Urban rail vehicle cooperation method and system, electronic equipment and storage medium

Abstract

The invention provides an urban rail vehicle cooperation method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining the current operation data of a vehicle, evaluating the energy consumption efficiency and passenger comfort of the vehicle based on the historical operation data and historical environment data of the vehicle, and preliminarily determining a vehicle operation and energy consumption management strategy; carrying out data fusion on the obtained current environment data and the current vehicle operation data, carrying out comprehensive analysis, and dynamically adjusting a preliminary vehicle operation and energy consumption management strategy based on an analysis result; finely adjusting the dynamically adjusted vehicle operation and energy consumption management strategy according to the requirements and preferences of passengers on the compartment environment; and the vehicle operation and energy consumption management strategy obtained after fine adjustment is converted into a control instruction, and control operation is executed according to the control instruction. The energy efficiency of vehicle operation is remarkably improved, the operation cost of an urban rail transit system is reduced, the comfort requirement of passengers is met to the maximum extent, and the travel experience of the passengers is improved.

Description

Technical Field

[0001] The present application belongs to the field of urban rail transit technology, and in particular, relates to an urban rail vehicle coordination method, system, electronic device and storage medium. Background Art

[0002] With the acceleration of urbanization, urban rail transit systems, as an important part of urban public transportation, are being constructed and developed rapidly. With its high efficiency, convenience and environmental protection, urban rail transit has become an effective means to alleviate urban traffic congestion and improve air quality. However, with the expansion of operation scale and the increase of passenger demand, the energy consumption problem of urban rail transit systems has become increasingly prominent, becoming an important factor restricting its sustainable development. Therefore, how to effectively reduce energy consumption while ensuring operational efficiency and service quality has become a key issue that needs to be urgently addressed in the current urban rail transit field.

[0003] Traditional urban rail transit vehicle operation strategies are often designed with a focus on fixed operation modes and energy consumption distribution, lacking the ability to perceive and dynamically respond to external environmental factors in real time. Specifically, traditional systems are unable to effectively cope with the impact of extreme weather conditions or special road conditions on vehicle operation and energy consumption, which results in a significant increase in vehicle energy consumption under adverse environmental conditions, while passenger comfort is also greatly reduced. In addition, traditional energy-saving optimization methods are mostly based on static data analysis, lacking real-time and dynamic features, and unable to be precisely adjusted according to real-time environmental changes and vehicle status, thus limiting further improvements in energy-saving effects. Summary of the invention

[0004] In view of this, the present application aims to propose a method, system, electronic device and storage medium for urban rail vehicle coordination to solve the problems of high vehicle energy consumption, poor passenger comfort and single adaptability.

[0005] To achieve the above purpose, the technical solution of this application is implemented as follows:

[0006] In a first aspect, the present application provides a method for urban rail vehicle coordination, comprising:

[0007] Obtain the current operation data of the vehicle, evaluate the vehicle's energy efficiency and passenger comfort based on the vehicle's historical operation data and historical environmental data, and preliminarily determine the vehicle's operation and energy management strategies;

[0008] Acquire current environment data, fuse the acquired current environment data with the current operation data of the vehicle, and conduct comprehensive analysis, and dynamically adjust the preliminary vehicle operation and energy consumption management strategy based on the analysis results to obtain an intermediate vehicle operation and energy consumption management strategy;

[0009] According to the needs and preferences of passengers for the cabin environment, the intermediate vehicle operation and energy consumption management strategy is fine-tuned through a dynamic programming algorithm;

[0010] The vehicle operation and energy consumption management strategies obtained after fine-tuning are converted into control instructions, and control operations are performed according to the control instructions.

