CN114580191A - Evaluation system and method suitable for locomotive automatic driving - Google Patents

Evaluation system and method suitable for locomotive automatic driving Download PDF

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CN114580191A
CN114580191A CN202210252724.XA CN202210252724A CN114580191A CN 114580191 A CN114580191 A CN 114580191A CN 202210252724 A CN202210252724 A CN 202210252724A CN 114580191 A CN114580191 A CN 114580191A
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evaluation
data
locomotive
automatic driving
curve
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周文伟
刘勇
江帆
沈凯
赵云伟
李铁兵
吴春玉
陈佳晖
罗帅
唐伟
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Zhuzhou CRRC Times Electric Co Ltd
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Abstract

The invention provides an evaluation system and a method suitable for locomotive automatic driving, wherein the evaluation system comprises: the locomotive automatic driving system is used for providing operation data of locomotive automatic driving, the big data platform comprises a database and a data analysis and evaluation device, and the dynamics simulation system is connected with the locomotive automatic driving system; the dynamic simulation system is used for performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive; the data analysis and evaluation device is used for evaluating the safety and the rationality according to the safety evaluation criterion, the rationality evaluation criterion and the operation data, evaluating the stationarity according to the stationarity evaluation rule and the car coupler force variation curve and obtaining an evaluation result; the database is used for storing the operation data and the evaluation result. The invention can carry out all-around and all-around analysis on the running condition of the locomotive automatic driving system in the aspects of macro and micro, and has wide application prospect.

Description

Evaluation system and method suitable for locomotive automatic driving
Technical Field
The invention belongs to the technical field of big data, and particularly relates to an evaluation system and method suitable for locomotive automatic driving.
Background
With the development of big data technology and the continuous development of modern information technology, the world has already crossed the internet + big data era. Big data is changing people's thinking, production and life style deeply, and a new round of industry and technology revolution is about to be started. The deep integration of big data with various industries will generate unprecedented social and commercial value. And the national-level big data industry is comprehensively developed, so that an integrated big data industry innovation chain is formed, and the quick and stable growth of the big data industry is promoted. With the development of big data cloud computing technology, the application field in the future must be expanded in order, and brand new appearances are brought to the production and life of human beings. The dramatic progress made possible by artificial intelligence was not to mention the result of the great data development over the years. The nature of big data is massive, multidimensional, multiform data. Due to the development of various sensors and data acquisition technologies, the sensors begin to have massive data which is difficult to imagine in the past, and meanwhile, deep and detailed data also begin to be possessed in a certain field. Big data also affects the development of a system accompanying automatic driving of a locomotive in a new field, and an evaluation system is a system for serving automatic driving of the locomotive based on a big data technology platform.
Relevant technical indexes of automatic driving operation of the locomotive are not clearly specified by relevant standards, and field application tests are usually counted by manually analyzing recorded data: the coverage rate, the vehicle control rate, the energy consumption index, the impulse, the comfort level, the high efficiency and the like of the test scene consume a large amount of manpower, and meanwhile, the accuracy, the integrity and the uniformity of data cannot be guaranteed by artificially checking the problems and counting related indexes. At present, each road bureau is temporarily provided with a ground system for supporting the data analysis and statistical capability of the automatic driving operation quality of the locomotive. The verification work and the popularization work of the follow-up project are influenced due to the lack of relevant data bases for data verification, analysis and the like of the follow-up project.
Disclosure of Invention
The invention provides an evaluation system and method suitable for locomotive automatic driving, and aims to solve the problem that the accuracy, integrity and uniformity of data cannot be guaranteed by manual automatic driving evaluation in the prior art.
Based on the above purpose, an embodiment of the present invention provides an evaluation system suitable for locomotive automatic driving, including: the locomotive automatic driving system is used for providing operation data of locomotive automatic driving, the big data platform comprises a database and a data analysis and evaluation device, and the dynamics simulation system is connected with the locomotive automatic driving system and the dynamics simulation system; the database at least comprises a data storage library and an evaluation criterion library; the dynamic simulation system is used for performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive; the evaluation criterion library comprises: a safety evaluation criterion, a stability evaluation rule and a rationality evaluation criterion; the data analysis and evaluation device is used for evaluating the safety and the rationality according to the safety evaluation criterion, the rationality evaluation criterion and the operation data, evaluating the stationarity according to the stationarity evaluation rule and the car coupler force variation curve and obtaining an evaluation result; the database is used for storing the operation data and the evaluation result.
