Train safety following driving method suitable for train-train communication train control system

Abstract

The invention discloses a safe train following driving method suitable for a train-train communication train control system, which fully considers the running characteristics of train following driving in the train-train communication train control system and can realize safe tracking between trains at shorter intervals. In addition, it can be guaranteed that the rear train can still keep a safe interval with the front train within a larger train initial state range and run at a smaller interval, and the requirements for safety and small-interval running capacity guarantee of a high-speed railway transportation road network can be met.

Description

Technical Field

[0001] The present invention relates to the technical field of train operation control, and in particular to a safe train following driving method suitable for a train-to-train communication train control system. Background Art

[0002] The train operation control system is a control system composed of ground equipment and onboard equipment, which is used to control the train speed, ensure the safety and efficient operation of the train. It is one of the important components of the railway signal control system. The train operation control system is a rail transit signal system that has developed with the development of train technology and the development of train and ground information transmission systems. It integrates advanced control technology, communication technology, computer technology and railway signal technology to control the train direction, running interval and running speed. It is the core of ensuring driving safety and improving transportation efficiency.

[0003] The train control system based on vehicle-to-vehicle communication takes the vehicle-mounted mobile body as the core to realize train operation control, breaking through the traditional train control mode based on route control. Through two-way, large-capacity, high-speed vehicle-ground wireless communication, multi-sensor fusion train speed measurement and positioning, and train autonomous collaborative mobile block control technology, it relies on self-perception and autonomous decision-making to realize intelligent operation control. Compared with the wireless communication-based train control system (Communication-based Train Control, CBTC) and fully automatic operation system (Fully Automatic Operation, FAO) with many trackside equipment and complex interfaces, the train control system based on vehicle-to-vehicle communication transforms from "vehicle-ground-vehicle" communication to "vehicle-to-vehicle" communication data flow, streamlines system equipment, and has richer information interaction, including position, speed, mobile authorization, etc. Considering the movement trend of the train, it adopts the "soft wall collision" method for safety protection and shortens the tracking interval.

[0004] The onboard equipment of the train control system based on vehicle-to-vehicle communication assumes the functions of mobile authorization calculation and information interaction of traditional RBC, and has functions such as interlocking, target-distance mode curve calculation, automatic driving and train integrity check. Compared with the traditional Radio Block Center (RBC), the onboard equipment of the train control system based on vehicle-to-vehicle communication has obvious similarities and differences. Both of them mainly complete the functions of two-way communication and driving permission calculation, but from the design concept of the whole system, the specific differences are reflected in:

[0005] Structural differences: RBC is arranged at a fixed physical location, and the train needs to switch when passing through two RBC ranges; RBC generates control commands sent to the train from external ground equipment and information exchanged with on-board equipment through two-way vehicle-ground communication, mainly to provide driving permits, so that the train can run safely on the line within the jurisdiction of the RBC, and complete train interval control and train protection. The train control system based on vehicle-to-vehicle communication realizes two-way wireless communication functions with the on-board equipment of the preceding / following trains, the ground system data server, the trackside controller, and the tail equipment through wireless communication units and GPRS radio stations, and the on-board main control unit has the function of calculating driving permits based on information such as station routes and section directions, electronic maps, the position and speed of the vehicle, and the position and speed of the preceding train.

[0006] Safety protection differences: Traditional train control systems are generally designed based on the "hitting a hard wall" tracking mode. Considering that the front train may stop immediately (such as derailment, collision, etc.), the tracking end point of the rear train is the entrance of the block section where the front train is located, and a certain safety protection distance is added. A vehicle-mounted monitoring braking distance is maintained between the front and rear trains to ensure that the rear train can stop at the entrance of the block section where the front train is located at any time to ensure safety. The train control system based on vehicle-to-vehicle communication adopts the "hitting a soft wall" train tracking mode, that is, assuming that the front train will not derail or collide and stop within a very short distance, after the front train uses emergency braking to stop, the rear train can use normal braking to stop at the tail of the front train. Compared with the "hitting a hard wall" mode, the tracking interval between the two trains will compress the emergency braking distance of the front train, thereby greatly improving the traffic density.

[0007] Therefore, for the onboard equipment of the communication-based train control system, considering the above differences, it is an urgent problem to design a set of train operation control systems based on vehicle-to-vehicle communication to meet the train following safety protection method. At present, there are mainly three types of related solutions.

[0008] Solution 1: CTCS-2 / CTCS-3+ATO train control system is an important technical solution in China's train control system. Based on the traditional ATP system, it receives the operation plan, station-to-station data and line basic information (such as permanent speed limit and temporary speed limit) of the dispatching center through wireless communication technology. The system is mainly used in China's high-speed railway and intercity railway networks. In the CTCS-2 / CTCS-3 level train control system, ATO (automatic train operation system) integrates various sensors and train control equipment to realize the automatic departure, interval operation, precise parking, and automatic linkage control of stations and platform doors of trains. In addition, the CTCS-2 / CTCS-3+ATO train control system has high security and stability. Through two-way communication between ground equipment and on-board equipment, it ensures that the train can run at a safe distance and speed. The system is widely used in my country's high-speed railway network, greatly improving the automation and efficiency of train operation.