[0011] In the second aspect, based on the same inventive concept, the present application also provides an urban rail vehicle cooperative system, including:

[0012] A vehicle status monitoring module is configured to obtain current vehicle operation data, evaluate the vehicle's energy efficiency and passenger comfort based on historical vehicle operation data and historical environmental data, and preliminarily determine vehicle operation and energy management strategies;

[0013] The collaborative decision-making module is configured to obtain current environmental data, fuse the obtained current environmental data with the current operation data of the vehicle, and perform comprehensive analysis, and dynamically adjust the preliminary vehicle operation and energy consumption management strategy based on the analysis result to obtain an intermediate vehicle operation and energy consumption management strategy;

[0014] A passenger demand response module is configured to fine-tune the intermediate vehicle operation and energy consumption management strategy based on the passenger's demand and preference for the vehicle cabin environment through a dynamic programming algorithm;

[0015] The execution and feedback module is configured to convert the vehicle operation and energy consumption management strategy obtained after fine-tuning into a control instruction, and execute the control operation according to the control instruction.

[0016] In a third aspect, based on the same inventive concept, the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the first aspect is implemented.

[0017] In a fourth aspect, based on the same inventive concept, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0018] Compared with the prior art, the urban rail vehicle coordination method, system, electronic device and storage medium described in this application have the following beneficial effects:

[0019] (1) The urban rail vehicle coordination method described in this embodiment is based on real-time collection and analysis of external environment data and vehicle operation data. By using intelligent algorithms for comprehensive analysis, the vehicle operation and energy consumption management strategies are dynamically adjusted, which significantly improves the energy efficiency of vehicle operation and reduces unnecessary energy consumption, thereby effectively achieving the goal of energy conservation and emission reduction, reducing the operating cost of the urban rail transit system, and having a positive impact on environmental protection.

[0020] (2) The urban rail vehicle coordination method described in this embodiment combines the historical vehicle operation data and historical environmental data to conduct real-time evaluation of parameters such as the temperature in the car, thereby adjusting the vehicle's operating status to optimize passenger comfort. At the same time, the passenger demand response module collects and analyzes passengers' needs and preferences for the car environment, and continues to fine-tune the vehicle operation and energy consumption management strategies to ensure that while meeting the energy conservation and emission reduction requirements, the passenger's comfort needs are met to the greatest extent possible, thereby improving the passenger's travel experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0022] Figure 1 This is a flow chart of the urban rail vehicle coordination method described in an embodiment of the present application;

[0023] Figure 2 This is a schematic diagram of the structure of the urban rail vehicle cooperative system described in an embodiment of the present application;

[0024] Figure 3 This is a schematic diagram of the hardware structure of the electronic device described in the embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0026] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0027] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0028] See also Figure 1 As shown, this embodiment provides a method for urban rail vehicle coordination, which specifically includes the following steps:

[0029] Step S101, obtaining the current operation data of the vehicle, evaluating the energy efficiency and passenger comfort of the vehicle based on the historical operation data and historical environmental data of the vehicle, and preliminarily determining the vehicle operation and energy consumption management strategy;

[0030] Specifically, in this embodiment, various operating status data of the vehicle are collected in real time through high-precision sensors installed on the vehicle, including but not limited to operating speed, traction, braking force, cabin temperature, humidity, vibration conditions, motor efficiency, etc. The Kalman filter algorithm is used to analyze the collected vehicle status data in real time to evaluate the current operating status of the vehicle. The calculation formula is: in, is the posterior state estimate at time k, is the prior state estimate at time k, K k is the Kalman gain, z k is the observed value at time k, H k is the observation matrix.

[0031] Combined with the vehicle's historical operating data and historical environmental data, a comprehensive evaluation of the vehicle's energy efficiency and passenger comfort is conducted, and a preliminary vehicle operation and energy management strategy is determined.

[0032] Step S102, obtaining current environmental data, fusing the obtained current environmental data with the current vehicle operation data, and performing comprehensive analysis, dynamically adjusting the preliminary vehicle operation and energy consumption management strategy based on the analysis results to obtain an intermediate vehicle operation and energy consumption management strategy;

[0033] Specifically, in this embodiment, environmental data and vehicle operation data are obtained, wherein the environmental data includes real-time weather information, road conditions, temperature and humidity and other environmental parameters, and the vehicle operation data includes vehicle operating speed, traction, braking force, cabin temperature and other state parameters, and the received data are fused to ensure the accuracy and consistency of the data. At the same time, necessary preprocessing is performed on the data, such as data cleaning, denoising and calibration, to eliminate outliers and noise in the data.

