An intelligent hibernation and wake-up control method for a fully automatic unmanned vehicle

Abstract

The application discloses an automatic unmanned vehicle intelligent hibernation and wake-up method, which comprises the following steps: after receiving a wake-up power-on, a vehicle network control system (TCMS) is powered on and self-checked, while an expert system (WTS) collects system data from a bus, evaluates the comprehensive state of the vehicle and the comprehensive state of the train network quality, and feeds back to the TCMS system; after the TCMS reports the self-checking result, the self-checking is continued, if the TCMS reports a self-checking failure, the vehicle wake-up process is ended; a signal system (ATC) sends a high-voltage test instruction, the vehicle network control system receives the instruction and automatically completes the inspection items of the high-voltage test, the vehicle automatically rises the bow and waits for 1500V voltage access to perform the high-voltage part inspection of the vehicle, if the TCMS reports a high-voltage self-checking failure, the vehicle wake-up process is ended; the vehicle and the signal system cooperate to perform a joint self-checking, and after the joint self-checking is successful, the automatic unmanned vehicle is switched from the hibernation state to the wake-up state.

Description

Technical Field

[0001] This invention belongs to the field of fully automated products and relates to an intelligent sleep-wake control method for fully automated unmanned vehicles. Background Technology

[0002] Driverless subway vehicles are widely used worldwide, improving the operational safety, service quality, and economy of rail transit systems. my country is in the initial stages of research and application of driverless subway technology. It is a comprehensive technology; the maturity of the coordination between the vehicle and the signaling system is crucial.

[0003] From an automation perspective: Driverless rail transit systems aim to improve the safety, service quality, and economy of rail transit operations. They are a new generation of urban rail transit systems with a high level of automation, making full use of modern electronic, electrical, mechanical, and information technologies. The IEC standard defines five automation levels from GOA0 to GOA4. GOA3 and GOA4 are what we commonly refer to as driverless systems because they do not require a driver; driver control of the vehicle is completely handed over to the automated system.

[0004] Driverless vehicles offer several advantages, including: firstly, higher safety due to automated control and diagnostics, reducing human error; secondly, higher system redundancy with comprehensive remote recovery, bypass, and isolation functions; thirdly, improved operational quality through flexible operating schedules; fourthly, punctuality and high transportation efficiency; fifthly, a higher level of automation providing more user-friendly services; sixthly, better economic efficiency by reducing the number of trains required; seventhly, lower labor input; and eighthly, lower energy consumption. Driverless subway systems have been successfully implemented and are widely used in many countries and regions worldwide, demonstrating a relatively mature application track record.

[0005] Existing technical solution 1

[0006] Current methods for waking up driverless subway vehicles from hibernation are not highly intelligent. They primarily rely on traditional methods such as power-on self-checks of various subsystems, static testing, high-voltage testing, and dynamic testing after the vehicle is powered on to check its real-time status and wake it up to enter standby mode. Pre-hibernation, including battery voltage detection, total air pressure detection, and air conditioning status detection, confirms that the vehicle is ready for hibernation before initiating the hibernation process. In short, current methods for waking up vehicles from hibernation mainly depend on the vehicle's real-time status information, and the process is completed through frequent interaction with the vehicle's signaling system.

[0007] Disadvantages of existing technology

[0008] (1) The existing vehicle sleep-wake logic interacts too frequently with the signal system. The test command is initiated by the signal system, and after the vehicle executes it, it feeds back the status information to the signal system. The signal system controls the vehicle sleep-wake steps step by step, and each step has a maximum test tolerance time. If the test fails before the test tolerance time is exceeded, the signal system will automatically determine that the sleep-wake has failed. Due to the frequent interaction, the vehicle sleep-wake time increases, the vehicle preparation time increases significantly, and the vehicle's operating efficiency is reduced.