[0009] Although the CTCS-2 / CTCS-3+ATO system has advanced technical systems, it has some limitations. First, the system's decision-making relies on the driving permission information provided by ground equipment and lacks active perception capabilities. This means that the train cannot autonomously perceive changes in the surrounding environment, such as weather changes, obstacle intrusions, etc., and must rely on external equipment to provide information. In addition, the system still requires human intervention when dealing with complex emergencies and lacks the ability to make autonomous decisions. In extreme weather conditions, emergencies or other unconventional conditions, the need for human intervention increases, which limits the system's level of autonomous operation and cannot fully meet the needs of future intelligent train operation control.

[0010] Solution 2: The Next Generation of Train Control System (NGTC) of the European Railway Industry Association (UNIFE) is an advanced train automatic operation system based on satellite navigation and wireless communication technology, designed to improve the efficiency and flexibility of railway transportation. The system uses advanced satellite navigation and positioning technology, allowing trains to obtain accurate location information through the Global Satellite Positioning System (GNSS), and combines IP-based vehicle-to-ground wireless communication technology to achieve efficient communication between trains and the control center. Another highlight of NGTC is the introduction of mobile blocking technology, which can greatly shorten the running interval between trains compared to traditional fixed blocking, and improve the capacity and efficiency of railway transportation. In addition, the NGTC system also focuses on the development of automatic driving (ATO) technology, which can realize fully automatic operation of trains without human intervention, and supports operation in railway networks of different levels, including intercity railways and high-speed railways.

[0011] Although the NGTC system is relatively advanced in design concept, its technical solution has some shortcomings. First, the positioning of the train is completely dependent on the satellite navigation system, which will cause signal loss or reduced accuracy in certain scenarios (such as tunnels, mountainous areas or extreme weather), affecting the safe operation of the train. In addition, the NGTC system lacks other auxiliary positioning technologies such as inertial navigation and speedometers, and cannot provide stable position information when the satellite signal is interrupted. Secondly, although the NGTC system reduces the use of trackside equipment, its design concept and technical framework are quite different from China's CTCS system, and it cannot be seamlessly connected with the CTCS system. This leads to technical barriers in cross-border railway operations or international train operations, and it is impossible to achieve interconnection between systems, which limits its popularization and application in the global railway network.

[0012] Solution 3: Some urban rail transit systems in China have successfully applied GoA4-level fully automatic driving technology, which is a high-level train automatic operation system that can realize autonomous operation of trains without human supervision. Based on this technology, domestic urban rail transit has gradually developed towards autonomous train operation control, especially in vehicle-ground collaborative perception, vehicle-vehicle reliable communication, virtual formation and other aspects. Through these advanced technologies, the automation and intelligence level of the system has been greatly improved, greatly improving the operation efficiency and safety of the train. In addition, some urban rail transit systems in China have also further reduced the running interval of trains and significantly improved the scheduling flexibility of trains by optimizing the dispatching and control strategies of trains in terms of automatic driving technology. These technologies have greatly reduced the need for manual intervention, enabling trains to adapt to different operating environments more intelligently, and realizing the full automation and intelligence of train operation.

[0013] Although the GoA4 level autonomous driving technology in urban rail transit performs well in urban environments, its technical solutions do not fully consider the complexity of high-speed rail and intercity rail in terms of operating scenarios and environments. For example, urban rail transit systems usually operate at lower speeds, with smaller running intervals between trains and relatively simple line structures, while high-speed railways need to cope with complex operating environments with speeds exceeding 300 kilometers per hour, requiring higher safety redundancy and system response speed. In addition, the operating scenarios of the national railway system are more complex, and factors such as station interlocking, line conditions, and cross-regional operations have put forward higher requirements for the train control system. The autonomous driving technology of urban rail transit has not yet been fully adapted in these aspects, and the existing technical solutions cannot be directly transplanted to the high-speed railway system, and cannot meet the high-speed railway's requirements for safety, reliability, and complex operating environments. Therefore, although urban rail transit has made great progress in autonomous driving, the application of its technology in high-speed railways still needs to be further improved and enhanced. Summary of the invention

[0014] The purpose of the present invention is to solve the problem of unknown interference from the uncertain dynamics of the leading vehicle in the automatic driving of high-speed railway trains based on vehicle-to-vehicle communication, which affects the train following performance, and to provide a train safety following driving method suitable for a vehicle-to-vehicle communication train control system.

[0015] The objective of the present invention is achieved through the following technical solutions:

[0016] A train safety following driving method suitable for a train-to-train communication train control system, wherein a device in a following train performs the following steps:

[0017] Periodically receive train operation data sent by the preceding train;

[0018] According to the train operation data received from the preceding train, combined with the predetermined safety margin and time headway requirement, the following error between the preceding train and the preceding train is calculated;

[0019] Based on the following error, a train relative dynamic model is constructed to describe the relative motion relationship between trains.