[0034] The particle swarm optimization algorithm (PSO) is used to conduct a comprehensive analysis of the fused data set. The algorithm randomly initializes a group of particles, each particle represents a potential vehicle operation and energy consumption management strategy. The particle swarm optimization algorithm evaluates the fitness of each particle according to the input data set, that is, the effect of each potential solution. The algorithm iteratively updates the speed and position of each particle to find the optimal solution. Specifically, the speed and position of the particle are adjusted according to the speed update formula and the position update formula to gradually approach the global optimal solution. The speed update formula is: The position update formula is: in, and are the velocity and position of particle i in the dth dimension in the k+1th iteration, ω is the inertia weight, c1 and c2 are the individual learning factor and the social learning factor, r1 and r2 are random numbers, is the historical optimal position of particle i, The historical optimal position of the group is output, and the final global optimal position is used as the intermediate vehicle operation and energy consumption management strategy.

[0035] In addition, it should be noted that the environmental data collected in this embodiment is obtained with the help of the current mature environmental perception module. Such a module not only integrates the weather forecast system, road condition monitoring sensors and temperature and humidity sensors, but also further expands the diversified environmental data collection functions such as air quality monitoring and light intensity monitoring. These sensors are distributed along the urban rail transit line, and collect and process external environmental data in real time, including temperature, humidity, wind speed, visibility, road wetness, air quality index, etc., to provide comprehensive and accurate environmental information for subsequent vehicle status evaluation and operation strategy adjustment. The collected raw data is cleaned, denoised and calibrated, and then stored in time series, and in-depth analysis is performed using advanced data analysis technology to extract key environmental parameters that have an important impact on vehicle operation and energy consumption management. These parameters are not only used to evaluate the impact of the current environment on vehicle operation, but also provide a scientific basis for optimizing vehicle operation strategies.

[0036] Step S103: fine-tuning the intermediate vehicle operation and energy consumption management strategy based on the passenger's needs and preferences for the vehicle cabin environment and through a dynamic programming algorithm;

[0037] Specifically, in this embodiment, passengers' needs and preference information for the cabin environment are collected through various channels (such as passenger surveys, social media analysis, mobile application feedback, etc.), the collected data is organized and analyzed, and the main demand points and concerns are identified, such as temperature preferences, air quality requirements, noise control, etc. According to the results of the passenger demand analysis, the formulated intermediate vehicle operation and energy consumption management strategies are fine-tuned. By adopting a dynamic programming algorithm, the module can adjust the cabin environment control strategy in real time to meet the personalized needs of passengers and improve passenger satisfaction.

[0038] Furthermore, the intermediate vehicle operation and energy consumption management strategy is used as the initial solution to define the state space, including the vehicle's location, time, passenger demand, and energy consumption level. Based on the real-time passenger demand, the feasible decision set in each state is determined. The dynamic programming algorithm is applied to traverse all states and decisions, and the optimal solution for each state is calculated and recorded. The calculation formula is: Among them, J(s t ) is in state s t The optimal value under t ) is in state s t The feasible decision set, g(s t ,a t ) is in state s t Take decision a t The instant cost, γ is the discount factor, p(s t+1 ∣s t ,a t ) is from state st Take decision a t Transfer to state s t+1 The probability of S is the state space. According to the results of the dynamic programming algorithm, the intermediate vehicle operation and energy consumption management strategies are fine-tuned, and the fine-tuned vehicle operation and energy consumption management strategies are output for system execution.

[0039] Step S104: convert the vehicle operation and energy consumption management strategy obtained after fine-tuning into a control instruction, and execute the control operation according to the control instruction.

[0040] Specifically, in this embodiment, the fine-tuned vehicle operation and energy consumption management strategy is converted into specific control instructions, which are sent to the vehicle control system for execution. The vehicle operation status and energy consumption are monitored in real time to evaluate whether the execution effect has achieved the expected goal. Based on the execution effect monitoring results, the system is feedback analyzed and optimized.

