A relative position keeping fault-tolerant degradation method, device, equipment, medium and product of a train

Abstract

The application discloses a relative position keeping fault-tolerant degradation method, device, equipment, medium and product of a train, and relates to the technical field of railway train operation control. The method determines a normalized communication risk value according to a plurality of communication quality indexes of a communication link between each train of a heavy-haul train; the plurality of communication quality indexes include a message age, an end-to-end delay and a continuous packet loss number; the normalized communication risk value is compared with a preset grading threshold value to determine a current degradation state; a corresponding set of operation constraint parameters is generated according to the current degradation state; and the set of operation constraint parameters is executed by a train automatic driving unit and is superimposed on existing safety logic of a train automatic protection unit. The application can effectively keep the relative positions between heavy-haul trains and improve the control efficiency of the relative positions.

Description

Technical Field

[0001] This application relates to the field of railway train operation control technology, and in particular to a method, device, equipment, medium and product for maintaining the relative position of a train with fault tolerance and degradation. Background Technology

[0002] Virtual coupling technology enables multiple trains to operate collaboratively at set intervals through vehicle-to-vehicle wireless communication, reducing physical coupling operations and improving track utilization. However, in scenarios such as tunnels and mountainous areas, communication links may experience increased latency, jitter, or packet loss, which can affect the maintenance of relative positions.

[0003] Existing solutions typically rely on communication failures as the basis for judgment, making it difficult to distinguish between short-term disturbances and sustained deterioration. They also lack corresponding handling methods to address progressively tightening operational constraints. Furthermore, risks related to communication, braking, and positioning are often handled in a fragmented manner, with unclear degradation and recovery conditions, leading to frequent switching around thresholds. Therefore, the shortcomings of existing solutions can be summarized as follows: 1. Lack of continuous measurement of communication quality. Existing solutions mostly judge based on "whether communication is faulty", failing to make full use of input factors such as message age, end-to-end delay, jitter and packet loss. Therefore, it is difficult to handle occasional disturbances as conservative follow-up and to handle continuous deterioration as disconnection.

[0004] 2. The interface with existing ATP (Automatic Train Protection) / ATO (Automatic Operation) systems is not clearly defined. Some solutions directly change the ATP protection mode, increasing the workload of modifying and certifying existing systems. Summary of the Invention

[0005] The purpose of this application is to provide a method, apparatus, equipment, medium, and product for maintaining the relative position of trains with fault tolerance and degradation, which can effectively maintain the relative position between heavy-haul trains and improve the control efficiency of the relative position.

[0006] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a relative position maintenance fault-tolerant degradation method for trains, the method being applied to a virtual coupled train formation consisting of multiple heavy-haul trains, each heavy-haul train being equipped with an automatic train protection unit and an automatic train driving unit, the method comprising: Based on multiple communication quality indicators of the communication links between heavy-haul trains, a normalized communication risk value is determined; these multiple communication quality indicators include message age, end-to-end latency, and number of consecutive packet losses. The normalized communication risk value is compared with a preset classification threshold to determine the current downgrade status. Based on the current degradation state, generate the corresponding set of operational constraint parameters; The automatic train control unit executes the operation constraint parameter set according to the set of parameters, and then superimposes the set of parameters on the existing safety logic of the automatic train protection unit.

[0007] Secondly, this application provides a relative position holding fault-tolerant degradation device for trains, the device being used to implement the aforementioned relative position holding fault-tolerant degradation method for trains, the device comprising: The communication quality monitoring module is used to determine a normalized communication risk value based on multiple communication quality indicators of each vehicle-to-vehicle communication link. These multiple communication quality indicators include message age, end-to-end latency, and number of consecutive packet losses. The degradation status management module is used to compare the normalized communication risk value with a preset classification threshold to determine the current degradation status; The constraint generation module is used to generate a corresponding set of runtime constraint parameters based on the current degradation state. The output module is used by the train automatic driving unit to execute according to the set of operating constraint parameters and to superimpose the set of operating constraint parameters on the existing safety logic of the train automatic protection unit.

[0008] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the above-described fault-tolerant degradation method for maintaining the relative position of a train.

[0009] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described fault-tolerant degradation method for maintaining the relative position of a train.

[0010] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described fault-tolerant degradation method for maintaining the relative position of a train.

[0011] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a method, apparatus, device, medium, and product for maintaining the relative position of trains with fault tolerance and degradation. It fully utilizes communication quality indicators such as message age, end-to-end delay, and number of consecutive packet losses to achieve continuous measurement of communication quality, thereby clearly distinguishing between short-term disturbances and continuous deterioration in communication and imposing corresponding operational constraints. This effectively maintains the relative position between heavily loaded trains. Based on the current degradation state, it outputs a set of operational constraint parameters, which are executed by the train automatic driving unit. This does not require changing the protection mode of the train automatic protection unit, which continues to provide a safety baseline. This reduces the workload of modifying and certifying existing systems and improves the control efficiency of relative position. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A flowchart illustrating a fault-tolerant degradation method for maintaining the relative position of a train, provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0015] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0016] In one exemplary embodiment, such as Figure 1 As shown, a fault-tolerant degradation method for maintaining the relative position of a train is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to a virtual coupled train formation consisting of multiple heavy-haul trains, each equipped with an automatic train protection unit and an automatic train driving unit. The method includes steps 101 to 104.