[0020] Calculate the minimum safety margin and set the safety interval based on the minimum safety margin;

[0021] Designing a decision process of a controller based on the relative dynamic model of the train, the following error and the set safety interval;

[0022] By combining the set constraints, the train operation data of the preceding vehicle, its own operation data and the decision-making process of the controller, the corresponding decision information is obtained and used to control the train operation.

[0023] It can be seen from the technical solution provided by the present invention that the operating characteristics of train following driving in the vehicle-to-vehicle communication train control system are fully taken into consideration, and safe tracking of trains at shorter intervals can be achieved. It can also ensure that within a larger range of the train's initial state, the rear vehicle can still maintain a safe interval with the front vehicle and run at a smaller interval, which can meet the needs of ensuring the safety and small-interval operation capacity of the high-speed railway transportation network. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0025] Figure 1 A flow chart of a safe train following driving method suitable for a train-to-train communication train control system provided by an embodiment of the present invention;

[0026] Figure 2 A schematic diagram of the structure of a train operation control system provided by an embodiment of the present invention;

[0027] Figure 3 A schematic diagram of the train following error identification principle provided by an embodiment of the present invention;

[0028] Figure 4 Schematic diagram of train safety interval design provided by an embodiment of the present invention

[0029] Figure 5 Schematic diagram of the maximum initial state set calculation for real-time decision making of trains provided by an embodiment of the present invention

[0030] Figure 6 A schematic diagram of the overall process of a safe train following driving method suitable for a train-to-train communication train control system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the 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 protection scope of the present invention.

[0032] First, the terms that may be used in this article are explained as follows:

[0033] The terms "include", "comprises", "contains", "has" or other descriptions with similar semantics should be interpreted as non-exclusive inclusion. For example, including certain technical feature elements (such as raw materials, components, ingredients, carriers, dosage forms, materials, dimensions, parts, components, mechanisms, devices, steps, procedures, methods, reaction conditions, processing conditions, parameters, algorithms, signals, data, products or products, etc.) should be interpreted as including not only certain technical feature elements explicitly listed, but also other technical feature elements known in the art that are not explicitly listed.

[0034] The term "consisting of..." means excluding any technical feature elements not explicitly listed. If this term is used in a claim, it will make the claim closed, so that it does not contain technical feature elements other than the technical feature elements explicitly listed, except for the conventional impurities related to them. If this term only appears in a clause of a claim, it only limits the elements explicitly listed in the clause, and the elements recorded in other clauses are not excluded from the overall claim.

[0035] The following is a detailed description of a train safety following driving method suitable for a train-to-train communication train control system provided by the present invention. The contents not described in detail in the embodiments of the present invention belong to the prior art known to professional and technical personnel in this field. If no specific conditions are specified in the embodiments of the present invention, the conventional conditions in the field or the conditions recommended by the manufacturer shall be followed. The instruments used in the embodiments of the present invention, if the manufacturer is not specified, are all conventional products that can be purchased commercially.

[0036] like Figure 1 As shown, it is a flow chart of a train safety following driving method suitable for a train-to-train communication train control system provided by an embodiment of the present invention. The method is executed by a device in a following train and mainly includes the following steps:

[0037] Step 1: Periodically receive the train operation data sent by the preceding train.

[0038] Preferably, the on-board equipment of the rear vehicle periodically receives the train operation data sent by the front vehicle, including: the position, speed and acceleration of the front vehicle.

[0039] Step 2: Calculate the following error between the train and the preceding train based on the train operation data received from the preceding train and in combination with the predetermined safety margin and time headway requirement.

[0040] Preferably, the following vehicle obtains its own position and speed, and calculates the following error between the following vehicle and the preceding vehicle in combination with the train operation data of the preceding vehicle and the predetermined safety margin and time interval requirement, wherein the following error includes: position error and speed error; wherein: the position error is calculated as follows:

[0041] e p =p l -p f -d min -v f h f

[0042] Among them, p l is the position of the preceding vehicle, which belongs to the train operation data of the preceding vehicle; f 、v f are the position and speed of the following vehicle, d min is the predetermined safety margin, h f For time interval requirements.

[0043] Step 3: Based on the following error, a train relative dynamic model is constructed to describe the relative motion relationship between trains.

[0044] Preferably, the transfer function between the train acceleration and the expected acceleration is obtained using actual line operation data, and then combined with the following error to construct a train relative dynamic model for describing the relative motion relationship between trains.

[0045] Step 4: Calculate the minimum safety margin and set the safety interval based on the minimum safety margin.

[0046] Preferably, the acceleration of the leading vehicle is set as the disturbance vector, and the N-step forward reachable set is calculated from the time when the leading vehicle starts to implement emergency braking to the time when it stops completely. The absolute value of the maximum following error obtained is the minimum safety margin, and the safety interval is set accordingly.

[0047] Step 5: Design a decision process of the controller in combination with the relative dynamic model of the train, the following error and the set safety interval.

[0048] Preferably, the controller decision process of the following vehicle is to apply a mixed H2 / H ∞ Control theory, two robust controllers are designed to achieve the same control objective, which combines the above steps to obtain the relative dynamic model of the train, the following error and the safety interval.