[0041] This embodiment uses the PID control algorithm to convert the fine-tuned vehicle operation and energy consumption management strategy into a specific control instruction, which is sent to the vehicle control system for execution. Specifically, the current execution effect data is received, the error e(t) between the set value and the current execution effect data is calculated, and the control amount u(t) is calculated according to the PID control algorithm. The calculation formula is: Among them, K p , K i and K d They are respectively the preset proportional coefficient, integral coefficient and differential coefficient, and the control quantity u(t) is output to the vehicle control system to adjust the execution strategy.

[0042] The method described in this embodiment collects and analyzes external environmental data and vehicle operation data in real time, and dynamically adjusts vehicle operation and energy consumption management strategies by using intelligent algorithms for comprehensive analysis, thereby significantly improving the energy efficiency of vehicle operation and reducing unnecessary energy consumption, thereby effectively achieving the goal of energy conservation and emission reduction, reducing the operating costs of urban rail transit systems, and having a positive impact on environmental protection.

[0043] By combining the vehicle's historical operating data and historical environmental data, parameters such as the temperature in the vehicle cabin are evaluated in real time, thereby adjusting the vehicle's operating status to optimize passenger comfort. At the same time, the passenger demand response module continues to fine-tune the vehicle's operation and energy consumption management strategies by collecting and analyzing passengers' needs and preferences for the cabin environment, ensuring that while meeting energy-saving and emission-reduction requirements, it also maximizes passenger comfort needs and improves passengers' travel experience.

[0044] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0045] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the embodiment of the present application also provides an urban rail vehicle cooperative system.

[0046] like Figure 2 As shown, the urban rail vehicle cooperative system includes:

[0047] The vehicle status monitoring module 11 is configured to obtain the current operation data of the vehicle, evaluate the energy efficiency and passenger comfort of the vehicle based on the historical operation data and historical environmental data of the vehicle, and preliminarily determine the vehicle operation and energy consumption management strategy;

[0048] The collaborative decision-making module 12 is configured to obtain current environmental data, fuse the obtained current environmental data with the current operation data of the vehicle, and perform comprehensive analysis, and dynamically adjust the preliminary vehicle operation and energy consumption management strategy based on the analysis results to obtain the intermediate vehicle operation and energy consumption management strategy;

[0049] A passenger demand response module 13 is configured to fine-tune the intermediate vehicle operation and energy consumption management strategy based on the passenger's demand and preference for the cabin environment and through a dynamic programming algorithm;

[0050] The execution and feedback module 14 is configured to convert the fine-tuned vehicle operation and energy consumption management strategy into a control instruction and execute the control operation according to the control instruction.

[0051] For the convenience of description, the above system is described by dividing the functions into various modules. Of course, when implementing the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0052] The system of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0053] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in any of the above embodiments is implemented.

[0054] Figure 3 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0055] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0056] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0057] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0058] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0059] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0060] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0061] The electronic device of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0062] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in any of the above embodiments.

[0063] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0064] The computer instructions stored in the storage medium of the above embodiments are used to enable the computer to execute the method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0065] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0066] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0067] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0068] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

Claims

1. A method for coordinating urban rail vehicles, characterized in that: include: Obtain the current operation data of the vehicle, evaluate the vehicle's energy efficiency and passenger comfort based on the vehicle's historical operation data and historical environmental data, and preliminarily determine the vehicle's operation and energy management strategies; Acquire current environment data, fuse the acquired current environment data with the current operation data of the vehicle, and conduct comprehensive analysis, and dynamically adjust the preliminary vehicle operation and energy consumption management strategy based on the analysis results to obtain an intermediate vehicle operation and energy consumption management strategy; According to the needs and preferences of passengers for the cabin environment, the intermediate vehicle operation and energy consumption management strategy is fine-tuned through a dynamic programming algorithm; The vehicle operation and energy consumption management strategies obtained after fine-tuning are converted into control instructions, and control operations are performed according to the control instructions.

2. The method according to claim 1, characterized in that The acquisition of the current operation data of the vehicle, the evaluation of the energy efficiency and passenger comfort of the vehicle based on the historical operation data and historical environmental data of the vehicle, and the preliminary determination of the vehicle operation and energy consumption management strategy include: Acquire the vehicle's current operating data in real time, and use the Kalman filter algorithm to analyze the acquired vehicle's current operating data in real time to evaluate the vehicle's real-time operating status; Combined with the vehicle's historical operating data and historical environmental data, a comprehensive evaluation of the vehicle's energy efficiency and passenger comfort is conducted, and a preliminary vehicle operation and energy management strategy is determined.

