Train operation scheduling real-time adjustment method and system considering jump stop strategy

Abstract

The invention discloses a train operation scheduling real-time adjustment method and system considering a jump stop strategy, and the method comprises the steps: obtaining train operation adjustment data and passenger flow dynamic fluctuation data based on an original train operation plan, station real-time passenger flow data and predicted OD data; establishing a mathematical model with urban rail system capability and service quality as targets, and obtaining a train scheduling and jump stop adjustment strategy based on train operation adjustment data and passenger flow dynamic fluctuation data; and determining the station dwell time and the interval operation time of the jump stop train at each station based on the train dispatching and stopping and jump stop adjustment strategy and in combination with the real-time train dispatching condition, and performing real-time adjustment on the train operation. The comprehensive optimization problem based on the jump stop strategy is researched, and a novel thought is provided for the train operation control method in the aspects of improving the performance of the urban rail transit system and improving the passenger service quality in real time.

Description

Technical Field

[0001] The present invention relates to the field of train operation optimization and adjustment in an urban rail transit system, and in particular to a method and system for real-time adjustment of train operation scheduling taking into account a skip stop strategy. Background Art

[0002] Passenger flow and driving are the core of urban rail transit operations. Formulating an operation plan that meets the characteristics of passenger flow is the key to urban rail transit providing high-quality transportation services to the outside world. At present, urban rail transit operations in most cities in my country usually refer to historical passenger flow data and passenger flow forecast results, divide the operating hours of a day into several time periods in advance according to passenger flow demand, and adopt equal operating scales and departure intervals in different time periods. However, with the evolution of urban passenger flow conditions, this method of preparing transportation plans for preset passenger flow time periods can no longer meet the passenger flow needs that change dynamically over time. The method of pre-dividing time periods and starting at equal intervals has poor flexibility. When faced with real-time passenger flow fluctuations caused by time disturbances, it is impossible to make effective adjustments quickly, which is easy to cause large-scale train delays and passenger congestion at transfer stations, resulting in an increased risk of damage to the interests of enterprises and passengers.

[0003] With the continuous construction of urban rail transit networks, the number of super-long urban rail lines is increasing. Taking Beijing as an example, there are already 12 lines with a main line operating length of more than 35 kilometers, and the operating mileage accounts for nearly half of the total road network mileage, which has become an important part of the road network structure that cannot be ignored. Compared with other lines, super-long urban rail lines with large spatial spans and a large number of transfer stations often need to bear more transportation pressure. The increase in passenger flow and interference has put forward higher requirements on the convenience and scientificity of train organization methods. At the same time, the construction of super-long lines usually needs to be divided into multiple phases, so the lines built in each phase have the function of independent operation, which provides a facility foundation for the development of more diversified operation organization methods.

[0004] The existing urban rail train operation adjustment technology has a certain degree of practicality, but there are still some issues that deserve further study, mainly including:

[0005] 1) Most train operation adjustment methods only consider the adjustment of train timetables, and there are few methods that introduce route plans or stop plan adjustments based on passenger flow fluctuations.

[0006] 2) There are relatively few studies that consider real-time adjustment optimization during the delay adjustment process, and there are fewer studies on the impact of real-time passenger flow fluctuations on technical indicators such as the train's stop time at stations and the running time in the section, which will lead to a decrease in the coupling between train operation and passenger flow after adjustment. Summary of the invention

[0007] In view of the technical defects and technical drawbacks in the prior art, the embodiments of the present invention provide a method and system for real-time adjustment of train operation scheduling considering a skipping strategy to overcome the above problems or at least partially solve the above problems. The specific scheme is as follows:

[0008] As a first aspect of the present invention, a method for real-time adjustment of train operation scheduling considering a skip stop strategy is provided, the method comprising:

[0009] Step 1: Based on the original train operation plan, the real-time passenger flow data of the station and the predicted OD data, the train operation adjustment data and the passenger flow dynamic fluctuation data are obtained;

[0010] Step 2: Establish a mathematical model with the urban rail system capacity and service quality as the target, and obtain the train scheduling and skipping adjustment strategy based on the train operation adjustment data and passenger flow dynamic fluctuation data;

[0011] Step 3: Based on the train mediation and skip stop adjustment strategies and combined with the real-time train scheduling situation, determine the stop time of the skip stop train at each station and the interval running time, and make real-time adjustments to the train operation.

