Train operation and passenger flow coupling dynamic modeling and simulation system

Abstract

The application discloses a train operation and passenger flow coupling dynamic modeling and simulation system, which is applied to coping with peak passenger flow of urban rail transit and comprises train operation simulation and peak platform passenger flow characteristics; the train operation simulation comprises a driving simulation module, a monitoring simulation module, a protection simulation module and a simulation clock engine which are connected with each other, the monitoring simulation module sends instruction information to the driving simulation module, and the protection simulation module monitors the speed of adjacent trains; the simulation clock engine simulates real time to achieve the effect of timing guarantee; based on real data of rail transit lines, the application effectively designs a train operation scheduling adjustment scheme for simulation analysis in view of problems existing in early peak station passenger flow, improves the optimization space of the scheduling scheme under the early peak platform passenger flow congestion scene, evaluates the rationality and effectiveness of the scheduling scheme through system simulation analysis, and further verifies the relationship between train operation and dynamic passenger flow.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of rail transit, and in particular to a train operation and passenger flow coupling dynamic modeling and simulation system. BACKGROUND

[0002] The rail transit construction of a city has always been the development focus and difficulty of the entire city, and is one of the foundations of city development, but in the actual construction process, various situations need to be considered, for example, during the morning peak or evening peak period, the passenger flow at a bus station or a subway station will be relatively large, in order to avoid the adverse consequences caused by too many people, and to improve the operation capacity of rail transit, it is necessary to respond in a timely manner to various situations, so as to ensure the good operation of rail transit.

[0003] There are many theoretical studies on the relationship between train operation and dynamic passenger flow, but they cannot be applied to real scheduling systems at will; the "Urban Rail Transit CBTC Signal Control and Operation Management Simulation Training System" developed by Haitianwei Teaching and Experimental Equipment Co., Ltd. adopts the mainstream urban rail CBTC signal system architecture and technology, builds a training course system based on the work process, and constructs a training site according to the real work scene, real equipment and interface, and real work process. It can realize the simulation training of train operation signal, command system and scheduling system on the line, and the sand table adopts the mode of several physical stations + N virtual simulation stations to realize a complete line simulation system. Its advantage is that the investment is small, but it can simulate a complete subway line through the combination of virtual and real, and meet the requirements of full simulation of student training environment and working environment. But its defect is that it cannot simulate the whole line, and the physical sand table is not conducive to later maintenance and has high maintenance cost.

[0004] The "DB-DCZ21 Urban Rail Transit ATS (OCC) Virtual Training System" is developed by Shanghai Dingbang Education Equipment Manufacturing Co., Ltd. The system allows students to operate trains and handle trains from an operational perspective, and the simulation data is taken from real field data, and is equipped with a screen display system to display the operation of the train in real time. The advantage of the system is that it can enable students to fully understand the entire process and scene of handling trains, and improve the students' fault handling ability and response ability. But its defect is that in the simulation process, the traction data of train running is not added, so there is a big gap between the scene in the simulation process and the actual scene.

[0005] The "Urban Rail Transit Dispatching and Command Simulation System" developed by the National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology at Southwest Jiaotong University, using Chengdu Metro Line 1 as a case study, is a virtual-real hybrid simulation experimental system built through the transformation of scientific research achievements and independent research and development. The system comprises four platforms: a control center, a centralized interlocking station, a depot, and a simulation exercise management platform. It possesses functions such as urban rail transit train dispatching and control, train timetable compilation and adjustment, station interlocking equipment control, and depot vehicle operation plan management, making it the first of its kind among domestic universities. Through experimental operation of this system, trainees can become familiar with the train operation dispatching and command process and further master the basic operation methods of train dispatching and command in ATC mode and manual route mode. However, its shortcomings lie in the fact that it has not yet achieved coupling between simulated train operation and dynamic passenger flow, the simulation realism needs to be improved, and it lacks the ability to output energy-saving curves.

[0006] Because train operation and passenger flow evolution are mutually influential, excessive passenger waiting during the morning rush hour, uncivilized behavior on trains, and emergencies can affect normal train operation and platform overcrowding. Conversely, adjustments to train operation plans made in response to large passenger flows can, in turn, affect the number of passengers waiting at various stations. Therefore, how to study and explore the relationship between train operation scheduling and passenger flow, and how to address the impact of different train operation adjustment strategies on line passenger flow, is a challenge we face. Summary of the Invention

[0007] To address the shortcomings of the aforementioned technologies, this invention provides a dynamic modeling and simulation system for the coupling of train operation and passenger flow. Based on real data from rail transit lines, it effectively designs and simulates train dispatching adjustment schemes to address passenger flow issues during morning peak hours. This approach not only effectively expands the optimization space for dispatching schemes under congested platform scenarios during morning peak hours, but also evaluates the rationality and effectiveness of dispatching schemes through system simulation analysis, and further verifies the relationship between train operation and dynamic passenger flow.