[0009] (2) The existing vehicle sleep-wake process lacks attention to the early warning information of the vehicle's key systems and the historical alarm information of the key systems, which leads to the vehicle ignoring the early warning and historical alarm information of the key systems and continuing to wake up successfully. This may cause the mainline operation to fail, resulting in the vehicle being delayed or taken off the line, and the vehicle's operating indicators will decline.

[0010] (3) Existing vehicles cannot perform real-time detection of the train's central system (train network control system). If there are abnormalities such as interference, packet loss, or erroneous needles in the network control system, it may cause the vehicle control commands to be sent incorrectly or missed, which may lead to abnormal or failed vehicle control functions, resulting in vehicle mainline operation failures or even vehicle decommissioning, seriously affecting vehicle operation indicators. Summary of the Invention

[0011] To solve the above problems, the technical solution adopted by the present invention is: an intelligent sleep-wake method for autonomous vehicles, comprising the following steps:

[0012] S1: Upon receiving the wake-up power-on notification, the vehicle network control system TCMS powers on and performs a self-test. Other subsystems simultaneously perform power-on self-tests. At the same time, the expert system WTS collects data from each system on the bus, evaluates the overall status of the vehicle and the overall status of the train network quality, and feeds it back to the TCMS system. The vehicle network control system TCMS then integrates the self-test status of each system, the overall status of the vehicle, and the overall status of the network quality to determine the self-test result to be reported to the signal system ATC. After the vehicle network control system TCMS reports the self-test result, it will continue to perform a self-test, proceeding to S2. If the TCMS reports a self-test failure, the vehicle wake-up process ends.

[0013] S2: After the signal system ATC receives the self-test result from the vehicle network control system TCMS, the signal system ATC sends a high-voltage test command. After receiving the command, the vehicle network control system automatically completes the high-voltage test check item. The vehicle automatically raises the pantograph and waits for the 1500V voltage to be connected before checking the high-voltage part of the vehicle. When the vehicle network control system TCMS reports that the high-voltage self-test is successful, the self-test process will continue and proceed to S3. If the vehicle network control system TCMS reports that the high-voltage self-test fails, the vehicle wake-up process will end.

[0014] S3: After the signal system ATC receives the high-voltage self-test feedback from the vehicle network control system TCMS and the signal system successfully completes the joint self-test, the vehicle and the signal system cooperate to perform a joint self-test. After the joint self-test is successful, the vehicle enters the standby mode, realizing the automatic unmanned vehicle from the dormant state to the awakened state.

[0015] Furthermore, the other subsystems simultaneously perform power-on self-tests, including traction, auxiliary, braking, doors, pantograph, running gear, fire alarm, charger, air conditioning, passenger information system, vehicle cabinet door status, vehicle bypass button status, and vehicle key switch status.

[0016] Furthermore, the high-voltage component inspection includes the input / output inspection of the traction / auxiliary system, the air compressor's airflow and airtightness inspection, the charger inspection, and the mechanical brake inspection.

[0017] Furthermore, the vehicle and signal system perform a joint self-test, including switching the activation terminal, emergency braking self-test, door opening and closing, and creep test.

[0018] Furthermore, it also includes hibernation process control, including the following processes:

[0019] The train operates in FAM mode to the hibernation / wake-up area and stops at the hibernation / wake-up platform.

[0020] Once the communication channel is established, the ATC (Automatic Traffic Control) system sends a hibernation request. After receiving the hibernation request signal, the vehicle TCMS (Traffic Control Management System) replies to the ATC with a confirmation of the hibernation request. At this time, the ATC sends a hibernation command to the vehicle TCMS. While the TCMS sends a confirmation of the hibernation command back to the ATC, it performs pre-hibernation preparations, including checking the overall airflow status, battery status, shutting down the air compressor and air conditioning, checking for critical vehicle faults, and combining the comprehensive vehicle status evaluation from the expert system with the overall network quality status. After all the vehicle's hibernation conditions are met, the TCMS sends a hibernation preparation completion message to the ATC. After the ATC sends a vehicle power-off command, the TCMS is responsible for executing the vehicle power-off.