[0017] Step 101: Determine the normalized communication risk value based on multiple communication quality indicators of the communication links between heavy-haul trains; the multiple communication quality indicators include message age, end-to-end delay, and number of consecutive packet losses.

[0018] Step 102: Compare the normalized communication risk value with the preset classification threshold to determine the current downgrade status.

[0019] Step 103: Generate the corresponding set of running constraint parameters based on the current downgraded state.

[0020] Step 104: The train automatic driving unit executes according to the set of operating constraints and superimposes the set of operating constraints onto the existing safety logic of the train automatic protection unit.

[0021] In another exemplary embodiment of this application, step 101 above is a communication risk quantification step, and the detailed process can be found in steps 201 to 208.

[0022] Step 201: Determine the remaining margin between adjacent heavy-haul trains as the current spacing margin, which is the current actual spacing margin relative to the minimum safe spacing margin.

[0023] Step 202: Based on the current spacing margin, use the formula To obtain the allowable communication time; where, To allow for acceptable communication time, This is the current spacing margin. As a positioning error margin, To approximate the velocity, This is the minimum calculation limit for the relative approximation velocity. For braking response time, Processing time for the train automatic driving unit. This represents the lower limit of the acceptable communication time in engineering.

[0024] Step 203: Based on the allowable communication time, use the formula To obtain the baseline value for the message's age; where, The age baseline for the message. This is a conversion factor for the age baseline value of the message. This is the lower limit of the age baseline for the message. This represents the upper limit of the age baseline for the message. These are the upper and lower limit constraint functions.

[0025] Step 204: Based on the allowable communication time, use the formula To obtain the delay reference value; where, As the baseline value for delay, This is a conversion factor for the delayed baseline value. This is the lower limit of the delay benchmark value. This is the upper limit of the delay baseline value.

[0026] Step 205: Based on the aforementioned delay reference value, use the formula To obtain the jitter reference value; where, As the jitter baseline value, The conversion factor is used to determine the jitter baseline value. This is the lower limit of the jitter baseline value. This is the upper limit of the jitter baseline value.

[0027] Step 206: Using the formula Determine the baseline value for packet loss rate; where, This is the baseline value for packet loss rate. The preset packet loss rate baseline value, This is the lower limit of the baseline value for packet loss rate. This represents the upper limit of the baseline value for packet loss rate.

[0028] Step 207: Using the formula Determine the baseline value for continuous packet loss; where, This is the baseline value for continuous packet loss. The preset baseline value for the number of consecutive packet losses. This is the lower limit of the baseline value for continuous packet loss. This is the upper limit of the baseline value for continuous packet loss.

[0029] The message age benchmark, latency benchmark, jitter benchmark, packet loss rate benchmark, and continuous packet loss benchmark are all normalized benchmarks with preset engineering upper and lower limits to avoid oversensitivity or oversluggishness.

[0030] The inputs for steps 201-207 above are the current spacing margin, relative approximation speed, and processing time. The processing involves safety margin conversion and upper and lower limit constraints. The output is... , , , , The core code snippet is as follows: # Calculate the allowable communication time based on the current operating margin M = d - d_min Tsafe = max((M - ep) / max(vc, v_min) - tb - ta, Tmin) A1 = clamp(kA Tsafe, A1_min, A1_max D1 = clamp(kD Tsafe, D1_min, D1_max) J1 = clamp(kJ D1, J1_min, J1_max) # Maintain the upper and lower limits of the packet loss baseline to avoid widening the threshold with intervals. P1 = clamp(P_set, P1_min, P1_max) L1 = clamp(L_set, L1_min, L1_max) return A1, D1, J1, P1, L1.

[0031] The meanings of the letters in the above code are shown in Table 1.

[0032] Table 1. Letter Meanings

[0033] Step 208: Based on multiple communication quality indicators and the benchmark values ​​of each communication quality indicator, use the formula... To obtain the normalized communication risk value; where, The normalized communication risk value, For the age of the message, For end-to-end delay, For time delay jitter, For packet loss rate, This represents the number of consecutive packet losses.

[0034] The communication risk value prioritizes message age and end-to-end delay as metrics, and combines the normalized components using the largest of the functions.