[0008] To achieve the above objectives, this invention provides a dynamic modeling and simulation system for coupling train operation and passenger flow, which is applied to dealing with peak passenger flow in urban rail transit, including train operation simulation and peak platform passenger flow characteristics;

[0009] The train operation simulation includes interconnected driving simulation module, monitoring simulation module, protection simulation module, and simulation clock engine. The monitoring simulation module sends command information to the driving simulation module, which then adjusts the train's operation accordingly. The protection simulation module monitors the speed of adjacent trains to prevent rear trains from colliding with the train in front due to excessive speed. The simulation clock engine simulates real time to ensure timely execution, guaranteeing that each system can receive command information from the monitoring simulation module and that the transmitted signals are executed within a given time.

[0010] The peak station passenger flow characteristics include crowding degree, inbound passenger flow and average service efficiency of the train, the train passenger flow coupling model is built by monitoring and analyzing the passenger flow and combining the train operation simulation according to the change of the passenger flow.

[0011] As preferred, the train operation simulation further includes a dynamic simulation model, the train dynamic simulation model is modeled by the traction, braking and acceleration motion parameters and the physical principles behind them in the train operation process, including the traction force, the braking force and the running resistance, the traction force is the same force as the train operation direction generated by the traction electromechanical device, the train traction characteristic curve is obtained by quantitative mechanical test data analysis fitting, there are three key speed control points in the train traction characteristic curve, which are the turning speed v a of the constant torque phase and the constant power phase, the turning speed v b of the constant power phase and the natural characteristic phase and the maximum limit speed v c of the natural characteristic phase.

[0012] As preferred, in the constant torque traction control phase of the train, the motor output power is always increased, so that the train steel wheel motion can maintain the maximum rotation torque, therefore the motor device maintains the maximum traction force F t , and their relationship is:

[0013]

[0014] As preferred, the train braking force is determined by the maximum braking force and the traction coefficient μ ∈ [0, 1] corresponding to the train traction watch level, the actual braking force B of the train is B = μ · B max .

[0015] As preferred, the running resistance includes basic running resistance and additional resistance, the basic running resistance is the force generated by air friction and mechanical friction when the train moves horizontally and linearly, and its calculation formula is w0 = a + bv + cv 2 , wherein w0 is the basic resistance of the train; a is the basic resistance term constant; b is the rolling resistance term constant; c is the air resistance term constant; v is the train speed.

[0016] As preferred, the additional resistance is the force increased when the train runs in the tunnel, slope and curve compared with the flat and straight line, when calculating the additional resistance, only the slope resistance, curve resistance and tunnel air resistance are considered, and the calculation formula is w1 = w i +w r +w s ; the slope resistance is the component force parallel to the track generated by the train weight when the train runs on the slope line, and its size is mainly related to the line slope value, and the calculation formula is w i =i, wherein wi Here, is the unit gradient resistance coefficient, and 'i' is the gradient. Curve resistance is the force generated by the lateral and longitudinal friction between the train's wheels and the track when the train is running on a curved track, acting in the opposite direction to the train's movement. Its magnitude is mainly related to the radius of the curve, and the calculation formula is: Among them W r R is the unit curve drag coefficient, and R is the curve radius. Tunnel resistance is the force generated when a train runs in a tunnel. Due to the high speed of the train, friction occurs between the train and the air inside the tunnel, which in turn causes friction between the air and the tunnel walls, resulting in a force opposite to the direction of the train's movement. The formula is: w s =0.00013·L s , where w s L is the unit tunnel resistance coefficient; s This represents the tunnel length.

[0017] As a preferred option, in the peak platform passenger flow characteristics, the inbound passenger flow is λ = Q. max / t, where λ is the number of customers arriving during peak hours, Q max Let t represent the total number of passengers entering the station, and t represent the time duration; the average service efficiency of the train is μ = (Q / T). 单 (×M×n×T) / t, where μ is the average number of customers served, and Q is the number of customers served. 单 M represents the number of passengers that can board each train at a single door; n represents the number of carriages on a single train; n represents the number of doors for boarding and alighting on one side of a single carriage; and T represents the time unit.

[0018] As a preferred option, platform congestion is one of the basic indicators used to measure the operational status of subway stations. The calculation method is k=(M×l×d×n) / (I×t), where I=λ-μ, k is the platform congestion, I is the net passenger flow during the morning peak hour, l is the platform waiting length, d is the platform waiting width, and t is the time length.