[0012] Further, step 1 comprises:

[0013] During the operation of the train, due to various factors, there will be small delays, causing the train to deviate from the nominal schedule, which can be expressed by the formula:

[0014]

[0015] Where: represents the actual departure time of train i at station k, is the actual departure time of train i at station k-1, and are the actual running time of the i-th train from station k-1 to station k and the stop time of the i-th train at station k, respectively. is the departure time deviation of the i-th train at station k, is the scheduled departure time of train i at station k;

[0016] The dynamic equation for the change of passengers on the bus from one stop to the next can be expressed as:

[0017]

[0018] In the formula: represents the number of passengers on train i when it leaves station k, represents the number of passengers on train i when it leaves station k-1, represents the number of passengers boarding train i at station k, represents the number of passengers getting off train i at station k;

[0019] Since the number of passengers on the train is determined by the number of people waiting and the train capacity, the following formula can be obtained:

[0020]

[0021] Where: P max is the maximum passenger capacity of the train, is the number of people waiting at platform k when train i-1 departs, represents the passenger arrival rate at platform k before train i departs and after train i-1 departs, which can be measured in real time using monitoring technology. is a 0-1 variable used to determine whether train i stops at station k;

[0022] When the i-th train skips the k-th station, no passengers are allowed to board the train, that is, It can be expressed as:

[0023]

[0024] In the formula, It represents the number of passengers arriving at station k during the time interval between the departure of train i-1 and the arrival of train i.

[0025] Furthermore, step 2 includes:

[0026] From the perspective of the urban rail transit system, the model aims to minimize the deviation between the actual train departure time and the timetable and minimize the adjustment cost, and establish a mathematical model with the urban rail system capacity and service quality as the goal, which can be expressed as:

[0027] J=αJ1+βJ2

[0028] Wherein, J represents the total service quality, i.e., the objective function of the mathematical model, J1 represents the station service quality, J2 represents the train punctuality service quality, α and β are the weight coefficients of the station service quality and the train punctuality service quality, respectively. By setting the weight coefficients α and β, a trade-off between passenger service quality and system performance can be achieved;

[0029] The service quality of passengers is measured by the weighted number of skipped stations and the weighted number of the total number of waiting passengers. Since the skip station strategy will reduce the service quality of passengers who want to get off at the skipped station, and the skip stop strategy will change the original transportation plan, thereby increasing the difficulty of urban rail transit operation scheduling, in addition, the increase in the number of passengers waiting on the platform makes the platform crowded, creates safety hazards, and thus reduces passenger satisfaction. Based on this, the mathematical model uses the number of waiting passengers on each platform to measure the service quality, which is expressed as:

[0030]

[0031] Among them, ω1~ω5 are weight coefficients, is the departure time deviation of the i-th train at station k, is the train running time adjustment of train i from station k-1 to station k, in seconds. is the adjustment of the stop time of train i at station k, is a 0-1 variable used to determine whether train i stops at station k. Refers to the number of passengers stranded on the platform after train i leaves station k.

[0032] Through the mathematical model, based on It can be obtained whether train i stops at station k. The model can be used to calculate whether train i stops at each station in turn. Based on the adjustment amount of the stop time of train i at station k and the stop time of train i at station k in the original train operation plan, the stop time of train i at station k can be calculated to realize the scheduling and skipping adjustment of the train.

[0033] Further, step 3 includes:

[0034] The stop time of train i at station k calculated according to the skip stop adjustment strategy is defined as have:

[0035]

[0036] In the formula represents the fixed operating time of train i at station k, is the boarding and alighting time of passengers of train i at station k, is the redundant boarding and alighting time of train i at station k.

[0037] The ATS system automatically adjusts the running trains. The value is consistent with the minimum dwell time pre-set in the ATS system. and maximum stay time Compare and finally determine the actual stay time of train i at station k according to the following formula It is expressed as follows:

[0038]

[0039] Define the running time of train i from the kth station to the k+1th station calculated by ATS as but:

[0040]

[0041] In the formula, is the scheduled running time of train i from the kth station to the k+1th station, The additional time that train i stops at station k+1.

[0042] The ATS system will The calculated value and the preset minimum running time and the maximum running time Compare and finally determine the actual running time according to the following formula It is expressed as follows:

[0043]

[0044] Furthermore, the method further includes: maintaining the safe running distance of the train, checking whether the current train and the adjacent trains meet the safety constraints, and if not, further adjusting or Until the safety constraints are met to ensure the normal operation of the train set.

[0045] Furthermore, the method also includes: using an MPC algorithm to perform comprehensive real-time optimization on train scheduling and skip-stop adjustment strategies.

[0046] Furthermore, the use of the MPC algorithm to comprehensively optimize the train scheduling and skipping adjustment strategy in real time includes:

[0047] Step 101, at each sampling stage h, the prediction time step is t p According to the current measured state information, the optimization problem is obtained at the optimization layer [h,h+t p ] in the desired prediction state;

[0048] Step 102: According to the measured state data and the preset optimized time domain [h,h+t p ] (including the number of stations within the optimization range), establish a mixed integer quadratic programming model, and solve the model to obtain a series of optimal control behaviors φ * (h:h+t p );

[0049] In step 103, the first control action is applied, and steps 101 and 102 are repeated until the optimization range is exceeded.

