

[0049] 3) Safety constraints for single-track two-way shared track: For shared track sections in single-track two-way routes, in addition to the tracking trains in the same direction, there are also safety constraints for trains in the opposite direction. For trains that choose to run on a single track in both directions, the route can only be opened when there are no trains occupying the shared section. If a single-track two-way train enters the shared section and the j+1 train ahead is a reverse train, it must wait until the train leaves the switch node before it is allowed to exit the station. If the j+1 train ahead is a train in the same direction, it will be controlled according to the automatic station-to-station blocking;

[0050]

[0051] 4) Constraints on the operation time of adjacent nodes: Both stopover and interval operation can be described as the operation time between nodes in the mesoscopic track line model, so the operation time between adjacent nodes should meet the constraints;

[0052]

[0053] 5) Passenger boarding constraints: Choosing different route plans for a train will change the destinations that the train can reach. If a passenger is willing to board a certain train, first, the set of reachable nodes for the train must contain the node of the passenger's destination station, and second, the direction of the train must be correct;

[0054]

[0055] 6) Train capacity constraint: At any time T, the number of passengers on the train should meet the train passenger capacity constraint. When the sum of the number of passengers on the train and the number of passengers in the carriage exceeds the maximum passenger capacity of the train, the passengers exceeding the capacity will stay at the original platform waiting for the next train. The destinations of the passengers on the train are distributed in proportion to the passenger flow composition;

[0056]

[0057] It can be seen from the above technical solutions that a method for adjusting traffic during operation interruptions based on mixed routes provided by an embodiment of the present invention has achieved the following beneficial effects: a mixed route traffic adjustment strategy is proposed based on the small route and single-line two-way adjustment strategies, and the BFS best priority search algorithm is used to solve the traffic adjustment model with the minimum total passenger travel time as the goal; the mixed route traffic adjustment strategy can reduce the total passenger travel time more than using the single-line two-way traffic or small route traffic adjustment strategy alone; the improved BFS best priority search algorithm significantly improves the calculation speed when solving the traffic adjustment model. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The accompanying drawings are only provided for reference and explanation and are not intended to limit the present invention.

[0059] Figure 1 A schematic diagram of the steps of a hybrid cross-path adjustment method of the present invention;

[0060] Figure 2 This is a schematic diagram of a mixed adjustment mode that simultaneously uses a small circuit and a single-line bidirectional mode in the present invention;

[0061] Figure 3 This is a schematic diagram of safe departure when the j+1 train ahead is a reverse train according to the present invention;

[0062] Figure 4 This is a schematic diagram of safe departure when the j+1 train ahead is a train in the same direction according to the present invention;

[0063] Figure 5 This is a flow chart of the improved search algorithm of the present invention;

[0064] Figure 6 This is a schematic diagram of Nanjing Metro Line S1 of the present invention;

[0065] Figure 7 This is a schematic diagram of the mesoscopic track model of Nanjing Metro S1 Line of the present invention

[0066] Figure 8 Schematic diagram of optional route plan after interruption of the present invention

[0067] Fig. 9 This is the optimal driving diagram for the interruption continuation phase of the present invention. DETAILED DESCRIPTION

[0068] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below with reference to specific diagrams.

[0069] The present invention considers a method for adjusting traffic under operation interruption based on mixed routes, and models the traffic adjustment under operation interruption, such as Figure 1As shown, the following steps are included:

[0070] S1, mixed route traffic adjustment strategy based on small routes and single-track bidirectional to reduce the impact of interruption on passenger travel;

[0071] S2, measure the impact of traffic adjustment schemes on passengers based on total passenger travel time;

[0072] S3, establish a traffic adjustment model based on S1 and S2: take the train route plan as the decision variable and establish an optimization model with the minimum total passenger travel time as the goal;

[0073] S4. Use the BFS best-first search algorithm to solve the model, evaluate the traversed solutions according to the heuristic evaluation function to save computing time and obtain the best driving adjustment plan.

[0074] like Figure 2-Figure 9 As shown,

[0075] S1 specifically includes the following steps:

[0076] like Figure 2 As shown, S101, it is clear that the research object is an operational interruption scenario in which a one-way interruption occurs on a two-way urban rail line. Some stations on the line have conditions such as crossovers, which allow trains to run small routes at turnaround stations, and also allow trains to use crossovers to borrow opposite tracks to organize single-line two-way operation. Except for the trains trapped by the interruption, no train suspension is allowed.