[0049] Step 6: Combine the set constraints, the train operation data of the preceding train, its own operation data and the decision-making process of the controller to obtain the corresponding decision information, and use it to control the train operation.

[0050] Preferably, the set constraints are the following error, the acceleration difference and the constraints that the control input must satisfy, and the set constraints form a system allowable set; the train operation data of the leading vehicle and its own operation data include: the position, speed and acceleration of the leading vehicle, and the position, speed and acceleration of the rear vehicle; the system allowable set, the train operation data of the leading vehicle and its own operation data are input into the controller, and the corresponding decision information is obtained through the decision-making process of the controller.

[0051] In the embodiment of the present invention, the sequence numbers of the above steps are mainly used to identify different steps, and do not refer to the execution order of the steps. The specific execution order of each step can be determined based on the content of the step.

[0052] The above method provided by the embodiment of the present invention fully considers the operating characteristics of train following driving in the vehicle-to-vehicle communication train control system, can realize safe tracking between trains at shorter intervals, and can ensure that the rear vehicle can still maintain a safe interval with the front vehicle and run at a smaller interval within a larger range of the train initial state, which can meet the needs of ensuring the safety and small interval operation capacity of the high-speed railway transportation network.

[0053] In order to more clearly demonstrate the technical solution and technical effects provided by the present invention, the method provided by the embodiment of the present invention is described in detail with reference to specific embodiments below.

[0054] 1. Information reception.

[0055] In the embodiment of the present invention, the train is provided with information collection devices and communication equipment. The information collection device includes: a hybrid speed measuring device based on axle speed measuring sensor and transponder, an acceleration measuring device based on inertial positioning, and a train positioning system based on the Global Navigation Satellite System (GNSS); the communication equipment is a new generation of railway broadband mobile communication system (Long Term Evolution-Railway, LTE-R) information transmission platform, with the on-board control platform as the core, deeply integrating train control with on-board network, traction, braking and other systems.

[0056] The steps of periodically receiving the position, speed and acceleration information sent by the front vehicle by the on-board communication device of the rear vehicle include:

[0057] 1) After receiving the signal from the vehicle in front, the on-board communication equipment of the vehicle behind needs to open the receiving channel so that it can correctly receive and analyze the signal;

[0058] 2) Once the position, speed and acceleration information of the leading vehicle is received, the onboard communication equipment of the following vehicle needs to use it to update the status of the leading vehicle;

[0059] 3) The on-board communication equipment of the rear vehicle can send a confirmation message to the front vehicle to inform the front vehicle that the information received is correct.

[0060] 2. Calculation method of following error between front and rear vehicles.

[0061] In the embodiment of the present invention, the following error between two adjacent trains, including position error and speed error, is calculated based on the operation data of the front and rear trains in combination with the set safety margin and time interval requirement.

[0062] The rear vehicle obtains its own position and speed from satellite communications and on-board speed sensors and calculates its acceleration. The running speeds of the two vehicles affect the relative braking distance between the two vehicles, and the maximum braking acceleration of the two vehicles is also a decisive factor in the relative braking distance. Let p j ,v j and a j Respectively represent the train position, speed and acceleration, j = l, f, l refers to the front car, f refers to the rear car, such as Figure 2 As shown, the position error between the two vehicles is obtained by deducting the predetermined safety margin of the two vehicles and the braking reaction of the rear vehicle according to the distance between the two vehicles:

[0063] e p =p l -p f -d min -v f h f

[0064] Among them, d min and h f They are the predetermined safety margin and time distance requirement (headway).

[0065] The predetermined safety margin is an additional value based on the safety interval that should be maintained between two adjacent trains, taking into account train communication delays, sensor measurement errors, interference caused by acceleration fluctuations of the leading train, etc.; the time requirement is an additional value based on the safety interval that should be maintained between two adjacent trains, taking into account the reaction time of the following train.

[0066] 3. Construct a relative dynamic model of the train.

[0067] The construction method is as follows:

[0068] 1. Identify the quantitative relationship between the following error of the front and rear trains and the positions of the front and rear trains, the predetermined safety margin and the headway time.

[0069] This step can be found in the introduction of the second part above.

[0070] 2. Obtain the transfer function between the actual acceleration and expected acceleration of the train from the actual line operation data.

[0071] In the embodiment of the present invention, the transfer function derived from the step response of the train is used, assuming that the acceleration a f Described by a first-order system, it is expressed as:

[0072]

[0073] Among them, K f With τ f corresponds to the static gain and time constant, s is the complex frequency variable in the Laplace transform, a F des is the expected acceleration of the following vehicle, a f is the acceleration of the following vehicle.

[0074] 3. Establish the state space equation of two adjacent trains following each other, where the state vector is the position difference and speed difference between the two trains and the acceleration of the rear train, the control input is the desired acceleration of the rear train, and the interference vector is the acceleration of the front train.

[0075] The relative dynamic model of the train in state space form is expressed as:

[0076]

[0077] Among them, (t) corresponds to time t, is the relative dynamic model of the train at time t, that is, the derivative of the state vector x(t) at time t, the state vector x = [e p e v af ] T , control input Perturbation vector ω = a l , T is the transposition symbol, a l is the acceleration of the front vehicle, is the speed error, Indicates the position error e p The derivative of ; A, B1, B2 are three matrices in the form of:

[0078]

[0079] Among them, h f For time interval requirements.