[0050] As a second aspect of the present invention, a real-time adjustment system for train operation scheduling considering a skip stop strategy is provided, the system comprising:

[0051] The train operation dynamic adjustment module is used to obtain train operation adjustment data and passenger flow dynamic fluctuation data based on the original train operation plan, station real-time passenger flow data and predicted OD data;

[0052] The train skipping adjustment module establishes a mathematical model based on the urban rail system capacity and service quality, and obtains train scheduling and skipping adjustment strategies based on train operation adjustment data and passenger flow dynamic fluctuation data;

[0053] The real-time train adjustment module is used to determine the stop time and section running time of skip-stop trains at each station based on the train mediation and skip-stop adjustment strategies and combined with the real-time train scheduling situation, and make real-time adjustments to the train operation.

[0054] Furthermore, the train operation dynamic adjustment module is specifically used for:

[0055] During the operation of the train, due to various factors, there will be small delays, causing the train to deviate from the nominal schedule, which can be expressed by the formula:

[0056]

[0057] Where: represents the actual departure time of train i at station k, is the actual departure time of train i at station k-1, and are the actual running time of the i-th train from station k-1 to station k and the stop time of the i-th train at station k, respectively. is the departure time deviation of the i-th train at station k, is the scheduled departure time of train i at station k;

[0058] The dynamic equation for the change of passengers on the bus from one stop to the next can be expressed as:

[0059]

[0060] In the formula: represents the number of passengers on train i when it leaves station k, represents the number of passengers on train i when it leaves station k-1, represents the number of passengers boarding train i at station k, represents the number of passengers getting off train i at station k;

[0061] Since the number of passengers on the train is determined by the number of people waiting and the train capacity, the following formula can be obtained:

[0062]

[0063] Where: P max is the maximum passenger capacity of the train, is the number of people waiting at platform k when train i-1 departs, represents the passenger arrival rate at platform k before train i departs and after train i-1 departs, which can be measured in real time using monitoring technology. is a 0-1 variable used to determine whether train i stops at station k;

[0064] When the i-th train skips the k-th station, no passengers are allowed to board the train, that is, It can be expressed as:

[0065]

[0066] In the formula, represents the number of passengers arriving at station k during the time interval between the departure of train i-1 and the arrival of train i;

[0067] The train skip adjustment module is specifically used for:

[0068] From the perspective of the urban rail transit system, the model aims to minimize the deviation between the actual train departure time and the timetable and minimize the adjustment cost, and establish a mathematical model with the urban rail system capacity and service quality as the goal, which can be expressed as:

[0069] J=αJ1+βJ2

[0070] Wherein, J represents the total service quality, i.e., the objective function of the mathematical model, J1 represents the station service quality, J2 represents the train punctuality service quality, α and β are the weight coefficients of the station service quality and the train punctuality service quality, respectively. By setting the weight coefficients α and β, a trade-off between passenger service quality and system performance can be achieved;

[0071] The service quality of passengers is measured by the weighted number of skipped stations and the weighted number of the total number of waiting passengers. Since the skip station strategy will reduce the service quality of passengers who want to get off at the skipped station, and the skip stop strategy will change the original transportation plan, thereby increasing the difficulty of urban rail transit operation scheduling, in addition, the increase in the number of passengers waiting on the platform makes the platform crowded, creates safety hazards, and thus reduces passenger satisfaction. Based on this, the mathematical model uses the number of waiting passengers on each platform to measure the service quality, which is expressed as:

[0072]

[0073] Among them, ω1~ω5 are weight coefficients, is the train running time adjustment of train i from station k-1 to station k, in seconds, is the adjustment of the stop time of train i at station k, is a 0-1 variable used to determine whether train i stops at station k. Refers to the number of passengers stranded on the platform after train i leaves station k.

[0074] Furthermore, the train real-time adjustment module is specifically used for:

[0075] The stop time of train i at station k calculated according to the skip stop adjustment strategy is defined as have:

[0076]

[0077] In the formula represents the fixed operating time of train i at station k, is the boarding and alighting time of passengers of train i at station k, is the redundant boarding and alighting time of train i at station k.

[0078] The ATS system automatically adjusts the running trains. The value is consistent with the minimum dwell time pre-set in the ATS system. and maximum stay time Compare and finally determine the actual stay time of train i at station k according to the following formula It is expressed as follows:

[0079]

[0080] Define the running time of train i from the kth station to the k+1th station calculated by ATS as but:

[0081]

[0082] In the formula, is the scheduled running time of train i from the kth station to the k+1th station, The additional time that train i stops at station k+1.

