CN115112169A - Method, equipment and medium for acquiring and analyzing environmental data in tunnel - Google Patents
Method, equipment and medium for acquiring and analyzing environmental data in tunnel Download PDFInfo
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Abstract
The application discloses a method, a device and a medium for acquiring and analyzing environmental data in a tunnel, wherein the method comprises the following steps: acquiring first environment data and first vehicle state data in a tunnel; analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves; generating a corresponding mapping relation according to the environment curve and the vehicle state curve; performing adaptive adjustment on the first environmental data according to the change curve to obtain second environmental data; and compensating the second environment data to obtain third environment data. The method comprises the steps of firstly, collecting first environment data and first vehicle state data in a tunnel, obtaining a corresponding mapping relation and reflecting the influence of a vehicle on the environment in the tunnel. And then through the change of external environment data and the compensation of this mapping relation, can carry out quick accurate analysis to the environmental data in the tunnel of future, improve the degree of accuracy, reliability when just also can guarantee relevant equipment adjustment.
Description
Technical Field
The application relates to the field of computers, in particular to a method, equipment and medium for acquiring and analyzing environmental data in a tunnel.
Background
As a transportation means, the tunnel enables people to quickly pass through geographical structures such as mountains, or enables the overall transportation system to be more convenient.
However, due to the sealing property of the tunnel compared with the outside, the change process of the internal environment data of the tunnel is often inconsistent with that of the outside, which causes that when the environment data in the tunnel needs to be collected for analysis, the analysis is difficult to be performed through the outside environment.
With the development of automation technology, more and more systems need to predict future data in advance so as to assist in adjusting relevant equipment. Due to the sealing property, the difficulty of analyzing and predicting the data is caused, and the related equipment is difficult to be effectively adjusted.
Disclosure of Invention
In order to solve the above problem, the present application provides a method for acquiring and analyzing environmental data in a tunnel, including:
determining a data acquisition device arranged in a tunnel;
acquiring first environmental data and first vehicle state data in the tunnel through the data acquisition device;
analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves;
generating a corresponding mapping relation according to the environment curve and the vehicle state curve;
acquiring a change curve of external environment data within a specified time in the future, and adaptively adjusting the first environment data according to the change curve to obtain second environment data;
and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
In one example, acquiring, by the data acquisition device, first environment data and first vehicle state data in the tunnel specifically includes:
receiving the collected data sent by the data collecting device;
determining the identification of the data acquisition device, and determining the type of the data acquired by the data acquisition device according to the identification;
according to the data type, correspondingly preprocessing the acquired data to obtain preprocessed data;
regarding each data acquisition device, taking all the preprocessed data corresponding to the data acquisition device as a sample set to obtain the sample sets corresponding to the data acquisition devices respectively;
training the sample set to obtain a data cleaning model, and cleaning the preprocessed data according to the data cleaning model to obtain cleaning data;
and dividing the cleaning data into first environment data and first vehicle state data according to the data types corresponding to the cleaning data.
In one example, training the sample set to obtain a data cleaning model, and performing data cleaning on the preprocessed data according to the data cleaning model to obtain cleaned data specifically includes:
generating a corresponding label for the sample set according to the data type corresponding to the sample set;
selecting a plurality of sample sets from all sample sets in the same label, training the sample sets as training sets to obtain a data cleaning model corresponding to the label, and verifying the data cleaning model by using the rest sample sets as verification sets;
screening out the preprocessed data of which the verification result in the verification set does not meet the preset requirement;
and repeating the data cleaning process of the data cleaning model, and reselecting the training set and the verification set in each repeating process.
In one example, generating a corresponding mapping relationship according to the environment curve and the vehicle state curve specifically includes:
determining a curve trend corresponding to the environment curve aiming at the environment curve corresponding to each dimension, and determining a curve trend corresponding to the vehicle state curve, wherein the curve trend comprises at least one of acceleration, inflection points and extreme values;
determining similarity of curve trends of the vehicle state curves and curve trends among the environmental curves;
and selecting an environment curve corresponding to the corresponding dimensionality according to the similarity, and generating a corresponding mapping relation according to the selected environment curve and the vehicle state curve.