[0035] The input for step 208 is the communication link quality index, which is processed by normalization and taking the largest value, and the output is the communication risk value. The core code snippet is as follows: # Collect communication quality input and normalize it according to the benchmark q = [Age / A1, Delay / D1, Jitter / J1, LossRate / P1, ConsecutiveLoss / L1] Rcom = max(q) # Retain the largest component to avoid the average masking serious risks. risk_source = q.index(Rcom) return Rcom, risk_source.

[0036] In one example, the communication risk quantification step also includes a time synchronization error metric; when the time synchronization error exceeds a preset error threshold, Set it directly to a value not less than 1.0.

[0037] In another exemplary embodiment of this application, the level states, in order of increasing tightness of operational constraints, include: normal mode, conservative following mode, speed holding mode, and decoupling mode. Normal mode S0: Target spacing is Follow the target speed of the queue, allowing for acceleration and braking rates; Conservative Follow Mode S1: Target Spacing is This reduces the upper limit of acceleration and increases the braking preparation margin. Speed ​​Holding Mode S2: Target Spacing is , Actively shortening the spacing is prohibited, and acceleration is limited to zero or negative values. Decoupling Mode S3: Exit virtual spacing, each heavy-haul train switches to independent ATP protection operation. In another exemplary embodiment of this application, the process for determining the current downgraded state when the risk state is downgraded is as follows: like And continue If a communication cycle is completed, the current degraded state will be set to conservative follow mode; The normalized communication risk value, This is the first downgrade threshold; like And continue If a communication cycle is completed, the current degraded state will be switched to speed-maintaining mode; where, The second downgrade threshold, , Use a more stringent threshold set A more stringent threshold set is used to identify compared to More severe communication quality degradation, to avoid state escalation or entry due to short-term disturbances. .

[0038] like ,or If the relative position data is invalid, the current downgraded state will be changed to the unattached mode; among which, For the age of the message, Set a threshold for downgrading the age of messages. This represents the number of consecutive packet losses. The threshold for downgrading the number of consecutive packet losses is set. Relative position data failure refers to situations where the position, speed, and time information of adjacent trains cannot meet the preset timeliness, integrity, or reliability conditions, including data timeout, integrity verification failure, time synchronization anomaly, invalid positioning unit output, or deviation between relative position data and independent positioning results exceeding the preset threshold.

[0039] For example, the degradation condition in the degradation status determination step is: S0 S1: continued One communication cycle; S1 S2: continued One cycle; S2 S3: The relative position data is invalid.

[0040] Self-consistency maintenance step: In the degradation state determination step, the expanded target spacing in mode S1 or S2 is only used as an operational safety buffer and not as a relaxation of the communication risk value. The triggering of S2 and S3 still depends on the absolute thresholds of the multiple communication quality indicators, or on the basis of their component thresholds.

[0041] The process for determining the current risk level when the risk condition escalates is as follows: like continued If the relative distance error remains stable for a given number of seconds, then the current level status is set to normal mode. Here, stable relative distance error means that the absolute value of the error between the actual relative distance and the target distance does not exceed the preset distance error threshold, and the error change rate does not exceed the preset change rate threshold, and this is maintained continuously for a preset time. The threshold for upgrading is set. Stable relative distance error means that the absolute value of the error between the actual relative distance and the target distance does not exceed the preset distance error threshold, and the error change rate does not exceed the preset change rate threshold, and remains stable for a preset time.

[0042] like continued If the braking state is effective within seconds, then the current level state is set to conservative follow mode.

[0043] For example, the recovery condition in the hysteresis switching step is: S1 S0: continued Second Relative distance error stable S2 S1: ( (Continued below) Second Braking status effective S3 S0 / S1: No automatic recovery; communication handshake, braking capability verification, relative position verification, and mode authorization need to be re-executed.

[0044] The input for the hysteresis switching step is The duration and state holding time are specified, and the output is the new degraded state S. The core code snippet for hysteresis switching is as follows: # Downgrade uses a threshold of 1.0, recovery uses a threshold of 0.6. if S == 'S0' and Rcom>= 1.0 and n>= N1: S = 'S1' elif S == 'S1' and Rcom>= 1.0 and T == T2 and n>= N2: S = 'S2' elif S == 'S2' and (Age>A3 or ConsecutiveLoss>L3 or pos_invalid): S = 'S3' # Recovery requires both communication restoration and vehicle status stabilization. elif S == 'S1' and Rcom<= 0.6 and stable and t>= M1: S = 'S0' elif S == 'S2' and Rcom<= 0.6 and brake_ok and t>= M2: S = 'S1' # S3 does not automatically revert; external authorization is required. return S.

[0045] As can be seen from the above, asymmetric threshold conditions are used for both downgrade and recovery, where: The downgrade from a low-risk state to a high-risk state is based on the first threshold condition; The recovery from a high-risk state to a low-risk state employs a second threshold condition, which is more stringent than the corresponding downgrade condition, in order to suppress frequent state oscillations near the threshold.