[0083] The ATS system will The calculated value and the preset minimum running time and the maximum running time Compare and finally determine the actual running time according to the following formula It is expressed as follows:

[0084]

[0085] The present invention has the following beneficial effects:

[0086] The present invention aims to reduce the timetable error of the urban rail transit system and improve passenger satisfaction. Taking into account vehicle constraints and the dynamic evolution of passenger flow, the present invention studies the comprehensive optimization problem based on the skip-stop strategy, and proposes a novel idea for the train operation control method in improving the performance of the urban rail transit system and improving the passenger service quality in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 A flow chart of a method for real-time adjustment of train operation scheduling considering a skip stop strategy provided by an embodiment of the present invention;

[0088] Figure 2 A diagram of the bidirectional urban rail line and station configuration provided by an embodiment of the present invention;

[0089] Figure 3 A diagram of the state transfer portion of the algorithm provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0090] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0091] See also Figure 1 As shown, a real-time adjustment method for train operation scheduling considering a skipping strategy is provided in an embodiment of the present invention, and the method includes:

[0092] Step 1: Based on the original train operation plan, the real-time passenger flow data of the station and the predicted OD data, the train operation adjustment data and the passenger flow dynamic fluctuation data are obtained;

[0093] Step 2: Establish a mathematical model with the urban rail system capacity and service quality as the target, and obtain the train scheduling and skipping adjustment strategy based on the train operation adjustment data and passenger flow dynamic fluctuation data;

[0094] Step 3: Based on the train mediation and skip stop adjustment strategies and combined with the real-time train scheduling situation, determine the stop time of the skip stop train at each station and the interval running time, and make real-time adjustments to the train operation.

[0095] The present invention aims to reduce the timetable error of the urban rail transit system and improve passenger satisfaction. Taking into account vehicle constraints and the dynamic evolution of passenger flow, the present invention studies the comprehensive optimization problem based on the skip-stop strategy, and proposes a novel idea for the train operation control method in improving the performance of the urban rail transit system and improving the passenger service quality in real time.

[0096] Preferably, step 1 comprises:

[0097] Assume that all trains in the original timetable generated before daily operation are stop-at-every-station trains. Ideally, all trains will run strictly according to the scheduled schedule and perfectly achieve their respective transportation tasks in the plan. However, the actual operation of trains cannot be perfectly executed due to various interferences. Therefore, it is necessary to dynamically adjust the trains according to the actual situation. The dynamic nature of this aspect is specifically manifested in:

[0098] Get train operation adjustment data, as follows:

[0099] During the operation of the train, due to various factors (such as equipment failure, weather, etc.), there will be small delays, causing the train to deviate from the nominal schedule, which can be expressed by the formula:

[0100]

[0101] Where: represents the actual departure time of train i at station k, is the actual departure time of train i at station k-1, and are the actual running time of the i-th train from station k-1 to station k and the stop time of the i-th train at station k, respectively. is the departure time deviation of the i-th train at station k, is the scheduled departure time of train i at station k;

[0102] Get passenger flow dynamic fluctuation data, as follows:

[0103] This model explicitly describes the dynamic changes of passengers on board and waiting passengers as each train moves from one station to the next. The dynamic equation for the change of passengers on board from one station to the next can be expressed as:

[0104]

[0105] In the formula: represents the number of passengers on train i when it leaves station k, represents the number of passengers on train i when it leaves station k-1, represents the number of passengers boarding train i at station k, represents the number of passengers getting off train i at station k;

[0106] Since the number of passengers on the train is determined by the number of people waiting and the train capacity, the following formula can be obtained:

[0107]

[0108] Where: P max is the maximum passenger capacity of the train, is the number of people waiting at platform k when train i-1 departs, represents the passenger arrival rate at platform k before train i departs and after train i-1 departs, which can be measured in real time using monitoring technology. is a 0-1 variable used to determine whether train i stops at station k;

[0109] When the i-th train skips the k-th station, no passengers are allowed to board the train, that is, It can be expressed as:

[0110]

[0111] In the formula, It represents the number of passengers arriving at station k during the time interval between the departure of train i-1 and the arrival of train i.

[0112] Preferably, step 2 comprises:

[0113] It is often difficult for urban rail transit operators to make real-time decisions that satisfy all stakeholders at the same time. Taking this into consideration, the present invention proposes a comprehensive optimization method that takes into account both the capacity of the urban rail transit system and the quality of passenger service. From the perspective of the urban rail transit system, the model objectives are to minimize the deviation between the actual train departure time and the schedule and to minimize the adjustment cost, which can be expressed as:

[0114] J=αJ1+βJ2

[0115] Wherein, J represents the total service quality, i.e., the objective function of the mathematical model, J1 represents the station service quality, J2 represents the train punctuality service quality, α and β are the weight coefficients of the station service quality and the train punctuality service quality, respectively. By setting the weight coefficients α and β, a trade-off between passenger service quality and system performance can be achieved;

[0116] The service quality of passengers is measured by the weighted number of skipped stations and the weighted number of the total number of waiting passengers. Since the skip station strategy will reduce the service quality of passengers who want to get off at the skipped station, and the skip stop strategy will change the original transportation plan, thereby increasing the difficulty of urban rail transit operation scheduling, in addition, the increase in the number of passengers waiting on the platform makes the platform crowded, creates safety hazards, and thus reduces passenger satisfaction. Based on this, the mathematical model uses the number of waiting passengers on each platform to measure the service quality, which is expressed as:

[0117]

[0118] Among them, ω1~ω5 are weight coefficients, is the departure time deviation of the i-th train at station k, is the train running time adjustment of train i from station k-1 to station k, in seconds. is the adjustment of the stop time of train i at station k, is a 0-1 variable used to determine whether train i stops at station k. Refers to the number of passengers stranded on the platform after train i leaves station k.