[0021] Furthermore, the process for assessing the overall condition of the vehicle is as follows:

[0022] The overall evaluation value of vehicle C is obtained by calculating the health of the single vehicle subsystem, the health of the whole vehicle subsystem, and the overall vehicle evaluation. The specific steps are as follows.

[0023] Single vehicle subsystem health calculation:

[0024]

[0025] Where: A1 is the score of the single vehicle subsystem (0-100), X is the evaluation dimension, and Y is the weight ratio of the subsystem;

[0026] Vehicle subsystem health calculation:

[0027] B1 = (A1 + A2 + A3…) / N;

[0028] Where: B1 is the score of the whole vehicle subsystem (0-100), Ai is the score of the i-th vehicle system, and N is the number of vehicle sections;

[0029] Overall vehicle score calculation:

[0030] C = B1*P1 + B2*P2 + ... + Bn*Pn;

[0031] Where: C is the actual vehicle comprehensive score (0-100), Bn is the vehicle subsystem score, and Pn is the weight ratio of the vehicle system.

[0032] Furthermore: The comprehensive status of the train network quality is obtained by collecting waveform data of MVB network communication messages for a period of time (30S-180S) and one macro cycle, and analyzing the data according to the configuration parameters to automatically obtain the analysis results of each device / port and generate an analysis report.

[0033] By collecting communication messages and physical waveforms of the train's MVB network, a comprehensive analysis of the train network is conducted from the communication physical layer, link layer, and network layer, and a train network quality analysis report is output.

[0034] This invention provides an intelligent sleep / wake-up control method for fully automated driverless vehicles. Through a concentrated investigation of several existing driverless subway sleep / wake-up logics, the problems existing in the vehicle's sleep / wake-up process were identified. This invention proposes a novel intelligent sleep / wake-up control method for driverless vehicles, shortening the vehicle's sleep / wake-up time. It utilizes big data analysis technology to diagnose the critical system status of the vehicle, ensuring that the vehicle is in good condition before wake-up, thus ensuring safe operation, reducing the failure rate of vehicles on the main line, and improving operational efficiency. This method controls...

[0035] (1) The interaction between the vehicle sleep wake-up logic and the signal system is simple. The TCMS intelligent control of the vehicle self-test greatly improves efficiency, significantly shortens the vehicle preparation time, and improves the vehicle's operating efficiency.

[0036] (2) The sleep-wake process of the vehicle has been improved by adding early warning information of the vehicle's key systems and analysis of historical alarm information of the key systems, which effectively avoids the possibility of failures in the main line operation that may cause the vehicle to be delayed or taken off the line, and improves the vehicle operation indicators.

[0037] (3) Real-time detection of the train’s central system (train network control system) can prevent vehicles from waking up normally when the network quality is poor if there are abnormalities such as interference, packet loss, or error needles in the network control system. This can prevent the mis-sending or omission of vehicle control commands, which could lead to abnormal or failed vehicle control functions, resulting in vehicle mainline operation failures or even vehicle decommissioning, thus ensuring vehicle operation safety.

[0038] This method has the following advantages:

[0039] (1) The vehicle intelligent sleep-time replacement control method simplifies the interaction process and improves wake-up efficiency. Most of the wake-up is controlled and detected autonomously by the vehicle. Compared with the traditional wake-up method, it has the following characteristics:

[0040] 1) The interaction process is simple and the vehicle has strong autonomous detection and control capabilities, thereby reducing vehicle wake-up failures caused by data loss due to frequent interactions between the vehicle and the signal system, which directly affects the vehicle's operating efficiency.

[0041] 2) The vehicle wake-up control process is highly intelligent. After receiving the signal system instruction, the vehicle autonomously decides on self-check items according to the predetermined sequence, which reduces repeated interactions with the signal system, shortens the vehicle wake-up time, and enables the vehicle to quickly enter the standby state, thereby improving the vehicle's operating efficiency.