[0077] S2 specifically includes the following steps: S201, aiming to minimize the total passenger travel time.

[0078] MinZ=t p_total

[0079] S3 specifically includes the following steps:

[0080] S301 In order to make the model feasible, it is necessary to simplify the actual situation and make assumptions;

[0081] S302 uses the train route plan as a decision variable, and specifically includes the following steps:

[0082] (1) Train-reachable node constraint: The node reached by a certain train must be reachable by the route plan selected by the train;

[0083] (2) Tracking train safety constraints: Tracking train safety constraints comply with automatic station-to-station blocking, and the time when the train arrives at the exit node must meet the constraints;

[0084] (3) Safety constraints for single-track bidirectional shared track: For the shared track section in a single-track bidirectional intersection, in addition to the tracking trains in the same direction, there are also safety constraints for the trains in the opposite direction;

[0085] like Figure 3 As shown in the figure, if for a single-track two-way train, when entering the shared section, the j+1 train ahead is a reverse train, then it must wait until the train leaves the switch node before it is allowed to exit the station; Figure 4 As shown in the figure, if the j+1 train ahead is a train in the same direction, it will be controlled according to the automatic station-to-station blocking;

[0086] (4) Constraints on the operation time of adjacent nodes: In the mesoscopic track line model, both stop and interval operation can be described as the operation time between nodes, so the operation time between adjacent nodes should meet the constraints;

[0087] (5) Passenger boarding constraints: Selecting different route plans for trains will result in changes in the destinations that the trains can reach;

[0088] (6) Train capacity constraint: At any time T, the number of passengers on the train should satisfy the train passenger capacity constraint.

[0089] like Figure 5 As shown, S4 specifically includes the following steps:

[0090] S401, initializing the intersection combination i=0; initial optimal solution and target value [0, Z min =+∞];

[0091] S402, simplifying the calculation of the valuation function H of the intersection combination i, requiring the valuation function H ≤ the actual target value Z, so as not to miss the best solution due to estimation errors, and the valuation function H is as close to the actual target value Z as possible under the premise of convenient calculation;

[0092] S403. Compare the valuation function value of a certain plan with the actual value of the currently calculated best plan. If the valuation of the plan is higher than the current best plan, it is considered that the actual value of the plan cannot be better than the current result. There is no need to calculate this plan, which saves calculation time and ultimately finds the optimal driving adjustment plan.

[0093] The model is verified using Nanjing Metro Line S1:

[0094] like Figure 6 As shown in the figure, the example uses the Nanjing Metro Line S1 map, as shown in Figure 7 As shown, Figure 6The line diagram is simplified and converted into a mesoscopic track model. Assuming that the interruption occurs at 12:08 (43680) noon on a normal working day, the time in brackets is in seconds, and the interruption area occurs on the up track of Fangzheng Middle Road Station. According to the track network after the interruption, there are several intersection plans, such as Figure 8 As shown. Assume that it takes 5 minutes of transition time from the occurrence of an interruption to the activation of the driving adjustment strategy. During this period, the train waits at the current station and makes driving adjustments in the waiting position during the interruption period. The fuzzy passenger flow used in the example is based on the daily passenger flow of Line S1. According to the 2020 data, the average daily passenger flow is 90,000, the operating time is 16 hours, and the average passenger flow rate of the entire line is 1.56 people / second. Considering that the interruption time is a flat-peak period, the passenger flow arrival rate of the entire line is α = 1.5 people / second. Nanjing South Station is set to account for 25%, Lukou Airport accounts for 20%, Xiangyu Road South accounts for 15%, and the remaining 5 stations account for 8% each. The dispatcher estimates that the interruption will end at 14:00. The driving adjustment model for the interruption period starts immediately after the line situation is known. The minimum stop time is set to 20 seconds. The platform waiting time penalty coefficient is set to 1 in the calculation of this article.