In one example, selecting an environment curve corresponding to a corresponding dimension according to the similarity specifically includes:
determining a first preset similarity and a second preset similarity, wherein the first preset similarity is higher than the second preset similarity;
and selecting an environment curve corresponding to the dimension with the similarity exceeding the first preset similarity, and selecting an environment curve corresponding to the dimension with the similarity lower than the second preset similarity.
In one example, adaptively adjusting the first environment data according to the change curve to obtain second environment data specifically includes:
dividing the tunnel to obtain a plurality of paragraphs, wherein the paragraphs at least comprise a middle paragraph and an entrance paragraph;
and respectively carrying out adaptive adjustment on the first environment data corresponding to the plurality of paragraphs according to the change curve to obtain second environment data corresponding to the plurality of paragraphs, wherein the adjustment amplitude of the middle paragraph is smaller than that of the entrance paragraph.
In one example, before the vehicle state data within the specified time period is estimated according to the mapping relation, the method further comprises the following steps:
determining a time period corresponding to the future specified duration and a date corresponding to the time period;
estimating the traffic flow in the appointed time according to the time period, and compensating the estimated result according to the date;
and estimating the vehicle state data in the specified time according to the compensated traffic flow.
In one example, the first environmental data includes at least one of brightness, temperature, humidity, wind power.
On the other hand, this application has still provided an environmental data collection analytical equipment in tunnel, includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform such as:
determining a data acquisition device arranged in a tunnel;
acquiring first environmental data and first vehicle state data in the tunnel through the data acquisition device;
analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves;
generating a corresponding mapping relation according to the environment curve and the vehicle state curve;
acquiring a change curve of external environment data within a specified time in the future, and performing adaptive adjustment on the first environment data according to the change curve to obtain second environment data;
and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
In another aspect, the present application further provides a non-volatile computer storage medium storing computer-executable instructions configured to:
determining a data acquisition device arranged in a tunnel;
acquiring first environmental data and first vehicle state data in the tunnel through the data acquisition device;
analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves;
generating a corresponding mapping relation according to the environment curve and the vehicle state curve;
acquiring a change curve of external environment data within a specified time in the future, and adaptively adjusting the first environment data according to the change curve to obtain second environment data;
and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
The method provided by the application can bring the following beneficial effects:
the method comprises the steps of firstly, collecting first environment data and first vehicle state data in a tunnel, obtaining a corresponding mapping relation and reflecting the influence of a vehicle on the environment in the tunnel. And then through the change of external environment data and the compensation of this mapping relation, can carry out quick accurate analysis to the environmental data in the tunnel of future, improve the degree of accuracy, reliability when just also can guarantee relevant equipment adjustment.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flowchart of an environmental data collection and analysis method in a tunnel according to an embodiment of the present application;
fig. 2 is a schematic diagram of an environmental data acquisition and analysis device in a tunnel according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
As shown in fig. 1, an embodiment of the present application provides a method for acquiring and analyzing environmental data in a tunnel, including:
s101: and determining the data acquisition device arranged in the tunnel.
S102: and acquiring first environment data and first vehicle state data in the tunnel through the data acquisition device.
The data collecting device may be classified into an environmental data collecting device (e.g., a brightness sensor, a temperature sensor, a humidity sensor, a wind sensor, etc.) and a vehicle state collecting device (e.g., a camera). The number of each type of data acquisition device may be plural.
The data acquisition device is used for acquiring data, so that first environment data (such as brightness, temperature, humidity and wind power) and first vehicle state data (such as traffic flow) can be obtained, and the first vehicle state data can be analyzed based on the traffic flow besides the traffic flow, so that other data, such as tail gas emission data, vehicle lamp data and the like, can be obtained.
S103: and analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves.