[0042] 3) The vehicle wake-up conditions fully consider various conditions for vehicle driving safety, such as the status of the vehicle circuit breaker, bypass switch, critical relays, and cabinet doors. The wake-up operation can only be performed after all conditions are met.

[0043] (2) The expert system diagnoses and applies the subsystem, uses big data analysis to conduct a comprehensive health assessment of the vehicle, and controls the vehicle's hibernation and wake-up based on the assessment results.

[0044] (3) The expert system analyzes and applies the train control bus, evaluates the MVB network communication quality of the rail train and locates communication faults, and performs vehicle sleep-wake control based on the evaluation results. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a network control system topology diagram for autonomous vehicles;

[0047] Figure 2 This is the wake-up flowchart;

[0048] Figure 3 This is the hibernation flowchart;

[0049] Figure 4 This is a graph showing the relationship between health score and influencing factors;

[0050] Figure 5 This is a network report test graph. Detailed Implementation

[0051] It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0054] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0055] In the description of this invention, it should be understood that the orientation or positional relationship indicated by directional terms such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" is generally based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing this invention and simplifying the description. Unless otherwise stated, these directional terms do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the scope of protection of this invention. The directional terms "inner" and "outer" refer to the inner and outer contours relative to the outline of each component itself.

[0056] For ease of description, spatial relative terms such as "above," "over," "on the upper surface of," "above," etc., are used herein to describe the spatial positional relationship of a device or feature as shown in the figures to other devices or features. It should be understood that spatial relative terms are intended to encompass different orientations in use or operation besides the orientation of the device as described in the figures. For example, if the device in the figures is inverted, a device described as "above" or "above" other devices or structures would subsequently be positioned as "below" or "under" other devices or structures. Thus, the exemplary term "above" can include both "above" and "below." The device may also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatial relative descriptions used herein will be interpreted accordingly.

[0057] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore should not be construed as limiting the scope of protection of this invention.

[0058] Figure 1 This is a network control system topology diagram of an autonomous vehicle. The orange parts in the diagram represent the network control system devices.

[0059] (1) Each Tc car has one train control unit (CCU), and the two are redundant. The main CCU is responsible for controlling the car, monitoring and diagnosing the car's equipment;

[0060] (2) Two human-machine interface units (HMIs) are located in two Tc cars, one in each Tc car, and are responsible for displaying the status of the equipment and guiding the driver and passengers to operate it.

[0061] (3) Each carriage has a RIOM module connected to the vehicle bus via an MVB interface to collect and control the main signals of the 110V control circuit, as well as to collect and control the analog or digital signals of the driver controller, the steering handle, and other signals. Cars Tc1 and Tc2 each have two RIOM modules for redundant collection of key train signals.

[0062] (4) Each car is equipped with a repeater, and each repeater contains two redundant repeater modules. When one repeater fails, the other repeater will relay the original A or B line transmission without affecting the signal reception of each subsystem. The repeater divides the train network into the train bus and the vehicle bus, amplifies and regenerates the signals transmitted in the MVB line, and ensures the reliable transmission distance of the bus.

[0063] (6) The M1 car is equipped with an accident backup record device (ERD) to provide an independent accident backup record device, continuously record key train information, meet the requirements of accident impact, vibration, squeezing, waterproofing, fire prevention, etc., and be used to analyze major train accidents.

[0064] (7) Other subsystems are connected to the TCMS via the MVB bus or RIOM. Subsystem component failures do not affect the normal operation of the MVB vehicle bus. The interfaces between the subsystems and the vehicle bus are redundant, and a failure of a single interface does not affect the normal operation of the train.

[0065] (8) The subsystem connects to the Ethernet switch of each car via Ethernet interface and Ethernet cable, jointly constructing a train maintenance Ethernet local area network for remote debugging, updating, and data downloading of equipment. At the same time, this local area network provides a reliable and high-speed data transmission path for the data collection of the train system.