[0046] In another exemplary embodiment of this application, step 103 above is a constraint output step: based on the current degraded state, a corresponding set of operational constraint parameters is generated and output to the on-board ATO unit and / or the on-board ATP unit. The operational constraint parameter set of the ATP unit includes at least: the updated target spacing, speed limit, acceleration / braking slope limit value, current virtual coupling mode status identifier, indication of whether to release virtual coupling, and indication of whether to request independent movement authorization or conventional block protection. The operational constraint parameter set is superimposed on the existing safety logic of the on-board ATP unit without replacing it.

[0047] The input to the constraint output step is the current degraded state S and the existing ATP velocity constraints. The processing involves mapping target spacing, velocity upper limits, and acceleration limits. The output is the set of constraint parameters sent to the ATO and ATP. The core code snippet for the constraint output step is as follows: # Map the degraded state to an ATO executable constraint Dtarget = D0 + d_add[S] # Base target spacing Add status The target spacing is obtained from the corresponding spacing increment. Vlimit = min(Vplan, v_cap[S], V_atp) # Take the minimum value among the planned velocity, the state velocity limit, and the ATP velocity limit as the final velocity limit. Alimit = min(a_cmd, a_cap[S]) # Take the smaller value between the original ATO acceleration command and the state acceleration upper limit as the acceleration limit. if S == 'S2': # Determine if the current mode is S2 speed hold mode Alimit = min(Alimit, 0.0) # In S2 mode, limit the acceleration to no greater than zero, and disable active acceleration to shorten the distance. release_vc = (S == 'S3') # When the state is S3, set the virtual link removal flag to true. # ATP only accepts constraints and identifiers; existing protection logic remains in effect. packet = {'S': S, 'Dtarget': Dtarget, 'Vlimit': Vlimit, 'Alimit': Alimit, 'release_vc': release_vc} # Encapsulate the downgrade status, target spacing, speed limit, acceleration limit, and decoupling flag into a constraint data package. send_to_ATO(packet); send_to_ATP(packet) # Send the constraint data packet to the ATO unit and the ATP unit respectively return packet # Output the generated operation constraint data packet.

[0048] In another exemplary embodiment of the present application, the method of the present application further includes a multi-risk superposition step, and the detailed execution process is as shown in the following Step 301 to Step 305.

[0049] Step 301: According to the formula , determine the braking capacity risk state; in the formula, is the braking capacity risk state, is the available braking force proportion, is the first braking threshold, is the second braking threshold, is the third braking threshold, is the conservative following mode, is the speed keeping mode, is the uncoupling mode.

[0050] The determination of the braking capacity risk state includes: when it is detected that the available braking force proportion is lower than the first braking threshold, set to S1; when the available braking force proportion is lower than the second braking threshold, set to S2; when the available braking force proportion is lower than the third braking threshold, or the complete braking failure of any bogie is detected, directly set to S3; where the first braking threshold is greater than the second braking threshold, and the second braking threshold is greater than the third braking threshold.

[0051] Braking capacity risk state determination step: the inputs are the available braking force proportion and the bogie braking state, the processing is hierarchical threshold judgment, the output is the braking risk state Sbrake, and the core code snippet is as follows: # Fuse braking capacity with sliding window to avoid single-point sampling misjudgment hist.append((B_avail, bogie_fail)); hist = hist[-W:] # Add the current available braking force and bogie fault state to the historical data, and only keep the latest W cycles valid = [x for x in hist if not x[1]] # Filter out valid data without bogie braking fault if len(valid)<N_min: # Judge whether the number of valid data is less than the minimum requirement return 'S3', 'brake_data_invalid' # When valid data is insufficient, directly determine as , and mark the brake data as invalid r = median([x[0] for x in valid]) / B_need # Calculate the ratio of the median of the valid available braking force to the required braking force the ratio drop = (hist[-2][0]- hist[-1][0]) / max(hist[-2][0], eps) # Calculate the relative drop ratio of the available braking force in two adjacent cycles # Sudden drop and bogie failure directly increase the risk level if any(x[1] for x in hist[-K:]) or drop>B_drop: # In the recent cycles, there is a bogie failure, or the braking force drop ratio exceeds the threshold Sbrake = 'S3' # Set the brake risk state to elif r<B3: If the braking force ratio is lower than the third brake threshold Sbrake = 'S3' # Set the brake risk state to elif r<B2 or trend(valid)<-B_slope: # If the braking force ratio is lower than the second threshold , or the braking force shows a significant downward trend Sbrake = 'S2' # Set the brake risk state to elif r<B1: # If the braking force ratio is lower than the first threshold Sbrake = 'S1' # Set the brake risk state to else: # None of the above risk conditions are met Sbrake = 'S0' # Set the brake risk state to return Sbrake, r # Output the brake risk state and the available braking force ratio .

[0052] Step 302: Determine the current degradation state as the communication risk state.