When the environmental curve corresponds to multiple dimensions (e.g., multiple dimensions of brightness, temperature, humidity, wind, etc.), the environmental curve may be multiple. Similarly, the vehicle state curve may also be multiple. And the curve may be obtained by collecting corresponding data over a period of time.
S104: and generating a corresponding mapping relation according to the environment curve and the vehicle state curve.
The mapping relationship refers to a corresponding change in the environmental curve when the vehicle state curve changes. Of course, not the change of the vehicle state curve, but the change of the environment curves of all dimensions is caused, so that the curve of a part of dimensions can be selected from the environment curves to generate the mapping relation.
S105: and acquiring a change curve of the external environment data within a specified time in the future, and performing adaptive adjustment on the first environment data according to the change curve to obtain second environment data.
The variation curve of the environmental data over a specified time period in the future can be obtained by an associated weather system, such as a weather forecast system. When the outside changes, the inside of the tunnel also changes, and at this time, the first environment data in the tunnel is adaptively adjusted.
S106: and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
In addition to the change of the outside world, the mapping relationship is obtained, which shows that the vehicle state data can also influence the internal environment data, so that the vehicle state data in the specified time duration is estimated, the vehicle state data is compensated through the mapping relationship, and the third environment data is finally obtained, wherein the third environment data is finally obtained as the environment data in the tunnel in the future specified time duration, and at the moment, the equipment in the tunnel can be pre-adjusted according to the third environment data.
In one embodiment, when acquiring the first environment data and the first vehicle state data, the acquired data transmitted by the data acquisition device may be received first, then the identifier of the data acquisition device is determined, and the type of data acquired by the data acquisition device, such as luminance data, temperature data, image data, etc., is determined according to the identifier.
According to the data type, the acquired data is correspondingly preprocessed to obtain preprocessed data, for example, the image data is subjected to noise reduction processing and the like. And regarding each data acquisition device, taking all the preprocessed data corresponding to the data acquisition device as a sample set to obtain the sample sets corresponding to the data acquisition devices respectively. Each sample set includes only the plurality of data collected by the data collection device. And obtaining a data cleaning model through sample set training, and performing data cleaning on the preprocessed data according to the data cleaning model to obtain cleaning data. The cleaned data can be used for screening out abnormal data. And dividing the cleaning data into first environment data and first vehicle state data according to the data types corresponding to the cleaning data.
Further, the specific process of data cleansing may include: and generating corresponding labels for the sample set according to the data types corresponding to the sample set, wherein one label can be generated by one data type. And selecting a plurality of sample sets from all sample sets in the same label, training the sample sets as training sets to obtain a data cleaning model corresponding to the label, and verifying the data cleaning model by using the rest sample sets as verification sets. Each tag may train a data cleansing model. And screening out the preprocessed data of which the verification result in the verification set does not meet the preset requirement. Thus, data cleaning in the verification set is completed. And repeating the data cleaning process of the data cleaning model, and reselecting the training set and the verification set in each repeating process. Thus, all sample sets can be subjected to data cleaning.
In one embodiment, when the mapping relationship is generated, first, for an environment curve corresponding to each dimension, a curve trend corresponding to the environment curve is determined, and a curve trend corresponding to a vehicle state curve is determined. The curve trend includes at least one of a speed increase, an inflection point, and an extremum, and the curve trend can be reflected by these values.
Then, the similarity of the curve trend of the vehicle state curve and the curve trend among the environment curves is determined, and the environment curves corresponding to the dimensions with the similarity exceeding a first preset similarity (for example, 80%) and the similarity lower than a second preset similarity (for example, 20%) are selected, wherein the first preset similarity is higher than the second preset similarity. The curve with high similarity indicates that the two are in positive correlation, while the curve with low similarity indicates that the two are in negative correlation, which indicates that the two are usually in a certain relationship. For example, the more vehicles, the more exhaust gas is discharged, and the tunnel is a relatively closed space, so the temperature inside the tunnel also rises. At this time, a corresponding mapping relation is generated according to the selected environment curve and the vehicle state curve.