3. The method according to claim 1, characterized in that The acquiring of current environment data, fusing the acquired current environment data with the current operation data of the vehicle, and conducting a comprehensive analysis, and dynamically adjusting the preliminary vehicle operation and energy consumption management strategy based on the analysis result to obtain an intermediate vehicle operation and energy consumption management strategy, includes: Fusing the current environment data with the current operation data of the vehicle, and preprocessing the fused data, wherein the preprocessing includes data cleaning, denoising and calibration; The preprocessed fusion data is comprehensively weighed and optimized through the particle swarm optimization algorithm. The speed and position of each particle are iteratively updated to gradually approach the global optimal solution. The final output global optimal position is used to dynamically adjust the preliminary vehicle operation and energy consumption management strategy to obtain the intermediate vehicle operation and energy consumption management strategy.

4. The method according to claim 1, characterized in that: The intermediate vehicle operation and energy consumption management strategy is fine-tuned based on the passenger's needs and preferences for the cabin environment and through a dynamic programming algorithm, including: Taking the intermediate vehicle operation and energy consumption management strategy as the initial solution, defining the state space, and determining the decision set in each state according to the real-time passenger demand and preference, applying the dynamic programming algorithm to traverse all states and decisions, and calculating the optimal solution for each state, wherein the state space includes the vehicle's location, time, passenger demand, and energy consumption level; According to the optimal solution result, the intermediate vehicle operation and energy consumption management strategy is fine-tuned to obtain a fine-tuned vehicle operation and energy consumption management strategy.

5. The method according to claim 4, characterized in that The dynamic programming algorithm formula is: J(s t )=min at∈A(st) [g(s t ,a t )+γ∑ st+1∈S p(s t+1 ∣s t ,a t )J(s t+1 )]; Among them, J(s t ) means in state s t The optimal value under t ) means in state s t The feasible decision set, g(s t ,a t ) means in state s t Take decision a t The instant cost, γ represents the discount factor, p(s t+1 ∣s t ,a t ) indicates that from state s t Take decision a t Transfer to state s t+1 The probability of , S represents the state space.

6. The method according to claim 1, characterized in that The vehicle operation and energy consumption management strategy obtained after fine-tuning is converted into a control instruction, and a control operation is performed according to the control instruction, including: The fine-tuned vehicle operation and energy consumption management strategies are converted into specific control instructions and sent to the vehicle control system for execution. The vehicle operation status and energy consumption are monitored in real time to evaluate whether the execution effect has achieved the expected goal. Based on the execution effect monitoring results, the PID control algorithm is used to conduct feedback analysis and optimization adjustments to the system.

7. The method according to claim 6, characterized in that Get the current execution effect data, calculate the error e(t) between the set value and the current execution effect data, and calculate the control amount u(t) according to the PID control algorithm. The calculation formula is: Among them, K p , K i and K d They are the preset proportional coefficient, integral coefficient and differential coefficient respectively.

8. An urban rail vehicle cooperative system, characterized in that: include: A vehicle status monitoring module is configured to obtain current vehicle operation data, evaluate the vehicle's energy efficiency and passenger comfort based on historical vehicle operation data and historical environmental data, and preliminarily determine vehicle operation and energy management strategies; The collaborative decision-making module is configured to obtain current environmental data, fuse the obtained current environmental data with the current operation data of the vehicle, and perform comprehensive analysis, and dynamically adjust the preliminary vehicle operation and energy consumption management strategy based on the analysis result to obtain an intermediate vehicle operation and energy consumption management strategy; A passenger demand response module is configured to fine-tune the intermediate vehicle operation and energy consumption management strategy based on the passenger's demand and preference for the vehicle cabin environment through a dynamic programming algorithm; The execution and feedback module is configured to convert the vehicle operation and energy consumption management strategy obtained after fine-tuning into a control instruction, and execute the control operation according to the control instruction.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium, characterized in that: in, The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 7.

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