[0119] Through the mathematical model, based on It can be obtained whether train i stops at station k. The model is used to calculate whether train i stops at each station in turn. Based on the stop time adjustment amount of train i at station k and the stop time of train i at station k in the original train operation plan, the stop time of train i at station k can be calculated. That is, the mathematical model can be used to obtain whether the train stops at each station and the corresponding stop time, thereby realizing the scheduling and skipping adjustment of the train.

[0120] Preferably, step 3 comprises:

[0121] Combined with the real-time train dispatching situation, under the condition of ensuring that there is no conflict in train operation, the arrival and departure times of skip-stop trains at each station are determined, and the real-time adjustment technology of train operation dispatching for super-long urban rail lines based on the skip-stop strategy is considered, as follows:

[0122] The stop time of train i at station k calculated according to the skip stop adjustment strategy is defined as have:

[0123]

[0124] In the formula represents the fixed operating time of train i at station k, is the boarding and alighting time of passengers of train i at station k, is the redundant boarding and alighting time of train i at station k.

[0125] The ATS system automatically adjusts the running trains. The value is consistent with the minimum dwell time pre-set in the ATS system. and maximum stay time Compare and finally determine the actual stay time of train i at station k according to the following formula It is expressed as follows:

[0126]

[0127] Define the running time of train i from the kth station to the k+1th station calculated by ATS as but:

[0128]

[0129] In the formula, is the scheduled running time of train i from the kth station to the k+1th station, The additional time that train i stops at station k+1.

[0130] The ATS system will The calculated value and the preset minimum running time and the maximum running time Compare and finally determine the actual running time according to the following formula It is expressed as follows:

[0131]

[0132] Maintain the safe running distance of the train, check whether the current train and adjacent trains meet the safety constraints, if not, make further adjustments or Until the safety constraints are met to ensure the normal operation of the train set.

[0133] Preferably, the real-time adjustment method for train operation scheduling considering the skip stop strategy provided by the present invention further comprises: using an MPC algorithm to comprehensively optimize the train scheduling and skip stop adjustment strategy in real time;

[0134] The specific steps are as follows:

[0135] 1a) In each sampling stage, the predicted state required by the optimization problem in the optimization layer is obtained based on the current measured state information.

[0136] 1b) Based on the measured state data and the given optimization horizon (including the number of stations within the optimization range), a mixed integer quadratic programming model is established and a series of optimal control behaviors are obtained by solving the model.

[0137] 1c) Apply the first control action and repeat the above steps until the optimization range is exceeded.

[0138] Reference Figure 2-3 As shown, the present invention:

[0139] At each sampling stage h, the prediction time step is t p According to the current measured state information, the optimization problem is obtained at the optimization layer [h,h+t p ] in the desired prediction state;

[0140] According to the measured state data and the preset optimized time domain [h,h+t p ] (including the number of stations within the optimization range), establish a mixed integer quadratic programming model, and solve the model to obtain a series of optimal control behaviors φ * (h:h+t p);

[0141] In step 103, the first control action is applied, and steps 101 and 102 are repeated until the optimization range is exceeded.

[0142] In the above embodiment, a model predictive control (MPC) algorithm is specially designed to solve the optimization model with a heuristic method, while meeting the real-time requirements of train operation automatic control for train scheduling.

[0143] As a second aspect of the present invention, a real-time adjustment system for train operation scheduling considering a skip stop strategy is provided, the system comprising:

[0144] The train operation dynamic adjustment module is used to obtain train operation adjustment data and passenger flow dynamic fluctuation data based on the original train operation plan, station real-time passenger flow data and predicted OD data;

[0145] The train skipping adjustment module establishes a mathematical model based on the urban rail system capacity and service quality, and obtains train scheduling and skipping adjustment strategies based on train operation adjustment data and passenger flow dynamic fluctuation data;

[0146] The real-time train adjustment module is used to determine the stop time and section running time of skip-stop trains at each station based on the train mediation and skip-stop adjustment strategies and combined with the real-time train scheduling situation, and make real-time adjustments to the train operation.