[0019] As a preferred approach, the train passenger flow coupling model construction process includes adjustments to train stop plans, train route plans, and train intervals. Before adjusting the train stop plans, it is assumed that during peak hours, there are Q passengers waiting at upstream skip-stop platforms. 跳停 = (Q1-Q2)×p, where Q 跳停 Q1 represents the number of passengers boarding trains at upstream skip-stop platforms during the morning rush hour; Q2 represents the total number of passengers at the platform before the skip-stop for the entire day; p represents the percentage of passenger flow during the morning rush hour to the total daily passenger flow. The number of passengers that can board each train at a single door of a high-traffic platform after the train stopping plan adjustment is... Q 单2 Q represents the number of passengers that can board each train at a single door after the plan is adjusted. 单The number of boarding passengers per train for a single door is c, the number of service windows is c, the train interval is t, the early morning peak time span is T, and the train skip-stop frequency is p. Then, the average service customer efficiency after the adjustment of the scheme is calculated according to the formula, and then substituted into the formula The queue length and waiting time parameters of the large passenger flow platform after the adjustment of the train scheme are calculated.

[0020] Preferably, in the adjustment of the train route scheme and the adjustment of the train running interval, t in mu=(Q 单 ×T) / t is changed, and then substituted into the corresponding formula to calculate the relevant time parameters.

[0021] The application has the advantages that, by analyzing the passenger flow and combining the train running state, the long waiting time of passengers during the peak period can be effectively solved, and the problem of congestion caused by too many people can be avoided. The model constructed can be targeted at the influence of the train operation and scheduling scheme on the subway platform passenger flow, the efficiency of the train operation and scheduling scheme can improve the operation speed of the train, reduce the stopping time of the train, and thus improve the congestion of the platform, reduce the waiting time of the passengers, and improve the travel efficiency of the passengers, thereby effectively relieving the passenger flow pressure of the platform. During many peak periods, efficient passenger flow transportation can reduce the passenger flow management pressure of the platform, and can also ensure the safe waiting environment of the passengers. The construction of a scientific and effective operation and scheduling scheme can better cooperate with the line operation planning, speed up the empty car time between lines, reduce the congestion of the subway, and improve the overall efficiency of the subway operation. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The train traction characteristic curve is shown in the figure.

[0023] Figure 2 The train braking characteristic curve under different loads is shown in the figure.

[0024] Figure 3 The relationship table between the congestion degree and the proportion of passengers in the station hall is shown in the figure.

[0025] Figure 4 The single-path queuing multi-channel service is shown in the figure.

[0026] Figure 5 The algorithm flow framework diagram is shown in the figure.

[0027] Figure 6 The train passenger flow coupling flow chart is shown in the figure. DETAILED DESCRIPTION

[0028] In order to make the present application clearer, further description will be made in conjunction with the accompanying drawings. Of course, the present application is not limited to these. Simple substitutions made by those skilled in the art without creative effort are within the scope of the application.

[0029] The application discloses a train operation and passenger flow coupling dynamic modeling and simulation system, which is applied to coping with peak passenger flow of urban rail transit, and is characterized in that the system comprises train operation simulation and peak platform passenger flow characteristics.

[0030] The train operation simulation includes a driving simulation module, a monitoring simulation module, a protection simulation module and a simulation clock engine connected with each other. The monitoring simulation module sends instruction information to the driving simulation module. The driving simulation module adjusts the train operation after receiving the instruction information. The protection simulation module monitors the speed of the adjacent train to prevent the rear train from colliding with the front train due to too high speed. The simulation clock engine simulates the real time to achieve the effect of timing guarantee. The real time guarantees that each system can receive the instruction information sent by the monitoring simulation module. The signals transmitted are executed within the given time. The peak platform passenger flow characteristics include the crowded degree, the inbound passenger flow and the average service efficiency of the train. The train passenger flow coupling model is built by combining the passenger flow variation with the train operation simulation. In the specific embodiment, the driving simulation module has the functions of train operation and parking, automatic train operation adjustment, platform operation, unmanned turnaround and the like. The module can simulate the normal operation of the train and execute the train dispatching adjustment command. The module realizes the traction, cruise and brake control of the train by collecting the information of the block section and the platform. Meanwhile, the module can set a series of dispatching commands such as parking and skipping stop. The module is a very important subsystem of the software. The module mainly completes the intra-station operation and fixed-position parking and can perform the dispatching command to realize the automatic adjustment of the train operation and adapt to the needs of high-speed and high-density train operation. The monitoring simulation module can complete the real-time monitoring and management of the train and the signal equipment, can adjust the signal indicator in each section and is responsible for the control of the train operation adjustment. The protection simulation module prevents the rear train from colliding with the front train due to too high speed and prevents other dangerous situations that may occur during the train operation. The train system protection system transmits the highest safety speed limit signal to the train through the track and continuously compares the actual speed of the train with the highest safety speed. If the actual speed of the train exceeds the highest safety speed, the system instructs the train to make emergency brake to avoid overspeed. The system also ensures that there is enough unoccupied track in front of the train to stop the train without collision when the train makes emergency brake. Since the simulation model is built, the time needs to be effectively simulated in the simulation model. The simulation clock engine simulates the real time in the simulation software to achieve the effect of timing guarantee. The system can execute the information and command received by the train automatic control system within the given time. Meanwhile, the simulation clock engine can realize the functions of acceleration, pause, jump, playback, global clock simulation and distribution of the system simulation.