Optionally, the database further includes a data analysis configuration library, and the data analysis and evaluation device performs data analysis on the operating data according to a preset data analysis configuration library by using a data analysis and evaluation software method, and stores the operating data in the data storage library.
Optionally, the data analysis and evaluation device is further configured to: programming and datamation are carried out according to railway specifications to generate the safety evaluation criterion; and obtaining a speed running curve of a standard train running model by applying an intelligent algorithm software method and a standard train intelligent software method to serve as the rationality evaluation criterion.
Optionally, the data analysis and evaluation device is configured to: generating the standard train operation model by applying an intelligent algorithm software method according to manual driving manipulation operation data of the excellent drivers stored in a database; and acquiring a simulation curve of the standard train operation model running according to a real environment by applying a standard train intelligent software method, and taking the simulation curve as the speed operation curve of the standard train operation model.
Optionally, the dynamic simulation system is configured to: extracting operating parameters related to coupler force calculation according to the operating data, wherein the operating parameters related to coupler force calculation at least comprise: air braking amount, gradient data, curve data, tunnel data, train marshalling data and running speed; and performing dynamic simulation and coupler force calculation according to the operation parameters to obtain a coupler force variation curve of the locomotive.
Optionally, the big data platform further includes a statistics display module, configured to: counting the evaluation results of one or more locomotives in different time periods from a time dimension; counting the evaluation results of the locomotives of each road bureau, line or each section from the position dimension; and counting the accurate parking position distribution and the interval time distribution of the automatic driving system of a single station track from the accuracy probability distribution.
Optionally, the statistics presentation module is further configured to: receiving a query request input by a user; and responding to the query request pair, and counting and displaying the evaluation results of one or more locomotives from a time dimension, a position dimension or an accuracy probability distribution.
Optionally, the evaluation system further includes a transmission system, connected to the automatic driving system and the big data platform, for transmitting the operation data of the automatic driving system and the locomotive to the big data platform.
Based on the same inventive concept, the embodiment of the invention also provides an evaluation method suitable for locomotive automatic driving, which is applied to the evaluation system suitable for locomotive automatic driving, and the method comprises the following steps: receiving operation data acquired in the automatic driving process of the locomotive transmitted by an automatic driving system of the locomotive; performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive; and evaluating the safety and the rationality according to a safety evaluation criterion and a rationality evaluation criterion in an evaluation criterion library and the operation data, and evaluating the stationarity according to a stationarity evaluation rule in the evaluation criterion library and the car coupler force variation curve to obtain an evaluation result.
Optionally, the method further comprises: counting the evaluation results of one or more locomotives in different time periods from a time dimension; counting the evaluation results of each locomotive of each road bureau, line or each section from the position dimension; and counting the accurate parking position distribution and the interval time distribution of the automatic driving system of a single station track from the accuracy probability distribution.
The beneficial effects of the invention are: from the above, it can be seen that the evaluation system and method provided by the embodiments of the present invention are suitable for automatic driving of a locomotive, and the evaluation system includes: the method comprises the following steps: the locomotive automatic driving system is used for providing operation data of locomotive automatic driving, the big data platform comprises a database and a data analysis and evaluation device, and the dynamics simulation system is connected with the locomotive automatic driving system and the dynamics simulation system; the database at least comprises a data storage library and an evaluation criterion library; the dynamic simulation system is used for performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive; the evaluation criterion library comprises: a safety evaluation criterion, a stability evaluation rule and a rationality evaluation criterion; the data analysis and evaluation device is used for evaluating the safety and the rationality according to the safety evaluation criterion, the rationality evaluation criterion and the operation data, evaluating the stationarity according to the stationarity evaluation rule and the car coupler force variation curve and obtaining an evaluation result; the database is used for storing the operation data and the evaluation result, can perform all-around and all-around analysis on the operation condition of the automatic driving system of the locomotive in the aspects of macro and micro, and has wide application prospect.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of an evaluation system suitable for locomotive autopilot in an embodiment of the invention;
FIG. 2 is a schematic diagram of a standard train operating curve generation in an embodiment of the present invention;
FIG. 3 is a schematic illustration of an operating speed profile of a locomotive in an embodiment of the present invention;
FIG. 4 is a schematic diagram of a coupler force variation curve in an embodiment of the present invention;
FIG. 5 is a schematic diagram of an evaluation method of the evaluation system in an embodiment of the present invention;
fig. 6 is a schematic flow chart of an evaluation method suitable for locomotive automatic driving according to an embodiment of the present invention.