In an embodiment, when the first environment data is adaptively adjusted, the tunnel may be divided into a plurality of paragraphs, where the plurality of paragraphs at least include a middle paragraph, an entrance paragraph (including an exit paragraph and an entrance paragraph). In general, the external environment affects the entrance and exit sections more than the middle section. Therefore, at this time, the first environment data corresponding to the plurality of paragraphs can be respectively adjusted adaptively according to the variation curve to obtain the second environment data corresponding to the plurality of paragraphs, wherein the adjustment range of the middle paragraph is smaller than the adjustment range of the entrance paragraph. In this case, the second environment data corresponding to the tunnel may be obtained by summarizing the second environment data of the plurality of paragraphs.
In one embodiment, in predicting future vehicle state data, a time period corresponding to a specified future time period and a date corresponding to the time period may be determined first. And then, estimating the traffic flow in the specified time period according to the time period, for example, if the time period is a peak in the morning and evening, the traffic flow is higher. And compensating the estimated result according to the date, for example, the traffic flow of the morning and evening peaks of the weekend is smaller than the traffic flow at ordinary times. And estimating the vehicle state data in the specified time according to the compensated traffic flow. For example, the traffic flow may be regarded as vehicle state data, and exhaust emission, vehicle lamp brightness, and the like may be determined according to the traffic flow for prediction.
As shown in fig. 2, an embodiment of the present application further provides an environmental data collecting and analyzing device in a tunnel, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform such as:
determining a data acquisition device arranged in a tunnel;
acquiring first environmental data and first vehicle state data in the tunnel through the data acquisition device;
analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves;
generating a corresponding mapping relation according to the environment curve and the vehicle state curve;
acquiring a change curve of external environment data within a specified time in the future, and adaptively adjusting the first environment data according to the change curve to obtain second environment data;
and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
An embodiment of the present application further provides a non-volatile computer storage medium storing computer-executable instructions, where the computer-executable instructions are configured to:
determining a data acquisition device arranged in a tunnel;
acquiring first environmental data and first vehicle state data in the tunnel through the data acquisition device;
analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves;
generating a corresponding mapping relation according to the environment curve and the vehicle state curve;
acquiring a change curve of external environment data within a specified time in the future, and adaptively adjusting the first environment data according to the change curve to obtain second environment data;
and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
The embodiments in the present application are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the device and media embodiments, the description is relatively simple as it is substantially similar to the method embodiments, and reference may be made to some descriptions of the method embodiments for relevant points.
The device and the medium provided by the embodiment of the application correspond to the method one to one, so the device and the medium also have the similar beneficial technical effects as the corresponding method, and the beneficial technical effects of the method are explained in detail above, so the beneficial technical effects of the device and the medium are not repeated herein.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both permanent and non-permanent, removable and non-removable media, may implement the information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, 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, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for acquiring and analyzing environmental data in a tunnel is characterized by comprising the following steps:
determining a data acquisition device arranged in a tunnel;
acquiring first environmental data and first vehicle state data in the tunnel through the data acquisition device;
analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves;
generating a corresponding mapping relation according to the environment curve and the vehicle state curve;
acquiring a change curve of external environment data within a specified time in the future, and adaptively adjusting the first environment data according to the change curve to obtain second environment data;
and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
2. The method according to claim 1, wherein the acquiring, by the data acquisition device, the first environmental data and the first vehicle state data in the tunnel comprises:
receiving the collected data sent by the data collecting device;
determining the identification of the data acquisition device, and determining the type of the data acquired by the data acquisition device according to the identification;
according to the data type, correspondingly preprocessing the acquired data to obtain preprocessed data;
regarding each data acquisition device, taking all the preprocessed data corresponding to the data acquisition device as a sample set to obtain the sample sets corresponding to the data acquisition devices respectively;
training the sample set to obtain a data cleaning model, and performing data cleaning on the preprocessed data according to the data cleaning model to obtain cleaning data;
and dividing the cleaning data into first environment data and first vehicle state data according to the data types corresponding to the cleaning data.