[0031] In the specific implementation process, the simulation clock engine includes a real-time clock engine and a simulation clock management module. The real-time clock engine can generate a real-time period by an external real-time operating system or generate a simulation real-time period by Simulink Realtime. The period of the real-time clock engine is 5 ms. At the beginning and end of each period, a period start / end message is sent through UDP communication to drive the simulation clock. The simulation clock management module multiplies the corresponding acceleration rate according to the clock period of the real-time clock engine, and triggers the clock period of each device according to the registered clock period of the corresponding simulation real-time device.

[0032] The train operation simulation also includes a dynamic simulation model. The train dynamics simulation model is modeled by modeling the traction, braking and acceleration motion parameters and the physical principles behind them during train operation, including traction, braking and running resistance. The traction is the same force as the train running direction generated by the traction electromechanical device. The train traction characteristic curve is obtained by quantitative mechanical test data analysis fitting. In this embodiment, the train dynamics simulation model refers to a mathematical model for describing the dynamic performance and running characteristics of the train in different running states by modeling the traction, braking, acceleration and other motion parameters and the physical principles behind them during train operation. During the movement of the urban rail transit train on the line, the train is subjected to complex forces due to factors such as line slope, turning radius and tunnel length. Generally, when analyzing the forces acting on the moving train, the train can be regarded as a single mass point and only the forces in its motion direction are considered, and the forces acting on the train mainly include traction, braking and running resistance.

[0033] Traction characteristic analysis

[0034] The train traction force refers to the force generated by the traction electromechanical device of the train running on the line in the same direction as the train running direction. The train traction characteristic curve is generally obtained by quantitative mechanical test data analysis fitting by the locomotive and vehicle manufacturer. The traction characteristic curve reflects the size of the traction force provided by the traction motor of the train at a certain running speed under traction working conditions. The acceleration motion process of the train under the action of the traction force is as shown in Figure 1

[0035] There are three key speed control points in the train traction characteristic curve, which are the turning speed v a of the constant torque phase and the constant power phase, the turning speed v b of the constant power phase and the natural characteristic phase, and the maximum limit speed v c of the natural characteristic phase. In the constant torque traction control phase, the train steel wheel motion can maintain the maximum rotational torque because the motor output power is always increasing, so the motor device maintains the maximum traction force F t :​

[0036] Generally, the train traction characteristic curve refers to the maximum train traction characteristic curve. In the actual operation of the train, the maximum traction force is not used in all traction conditions, and the traction coefficient μ ∈ [0, 1] corresponding to the train traction handle level in the running state should be considered. The actual train traction force F is calculated as F = μ · F max (v).

[0037] Braking characteristic analysis:

[0038] Please refer to Figure 2 , the train braking force refers to the force generated by the train braking device in the opposite direction of the train running direction. At present, the city rail train in China generally adopts the combined braking mode of electric braking and air braking, and the electric braking is divided into regenerative braking and resistance braking. In the train braking operation, the electric braking mode is adopted in the initial stage of the braking condition. The electric braking can return the braking energy generated by the train to the catenary power supply system for other trains or other electromechanical equipment, or consume the braking energy generated by the train through the braking resistor to form heat. When the train is in the final stage of the braking condition, the air braking mode is generally adopted when the train speed is less than 5 km / h to achieve the purpose of precise parking of the train. Like the traction characteristic curve, the braking characteristic curve can represent the braking force generated by the braking device at a certain speed, and the curve is also provided by the locomotive and vehicle manufacturer. In the actual operation of the train, the maximum braking force is not used in all braking conditions, and the traction coefficient μ ∈ [0, 1] corresponding to the train traction handle level in the running state should be considered. The actual train braking force B is calculated as shown in the formula: B = μ · B max .