[0080] 4. Train following error identification strategy based on vehicle-to-vehicle communication.

[0081] Considering the disturbance behavior of the preceding vehicle, a mixed H2 / H ∞ Control theory designs the state feedback gain of controller Ψ and the state feedback / feedforward gain of controller Φ respectively, and establishes a linear closed-loop system model.

[0082] The controller Ψ output value is determined by the state feedback gain and the relative state of the two vehicles (including tracking error, relative speed, and braking acceleration of the rear vehicle);

[0083] u(t)=K Ψ x(t)

[0084] The controller Φ output value is determined by the state feedback gain, the relative state of the two vehicles and the acceleration of the leading vehicle;

[0085]

[0086] Among them, K Ψ and K Φ is the gain matrix used to generate the control input, K Ψ is the feedback gain matrix of the controller Ψ, K Φ is the feedforward gain matrix of the controller Φ, K Φ1 and K Φ2 K Φ The specific amount.

[0087] The output state of the train can be expressed as the combined effect of the relative state of the train and the disturbance.

[0088] The feedback gain of the controller can be obtained by mixing H2 / H ∞ The optimization problem is solved and we get: i ∥ ∞ and ∥H i ∥2 is the method function of the disturbance's effect on the controller's expected output.

[0089]

[0090] st∥F i ∥ ∞ ≤γ1

[0091] ∥H i ∥2≤γ2

[0092] i=Ψ,B

[0093] Among them, α and β are weight parameters used to balance ∥F i ∥ ∞ and ∥H i ∥2 is the relative importance of γ1 and γ2. Both γ1 and γ2 are the thresholds in the constraints, and the corresponding restrictions are ∥F i ∥ ∞ and ∥H i ∥The maximum value of 2.

[0094] In the embodiment of the present invention, the train following error identification strategy based on vehicle-to-vehicle communication is mainly to reveal and analyze the evolution law of the train following error, especially when considering the disturbance behavior of the leading vehicle. ∞ The control theory designs two controllers (controller Ψ and controller B) and calculates the control input by means of state feedback gain and feedforward gain. In order to ensure the optimal performance of the controller, the following part solves the gain matrix by the linear matrix inequality (LMI) method to achieve the control objectives proposed in the theoretical design. Specifically, the appropriate gain matrix is ​​determined by LMI solution to ensure that the system can meet the minimum error and performance constraints when facing disturbances.

[0095] Specifically, the strategy includes the following steps:

[0096] 1. Use mixed H2 / H ∞ Control theory, design the state feedback gain of controller Ψ and the state feedback-feedforward gain matrix of controller Φ, and establish a linear closed-loop system model.

[0097] In this step, a mixture of H2 / H ∞ Based on control theory, two controllers (controller Ψ and controller Φ) are designed to achieve the same control objective. Controller Ψ calculates the control input u of the system as a state feedback control law, while controller Φ uses the acceleration a of the leading vehicle in addition to the model state. l , the control input u of the system is calculated as a state feedback-feedforward control law.

[0098] 2. The design problem of the two controllers is expressed as Figure 3The optimization problem shown in the figure designs the two-norm optimization target z2 and the infinite-norm optimization target z of each controller. ∞ To achieve the following control objectives: minimize and constrain the maximum position error between the front and rear vehicles and the acceleration of the rear vehicle, and minimize and constrain the position error and the second norm of the control input.

[0099] The outputs z2 and z2 of the two controllers ∞ After designing, we get the following system:

[0100]

[0101] z ∞ =[a f e p ] T =C F ·x(t)+D i ω(t)

[0102] z2=[e p u] T =C Hi ·x(t)+D i ω(t)

[0103] i=Ψ,Φ

[0104] in,

[0105] A Ψ =A+B1K Ψ

[0106] A Φ =A+B1K Φ1

[0107] B Ψ =B2

[0108] B Φ =B2+B1K Φ2 ,

[0109]

[0110] D Ψ =0

[0111] D Φ =K Φ2

[0112] in, is the derivative of the system state vector (i.e., the relative dynamic model of the train at time t), which indicates the rate of change of the system state vector x(t) over time. i is the state matrix of the controller, B i is the disturbance input matrix of the controller, C Fis the infinite norm output matrix, D i is the controller gain matrix, B1 is the control input matrix used to adjust the feedback controller, B2 is the input matrix used to model the uncertainty disturbance in the system, and C Hi is the two-norm output matrix, and i is the identifier of the controller.

[0113] 3. Set the acceleration of the front vehicle as the disturbance vector ω, and apply the disturbance vector ω to the outputs z2 and z ∞ The influence of is expressed as a transfer function:

[0114]

[0115]

[0116] i=Ψ,Φ

[0117] The output of the corresponding infinite norm transfer function and the output of the two norm transfer function perform an interference amplifier function.