Detailed Description
For the purpose of promoting a better understanding of the objects, aspects and advantages of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings.
It is to be noted that technical terms or scientific terms used in the embodiments of the present invention should have a general meaning as understood by one having ordinary skill in the art to which the present disclosure belongs, unless otherwise defined. The use of "first," "second," and similar language in the embodiments of the present invention does not denote any order, quantity, or importance, but rather the terms "first," "second," and similar language are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
The embodiment of the invention provides an evaluation system suitable for locomotive automatic driving. As shown in fig. 1, the evaluation system for automatic driving of a locomotive comprises: the locomotive automatic driving system is used for providing operation data of locomotive automatic driving, the big data platform comprises a database and a data analysis and evaluation device, and the dynamics simulation system is connected with the locomotive automatic driving system and the dynamics simulation system; the database includes at least a data repository and a library of evaluation criteria.
The dynamic simulation system is used for performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive; the evaluation criterion library comprises: a safety evaluation criterion, a stability evaluation rule and a rationality evaluation criterion; the data analysis evaluation device is used for evaluating the safety and the rationality according to the safety evaluation criterion, the rationality evaluation criterion and the operation data, evaluating the stationarity according to the stationarity evaluation rule and the car coupler force variation curve and obtaining an evaluation result; the database is used for storing the operation data and the evaluation result.
The evaluation system analyzes data sent by the locomotive automatic driving system through a configurable data analysis configuration library, and stores the data into a data storage library according to a regular or non-regular storage mode, so as to provide a data source for subsequent data statistics and evaluation. The evaluation system is a special application system developed based on a big data cluster/platform and can be divided into an evaluation system and a statistical system. The automatic driving evaluation system of the locomotive covers all time periods of driver operation, and comprises 4 stages of preparation operation in a garage, ex-garage shunting operation, on-line operation and in-garage shunting operation. And (3) setting evaluation item points under each operation division item, setting subdivided evaluation items and evaluation standards under each evaluation item point, and setting action (occurrence or non-occurrence), size (speed, moment and position) and time (duration) dimensions to measure the correctness of the items by the evaluation standards. The collection of each evaluation item, and criterion is referred to as an evaluation criterion. Each item is classified into three grades of severity, warning, and cue according to the importance of the evaluation-related matter. The evaluation system should divide the safety, rationality and stability evaluation according to the item information.
With continued reference to fig. 1, the evaluation system further includes a transmission system coupled to the autopilot system and the big data platform for transmitting operational data associated with the locomotive autopilot system to the big data platform.
The evaluation system applicable to locomotive automatic driving provided by the embodiment of the invention can be divided into online evaluation and offline evaluation according to different data sources of the locomotive automatic driving system. And the data adopted by the off-line evaluation is recorded data of the field operation of the automatic driving system of the locomotive. The online evaluation is mainly used for laboratory tests, the adopted data is real-time data of a locomotive automatic driving system laboratory, the principle and the function of the online evaluation are consistent with those of offline evaluation, and the online evaluation is different from the real-time data processing and the partitioned storage of evaluation results. The embodiment of the invention utilizes the big data cluster/platform to build the automatic driving evaluation system of the locomotive, and develops corresponding software and a database on the big data cluster to adapt to the application of the evaluation of the automatic driving system of the locomotive. The system consists of system hardware, a database and software. The evaluation system realizes the whole process of the evaluation method according to the basic flow of 'data input-data storage-driving evaluation-statistical display'. The evaluation system software is divided into software modules such as data analysis, evaluation software, standard train intelligent software, intelligent algorithm software, evaluation system display and the like. The locomotive automatic driving system comprises a vehicle-mounted locomotive automatic driving system and a laboratory locomotive automatic driving system. The brain is the brain for controlling the automatic driving of the locomotive, provides online data and offline recorded data for an evaluation system, and is a data source of the evaluation system. The dynamics simulation system provides longitudinal, transverse and vertical coupler acting force calculation results of the locomotive automatic driving system and provides a basis for stability evaluation. The big data platform is the basic hardware and system architecture foundation of the automatic driving evaluation system of the locomotive. The evaluation criteria library is a set of criteria used for locomotive autopilot evaluation.