[0039] Resistance analysis:

[0040] When the train runs on a flat and straight line, the force opposite to the direction of train advancement mainly caused by air friction and mechanical friction is called basic running resistance. The basic running resistance of the train has a direct relationship with the running speed of the train, but its influencing factors not only include the vehicle structure (the total number of axles of the train vehicle formation, the number of trailers and the number of motor cars in the train vehicle formation, the train head area and the total mass of the train, etc.), but also the line conditions and climate conditions. Different train vehicles have different basic resistances when running on the line. The Davis formula is generally used to calculate w0 = a + bv + cv 2 , in the formula, w0 is the basic resistance of the train, the unit is N / kN; a is the basic resistance constant; b is the rolling resistance constant; c is the air resistance constant; v is the train speed, the unit is km / h;

[0041] The additional resistance refers to the force increased when the train runs in the tunnel, slope and curve of the line than in the flat and straight line.

[0042] w1=w i +w r +w s

[0043] The slope resistance is the force parallel to the track generated by the train weight when the train runs in the slope line. Its size is mainly related to the line slope value, and is calculated as w i =i, wherein w i is the unit slope resistance coefficient, with the unit of N / kN; i is the slope (‰); the curve resistance is the force opposite to the train advancing direction generated by the transverse and longitudinal friction between the train steel wheel and the track when the train runs in the curve line; its size is mainly related to the line curve radius value, and the calculation formula is wherein W r is the unit curve resistance coefficient, with the unit of N / kN; R is the curve radius, with the unit of m; the tunnel resistance is the force opposite to the train advancing direction generated by the friction between the train itself and the air inside the tunnel due to the high-speed running of the train, and the friction between the air inside the tunnel and the tunnel inner wall, when the train runs in the tunnel. Its size is mainly related to the tunnel length, and the calculation formula is w s =0.00013·L s , wherein w s is the unit tunnel resistance coefficient, with the unit of N / kN; L s is the tunnel length, with the unit of m.

[0044] The process of passengers after entering the station can be divided into two stages of walking in the station and waiting on the platform, and the two parts are modeled and analyzed respectively, the time consumed by passengers in the two stages is researched, so as to realize the whole process from AFC card swiping to getting on the train; the three types of models of congestion degree, average entering passenger flow and average train service efficiency are used to describe the dynamic passenger flow of the platform in the peak period, so as to study the passenger flow characteristics.

[0045] Taking the early peak of the subway as an example, the average entering passenger flow of the subway in the early peak refers to the average passenger flow entering each subway station during the daily working time, that is, the early peak period (usually 7:00-9:00 in the morning). This index can reflect the passenger flow in the subway operation process, and the early peak period is one of the key periods in the subway operation, because most citizens choose the subway during this period due to work; the average entering passenger flow is λ = Q max / t (wherein λ is the passenger arriving in the peak period, Q maxFor the total number of inbound passengers, t is the length of time, and the average service efficiency of the train μ = (Q 单 × M × n × T) / t (where μ is the average number of customers served, Q 单 is the number of boarding passengers per train, M is the number of carriages per train, n is the number of doors on one side of a single carriage, and T is the unit of time); platform congestion is one of the basic indicators used to measure the operational status of a subway station. High platform congestion can easily lead to accidents such as overcrowding, loss of control, and stampedes, resulting in safety incidents. In addition, high platform congestion can make waiting and boarding passengers feel crowded and uncomfortable, leading to increased passenger waiting time, higher subway train load rates, longer operating times, and increased likelihood of subway line congestion, all of which negatively impact the passenger experience. The model for platform congestion is k = (M × l × d × n) / (I × t), where I = λ - μ (where k is the platform congestion, I is the net passenger flow per hour during the morning rush hour, l is the length of the platform, d is the width of the platform, and t is the length of time). Generally speaking, the passenger service level of urban rail transit corresponds to the following table:

[0046]

[0047]

[0048] According to this table, and in combination with the platform congestion, the service level is classified, and the table of different congestion levels corresponding to the proportion of passengers in the station hall is obtained:

[0049]

[0050]

[0051] The fitting table is obtained by fitting the congestion level and the proportion of passengers in the station hall: Figure 3 The relationship between the two is y = 275.99e -3.641x (where y is the congestion level (m 2 / person) and x is the proportion of passengers in the station hall (%)); after calculating the corresponding platform waiting congestion level using the congestion model, the evaluation can be performed in combination with the evaluation standard for the service level of urban rail transit in the United States. This standard classifies the service of urban rail transit trains from high to low into seven levels, A-F. The closer the peak-hour service level is to level A, the more comfortable the passenger environment in the train system, and the closer the service level is to F, the more crowded the passenger environment in the train system due to excessive passenger flow, resulting in a poor train experience.