[0118] in, From ω to z ∞ The transfer function of is the transfer function from ω to z2, F i represents the infinite norm z ∞ The output direct transfer matrix, H i represents the direct transfer matrix of the two-norm z2 output, and s is the complex frequency variable in the Laplace transform.

[0119] According to the transfer function and The effect of disturbance ω on the system optimization target z can be analyzed ∞ and z2. These transfer functions provide a theoretical basis for the subsequent optimization of control gains through linear matrix inequality (LMI). Specifically, the LMI method incorporates these transfer function models into constraints, thereby solving the appropriate gain matrix in the optimization process to ensure that the steady-state performance and dynamic response of the system meet the design requirements.

[0120] 4. Combined with the Lyapunov function, the gain matrices of the two controllers are solved through linear matrix inequalities.

[0121] The linear matrix inequality for the controller Ψ to solve the feedback gain is shown below:

[0122]

[0123] The controller Φ solves the linear matrix inequalities for the feedback gain and feedforward gain as follows:

[0124]

[0125] Where γ1 is the slack variable used to adjust the boundary conditions of the linear matrix inequality, Z represents the performance constraint, trace(Z) represents the sum of the diagonal elements of the matrix, X is the covariance matrix describing the system state, Y is the control gain matrix, I is an all-one matrix, and D ∞,1 is the transfer function matrix of the controller gain on the disturbance response, D ∞,2 is the transfer function matrix of the system when facing external disturbances, C2 is the output matrix of the second norm, D 2,1 is the transfer function matrix describing the two-norm performance.

[0126] The controller feedback gain matrix K is optimized by combining the disturbance response of the transfer function through the linear matrix inequality (LMI) method. Ψ And the feedforward gain matrix K Φ , so that the system can maintain the expected output performance under disturbance. This optimization process ensures the performance indicators such as the maximum position error of the front and rear vehicles, acceleration constraints and the second norm of the control input.

[0127] 5. Create a safe distance.

[0128] In the embodiment of the present invention, the safety interval between the front vehicle and the rear vehicle is constructed based on the speed information of the front vehicle and the rear vehicle, combined with the emergency braking performance and safety margin information of the front vehicle and the rear vehicle. The main steps include:

[0129] 1. Consider the emergency braking scenario of the preceding vehicle where the fluctuation of acceleration has the most serious impact on the closed-loop system.

[0130] In this step, consider the following autonomous linear system:

[0131]

[0132] With sampling time T s Discretize it to get:

[0133]

[0134] The one-step forward reachable set of the above closed-loop system can be calculated as:

[0135]

[0136] in, and The coefficient matrices representing the state equations of the two different discrete post-controllers Ψ, and Represents the coefficient matrix of the state equation of two different discrete post-controllers Φ, k is the sampling time, For uncertain initial conditions, is the additional perturbation set, Reach is the forward reachable set, ° represents the element-by-element multiplication between matrices or vectors, is the Minkowski sum operator.

[0137] When the system is subjected to additional disturbances When the initial conditions are never determined Starting from this, can the growth of all state trajectories of the system be kept within the admissible set? Within, we get the N-step forward reachable set, which proves the system's ability to tolerate disturbances.

[0138] 2. In order to obtain the minimum safety margin, it should be reflected in the fact that it can ensure that the following error after complete parking is 0. Therefore, the initial state set is set near the equilibrium point.

[0139] In this step, the initial state is considered to be near the equilibrium point of the above closed-loop system, that is, and The disturbance set ω is defined as the acceleration of the previous train, that is,

[0140] 3. Apply emergency braking from the vehicle in front to a complete stop, such as Figure 4 As shown, an N-step forward reachable set is iterated and the absolute value of the maximum following error obtained is the required minimum safety margin.

[0141] In this step, the absolute value of the calculated maximum position error is the headway h f The expected d when it is 0 min This shows that How much margin is needed to ensure the safety of the system when there is interference.

[0142] 6. Train driving strategy generation process.

[0143] In the embodiment of the present invention, the corresponding decision information is obtained by combining the set constraints, the train operation data of the preceding vehicle, the vehicle's own operation data and the decision process of the controller. The set constraints are the following error, the acceleration difference and the constraints that the control input u needs to satisfy, and the set constraints form a system allowable set; the train operation data of the preceding vehicle and the vehicle's own operation data include: the position, speed and acceleration of the preceding vehicle, and the position, speed and acceleration of the following vehicle; the system allowable set, the train operation data of the preceding vehicle and the vehicle's own operation data are input into the controller, and the corresponding decision information is obtained through the decision process of the controller (including solving the maximum initial state set and calculating the driving control strategy of the train, etc.).

[0144] In this section, the polyhedron represented by multiple constraints is defined as the system admissible set, such as Figure 5As shown, by iterating the backward reachable set until the reachable set calculated in this step is the same as that in the previous step, the obtained invariant set is the maximum initial state set required. Specifically:

[0145] Following error includes: Position error e p With speed error e v ; The constraints are expressed as: Among them, e p,min and e p,max are the minimum and maximum deviations allowed from the position of the preceding vehicle, e v,min and e v,max are the minimum and maximum deviations allowed from the speed of the vehicle ahead; exemplary: e p,min Enforce that the distance between the front and rear trains is greater than d min +v f h f , e p,max Selection can be made based on performance criteria.