In the embodiment of the invention, the database also comprises a data analysis configuration library. And the data analysis and evaluation device analyzes the data of the running data according to a preset data analysis configuration library by using a data analysis and evaluation software method and stores the data into the data storage library. The data analysis and evaluation device is also used for analyzing and evaluating the data; and programming and digitizing according to the railway specification to generate the safety evaluation criterion. The method is mainly characterized in that the rules of national railway operation rules, running rules, technical rules and other rules are programmed and digitalized, and the rules are judged through software rules, so that whether the violation behaviors exist in the operation process of the automatic locomotive driving system can be found and judged. For example, when the freight train speed specified in the railway locomotive operating rules is below 15km/h, the train brake should not be relieved; the speed of the heavy-duty freight train is below 30km/h, the contents such as train braking should not be relieved are used as evaluation criteria, and the evaluation system judges that the locomotive automatic driving system has a serious-grade safety event when the speed condition is lower than the relief limiting speed when the locomotive automatic driving system stops under the relief limiting speed condition by setting two evaluation items and items of 'normal load + relief limiting speed' and 'normal load + relief limiting speed'.
The data analysis and evaluation device also obtains a speed running curve of a standard train running model by using an intelligent algorithm software method and a standard train intelligent software method as the rationality evaluation criterion. Rationality includes, but is not limited to, whether the speed is controlled reasonably, whether the departure process is reasonable, whether the stop process is reasonable, etc. Optionally, the data analysis and evaluation device is configured to: according to excellence stored in databaseGenerating the standard train operation model by applying an intelligent algorithm software method to the manual driving operation data of the driver; and acquiring a simulation curve of the standard train operation model operating according to a real environment by applying a standard train intelligent software method, and taking the simulation curve as the speed operation curve of the standard train operation model. For example, the method includes the steps of correcting basic resistance operation parameters (A, B, C values) and air brake force parameters by using manual driving operation data of excellent drivers stored in a big data platform and using an Artificial Intelligence (AI) algorithm such as machine learning and model training, forming a standard train model by using parameters and formulas obtained by correcting and training the AI algorithm, using a simulation curve of the standard train model running according to a real environment as a standard train running curve, using the curve as an evaluation standard of train running, and comparing whether the curve of actual automatic driving running is reasonable (including section time, high speed and the like) so as to guide the improvement of an automatic driving technology. Referring to fig. 2, a standard train model is constructed by correcting the basic resistance operation parameter and the air brake force parameter using an AI algorithm according to a plurality of operation speed curves of manual driving manipulation of excellent drivers stored in a big data platform. The standard model of the train comprises a basic resistance model and an air braking force model. The basic drag model is w'0＝A+Bv+Cv2The air braking force model is
Figure BDA0003547429040000051
Wherein A, B, C is the weight, v is the running speed, bcIs the unit braking force of a common train, betacFor the purpose of the service braking coefficient,
Figure BDA0003547429040000052
to convert the coefficient of friction, θhAnd b is train braking rate and train unit braking force during emergency braking. And simulating by applying the train standard model according to the real environment to obtain a simulation curve, namely a standard train operation curve, and performing reasonability evaluation by taking the simulation curve as a reasonability evaluation criterion.