[0053] Step 301: According to the formula Determine the location risk status; where, To determine the risk status, For location data, This represents the number of consecutive failures. For the preset number of times, For positioning error, The third positioning threshold, This is the relative position consistency error. For position jump variables, To preset the jump threshold, The second positioning threshold, To determine location reliability, The second confidence threshold. To show the positioning error trend, For trend threshold, The first positioning threshold, The first confidence threshold is... It indicates "or".

[0054] Determine the risk status The determination includes: acquiring the estimated value of train positioning error, relative position consistency error, positioning confidence, positioning data validity flag, and position jump variable; wherein, the relative position consistency error is the absolute value of the difference between the relative distance determined based on vehicle-to-vehicle communication data and the relative distance determined based on independent positioning information; when the estimated value of positioning error or the relative position consistency error exceeds a first positioning threshold, the positioning risk state is set to S1; when it exceeds a second positioning threshold, the positioning confidence is lower than a second confidence threshold, or the positioning error shows a continuous increasing trend, the positioning risk state is set to S2; when the positioning data fails, the number of consecutive failures exceeds a preset number, the positioning error exceeds a third positioning threshold, or the position jump variable exceeds a preset jump threshold, the positioning risk state is set to S3; wherein, the first positioning threshold is less than the second positioning threshold, and the second positioning threshold is less than the third positioning threshold.

[0055] Step 303: According to the formula Determine the communication integrity risk status; where, The communication integrity is at risk. To verify the source of the information, This represents the number of consecutive verification failures. The threshold for the third number, For time synchronization error, The third synchronization error threshold, The proportion of integrity exception messages, This is the second integrity threshold. For the second threshold number, This is the second synchronization error threshold. The first integrity threshold, The threshold for the first count, This is the first synchronization error threshold. This is a replay detection result flag, used to indicate whether message replay was detected; when message replay is detected... Take 1, otherwise Take 0.

[0056] Communication integrity risk status The determination includes: performing data verification, message source authentication, serial number continuity verification, timestamp validity verification, and replay detection on vehicle-to-vehicle communication messages, and statistically analyzing the proportion of integrity-abnormal messages, the number of consecutive verification failures, and the number of serial number abnormalities within a preset sliding window; when the proportion of integrity-abnormal messages exceeds a first integrity threshold, the communication integrity risk state is set to S1; when the proportion of integrity-abnormal messages exceeds a second integrity threshold, the number of consecutive verification failures exceeds a second threshold, or the time synchronization error exceeds a second synchronization error threshold, the communication integrity risk state is set to S2; when message source authentication fails, message tampering or replay is detected, the number of consecutive verification failures exceeds a third threshold, or the time synchronization error exceeds a third synchronization error threshold, the communication integrity risk state is set to S3.

[0057] Step 304: Establish the correspondence between the level status and the risk level value.

[0058] Step 305: Based on the correspondence, compare the communication risk status, braking capability risk status, positioning risk status, and communication integrity risk status, and select the status with the highest risk level value as the final downgrade status.

[0059] Communication risk status Braking capability risk status Identify the risk status and communication integrity risk status Each assessment is conducted independently, and the most conservative result is taken as the final relegation status: .

[0060] The input for the multi-risk stacking step consists of various risk states. The process involves selecting the most conservative state and outputting the final downgraded state, Sfinal. The core code snippet for multi-risk stacking is as follows: rank = {'S0': 0, 'S1': 1, 'S2': 2, 'S3': 3} # Establish the correspondence between downgrade status and risk level values S_list = [Scomm, Sbrake, Sposition, Sintegrity] # A list of risk states consisting of communication risk states, braking capability risk states, positioning risk states, and communication integrity risk states. # After independent risk assessment, the most conservative approach will be adopted. Sfinal = max(S_list, key=lambda S: rank[S]) # Compare the four risk states according to the state level specified in rank, and select the state with the highest level value as the final downgrade state. Dtarget, Vlimit, Alimit = limit_map[Sfinal] # Based on the final degradation state, read the corresponding target spacing from the preset state-constraint mapping limit_map. Speed ​​limit and acceleration limit value .

[0061] # Output constraint parameters, without replacing the existing safety logic of ATP. return Sfinal, Dtarget, Vlimit, Alimit # Output the final degraded state and the target spacing, velocity limit, and acceleration limit values ​​corresponding to that state.

[0062] In another exemplary embodiment of this application, the method further includes a multi-car link constraint propagation step. When the virtual coupled train group contains three or more train units, the degradation state of each car's communication link is determined independently, but the overall operation constraint of the train group is propagated using the worst constraint of each link.

[0063] When a virtual coupled train formation includes three sequentially connected heavy-haul trains A, B, and C, the overall operational constraints of the virtual coupled train formation are propagated using the worst-case constraints of all car-to-car communication links, including: Set the execution status of heavy-haul train A to AB link status, and the execution status of heavy-haul train C to BC link status; set the execution status of heavy-haul train B to the higher risk level between AB link status and BC link status; select the most conservative execution status from the execution statuses of heavy-haul train A, B, and C as the overall formation status; combine the statuses of each train and the overall formation status to generate an operational constraint plan; monotonically increment the sequence number of the operational constraint plan to generate the final multi-car formation operational constraint plan.