[0146] The acceleration difference constraint is the acceleration constraint for the following vehicle, expressed as: Among them, a min and a max are the minimum and maximum acceleration allowed, respectively.

[0147] The actuator is a device that executes the control input u, subject to the constraints:

[0148] u min ≤K Ψ x(k)≤u max ,

[0149]

[0150] Among them, u min and u max are the minimum and maximum accelerations that the actuator can provide, respectively;

[0151] The above constraints are expressed as a system admissible set in the form of a polyhedron:

[0152]

[0153] in, is the linear coefficient matrix of the polyhedral constraints, is the right-hand side of the inequality for each constraint.

[0154] For the above closed-loop system, the one-step backward reachable set can be written as:

[0155]

[0156] Using Pontryagin differences and affine mapping of polyhedra, we can also calculate the one-step backward reachable set:

[0157]

[0158] in, is the Pontryagin difference, ° represents the element-by-element multiplication between matrices or vectors, Pre is the backward reachable set, is the symbol for the real number set.

[0159] For any disturbance Need to find the largest set of initial states To ensure that the state trajectory of the closed-loop system is always within the allowable set The maximum set of initial states of a constrained autonomous system It can be expressed as:

[0160]

[0161] k=0,1,2...

[0162] Among them, f(.) is the autonomous system function.

[0163] Maximum initial state set The backward reachable set can be iterated until the reachable set calculated in this step is the same as that in the previous step. The obtained invariant set is the required maximum initial state set, and then the decision information is obtained by combining it with the train driving control strategy.

[0164] Therefore, let U = [u min ,u max ] is the complete set of control variables, and the train driving control strategy is:

[0165]

[0166] in Representing a collection Inside, Representing a collection The control input (the expected acceleration of the following vehicle) obtained by the above formula is the decision information.

[0167] like Figure 6 As shown in the figure, the overall process of the train safety following driving method is shown. It is a closed-loop process. According to the above scheme, the following vehicle receives the train operation data of the leading vehicle, calculates the following error, builds the relative dynamic model of the train, constructs the safe distance, and iterates the maximum initial state set based on the system allowable set. ∞The controller designed by control theory generates decision information, and the following car controls the train operation according to the decision information; at the same time, it continues to receive the train operation data of the leading car and starts a new cycle.

[0168] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above embodiments can be implemented by software, or by means of software plus necessary general hardware platforms. Based on such understanding, the technical solutions of the above embodiments can be embodied in the form of software products, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0169] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed in the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims. The information disclosed in the background technology section of this article is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as an admission or in any form that the information constitutes prior art known to those skilled in the art.

Claims

1. A train safety following driving method suitable for a train-to-train communication train control system, characterized in that: The following steps are performed by the equipment in the rear vehicle: Periodically receive train operation data sent by the preceding train; According to the train operation data received from the preceding train, combined with the predetermined safety margin and time headway requirement, the following error between the preceding train and the preceding train is calculated; Based on the following error, a train relative dynamic model is constructed to describe the relative motion relationship between trains. Calculate the minimum safety margin and set the safety interval based on the minimum safety margin; Designing a decision process of a controller based on the relative dynamic model of the train, the following error and the set safety interval; By combining the set constraints, the train operation data of the preceding vehicle, its own operation data and the decision-making process of the controller, the corresponding decision information is obtained and used to control the train operation.

2. A train safety following driving method suitable for a train-to-train communication train control system according to claim 1, characterized in that: The periodically receiving the train operation data sent by the preceding vehicle comprises: The on-board equipment of the rear car periodically receives the train operation data sent by the front car, including: the position, speed and acceleration of the front car.

3. A train safety following driving method suitable for a train-to-train communication train control system according to claim 1 or 2, characterized in that: The step of calculating the following error between the vehicle and the preceding vehicle based on the received train operation data of the preceding vehicle and in combination with a predetermined safety margin and a time headway requirement comprises: The following vehicle obtains its own position and speed, and calculates the following error between it and the preceding vehicle in combination with the train operation data of the preceding vehicle and the predetermined safety margin and time interval requirements. The following error includes: position error and speed error; wherein: the position error is calculated as follows: e p =p l -p f -d min -v f h f Among them, p l is the position of the preceding vehicle, which belongs to the train operation data of the preceding vehicle; f 、v f are the position and speed of the following vehicle, d min is the predetermined safety margin, h f For time interval requirements.