In an embodiment of the invention, the dynamics simulation system is configured to: extracting operating parameters related to coupler force calculation according to the operating data, wherein the operating parameters related to coupler force calculation at least comprise: air braking amount, gradient data, curve data, tunnel data, train marshalling data and running speed; and performing dynamic simulation and coupler force calculation according to the operation parameters to obtain a coupler force variation curve of the locomotive. And finally, carrying out stability evaluation according to the coupler force change curve and the stability evaluation rule. For example, the automatic driving actual operation data of a large data platform, such as the operation speed curve in fig. 3, is utilized to extract the operation parameters related to the coupler force calculation and transmit the operation parameters to a power vehicle simulation system, the coupler force calculation is carried out to obtain a single-pass train operation coupler force change curve, and the stability of the train is evaluated by comparing and calculating the coupler force curve value with the standard amplitude limit value. As shown in fig. 4, the obtained coupler force variation curve is compared with a coupler force limiting value to calculate, and stability evaluation is performed. The evaluation results can be divided into: whether there is an overrun; maximum force of single-trip car coupler; maximum coupler force change per unit time, etc. The coupler force limiting value comprises an upper limit and a lower limit, the upper limit is 900kN in FIG. 4, and the lower limit is-900 kN. In the embodiment of the present invention, the coupler force limiting value may be set according to needs, and is not particularly limited, for example, the coupler force limiting value is set according to a national standard, and a general item of the coupler force limiting value is a "longitudinal coupler force safety control limiting value". Operational parameters associated with coupler force calculation include traction/electric power, air brake amount, grade data, curve data, tunnel data, train consist data, operating speed, etc., and train consist data includes locomotive model, number of vehicles, consist length, load, gross weight, etc. The embodiment of the invention can also compare the car coupler force data of a plurality of locomotives, mainly compares the maximum value with the variation maximum value, screens out the optimal control curve to guide the technical promotion of the automatic driving system by analyzing the car coupler force of the operation data of the plurality of locomotives.
In an embodiment of the present invention, the big data platform further includes a statistics display module, configured to: counting the evaluation results of one or more locomotives in different time periods from a time dimension; counting the evaluation results of each locomotive of each road bureau, line or each section from the position dimension; and counting the accurate parking position distribution and the interval time distribution of the automatic driving system of a single station track from the accuracy probability distribution.
The evaluation system is used for carrying out statistical combination according to the time, position and precision probability distribution and the like according to the evaluation item results, efficiency, benefits, coverage rate and other indexes and the like for displaying to the user. The statistical system relates to various aspects in the operation process and is mainly used for mastering whether each index of automatic driving of the locomotive meets the requirements of customers (road bureaus, technology and after sales), design and management. The statistical information should be calculated according to different dimensions, and one trip, multiple trips, one week, multiple weeks, one month, multiple months, one year, multiple years and custom time periods need to be counted from the time dimension. From the position dimension, statistics calculation is carried out on each road bureau, a machine service section, a line, an uplink and a downlink, each signal machine interval, each station (in-out station signal machine), a phase separation area, a through test area, a temporary speed limit area and the like. For the evaluation system, the statistics of times, distribution, coverage rate, accumulation and time are needed, and the display form is displayed by adopting curves, pie charts, bar charts, time lines, electronic maps and the like. The accurate parking position distribution, the interval time distribution and the like of the locomotive automatic driving system of a single station track can be counted from the accuracy probability distribution. The users facing the statistical system comprise a road bureau, after sales, technical personnel and the like, and various personnel need to set different access authorities and the access authorities can be configured.
The statistics display module is further configured to: receiving a query request input by a user; and responding to the query request pair, and counting and displaying the evaluation results of one or more locomotives from a time dimension, a position dimension or an accuracy probability distribution. The evaluation system distinguishes the contents of the arrangement data storage according to, but not limited to, train number, locomotive model number, time, route, road bureau and the like, counts the evaluation results in the data storage, and displays the evaluation statistical results through a web end or a client end for a user to use. The user can be a road administration manager, a road administration locomotive automatic driving operator, a locomotive automatic driving developer and the like.
Referring to fig. 5, the database includes a data parsing configuration library, a data storage library, and an evaluation rule library. The operation data from the automatic driving system of the locomotive is processed by data analysis and evaluation software and then stored in a data storage library, evaluation item points and standards are set according to railway specifications, and the evaluation criteria are obtained through programming and datamation and are stored in an evaluation rule base. And applying intelligent algorithm software to manual driving operation data of excellent drivers stored in a data storage bank to generate a standard train operation model, applying the standard train intelligent software to operate according to a real environment according to the standard train operation model, acquiring a speed operation curve of the standard train operation model, using the speed operation curve as a rationality evaluation criterion, and storing the speed operation curve in an evaluation rule base. A dynamic simulation system is applied to extract data related to the car coupler force in the operation data, a car coupler force change curve is calculated, an optimal curve is screened as guidance according to the car coupler force change curves, and stability evaluation criteria can be obtained and stored in an evaluation rule base. When the operation data of any locomotive needs to be evaluated, the operation data is analyzed and processed by applying data analysis and evaluation software, then safety, smoothness and rationality evaluation is carried out according to each evaluation rule in the evaluation rule base, and the obtained evaluation result is stored in a data storage bank. And when the road bureau personnel or the designer need to check the evaluation result, the application evaluation system display software responds to the checking request and acquires the evaluation result from the data storage bank for statistics and display.