[0066] Figure 2 This is the wake-up flowchart;

[0067] It provides a reliable and high-speed data transmission path for the collection of data from the train system.

[0068] In the diagram, ATC represents the signal system, and WTS represents the vehicle expert system. The intelligent sleep / wake-up control method of this invention is mainly implemented through the cooperation of the network control system, signal system, and expert system. The wake-up process is shown in the figure.

[0069] A method for intelligent sleep / wake-up of an autonomous driverless vehicle includes the following steps:

[0070] The vehicle network control system TCMS collects network data from various vehicle subsystems and vehicle hardware data through the MVB and ETH buses, and performs vehicle wake-up operations by combining relevant control commands sent by the signal system (ATC).

[0071] S1: After the vehicle receives the wake-up power-on notification, the vehicle network control system (TCMS) powers on and performs a self-test. Other subsystems simultaneously perform power-on self-tests, including traction, auxiliary, braking, doors, pantograph-catenary, running gear, fire alarm, charger, air conditioning, passenger information system, vehicle cabinet door status, vehicle bypass button status, and vehicle key switch status. At the same time, the expert system (WTS) collects data from each system on the bus, uses big data analysis, statistics, and intelligent algorithms to evaluate the overall status of the vehicle and the overall quality of the train network, and feeds it back to the TCMS system. The TCMS system then integrates the self-test status of each system, the overall status of the vehicle, and the overall quality of the network to determine the self-test result to be reported to the signaling system (ATC). If the TCMS reports a successful self-test, the self-test process will continue; if the TCMS reports a failed self-test, the vehicle wake-up process will end.

[0072] S2: After the vehicle network control system TCMS reports a successful self-test to the signal system ATC, the signal system ATC sends a high-voltage test command. Upon receiving the command, the vehicle network control system automatically completes all the checks for this part. The vehicle automatically raises its pantograph and waits for the 1500V voltage to be connected before performing high-voltage checks on the vehicle, including input / output checks of the traction / auxiliary system, air compressor operation and airtightness checks, charger checks, and mechanical brake checks. If the vehicle network control system TCMS reports a successful high-voltage self-test, the self-test process will continue. If the vehicle network control system TCMS reports a failed high-voltage self-test, the vehicle wake-up process will end.

[0073] S3: After the vehicle network control system (TCMS) reports a successful high-voltage self-test to the signal system (ATC), the vehicle and the signal system cooperate to perform a joint self-test, including switching the activation terminal, emergency braking self-test, door opening and closing, and creep test. After the joint self-test is successful, the vehicle enters standby mode and can be dispatched and put into operation at any time.

[0074] Figure 3 This is the hibernation flowchart;

[0075] A method for intelligent hibernation of an autonomous vehicle includes the following steps:

[0076] The train operates in FAM mode to the hibernation / wake-up area and stops at the hibernation / wake-up platform.

[0077] Once the communication channel is established, the ATC sends a hibernation request. After receiving the hibernation request signal, the vehicle's TCMS system replies to the ATC with a hibernation request confirmation. At this time, the ATC sends a hibernation command to the vehicle's TCMS. While the TCMS sends a hibernation command confirmation back to the ATC, it performs pre-hibernation preparations, including checking the overall airflow status, battery status, shutting down the air compressor and air conditioning, checking for critical vehicle faults, and combining the comprehensive vehicle status evaluation from the expert system with the overall network quality status. After all the vehicle's hibernation conditions are met, the TCMS sends a hibernation preparation completion message to the ATC. After the ATC sends a vehicle power-off command, the TCMS is responsible for executing the vehicle power-off.

[0078] The architecture diagram of this intelligent sleep / wake control method is as follows: Figure 1 As shown, the various components are connected via the MVB bus and the ETH bus. The working process is as follows:

[0079] a. The various subsystems of the vehicle (blue part) interact with the vehicle TCMS control system (orange part) via the MVB bus and Ethernet bus.