[0052] In the actual process of taking the train, when the train is delayed, the passenger flow on the train and in the station will change. First, on the train, due to the inability of people to arrive at the destination on time, it may cause passengers to increase mental stress and affect their mood; at the same time, if the delay time is too long, the passenger flow on the train will gradually decrease, and some passengers may get off and transfer to other travel modes. Today, the passenger flow on urban rail transit is very large, and if these passenger flows enter the urban road traffic, it will easily bring great pressure to road traffic, causing traffic congestion and even traffic accidents. Secondly, in the station, the passenger flow usually presents two situations: one is that the station congestion is intensified due to the train delay, affecting the mood of passengers, and if the delay cannot be completed in time, it will cause the degree of passenger flow congestion in the station to further increase, easily causing safety accidents such as stampede, affecting the safety of passengers; the other is that the passenger flow in the station decreases due to the train delay, at this time the station becomes relatively quiet, but there will be some anxious passengers waiting. In summary, when the urban rail transit system has a train delay, it not only causes inconvenience to passengers, but also brings challenges to the management of station personnel.

[0053] The time consumed by passengers in the station is associated with the large passenger flow, and the process of passengers from entering the station to paying the fare to boarding the train is divided into three parts. The first part is the walking or taking the escalator of passengers after entering the station to enter the waiting floor. The second part is the process of passengers queuing for the train in the waiting floor. The last part combines the two parts to discuss the travel characteristics of passengers under different passenger flow conditions by analyzing the time consumed by passengers in the two parts.

[0054] 1. Walking or taking the escalator after entering the station to enter the waiting floor

[0055] In this part, the walking time of passengers is associated with the congestion degree in the station, i.e. the number of passenger flow in the station hall. The higher the number of passengers in the station hall (interior station hall, escalator / elevator, platform and train), the higher the congestion degree of passengers. Since the passing capacity of elevators and stairs is limited, according to the provisions of the “Metro Design Specification” for the passing capacity of facilities and equipment in urban rail transit system, the following results are obtained:

[0056]

[0057] The formula for the entering station passing capacity at the ticket checking place and the passing capacity of facilities and equipment from the station hall to the waiting hall is C 进 = c 检票 × n; C 上 = c 楼梯 × n + c 扶梯 × n (in the formula, C 进 is the entering station passenger flow capacity, C 上 is the passenger flow capacity from the station hall to the waiting floor, c检票 For the automatic ticket checking passage capacity, c 楼梯 For the stair up passage capacity, c 扶梯 For the escalator passage capacity, n1 is the number of ticket checking gates, n2 is the number of stairs, and n3 is the number of escalators, the formula can be embodied in the case of the maximum passage capacity in the peak period, that is, the in-station passengers can quickly enter the waiting floor, and whether the passage capacity of the station hall to the waiting floor can meet the passage capacity of the automatic ticket checking gate.

[0058] And once the automatic ticket checking gate is always in full load during the morning peak period, there will be a certain passenger flow congestion in the station hall, which will further cause the passenger route to be blocked and the time to rise. Under different congestion degrees in the station, the walking time of passengers from the gate to the waiting floor conforms to the exponential function, that is, before reaching a certain congestion degree, the walking time of passengers in the station is less affected by the congestion degree, but once the threshold is reached, the walking time begins to rise rapidly until the complete congestion in the station hall. The model is as follows: y = ae bx (where y is the walking time in the station (s), and x is the passenger proportion in the station hall (percent)).

[0059] 2. Waiting for trains in the waiting floor

[0060] The passenger flow characteristics under the delay condition are analyzed by using the theory of queuing theory. Please refer to Figure 4 In this process, the passengers from the station hall to the waiting floor are regarded as a single-channel queuing model, each door of each train is regarded as a separate service window, and since passengers will choose the least window to queue, the passenger boarding can be regarded as a single-path queuing multi-channel service model. The average waiting time, average stay time, average queue length, and average queue length of passenger flow in the morning peak period are calculated and analyzed by using the M / M / c / ∞ / ∞ model, and the calculation results show the characteristics of passenger flow congestion under the delay condition. The specific calculation process can be divided into the following steps:

[0061] 2.1 Average number of arriving customers λ = Q 总 / t (where λ is the average number of arriving customers, Q 总 is the total number of in-station passengers, and t is the time length (here, the value is taken as 7:00-9:00 in the morning peak period);

[0062] 2.2 Average service customer efficiency μ = (Q 单 × T) / t (where μ is the average service customer efficiency, Q 单 is the number of passengers who can board each train at a single door, T is the time unit, and t is the train interval)

[0063] 2.3 Average waiting queue length and average waiting time

[0064]

[0065] where P0 is the probability of no passenger in the waiting area, c is the number of service windows, L q is the average waiting queue length (the number of customers waiting in line), L s is the average number of customers in the system (i.e., the number of customers being served + the number of customers waiting), W q is the average waiting time per customer, W s is the average time spent.