The evaluation system suitable for locomotive automatic driving of the embodiment of the invention forms a data storage library for evaluating the locomotive automatic driving operation quality by analyzing and organizing the locomotive automatic driving operation data, forms an evaluation rule by combining methods such as ground big data intelligent analysis and the like, comprehensively evaluates the safety, the reasonability and the stability of the locomotive automatic driving system operation, simultaneously counts various evaluation indexes including but not limited to trip times, energy consumption, vehicle control rate, operation mileage, station coverage rate and the like, and displays the statistics and evaluation results. The automatic driving evaluation system of the locomotive is developed to completely replace manual data analysis and analysis, a statistical data report is formed and displayed through a web end or a special client, a foundation is laid for rapid popularization of subsequent project tests, and the development of the projects can be popularized and applied to a ground road bureau after being successful. The evaluation system performs all-around and all-around analysis and judgment on the operation condition of the locomotive automatic driving system in macro and micro aspects, and provides data support for developers and managers of the locomotive automatic driving system; the method is developed for the first time aiming at the evaluation of the automatic driving system of the locomotive; has prospective and wide application prospect. The evaluation method comprises online real-time evaluation and offline evaluation; the recorded data can be used for carrying out off-line evaluation and data statistical analysis on the field operation condition of automatic driving of the locomotive; the real-time data can be utilized to evaluate the laboratory condition of locomotive automatic driving in real time; basically covers all the applications of locomotive automatic driving and has good utilization value. The evaluation system is mainly used for comprehensively analyzing the automatic driving system of the locomotive from the aspects of safety, stability and rationality; the evaluation basis and the effect of the key points of safety, stability and rationality are designed. Aiming at the safety evaluation, the rules are judged by software rules mainly by programming and digitizing the regulation systems such as national railway operation regulations, running regulations, technical regulations and the like, so that whether the operation process of the automatic driving system of the locomotive has illegal behaviors or not can be found and judged, and a subsequent improvement method is provided for a development unit of the automatic driving system of the locomotive and an operation management unit of a locomotive depot. And aiming at stability evaluation, judging the stability by accessing a dynamics software and calculating whether the transverse and longitudinal impulse magnitude has a mutation or exceeds a standard value through a dynamics model. Aiming at the rationality evaluation, a standard train operation model (a model driver model) is generated by utilizing a big data platform and a machine learning method, the operation result of the standard train operation model is used as the basic standard of an evaluation system, the statistical distribution is used as the standard evaluation basis, and the high confidence coefficient is achieved. The evaluation system also designs a statistical system (method) of the locomotive automatic driving system, and statistical items cover indexes of each scene control of the locomotive automatic driving system, such as parking positions, interval technical speeds, interval operation scales, operation circuit diagrams and the like. The method can obtain evaluation statistical reports of different periods according to the evaluation results of periods such as single-pass, weekly, monthly, annual and the like, and enable locomotive automatic driving operation manufacturers to intuitively feel the operation condition of the locomotive automatic driving system in an evaluation statistical report mode, and can also display the operation condition of the locomotive automatic driving system in a web end/client side mode. The method and the device have the advantages that the automatic driving system evaluation system is built through the big data platform to realize visualization, manageability, retrievability and configurability of the automatic driving system, the big data platform is applied to the field of automatic driving of the locomotive, a complete locomotive automatic driving system evaluation method and a relevant algorithm are provided, and an evaluation system integrating technologies of AI artificial intelligence and big data of BigData is created; on one hand, users related to the automatic driving of the participatory locomotive understand and summarize the automatic driving system from the micro/macro perspective; and on the other hand, the function of the evaluation system serves the automatic driving system of the locomotive on the aspects of statistical information and a control model. During the operation of the locomotive automatic driving system, locomotive automatic driving system developers and operation unit managers can comprehensively know all functions and performance indexes of the locomotive automatic driving system through the evaluation system, so that guidance significance is provided for improving the functions of the locomotive automatic driving system and improving the control performance of the locomotive automatic driving system, and good popularization significance is achieved.