[0064] For example, if the AB link is in S0 and the BC link is in S2, then unit C must execute the S2 constraint, and unit B's backward coordination with unit C is executed according to the S2 constraint. The AB link can maintain the S0 constraint, but the overall target speed and spacing plan of the group is limited by the worst constraint of the BC link.

[0065] The input to the multi-train link constraint propagation step is the AB and BC link states. This is processed as worst-case constraints propagated along the train formation direction, and the output is the degraded state that each train should execute. The core code snippet for multi-train link constraint propagation is as follows: # First, verify the time validity of adjacent links, then propagate the most conservative constraints. state = {} # Create a dictionary to store the degradation state of each link. for e in ['A-B', 'B-C']: # Process links AB and BC sequentially. pkt = link_state[e] # Get the communication status data packet of the current link. if now - pkt.t>T_expire or pkt.pos_invalid: # If the data exceeds the validity period. Or the relative position data is invalid. state[e] = 'S3' # This link is directly determined to be in the S3 unconnected state. else: #If the link data is still valid state[e] = hysteresis(pkt.Rcom, pkt.S, pkt.cnt) # Determine the new state of the link based on the communication risk value, the original state, and the duration using hysteresis logic. rank = {'S0':0, 'S1':1, 'S2':2, 'S3':3} # Establish the correspondence between downgrade status and risk level S_A = state['A-B'] # Set the execution state of train A to the AB link state S_B = max([state['A-B'], state['B-C']], key=lambda S: rank[S]) # Train B is affected by both AB and BC links, so the state with the higher risk level is selected. # When BC deteriorates, a more conservative plan is implemented for C and the speed of the entire formation is constrained. S_C = state['B-C'] # Set the execution state of train C to the BC link state S_group = max([S_A, S_B, S_C], key=lambda S: rank[S]) # Select the most conservative state from the three train states A, B, and C as the overall state of the train group. plan = merge_constraints({'A':S_A, 'B':S_B, 'C':S_C}, S_group) # Generates a plan with target spacing, speed, and other operational constraints by combining the status of each train and the overall status of the train formation. `plan.seq = monotonic_seq(plan.seq)` # This monotonically increments the sequence numbers of the constraint plans to prevent old or out-of-order plans from being executed repeatedly. return plan # Outputs the final generated multi-vehicle formation operation constraint plan.

[0066] In another exemplary embodiment of this application, the method further includes a low-speed dedicated rule: when the train speed is lower than a preset minimum speed threshold... ( When the speed is between 5km / h and 10km / h, the dynamic time threshold is not used; instead, a fixed maximum message age, a fixed minimum spacing, and a fixed confirmation period are used. During shunting, approaching stop, and regrouping, a low-speed mode independent of the high-speed following logic is used.

[0067] The technical solution of this application will be further explained below with reference to simulation experimental parameters. This embodiment takes a virtual coupled train consisting of three HXD type heavy-haul electric locomotives as the object, and the input quantities are data such as message age, transmission delay, jitter, and packet loss rate of the vehicle-to-vehicle communication link. The onboard processing unit calculates the communication risk value based on the above inputs, determines four levels of states from S0 to S3, and outputs the target spacing, speed limit, and acceleration limit. Degradation and recovery use asymmetric thresholds, and the operating constraint parameters are superimposed on the existing ATP safety logic without replacing it.

[0068] The core parameters in the specific implementation are shown in Table 2.

[0069] Table 2 Core Parameters

[0070] The experimental results are shown in Table 3.

[0071] Table 3 Experimental Results

[0072] The simulation results show that under mild communication degradation, the virtual coupling maintenance rate is 78.25%, indicating that the graded degradation mechanism can preferentially enter a conservative following state when communication fluctuates briefly, rather than directly disengaging the virtual coupling. Under moderate communication degradation, the maintenance rate drops to 46.35%, indicating that the system gradually tightens operational constraints as communication quality deteriorates further. The number of unnecessary decouplings per 100 km is 7.25, and the driver intervention frequency is 4.15, indicating that intermediate degradation states and hysteresis recovery conditions can reduce frequent decouplings and manual intervention. The number of boundary condition degradation state oscillations is 1.82, indicating that the asymmetric threshold has a suppressive effect on repeated state switching. The number of safety baseline violations is 0, indicating that the operational constraints, superimposed on the existing ATP safety logic, do not exceed the existing safety protection boundary.

[0073] Based on the same inventive concept, this application also provides a train relative position holding fault-tolerant degradation device for implementing the train relative position holding fault-tolerant degradation method described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more train relative position holding fault-tolerant degradation device embodiments provided below can be found in the limitations of the train relative position holding fault-tolerant degradation method described above, and will not be repeated here.