3. The method according to claim 2, wherein training through the sample set obtains a data cleaning model, and performing data cleaning on the pre-processed data according to the data cleaning model to obtain cleaning data, specifically comprises:
generating a corresponding label for the sample set according to the data type corresponding to the sample set;
selecting a plurality of sample sets from all sample sets in the same label, training the sample sets as training sets to obtain a data cleaning model corresponding to the label, and verifying the data cleaning model by using the rest sample sets as verification sets;
screening out the preprocessed data of which the verification result in the verification set does not meet the preset requirement;
and repeating the data cleaning process of the data cleaning model, and reselecting the training set and the verification set in each repeating process.
4. The method according to claim 1, wherein generating a corresponding mapping relationship according to the environment curve and the vehicle state curve specifically comprises:
determining a curve trend corresponding to the environment curve aiming at the environment curve corresponding to each dimension, and determining a curve trend corresponding to the vehicle state curve, wherein the curve trend comprises at least one of acceleration, inflection points and extreme values;
determining similarity of curve trends of the vehicle state curves and curve trends among the environmental curves;
and selecting an environment curve corresponding to the corresponding dimensionality according to the similarity, and generating a corresponding mapping relation according to the selected environment curve and the vehicle state curve.
5. The method according to claim 4, wherein selecting the environment curve corresponding to the corresponding dimension according to the similarity specifically includes:
determining a first preset similarity and a second preset similarity, wherein the first preset similarity is higher than the second preset similarity;
and selecting an environment curve corresponding to the dimension with the similarity exceeding the first preset similarity, and selecting an environment curve corresponding to the dimension with the similarity lower than the second preset similarity.
6. The method according to claim 1, wherein adaptively adjusting the first environmental data according to the variation curve to obtain second environmental data specifically comprises:
dividing the tunnel to obtain a plurality of paragraphs, wherein the paragraphs at least comprise a middle paragraph and an entrance paragraph;
and respectively carrying out adaptive adjustment on the first environment data corresponding to the plurality of paragraphs according to the change curve to obtain second environment data corresponding to the plurality of paragraphs, wherein the adjustment amplitude of the middle paragraph is smaller than that of the entrance paragraph.
7. The method of claim 1, wherein prior to the mapping and the estimated vehicle state data for the specified duration, the method further comprises:
determining a time period corresponding to the future specified duration and a date corresponding to the time period;
estimating the traffic flow in the specified duration according to the time period, and compensating the estimated result according to the date;
and estimating the vehicle state data in the specified time according to the compensated traffic flow.
8. The method of any one of claims 1-7, wherein the first environmental data comprises at least one of brightness, temperature, humidity, wind power.
9. An environmental data collection and analysis device in a tunnel, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform such as:
determining a data acquisition device arranged in a tunnel;
acquiring first environmental data and first vehicle state data in the tunnel through the data acquisition device;
analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves;
generating a corresponding mapping relation according to the environment curve and the vehicle state curve;
acquiring a change curve of external environment data within a specified time in the future, and adaptively adjusting the first environment data according to the change curve to obtain second environment data;
and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
10. A non-transitory computer storage medium storing computer-executable instructions, the computer-executable instructions configured to:
determining a data acquisition device arranged in a tunnel;
acquiring first environmental data and first vehicle state data in the tunnel through the data acquisition device;
analyzing the first environment data and the first vehicle state data respectively to obtain corresponding environment curves and vehicle state curves;
generating a corresponding mapping relation according to the environment curve and the vehicle state curve;
acquiring a change curve of external environment data within a specified time in the future, and adaptively adjusting the first environment data according to the change curve to obtain second environment data;
and compensating the second environmental data according to the mapping relation and the estimated vehicle state data in the specified duration to obtain third environmental data.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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