[0147] Preferably, the train operation dynamic adjustment module is specifically used for:

[0148] During the operation of the train, due to various factors, there will be small delays, causing the train to deviate from the nominal schedule, which can be expressed by the formula:

[0149]

[0150] Where: represents the actual departure time of train i at station k, is the actual departure time of train i at station k-1, and are the actual running time of the i-th train from station k-1 to station k and the stop time of the i-th train at station k, respectively. is the departure time deviation of the i-th train at station k, is the scheduled departure time of train i at station k;

[0151] The dynamic equation for the change of passengers on the bus from one stop to the next can be expressed as:

[0152]

[0153] In the formula: represents the number of passengers on train i when it leaves station k, represents the number of passengers on train i when it leaves station k-1, represents the number of passengers boarding train i at station k, represents the number of passengers getting off train i at station k;

[0154] Since the number of passengers on the train is determined by the number of people waiting and the train capacity, the following formula can be obtained:

[0155]

[0156] Where: P max is the maximum passenger capacity of the train, is the number of people waiting at platform k when train i-1 departs, represents the passenger arrival rate at platform k before train i departs and after train i-1 departs, which can be measured in real time using monitoring technology. is a 0-1 variable used to determine whether train i stops at station k;

[0157] When the i-th train skips the k-th station, no passengers are allowed to board the train, that is, It can be expressed as:

[0158]

[0159] In the formula, represents the number of passengers arriving at station k during the time interval between the departure of train i-1 and the arrival of train i;

[0160] The train skip adjustment module is specifically used for:

[0161] From the perspective of the urban rail transit system, the model aims to minimize the deviation between the actual train departure time and the timetable and minimize the adjustment cost, and establish a mathematical model with the urban rail system capacity and service quality as the goal, which can be expressed as:

[0162] J=αJ1+βJ2

[0163] Wherein, J represents the total service quality, i.e., the objective function of the mathematical model, J1 represents the station service quality, J2 represents the train punctuality service quality, α and β are the weight coefficients of the station service quality and the train punctuality service quality, respectively. By setting the weight coefficients α and β, a trade-off between passenger service quality and system performance can be achieved;

[0164] The service quality of passengers is measured by the weighted number of skipped stations and the weighted number of the total number of waiting passengers. Since the skip station strategy will reduce the service quality of passengers who want to get off at the skipped station, and the skip stop strategy will change the original transportation plan, thereby increasing the difficulty of urban rail transit operation scheduling, in addition, the increase in the number of passengers waiting on the platform makes the platform crowded, creates safety hazards, and thus reduces passenger satisfaction. Based on this, the mathematical model uses the number of waiting passengers on each platform to measure the service quality, which is expressed as:

[0165]

[0166] Among them, ω1~ω5 are weight coefficients, is the train running time adjustment of train i from station k-1 to station k, is the adjustment of the stop time of train i at station k, is a 0-1 variable used to determine whether train i stops at station k. Refers to the number of passengers stranded on the platform after train i leaves station k.

[0167] Preferably, the train real-time adjustment module is specifically used for:

[0168] The stop time of train i at station k calculated according to the skip stop adjustment strategy is defined as have:

[0169]

[0170] In the formula represents the fixed operating time of train i at station k, is the boarding and alighting time of passengers of train i at station k, is the redundant boarding and alighting time of train i at station k.

[0171] The ATS system automatically adjusts the running trains. The value is consistent with the minimum dwell time pre-set in the ATS system. and maximum stay time Compare and finally determine the actual stay time of train i at station k according to the following formula It is expressed as follows:

[0172]

[0173] Define the running time of train i from the kth station to the k+1th station calculated by ATS as but:

[0174]

[0175] In the formula, is the scheduled running time of train i from the kth station to the k+1th station, The additional time that train i stops at station k+1.

[0176] The ATS system will The calculated value and the preset minimum running time and the maximum running time Compare and finally determine the actual running time according to the following formula It is expressed as follows:

[0177]

[0178] The present invention discloses a real-time adjustment technology for train operation scheduling of urban rail super-long lines considering the skipping strategy, with the goal of reducing the timetable error of the urban rail transit system and improving passenger satisfaction. Under the condition of considering vehicle constraints and dynamic evolution of passenger flow, the comprehensive optimization problem based on the skipping strategy is studied.

[0179] Firstly, a collaborative nonlinear programming model is established and then transformed into a mixed integer quadratic programming model which is easy to solve.

[0180] A model predictive control (MPC) algorithm is specially designed to solve the optimization model with a heuristic method, while meeting the real-time requirements of train scheduling for automatic train operation control.

[0181] The proposed model was tested under different adjustment strategies, passenger demands and model parameters. Compared with the actual urban rail train operation adjustment strategy, the proposed method showed the following characteristics:

[0182] 1) The skip-stop adjustment strategy can effectively reduce train timetable deviations and reduce the number of stranded passengers at stations.

[0183] 2) The proposed skip-stop strategy is also robust under uncertain passenger demand.

[0184] 3) A sensitivity analysis was performed on the weight coefficient of the objective function to provide a reference for adjusting the weight coefficient according to actual needs.

[0185] This work will provide a novel approach to train operation control methods in improving the performance of urban rail transit systems and enhancing the quality of passenger service in real time.