[0080] b. The TCMS system implements a hibernation / wake-up control process based on the system status feedback from each subsystem. For example... Figure 2 , Figure 3 .

[0081] c. The Vehicle Expert System (WTS) analyzes and comprehensively judges the status of key system components by analyzing data from various systems, which serves as a prerequisite for the vehicle to wake up from hibernation and determines whether the vehicle can successfully wake up from hibernation.

[0082] d. The bus analysis module in the Vehicle Expert System (WTS) analyzes the quality of the MVB bus, such as diagnosing abnormal conditions like interference, packet loss, and error pins, and feeds the diagnostic results back to the vehicle TCMS control system as a prerequisite for vehicle sleep-wake-up, determining whether the vehicle can successfully sleep-wake up.

[0083] e.TCMS control system according to Figure 2 ,、 Figure 3 The timing sequence completes the vehicle sleep-wake control process.

[0084] (2) This invention is a fully automatic unmanned vehicle intelligent sleep-wake control method, mainly implemented by a TCMS system and an expert system (WTS). The main function of the TCMS system is to... Figure 2 and Figure 3The process of controlling vehicle sleep and wake-up involves data interaction with the Automatic Traffic Control (ATC) system. The expert system consists of two main parts: one part provides fault information, early warning information, and life prediction information for key components of the real-time diagnostic subsystem, and the other part provides real-time diagnostic information for the quality of the control bus. Both parts of the information are transmitted to the TCMS system, which then makes a comprehensive judgment on whether sleep and wake-up should continue.

[0085] Furthermore, the expert system intelligently assesses the overall status of the subsystem and directly participates in the hibernation / wake-up control process as follows:

[0086] The in-vehicle expert system performs comprehensive diagnostics on vehicle data and intelligently decides whether to wake up the vehicle from sleep mode based on the diagnostic results, ensuring vehicle driving safety.

[0087] The vehicle expert system provides data support for vehicle health status assessment from the bottom up (vehicle-level assessment data comes from the system level, and system-level assessment data is provided by other business systems). Factors affecting system-level health status include train status information, fault information, and condition monitoring information. Vehicle-level influencing factors consist of systems (or some key systems) that participate in the system level assessment. Figure 4 This is a graph showing the relationship between health score and influencing factors;

[0088] The expert system supports the relationship between data items and impact factors with certain data editing rules. When multiple data items are required to support a certain impact factor, or when the calculation cannot be completed within a single function system, the health weighted calculation must be carried out after importing the data items and performing data editing (secondary data calculation).

[0089] The calculation result is the content of the input item for the final factor calculation.

[0090] The system status is digitally presented based on a health score. The system is divided into five levels according to the score, and the score values ​​for each level are adjustable. When the health status is good, vehicle sleep / wake-up operations are allowed; otherwise, manual intervention to check the vehicle is required.

[0091] Health grade >90 Good condition 90-75 Operational observation 75-65 Maintain operation 65-55 Affecting driving <55 Safety hazards

[0092] The vehicle expert system calculates the influencing factors on vehicle wake-up and hibernation based on data from the vehicle subsystems. Then, through weighted calculations, it ultimately assesses the vehicle's health level and reports the diagnostic results to the TCMS system via the vehicle bus. The TCMS system then decides whether to wake the vehicle from hibernation based on the health level. The TCMS is not allowed to wake the vehicle when its health level is at either the "safety hazard" or "impact on driving" level. This method significantly reduces the vehicle failure rate on the main line and improves the level of vehicle operation and service.

[0093] The process for assessing the overall condition of the vehicle is as follows:

[0094] The overall evaluation value of vehicle C is obtained by calculating the health of the single vehicle subsystem, the health of the whole vehicle subsystem, and the overall vehicle evaluation. The specific steps are as follows.