The evaluation system suitable for locomotive automatic driving of the embodiment of the invention comprises: the locomotive automatic driving system is used for providing operation data of locomotive automatic driving, the big data platform comprises a database and a data analysis and evaluation device, and the dynamics simulation system is connected with the locomotive automatic driving system and the dynamics simulation system; the database at least comprises a data storage library and an evaluation criterion library; the dynamic simulation system is used for performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive; the evaluation criterion library comprises: a safety evaluation criterion, a stability evaluation rule and a rationality evaluation criterion; the data analysis evaluation device is used for evaluating the safety and the rationality according to the safety evaluation criterion, the rationality evaluation criterion and the operation data, evaluating the stationarity according to the stationarity evaluation rule and the car coupler force variation curve and obtaining an evaluation result; the database is used for storing the operation data and the evaluation result, can perform all-around and all-around analysis on the operation condition of the automatic driving system of the locomotive in the aspects of macro and micro, and has wide application prospect.
For convenience of description, the above devices are described as being divided into various modules by functions, which are described separately. Of course, the functions of the modules may be implemented in the same or multiple software and/or hardware in implementing embodiments of the invention.
Based on the same conception, the embodiment of the invention also provides an evaluation method suitable for locomotive automatic driving. The method is applied to the evaluation system suitable for locomotive automatic driving. As shown in fig. 6, the evaluation method for automatic driving of a locomotive includes:
step S11: and receiving the operation data acquired in the automatic driving process of the locomotive transmitted by the automatic driving system of the locomotive.
In the embodiment of the invention, the operation data can be actual operation data acquired in the automatic driving process of the locomotive or operation data acquired in a laboratory. The former is used for off-line evaluation and data statistical analysis of the field operation condition of locomotive automatic driving by using recorded actual operation data. The latter is used for real-time evaluation of the laboratory situation of locomotive autopilot with real-time operational data.
Step S12: and performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive.
Optionally, extracting, by a dynamics simulation system, an operating parameter related to coupler force calculation from the operating data; and performing dynamic simulation and coupler force calculation according to the operation parameters to obtain a coupler force variation curve of the locomotive. The operational parameters associated with the coupler force calculation include at least: air braking amount, grade data, curve data, tunnel data, train consist data, and operating speed.
Step S13: and evaluating the safety and the rationality according to a safety evaluation criterion and a rationality evaluation criterion in an evaluation criterion library and the operation data, and evaluating the stationarity according to a stationarity evaluation rule in the evaluation criterion library and the car coupler force variation curve to obtain an evaluation result.
And performing data analysis on the operating data according to a preset data analysis configuration library by using a data analysis and evaluation software method, and storing the operating data in a data storage library. And programming and digitizing according to the railway specifications to generate a safety evaluation criterion, and further performing safety evaluation according to the safety evaluation criterion and the operation data.
And obtaining a speed running curve of a standard train running model by applying an intelligent algorithm software method and a standard train intelligent software method, taking the speed running curve as a rationality evaluation criterion, and further carrying out rationality evaluation according to the rationality evaluation criterion and the running data. Optionally, generating the standard train operation model by applying an intelligent algorithm software method according to manual driving maneuver operation data of the excellent drivers stored in the database; and acquiring a simulation curve of the standard train operation model operating according to a real environment by applying a standard train intelligent software method, and taking the simulation curve as the speed operation curve of the standard train operation model.
And (4) applying a dynamic simulation system to evaluate the stability according to the car coupler force change curve and the stability evaluation rule.
In the embodiment of the present invention, the method further includes: counting the evaluation results of one or more locomotives in different time periods from a time dimension; counting the evaluation results of each locomotive of each road bureau, line or each section from the position dimension; and counting the accurate parking position distribution and the interval time-use distribution of the automatic driving system of a single station track from the accuracy probability distribution.
The foregoing description of specific embodiments of the present invention has been presented. In some cases, acts or steps recited in embodiments of the invention may be performed in an order different than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The method of the foregoing embodiment is applied to the corresponding system in the foregoing embodiment, and has the beneficial effects of the corresponding system embodiment, which are not described herein again.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is merely exemplary and is not intended to suggest that the scope of the application is limited to these examples; within the context of the present application, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the present application as described above, which are not provided in detail for the sake of brevity.