[0186] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A real-time adjustment method for train operation scheduling considering skip stop strategy, characterized in that: The method comprises: Step 1: Based on the original train operation plan, the real-time passenger flow data of the station and the predicted OD data, the train operation adjustment data and the passenger flow dynamic fluctuation data are obtained; Step 2: Establish a mathematical model based on the capacity and service quality of the urban rail system, and obtain the train scheduling and skipping adjustment strategy based on the train operation adjustment data and passenger flow dynamic fluctuation data; Step 3: Based on the train mediation and skip stop adjustment strategies and combined with the real-time train scheduling situation, determine the stop time of the skip stop train at each station and the interval running time, and make real-time adjustments to the train operation.

2. The method for real-time adjustment of train operation scheduling considering skipping stop strategy according to claim 1 is characterized in that: Step 1 includes: During the operation of the train, due to various factors, there will be small delays, causing the train to deviate from the nominal schedule, which can be expressed by the formula: Where: represents the actual departure time of train i at station k, is the actual departure time of train i at station k-1, and are the actual running time of the i-th train from station k-1 to station k and the stop time of the i-th train at station k, respectively. is the departure time deviation of the i-th train at station k, is the scheduled departure time of train i at station k; The dynamic equation for the change of passengers on the bus from one stop to the next can be expressed as: In the formula: represents the number of passengers on train i when it leaves station k, represents the number of passengers on train i when it leaves station k-1, represents the number of passengers boarding train i at station k, represents the number of passengers getting off train i at station k; Since the number of passengers on the train is determined by the number of people waiting and the train capacity, the following formula can be obtained: Where: P max is the maximum passenger capacity of the train, is the number of people waiting at platform k when train i-1 departs, represents the passenger arrival rate before train i departs and after train i-1 departs, is a 0-1 variable used to determine whether train i stops at station k; When the i-th train skips the k-th station, no passengers are allowed to board the train, that is, It can be expressed as: In the formula, It represents the number of passengers arriving at station k during the time interval between the departure of train i-1 and the arrival of train i.

3. The real-time adjustment method for train operation scheduling considering the skipping strategy according to claim 1 is characterized in that: Step 2 includes: From the perspective of the urban rail transit system, the model aims to minimize the deviation between the actual train departure time and the timetable and minimize the adjustment cost, and establish a mathematical model with the urban rail system capacity and service quality as the goal, which can be expressed as: J=αJ1+βJ2 Wherein, J represents the total service quality, i.e., the objective function of the mathematical model, J1 represents the station service quality, J2 represents the train punctuality service quality, α and β are the weight coefficients of the station service quality and the train punctuality service quality, respectively. By setting the weight coefficients α and β, a trade-off between passenger service quality and system performance can be achieved; The service quality of passengers is measured by the weighted number of skipped stations and the weighted number of the total number of waiting passengers. Since the skipping station strategy will reduce the service quality of passengers who want to get off at the skipped station, and the skipping station strategy will reduce the service quality of passengers who want to get off at the skipped station. Strategy It will change the original transportation plan, thus increasing the difficulty of urban rail transit operation and scheduling. In addition, the increase in the number of passengers waiting on the platform makes the platform crowded, creates safety hazards, and reduces passenger satisfaction. Based on this, the mathematical model uses the number of people waiting on each platform to measure the service quality, which is expressed as: Among them, ω1~ω5 are weight coefficients, is the departure time deviation of the i-th train at station k, is the train running time adjustment of train i from station k-1 to station k, is the adjustment of the stop time of train i at station k, is a 0-1 variable used to determine whether train i stops at station k. Refers to the number of passengers stranded on the platform after train i leaves station k.

4. The method for real-time adjustment of train operation scheduling considering skipping strategy according to claim 1 is characterized in that: Step 3 includes: The stop time of train i at station k calculated according to the skip stop adjustment strategy is defined as have: In the formula represents the fixed operating time of train i at station k, is the boarding and alighting time of passengers of train i at station k, is the redundant boarding and alighting time of train i at station k; The ATS system automatically adjusts the running trains. The value is consistent with the minimum dwell time pre-set in the ATS system. and maximum stay time Compare and finally determine the actual stay time of train i at station k according to the following formula It is expressed as follows: Define the running time of train i from the kth station to the k+1th station calculated by ATS as but: In the formula, is the scheduled running time of train i from the kth station to the k+1th station, is the additional time for train i to stop at station k+1; The ATS system will The calculated value and the preset minimum running time and the maximum running time Compare and finally determine the actual running time according to the following formula It is expressed as follows:

5. The method for real-time adjustment of train operation scheduling considering skipping strategy according to claim 4 is characterized in that: The method also includes: maintaining the safe running distance of the train, checking whether the current train and the adjacent trains meet the safety constraints, and if not, further adjusting or Until the safety constraints are met to ensure the normal operation of the train set.

6. The method for real-time adjustment of train operation scheduling considering skipping strategy according to claim 1 is characterized in that: The method also includes: using an MPC algorithm to perform comprehensive real-time optimization on train scheduling and skip-stop adjustment strategies.