[0095] Table 1

[0096]

[0097] The optimal mixed-route traffic diagram for the interruption duration phase is obtained through calculation. Fig. 9 , except for the No. 11 car that was trapped due to the interruption fault, the No. 1, 3, 5, 7, and 9 car trains were used to operate the small route plan, and the No. 2, 4, 6, 8, and 10 car trains were used to operate the single-track two-way route plan. The total passenger travel time under this route combination is the shortest. When the platform waiting time penalty coefficient is 1, the target value result is 16989318 seconds, as shown in Table 1. Compared with not using the train adjustment at all, it reduces the passenger travel time by 64.4%; if only the small route plan is used, without considering the transfer of passengers through bus connections, the target value result is 35909244 seconds; if only the single-track two-way route plan is used, the target value result is 20874048 seconds. It can be seen that in the absence of good bus connection conditions, the single-line two-way driving adjustment mode can better meet the travel needs of passengers. The mixed route driving adjustment strategy proposed in this paper can reduce the passenger travel time by 18.6% compared with the single-line two-way driving adjustment scheme, proving the effectiveness and practical value of mixed routes in one-way interruption scenarios.

Claims

1. A method for adjusting traffic interruption based on mixed routes, characterized in that Modeling the train route plan includes the following steps: S1. Based on the small-route traffic adjustment strategy and the single-track two-way traffic adjustment strategy, a mixed-route traffic adjustment strategy of "single-track two-way + small-route" is proposed in the case of one-way interruption of the track line; S2, measure the impact of traffic adjustment schemes on passengers based on total passenger travel time; S3, establish a traffic adjustment model based on S1 and S2: take the train route plan as the decision variable and establish an optimization model with the minimum total passenger travel time as the goal; S4. Use the BFS best-first search algorithm to solve the model, evaluate the traversed solutions according to the heuristic evaluation function to save computing time and obtain the best driving adjustment plan.

2. The method for adjusting traffic interruption based on mixed routes according to claim 1, characterized in that: S1 specifically includes the following steps: S101. The research object is defined as an operational interruption scenario in which a one-way interruption occurs on a two-way urban rail line. Some stations on the line have conditions such as crossovers, which allow trains to operate in short routes at stations where they can turn back, and also allow trains to use crossovers to borrow the opposite track to organize single-line two-way operation. Except for the trains that are affected by the interruption and are trapped, no train service is allowed to be suspended.

3. The method for adjusting traffic interruption based on mixed routes according to claim 1, characterized in that: S2 specifically includes the following steps: S201, using the total passenger platform waiting time and the total passenger on-board time to represent the total passenger travel time t within the optimization period p_total .

4. The method for adjusting traffic interruption based on mixed routes according to claim 1, characterized in that: S3 specifically includes the following steps: S301. In order to make the model feasible, it is necessary to simplify the actual situation and make the following assumptions; S302, taking the train route plan as a decision variable; S303. During the interruption period, the main purpose of the train adjustment is to restore some capacity as much as possible, reduce the number of passengers stranded in the station, and complete the passenger transfer task under limited conditions. The objective function is to minimize the total passenger travel time, as follows: Z=t p_total 。 5. The method for adjusting traffic interruption based on mixed routes according to claim 1, characterized in that: S4 specifically includes the following steps: S401, initializing the intersection combination i=0; initial optimal solution and target value [0, Zmin=+∞]; S402, simplifying the calculation of the valuation function H of the intersection combination i, requiring the valuation function H ≤ the actual target value Z, so as not to miss the nearest solution due to estimation errors, and the valuation function H is as close to the actual target value Z as possible under the premise of convenient calculation; S403: Compare the valuation function value of a certain solution with the actual value of the currently calculated best solution.

6. The method for adjusting traffic interruption based on mixed routes according to claim 4, characterized in that: S301 specifically includes the following steps: (1) For single-track bidirectional trains, if there are trains waiting on both sides of the interruption area, the routes are arranged in order of priority. (2) Trains running on the same platform shall adopt the same route plan. (3) Trains should be dispatched as much as possible while satisfying the constraints. (4) Passengers enter the station at a fixed arrival rate, and the OD of passengers arriving at different stations is known. (5) Assume that the time it takes for a train to pass through the station section is the same as before the interruption. (6) Passenger boarding is subject to train capacity restrictions. Passengers who are unable to board will continue to wait for the next available train. (7) Assuming that passengers get on and off the train instantly, in order to make the calculation clear, it is stipulated that passengers get off when the train enters the station and get on when the train leaves the station.

7. The method for adjusting traffic interruption based on mixed routes according to claim 5, characterized in that: S403 specifically includes the following steps: (1) Compare the valuation function value of a solution with the actual value of the currently calculated best solution; (2) If the estimated value of the scheme is higher than the current optimal scheme, it is considered that the actual value of the scheme cannot be better than the current result. There is no need to calculate this scheme, which saves calculation time and ultimately finds the optimal driving adjustment plan.

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