This application is intended to embrace all such alternatives, modifications and variances that fall within the broad scope of embodiments of the present invention. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of the embodiments of the present invention are intended to be included within the scope of the present application.

Claims (10)

1. An evaluation system adapted for locomotive autopilot, the evaluation system comprising: the system comprises a locomotive automatic driving system, a big data platform and a dynamics simulation system, wherein the locomotive automatic driving system is used for providing operation data of locomotive automatic driving; the database at least comprises a data storage library and an evaluation criterion library;
the dynamic simulation system is used for performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive;
the evaluation criterion library comprises: a safety evaluation criterion, a stability evaluation rule and a rationality evaluation criterion; the data analysis evaluation device is used for evaluating the safety and the rationality according to the safety evaluation criterion, the rationality evaluation criterion and the operation data, evaluating the stationarity according to the stationarity evaluation rule and the car coupler force variation curve and obtaining an evaluation result; the database is used for storing the operation data and the evaluation result.
2. The evaluation system according to claim 1, wherein the database further comprises a data analysis configuration library, and the data analysis and evaluation device performs data analysis on the operation data according to the preset data analysis configuration library by using a data analysis and evaluation software method, and stores the operation data in the data storage library.
3. The evaluation system of claim 1, wherein the data analysis evaluation device is further configured to:
programming and datamation are carried out according to railway specifications to generate the safety evaluation criterion;
and obtaining a speed running curve of a standard train running model by applying an intelligent algorithm software method and a standard train intelligent software method to serve as the rationality evaluation criterion.
4. The evaluation system of claim 3, wherein the data analysis evaluation device is configured to:
generating the standard train operation model by applying an intelligent algorithm software method according to manual driving manipulation operation data of the excellent drivers stored in a database;
and acquiring a simulation curve of the standard train operation model operating according to a real environment by applying a standard train intelligent software method, and taking the simulation curve as the speed operation curve of the standard train operation model.
5. The evaluation system of claim 1, wherein the dynamics simulation system is configured to:
extracting operational parameters related to coupler force calculation according to the operational data, wherein the operational parameters related to coupler force calculation at least comprise: air braking amount, gradient data, curve data, tunnel data, train marshalling data and running speed;
and performing dynamic simulation and coupler force calculation according to the operation parameters to obtain a coupler force variation curve of the locomotive.
6. The evaluation system of claim 1, wherein the big data platform further comprises a statistics presentation module to:
counting the evaluation results of one or more locomotives in different time periods from a time dimension;
counting the evaluation results of the locomotives of each road bureau, line or each section from the position dimension;
and counting the accurate parking position distribution and the interval time distribution of the automatic driving system of a single station track from the accuracy probability distribution.
7. The evaluation system of claim 6, wherein the statistics presentation module is further configured to:
receiving a query request input by a user;
and responding to the query request pair, and counting and displaying the evaluation results of one or more locomotives from a time dimension, a position dimension or an accuracy probability distribution.
8. The evaluation system of claim 1 further comprising a transmission system coupled to the autopilot system and the big data platform for transmitting operational data associated with the locomotive autopilot system to the big data platform.
9. An evaluation method for automatic driving of a locomotive, which is applied to the evaluation system for automatic driving of a locomotive according to any one of claims 1 to 8, the method comprising:
receiving operation data acquired in the automatic driving process of the locomotive transmitted by an automatic driving system of the locomotive;
performing dynamic simulation according to the operation data to obtain a coupler force variation curve of the locomotive;
and evaluating the safety and the rationality according to a safety evaluation criterion and a rationality evaluation criterion in an evaluation criterion library and the operation data, and evaluating the stationarity according to a stationarity evaluation rule in the evaluation criterion library and the car coupler force variation curve to obtain an evaluation result.
10. The method of claim 9, further comprising:
counting the evaluation results of one or more locomotives in different time periods from a time dimension;
counting the evaluation results of each locomotive of each road bureau, line or each section from the position dimension;
and counting the accurate parking position distribution and the interval time-use distribution of the automatic driving system of a single station track from the accuracy probability distribution.
CN202210252724.XA 2022-03-15 2022-03-15 Evaluation system and method suitable for locomotive automatic driving Pending CN114580191A (en)

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