[0095] (1) Health calculation of single vehicle subsystem:

[0096]

[0097] Where: A1 is the score of the single-vehicle subsystem (0-100), X is the evaluation dimension, and Y is the weight ratio of the subsystem as follows:

[0098]

[0099]

[0100] (2) Vehicle subsystem health calculation:

[0101] B1 = (A1 + A2 + A3…) / N;

[0102] Where: B1 is the score of the whole vehicle subsystem (0-100), Ai is the score of the i-th vehicle system, and N is the number of vehicle sections;

[0103] (3) Calculation of overall vehicle score:

[0104] C = B1*P1 + B2*P2 + ... + Bn*Pn;

[0105] Where: C is the actual vehicle comprehensive score (0-100), Bn is the vehicle subsystem score, and Pn is the weighting ratio of the vehicle system as follows:

[0106] B (Evaluation Dimension) P (Subsystem weight ratio) Traction system 0.1 Braking system 0.1 auxiliary systems 0.1 door system 0.1 air conditioning system 0.1 Passenger Information System 0.1 Fire alarm detection system 0.1 Running gear maintenance system 0.05 Obstacle detection system 0.05 Train control system 0.15 Battery monitoring system 0.02 pantograph-catenary monitoring system 0.03

[0107] Furthermore, the expert system intelligently diagnoses and controls the bus quality, and directly participates in sleep / wake control. The specific process is as follows:

[0108] The onboard expert diagnostic system intelligently diagnoses the bus quality and reports the results to the TCMS, which then decides whether to wake the vehicle from sleep mode.

[0109] The onboard expert diagnostic system assesses the quality of train MVB network communication. After the analysis is started on the software, the device automatically collects MVB network communication packets for a period of time (30-180 seconds) and waveform data for one macro cycle, analyzes the data according to the configured parameters, automatically obtains the analysis results for each device / port, and generates an analysis report. Figure 5 This is a network report test graph.

[0110] The onboard expert diagnostic system assesses the communication quality and locates communication faults in the MVB network of rail trains. By collecting communication messages and physical waveforms from the train's MVB network, the product performs a comprehensive analysis of the train network from the physical layer, link layer, and network layer, outputting a train network quality analysis report. When a fault occurs in the train network, the expert system can quickly diagnose the location and possible causes of the fault.

[0111] TCMS controls vehicle sleep / wake-up based on diagnostic results. For example, if the bit error rate is >15%, the vehicle is not allowed to wake up; if the bit error rate is >25%, the vehicle is not allowed to sleep. This method can reduce vehicle offline failures caused by network quality issues and improve vehicle operating efficiency.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent hibernation and wake-up of an autonomous unmanned vehicle, characterized in that: Includes the following steps: S1: Upon receiving the wake-up power-on notification, the vehicle network control system TCMS powers on and performs a self-test. Other subsystems simultaneously perform power-on self-tests. At the same time, the expert system WTS collects data from each system on the bus, evaluates the overall status of the vehicle and the overall status of the train network quality, and feeds it back to the TCMS system. The vehicle network control system TCMS then integrates the self-test status of each system, the overall status of the vehicle, and the overall status of the network quality to determine the self-test result to be reported to the signal system ATC. After the vehicle network control system TCMS reports the self-test result, it will continue to perform a self-test, proceeding to S2. If the TCMS reports a self-test failure, the vehicle wake-up process ends. S2: After the signal system ATC receives the self-test result from the vehicle network control system TCMS, the signal system ATC sends a high-voltage test command. After receiving the command, the vehicle network control system automatically completes the high-voltage test check item. The vehicle automatically raises the pantograph and waits for the 1500V voltage to be connected before checking the high-voltage part of the vehicle. When the vehicle network control system TCMS reports that the high-voltage self-test is successful, the self-test process will continue and proceed to S3. If the vehicle network control system TCMS reports that the high-voltage self-test fails, the vehicle wake-up process will end. S3: After the signal system ATC receives the high-voltage self-test success feedback from the vehicle network control system TCMS, the vehicle and the signal system cooperate to perform a joint self-test. After the joint self-test is successful, the vehicle enters the standby mode, realizing the automatic unmanned vehicle from the dormant state to the awakened state.