[0066] In summary, please refer to Figure 5 When the process of walking or taking the escalator into the waiting area after swiping the card to enter the station is combined with the process of queuing in the waiting area to wait for the train, we can get the relationship between the time from swiping the card to enter the station to taking the train to leave the platform and the actual passenger flow: T = W s + ae bx (where T is the time spent in the waiting area after swiping the card to enter the station), therefore, the relationship between the time spent walking in the station after swiping the card to enter the station and the actual passenger flow is combined with the relationship between the waiting time in the waiting area and the actual passenger flow, and the time spent by passengers in this process and the passenger flow in the station are studied using queuing theory and other models. Such analysis helps to optimize passenger flow management and passenger travel experience in the subway system. Through monitoring and analysis of passenger flow, the train departure interval can be adjusted and the number of platform service personnel can be increased according to the changes in passenger flow, thereby shortening the waiting time and walking time of passengers, effectively alleviating the impact of large passenger flow on rail transit operation and train operation.

[0067] Please refer to Figure 6 For the coupling process of train passenger flow, as shown in the figure, the train operation scheduling scheme has two different effects on the subway platform passenger flow. On the one hand, the efficiency of the train operation scheduling scheme can improve the operation speed of the train, reduce the stopping time of the train, and thus improve the congestion of the platform, reduce the waiting time of the passengers, and improve the travel efficiency of the passengers, thereby effectively alleviating the passenger flow pressure of the platform. In many peak periods, efficient passenger flow transportation can reduce the passenger flow management pressure of the platform, and also can ensure the safe waiting environment of passengers; on the other hand, unreasonable scheduling scheme can also bring a series of negative effects, such as increasing the waiting time, increasing the passenger congestion, and reducing the passenger experience. Therefore, a scientific and effective operation scheduling scheme can better coordinate the line operation planning, speed up the empty car time between lines, reduce the congestion of the subway, and improve the overall efficiency of the subway operation.

[0068] (1) Adjustment of train stopping scheme

[0069] In the scheme, the train is stopped at the upstream platform to allow more passengers to get on the subway at the subsequent platform. In the case calculation, it is assumed that all passengers at the upstream stop platform are complementary to the passengers at the large passenger flow platform. According to the formula, the number of passengers waiting at the upstream stop platform during the morning peak period is Q 跳停 =(Q1-Q2)×p (in which Q 跳停 is the number of passengers getting on the train at the upstream stop platform during the morning peak period, Q1 is the total number of passengers at the section before the stop platform during the day, Q2 is the total number of passengers at the section after the stop platform during the day, and p is the proportion of passenger flow during the day during the morning peak period from 7:00 to 9:00); then the number of passengers that can get on the train at each door of the large passenger flow platform after adjustment of the train stop scheme is calculated according to the formula (in which Q 单2 is the number of passengers that can get on the train at each door of the large passenger flow platform after adjustment of the train stop scheme, Q 单 is the number of passengers that can get on the train at each door of the large passenger flow platform, c is the number of service windows, t is the interval between trains, T is the time span of the morning peak period, and p is the train stop frequency); after obtaining the number of passengers that can get on the train at each door of the large passenger flow platform after adjustment of the scheme, the efficiency of the average service customer is calculated according to the formula given above, and finally the parameters of the queue length and waiting time of the large passenger flow platform after adjustment of the train stop scheme are calculated by bringing them into the M / M / c / ∞ / ∞ model recorded above. The change of the passenger flow at the platform after adjustment of the train operation scheme can be obtained by comparing the data before the scheme adjustment, and the relationship between the passenger flow and the train is verified.

[0070] As for the adjustment of the dispatching time, the essence is to reduce the time interval of the train to the bottom, so only the t in the formula μ=(Q 单 ×T) / t needs to be adjusted and brought into the M / M / c / ∞ / ∞ model to calculate the parameters of the queue length and waiting time of the large passenger flow platform after adjustment of the train stop scheme.

[0071] The above disclosure is only a few specific embodiments of the present application, but the present application is not limited thereto, and any changes that can be thought of by those skilled in the art should fall within the scope of the present application.