4. A train safety following driving method suitable for a train-to-train communication train control system according to claim 1 or 2, characterized in that: The train relative dynamic model constructed based on the following error for describing the relative motion relationship between trains includes: The transfer function between train acceleration and expected acceleration is obtained by using actual line operation data, and then combined with the following error, a train relative dynamic model is constructed to describe the relative motion relationship of trains. Among them, the transfer function of the actual acceleration and the expected acceleration of the train is expressed as: Among them, a F des is the expected acceleration of the following vehicle, K f With τ f corresponds to the static gain and time constant, s is the complex frequency variable in the Laplace transform, a f is the acceleration of the following vehicle; The relative dynamic model of the train is in state space form and is expressed as: in, is the relative dynamic model of the train at time t, that is, the derivative of the state vector x(t) at time t, the state vector x = [e p e v a f ] T , control input Perturbation vector ω = a l , T is the transposition symbol, a l is the acceleration of the front vehicle, e p With e v belongs to the following error, e p is the position error, is the speed error, Indicates the position error e p The derivative of (t) corresponds to time t; A, B1, B2 are three matrices in the form of: Among them, h f For time interval requirements.

5. The train safety following driving method suitable for a train-to-train communication train control system according to claim 1, characterized in that: The calculation of the minimum safety margin includes: setting the acceleration of the front vehicle as the disturbance vector, calculating the N-step forward reachable set from the front vehicle starting to implement emergency braking to complete stop, and the absolute value of the maximum following error obtained is the minimum safety margin.

6. A train safety following driving method suitable for a train-to-train communication train control system according to claim 1, characterized in that: Also includes: Train following error identification strategy, which includes: Use mixed H2 / H ∞ Control theory, design the state feedback gain of controller Ψ and the state feedback-feedforward gain matrix of controller Φ, and establish a linear closed-loop system model; The design problem of the two controllers is expressed as an optimization problem. The two-norm optimization target z2 and the infinite-norm optimization target z2 of each controller are designed. ∞ To achieve the following control objectives: minimize and constrain the maximum position error of the front and rear vehicles and the acceleration of the rear vehicle, and minimize and constrain the position error and the second norm of the control input; Set the acceleration of the preceding vehicle as the disturbance vector ω, and apply the disturbance vector ω to the outputs z2 and z ∞ The influence of is expressed as a transfer function, and the corresponding infinite norm and two norm perform the function of interference amplifier on the desired output respectively; Combined with Lyapunov function, the gain matrices of the two controllers are solved by linear matrix inequalities.

7. A train safety following driving method suitable for a train-to-train communication train control system according to claim 6, characterized in that: The corresponding decision information obtained by combining the set constraint conditions, the train operation data of the preceding train, the own operation data and the decision process of the controller includes: The set constraints are the following error, the acceleration difference and the constraints that the control input needs to satisfy, and the set constraints form a system allowable set; wherein the control input is the expected acceleration of the following vehicle; The train operation data of the preceding train and its own operation data include: the position, speed and acceleration of the preceding train, and the position, speed and acceleration of the following train; The system allowable set, the train operation data of the preceding train and its own operation data are input into the controller, and the corresponding decision information is obtained through the decision-making process of the controller.

8. A train safety following driving method suitable for a train-to-train communication train control system according to claim 7, characterized in that: The set constraints are the following error, the acceleration difference and the constraints that the control input needs to satisfy. The set constraints form a system allowable set including: Following error includes: Position error e p With speed error e v ; The constraint condition is expressed as: e p,min ≤e p ≤e p,max ;e v,min ≤e v ≤e v,max ; Among them, e p,min and e p,max are the minimum and maximum deviations allowed from the position of the preceding vehicle, e v,min and e v,max are the minimum and maximum deviations allowed from the speed of the vehicle ahead, respectively; The acceleration difference constraint is the acceleration constraint for the following vehicle, expressed as: a min ≤a f ≤a max ; Among them, a min and a max are the minimum and maximum acceleration allowed, respectively; The constraints for the control input are: u min ≤K Ψ x(k)≤u max , Where k represents the sampling time, K Ψ is the feedback gain matrix of the controller Ψ, K Φ is the feedforward gain matrix of the controller Φ, K φ1 and K Φ2 It's K φ The weight, u min and u max are the minimum and maximum acceleration respectively, and the state vector x = [e p e v a f ] T , T is the transposition symbol, a l is the acceleration of the front vehicle, e p With e v belongs to the following error, e p is the position error, e v is the speed error; The above constraints are expressed as a system admissible set in the form of a polyhedron:

9. A train safety following driving method suitable for a train-to-train communication train control system according to claim 7, characterized in that: The obtaining of the corresponding decision information includes: calculating a one-step backward reachable set: in, is the Pontryagin difference, ° represents the element-by-element multiplication between matrices or vectors, Pre is the backward reachable set, and The coefficient matrix representing the state equation of the discrete post-controller Φ, is the perturbation set, is the uncertain initial condition, x is the system admissible set; Define the maximum set of initial states for: Where k represents the sampling time, and the state vector x = [e p e v a f ] T , the disturbance vector ω=a l , T is the transposition symbol, a l is the acceleration of the front vehicle, e p With e v belongs to the following error, e p is the position error, e v is the speed error, f(.) is the autonomous system function; Maximum initial state set Through backward reachable set iteration, until the reachable set calculated in this step is the same as that in the previous step, the obtained invariant set is the required maximum initial state set, and then combined with the train driving control strategy to obtain decision information; Let U=[u min ,u max ] is the complete set of control variables, and the train driving control strategy is: in, express Inside, express The boundary of , the control input obtained by the above formula is the decision information.

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