[0074] In one exemplary embodiment, a relative position holding fault-tolerant degradation device for a train is provided, comprising: The communication quality monitoring module is used to determine a normalized communication risk value based on multiple communication quality indicators of each vehicle-to-vehicle communication link. These multiple communication quality indicators include message age, end-to-end latency, and number of consecutive packet losses. The degradation status management module is used to compare the normalized communication risk value with a preset classification threshold to determine the current degradation status; The constraint generation module is used to generate a corresponding set of runtime constraint parameters based on the current degradation state. The output module is used by the train automatic driving unit to execute according to the set of operating constraint parameters and to superimpose the set of operating constraint parameters on the existing safety logic of the train automatic protection unit.

[0075] As an optional implementation, the device further includes: a multi-risk assessment module, used to acquire braking capability status, positioning status and communication integrity status, and determine the corresponding risk status respectively; the degradation status management module is also used to take the most conservative of the communication risk status, braking risk status, positioning risk status and integrity risk status as the final degradation status.

[0076] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 2 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores a set of operational constraint parameters. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a fault-tolerant degradation method for maintaining the relative position of a train.

[0077] Those skilled in the art will understand that Figure 2 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include, but are not limited to, the following: Figure 2 The embodiments show more or fewer components, combinations of certain components, or different component arrangements. In one exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, which the processor executes to implement the steps in the above-described method embodiments.

[0078] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0079] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0080] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0081] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0082] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0083] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for fault-tolerant degradation of maintaining the relative position of a train, characterized in that, The method is applied to a virtual coupled train formation consisting of multiple heavy-haul trains, each equipped with an automatic train protection unit and an automatic train control unit. The method includes: Based on multiple communication quality indicators of the communication links between heavy-haul trains, a normalized communication risk value is determined; these multiple communication quality indicators include message age, end-to-end latency, and number of consecutive packet losses. The normalized communication risk value is compared with a preset classification threshold to determine the current downgrade status. Based on the current degradation state, generate the corresponding set of operational constraint parameters; The automatic train control unit executes the operation constraint parameter set according to the set of parameters, and then superimposes the set of parameters on the existing safety logic of the automatic train protection unit.

2. The relative position maintenance fault-tolerant degradation method for trains according to claim 1, characterized in that, Based on multiple communication quality indicators of the communication links between heavy-haul trains, a normalized communication risk value is determined, including: The remaining margin between adjacent heavy-haul trains relative to the minimum safe distance is determined as the current spacing margin. Based on the current spacing margin, using the formula To obtain the allowable communication time; where, To allow for acceptable communication time, This is the current spacing margin. As a positioning error margin, To approximate the velocity, This is the minimum calculation limit for the relative approximation velocity. For braking response time, Processing time for the train automatic driving unit. This represents the lower limit of the acceptable communication time in engineering. Based on the allowable communication time, using the formula To obtain the baseline value for the message's age; where, The age baseline for the message. This is a conversion factor for the age baseline value of the message. This is the lower limit of the age baseline for the message. This represents the upper limit of the age baseline for the message. These are the upper and lower limit constraint functions; Based on the allowable communication time, using the formula To obtain the delay reference value; where, As the baseline value for delay, This is a conversion factor for the delayed baseline value. This is the lower limit of the delay benchmark value. This is the upper limit of the delay baseline value; Based on the aforementioned delay reference value, using the formula To obtain the jitter reference value; where, As the jitter baseline value, The conversion factor is used to determine the jitter baseline value. This is the lower limit of the jitter baseline value. This is the upper limit of the jitter baseline value; Using formula Determine the baseline value for packet loss rate; where, This is the baseline value for packet loss rate. The preset packet loss rate baseline value, This is the lower limit of the baseline value for packet loss rate. This represents the upper limit of the baseline value for packet loss rate. Using formula Determine the baseline value for continuous packet loss; where, This is the baseline value for continuous packet loss. The preset baseline value for the number of consecutive packet losses. This is the lower limit of the baseline value for continuous packet loss. This is the upper limit of the baseline value for continuous packet loss; Based on multiple communication quality indicators and their benchmark values, the formula is used. To obtain the normalized communication risk value; where, The normalized communication risk value, For the age of the message, For end-to-end delay, For time delay jitter, For packet loss rate, This represents the number of consecutive packet losses.

3. The relative position maintenance fault-tolerant degradation method for trains according to claim 1, characterized in that, The operational constraint tightening levels, from lowest to highest, are as follows: Normal Mode, Conservative Follow Mode, Speed ​​Hold Mode, and Uncoupling Mode. Normal mode: Target spacing is Follow the target speed of the queue, allowing for acceleration and braking rates; Conservative Follow Mode: Target Spacing is This reduces the upper limit of acceleration and increases the braking preparation margin. Speed ​​maintenance mode: target spacing is , Actively shortening the spacing is prohibited, and acceleration is limited to zero or negative values. Decoupled mode: Exit virtual spacing, each heavy-haul train switches to independent ATP protection operation; The set of operational constraint parameters includes target spacing, upper speed limit, and acceleration limit.