7. The method for real-time adjustment of train operation scheduling considering skipping strategy according to claim 6 is characterized in that: The comprehensive real-time optimization of train scheduling and skip adjustment strategies using the MPC algorithm includes: Step 101, in each sampling stage, obtaining the predicted state required by the optimization problem in the optimization layer according to the current measured state information; Step 102, based on the measured state data and the given optimization horizon (including the number of stations within the optimization range), a mixed integer quadratic programming model is established, and a series of optimal control behaviors are obtained by solving the model; Step 103, starting from applying the first control action, steps 101-102 are repeatedly executed until the optimization range is exceeded.

8. A real-time adjustment system for train operation scheduling considering skip stop strategy, characterized in that: The system comprises: The train operation dynamic adjustment module is used to obtain train operation adjustment data and passenger flow dynamic fluctuation data based on the original train operation plan, station real-time passenger flow data and predicted OD data; The train skipping adjustment module establishes a mathematical model based on the urban rail system capacity and service quality, and obtains train scheduling and skipping adjustment strategies based on train operation adjustment data and passenger flow dynamic fluctuation data; The real-time train adjustment module is used to determine the stop time and section running time of skip-stop trains at each station based on the train mediation and skip-stop adjustment strategies and combined with the real-time train scheduling situation, and make real-time adjustments to the train operation.

9. A train operation scheduling real-time adjustment system considering skipping strategy according to claim 8, characterized in that: The train operation dynamic adjustment module is specifically used for: During the operation of the train, due to various factors, there will be small delays, causing the train to deviate from the nominal schedule, which can be expressed by the formula: Where: represents the actual departure time of train i at station k, is the actual departure time of train i at station k-1, and are the actual running time of the i-th train from station k-1 to station k and the stop time of the i-th train at station k, respectively. is the departure time deviation of the i-th train at station k, is the scheduled departure time of train i at station k; The dynamic equation for the change of passengers on the bus from one stop to the next can be expressed as: In the formula: represents the number of passengers on train i when it leaves station k, represents the number of passengers on train i when it leaves station k-1, represents the number of passengers boarding train i at station k, represents the number of passengers getting off train i at station k; Since the number of passengers on the train is determined by the number of people waiting and the train capacity, the following formula can be obtained: Where: P max is the maximum passenger capacity of the train, is the number of people waiting at platform k when train i-1 departs, represents the passenger arrival rate before train i departs and after train i-1 departs, is a 0-1 variable used to determine whether train i stops at station k; When the i-th train skips the k-th station, no passengers are allowed to board the train, that is, It can be expressed as: In the formula, represents the number of passengers arriving at station k during the time interval between the departure of train i-1 and the arrival of train i; The train skip adjustment module is specifically used for: From the perspective of the urban rail transit system, the model aims to minimize the deviation between the actual train departure time and the timetable and minimize the adjustment cost, and establish a mathematical model with the urban rail system capacity and service quality as the goal, which can be expressed as: J=αJ1+βJ2 Wherein, J represents the total service quality, i.e., the objective function of the mathematical model, J1 represents the station service quality, J2 represents the train punctuality service quality, α and β are the weight coefficients of the station service quality and the train punctuality service quality, respectively. By setting the weight coefficients α and β, a trade-off between passenger service quality and system performance can be achieved; The service quality of passengers is measured by the weighted number of skipped stations and the weighted number of the total number of waiting passengers. Since the skipping station strategy will reduce the service quality of passengers who want to get off at the skipped station, and the skipping station strategy will reduce the service quality of passengers who want to get off at the skipped station. Strategy It will change the original transportation plan, thus increasing the difficulty of urban rail transit operation and scheduling. In addition, the increase in the number of passengers waiting on the platform makes the platform crowded, creates safety hazards, and reduces passenger satisfaction. Based on this, the mathematical model uses the number of people waiting on each platform to measure the service quality, which is expressed as: Among them, ω1~ω5 are weight coefficients, is the train running time adjustment of train i from station k-1 to station k, is the adjustment of the stop time of train i at station k, is a 0-1 variable used to determine whether train i stops at station k. Refers to the number of passengers stranded on the platform after train i leaves station k.

10. A train operation scheduling real-time adjustment system considering skipping strategy according to claim 8, characterized in that: The train real-time adjustment module is specifically used for: The stop time of train i at station k calculated according to the skip stop adjustment strategy is defined as have: In the formula represents the fixed operating time of train i at station k, is the boarding and alighting time of passengers of train i at station k, is the redundant boarding and alighting time of train i at station k; The ATS system automatically adjusts the running trains. The value is consistent with the minimum dwell time pre-set in the ATS system. and maximum stay time Compare and finally determine the actual stay time of train i at station k according to the following formula It is expressed as follows: Define the running time of train i from the kth station to the k+1th station calculated by ATS as but: In the formula, is the scheduled running time of train i from the kth station to the k+1th station, is the additional time for train i to stop at station k+1; The ATS system will The calculated value and the preset minimum running time and the maximum running time Compare and finally determine the actual running time according to the following formula It is expressed as follows:

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