Claims

1. A train operation and passenger flow coupling dynamic modeling and simulation system applied to the response of urban rail transit peak passenger flow, characterized in that, The train operation simulation includes driving simulation module, monitoring simulation module, protection simulation module and simulation clock engine connected with each other, the monitoring simulation module sends instruction information to the driving simulation module, the driving simulation module adjusts the train operation after receiving the instruction information, the protection simulation module monitors the speed of the adjacent train to prevent the rear train from colliding with the front train due to too high speed, and the simulation clock engine simulates the real time to achieve the effect of timing guarantee, so that each system can receive the instruction information sent by the monitoring simulation module, and the transmitted signal is executed within the given time; The peak platform passenger flow characteristics include crowding degree, inbound passenger flow and average train service efficiency, the train passenger flow coupling model is constructed by combining the change of passenger flow with the train operation simulation through monitoring and analyzing the passenger flow; The train passenger flow coupling model construction process includes train stopping scheme adjustment and train route scheme adjustment and train operation interval adjustment; The platform crowding degree is one of the basic indexes used to measure the operation state of the subway station, and the calculation method is , wherein , in the formula , the platform crowding degree is , the number of net passenger flow in the morning peak hour, , the length of the platform waiting, , the width of the platform waiting, , the time length, , the number of carriages of a single train; , the number of doors on one side of a single train car for passengers to get on and off; , the average service customer efficiency, , the average number of arriving customers; ​ Before the adjustment of train stop scheme, it is assumed that there are wherein is the number of passengers who take the train at the upstream skip-stop platform during the morning peak period, is the total number of passengers at the section of the platform before the skip-stop, is the total number of passengers at the section of the platform after the skip-stop, is the proportion of passenger flow during the morning peak period to the whole day; and the number of passengers who can board the train at each train door of the large passenger flow platform after the adjustment of train stop scheme is wherein is the number of passengers who can board the train at each train door of the large passenger flow platform after the adjustment of train stop scheme; is the number of passengers who can board the train at each train door of the large passenger flow platform after the adjustment of train stop scheme, is the number of service windows; is the train interval; is the time span of the morning peak period, is the train skip-stop frequency, and then the average service efficiency of customers after the adjustment of scheme is calculated according to the formula, and then substituted into the formula to calculate the parameters of the queue length and waiting time of passenger flow at the large passenger flow platform after the adjustment of train scheme, wherein P0 is the probability that there is no passenger in the waiting area. In the train route scheme adjustment and the train operation interval adjustment, t1 in the following formula is changed, and then is substituted into the corresponding formula to calculate the related time parameters, wherein T2 is a time unit. ​ In the characteristics of peak platform passenger flow, the inbound passenger flow is , is the total number of inbound passengers, and the average service efficiency of the train is .

2. The train operation and passenger flow coupled dynamic modeling and simulation system according to claim 1, wherein, The train operation simulation further comprises a dynamic simulation model. The train dynamic simulation model is modeled by the parameters of traction, braking and acceleration motion and the physical principles behind them in the process of train operation, including traction force, braking force and running resistance. The traction force is the same force as the train operation direction generated by the traction electromechanical equipment. The train traction characteristic curve is obtained by quantitative mechanical test data analysis fitting. There are three key speed control points in the train traction characteristic curve, which are the turning speed of constant torque stage and constant power stage , the turning speed of constant power stage and natural characteristic stage , and the maximum limit speed of natural characteristic stage .

3. The train operation and passenger flow coupled dynamic modeling and simulation system of claim 2, wherein, In the constant torque traction control phase, the motor device keeps outputting the maximum traction force because the motor output power is always increasing, so that the train steel wheel movement can maintain the maximum rotational torque , and the relationship is: .

4. The train operation and passenger flow coupled dynamic modeling and simulation system of claim 2, wherein, The train braking force is determined by the maximum braking force and the traction coefficient corresponding to the train traction watch level The actual braking force B of the train is determined as .

5. The train operation and passenger flow coupled dynamic modeling and simulation system of claim 2, wherein, The running resistance includes a basic running resistance and an additional resistance, the basic running resistance being a force generated by air friction and mechanical friction when the train is in horizontal straight motion, and a calculation formula thereof is wherein is a basic resistance of the train; is a constant of a basic resistance term; is a constant of a rolling resistance term; is a constant of an air resistance term; is a train speed.

6. The train operation and passenger flow coupled dynamic modeling and simulation system of claim 5, wherein, The additional resistance is the force increased when the train runs in the tunnel, slope and curve, compared with the force when the train runs in the flat and straight line. When calculating the additional resistance, only the slope resistance, curve resistance and tunnel air resistance are considered, and the calculation formula is The slope resistance is the force parallel to the track generated by the train weight when the train runs in the slope line, and the size is mainly related to the line slope value, and the calculation formula is , wherein is the unit slope resistance coefficient, is the slope gradient; the curve resistance is the force opposite to the train advancing direction generated by the transverse and longitudinal friction between the train steel wheel and the track when the train runs in the curve line, and the size is mainly related to the line curve radius value, and the calculation formula is , wherein W r is the unit curve resistance coefficient, is the curve radius; the tunnel resistance is the force opposite to the train advancing direction generated by the friction between the train itself and the air inside the tunnel, and the friction between the air inside the tunnel and the tunnel wall when the train runs in the tunnel, and the calculation formula is: , wherein is the unit tunnel resistance coefficient; is the tunnel length.

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