2. The intelligent sleep / wake-up method for an autonomous unmanned vehicle according to claim 1, characterized in that: The other subsystems simultaneously perform power-on self-tests, including traction, auxiliary, braking, doors, pantograph, running gear, fire alarm, charger, air conditioning, passenger information system, vehicle cabinet door status, vehicle bypass button status, and vehicle key switch status.

3. The intelligent sleep / wake-up method for an autonomous unmanned vehicle according to claim 1, characterized in that: The high-voltage component inspection includes the input / output inspection of the traction / auxiliary system, the air compressor's airflow and airtightness inspection, the charger inspection, and the mechanical brake inspection.

4. The intelligent sleep / wake-up method for an autonomous unmanned vehicle according to claim 1, characterized in that: The vehicle and signal system perform a joint self-test, including switching the activation terminal, emergency braking self-test, door opening and closing, and creep test.

5. The intelligent sleep / wake-up method for an autonomous unmanned vehicle according to claim 1, characterized in that: It also includes hibernation process control, including the following processes: The train operates in FAM mode to the hibernation / wake-up area and stops at the hibernation / wake-up platform. Once the communication channel is established, the ATC (Automatic Traffic Control) system sends a hibernation request. After receiving the hibernation request signal, the vehicle TCMS (Traffic Control Management System) replies to the ATC with a confirmation of the hibernation request. At this time, the ATC sends a hibernation command to the vehicle TCMS. While the TCMS sends a confirmation of the hibernation command back to the ATC, it performs pre-hibernation preparations, including checking the overall airflow status, battery status, shutting down the air compressor and air conditioning, checking for critical vehicle faults, and combining the comprehensive vehicle status evaluation from the expert system with the overall network quality status. After all the vehicle's hibernation conditions are met, the TCMS sends a hibernation preparation completion message to the ATC. After the ATC sends a vehicle power-off command, the TCMS is responsible for executing the vehicle power-off.

6. The intelligent sleep / wake-up method for an autonomous unmanned vehicle according to claim 1, characterized in that: The process for assessing the overall condition of the vehicle is as follows: The overall vehicle evaluation value is obtained by calculating the health of individual vehicle subsystems, the health of the entire vehicle subsystem, and the overall vehicle evaluation. The specific steps are as follows: Single vehicle subsystem health calculation: A1 = ； Where: A1 is the score of the single vehicle subsystem, ranging from 0 to 100; Xi is the evaluation dimension; and Yi is the weight ratio of the evaluation dimension of the subsystem. Vehicle subsystem health calculation: B1 = (A1+A2+A3…+Aj…) / N; Where: B1 is the score of the first vehicle subsystem, ranging from 0 to 100; Aj is the score of the j-th vehicle subsystem, j = 1, 2, 3, ...; N is the number of vehicle subsystems. Overall vehicle score calculation: C = B1*P1+B2*P2+…+Bn*Pn; Where: C is the actual vehicle comprehensive score, ranging from 0 to 100; Bn is the score of the nth vehicle subsystem; and Pn is the weight ratio of each subsystem in the vehicle system.

7. The intelligent sleep / wake-up method for an autonomous unmanned vehicle according to claim 1, characterized in that: The comprehensive status of the train network quality is obtained by collecting MVB network communication messages over a period of time and waveform data of a macro cycle, and analyzing the data according to the configuration parameters to automatically obtain the analysis results for each device / port and generate an analysis report; the period of time is 30S-180S. By collecting communication messages and physical waveforms of the train's MVB network, a comprehensive analysis of the train network is conducted from the communication physical layer, link layer, and network layer, and a train network quality analysis report is output.

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