4. The relative position maintenance fault-tolerant degradation method for trains according to claim 1, characterized in that, The process for determining the current downgraded status when the risk status is downgraded is as follows: like And continue If a communication cycle is completed, the current degraded state will be set to conservative follow mode; The normalized communication risk value, This is the first downgrade threshold; like And continue If a communication cycle is completed, the current degraded state will be switched to speed-maintaining mode; where, The second downgrade threshold, , ; like ,or If the relative position data is invalid, the current downgraded state will be changed to the unattached mode; among which, For the age of the message, Set a threshold for downgrading the age of messages. This represents the number of consecutive packet losses. The threshold for downgrading the number of consecutive packet losses is set. The process for determining the current risk level when the risk condition escalates is as follows: like continued If the relative distance error remains stable for a given number of seconds, then the current level status is set to normal mode. Here, stable relative distance error means that the absolute value of the error between the actual relative distance and the target distance does not exceed the preset distance error threshold, and the error change rate does not exceed the preset change rate threshold, and this is maintained continuously for a preset time. To upgrade the threshold; like continued If the braking state is active for a second, then the current level state is set to conservative follow mode.

5. The relative position maintenance fault-tolerant degradation method for trains according to claim 1, characterized in that, Also includes: According to the formula Determine the risk status of braking capacity; where, This indicates a risk to braking capacity. The ratio of available braking force. The first braking threshold, The second braking threshold, The third braking threshold, It is a conservative follower mode. For speed hold mode, To remove the linked mode; The current downgrade status is determined to be a communication risk status; According to the formula Determine the location risk status; where, To determine the risk status, For location data, This represents the number of consecutive failures. For the preset number of times, For positioning error, The third positioning threshold, This is the relative position consistency error. For position jump variables, To preset the jump threshold, The second positioning threshold, To determine location reliability, The second confidence threshold. To show the positioning error trend, For trend threshold, The first positioning threshold, The first confidence threshold is... Indicates or; According to the formula Determine the communication integrity risk status; where, The communication integrity is at risk. Verify the source of the information; This is a replay detection result flag, used to indicate whether message replay was detected; when message replay is detected... Take 1, otherwise Set to 0; This represents the number of consecutive verification failures. The threshold for the third number, For time synchronization error, The third synchronization error threshold, The proportion of integrity exception messages, This is the second integrity threshold. For the second threshold number, This is the second synchronization error threshold. The first integrity threshold, The threshold for the first count, The first synchronization error threshold; Establish a correspondence between the status level and the risk level value; Based on the aforementioned correspondence, the communication risk status, braking capability risk status, positioning risk status, and communication integrity risk status are compared, and the status with the highest risk level value is selected as the final downgrade status.

6. The relative position maintenance fault-tolerant degradation method for trains according to claim 1, characterized in that, When a virtual coupled train formation includes three sequentially connected heavy-haul trains A, B, and C, the overall operational constraints of the virtual coupled train formation are propagated using the worst-case constraints of all car-to-car communication links, including: Set the execution status of heavy-haul train A to AB link status and the execution status of heavy-haul train C to BC link status. Set the execution status of heavy-haul train B to the higher risk level between the AB link status and the BC link status. The most conservative state among the execution states of heavy-haul train A, heavy-haul train B, and heavy-haul train C is taken as the overall state of the train formation. By combining the status of each train and the overall status of the train formation, an operational constraint plan is generated; The sequence number of the operation constraint plan is monotonically increased to generate the final multi-car train operation constraint plan.

7. A relative position maintenance fault-tolerant degradation device for trains, characterized in that, The apparatus is used to implement the relative position maintenance fault-tolerant degradation method for trains according to any one of claims 1-6, and the apparatus comprises: The communication quality monitoring module is used to determine a normalized communication risk value based on multiple communication quality indicators of each vehicle-to-vehicle communication link. These multiple communication quality indicators include message age, end-to-end latency, and number of consecutive packet losses. The degradation status management module is used to compare the normalized communication risk value with a preset classification threshold to determine the current degradation status; The constraint generation module is used to generate a corresponding set of runtime constraint parameters based on the current degradation state. The output module is used by the train automatic driving unit to execute according to the set of operating constraint parameters and to superimpose the set of operating constraint parameters on the existing safety logic of the train automatic protection unit.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes the computer program to implement the relative position maintenance fault-tolerant degradation method for trains according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the relative position maintenance fault-tolerant degradation method for trains as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the relative position maintenance fault-tolerant degradation method for trains as described in any one of claims 1-6.

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