CN111539686B - Transportation management monitoring method based on vehicle running record visualization - Google Patents
Transportation management monitoring method based on vehicle running record visualization Download PDFInfo
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Abstract
The invention discloses a transportation management monitoring method based on vehicle running record visualization, which comprises the steps of selecting a corresponding date range, and importing historical data of the date range, wherein the historical data comprises a time tag and speed information; the data cleaning comprises removing redundant time labels and abnormal speed information, and sorting the speed information after data cleaning according to the sequence of the time labels; and determining a corresponding time window unit according to actual requirements, generating two columns of features of the actual date and time window unit from the time tag, and calculating the average speed of the vehicle in each time window unit to generate a data table, wherein the numerical value in each cell is the average speed corresponding to the actual date and time window unit. By utilizing the relation between the speed and the working condition, a single chart is designed, the rule and the change of the vehicle driving path or the transportation service in the time dimension are indirectly revealed, and the comparison of the service forms among vehicles is convenient for an analyst.
Description
Technical Field
The invention relates to the technical field of transportation management, in particular to a transportation management monitoring method based on vehicle driving record visualization.
Background
With the popularity of electronic informatization in modern transportation industry, the time, geography, driving mode (speed, acceleration and deceleration, etc.) and vehicle state information of the vehicle running process can be tracked. In the aspect of business scenes, the urban distribution process and the electronic commerce are prosperous, the urban and inter-urban distribution demands are remarkably increased, and the characteristics of complex and changeable distribution scenes, frequent logistics activities, numerous logistics nodes and the like are presented. This type of transportation need is mainly accomplished by distribution companies (having multiple vehicles), and individual carriers (owned or leased vehicles). Accordingly, the distribution company service personnel need to manage and dispatch a plurality of vehicles simultaneously, or the vehicle renting company needs to monitor the use condition of a plurality of rented vehicles so as to reduce the risk of escaping renting or improper use. All the above scenarios belong to one-to-many relationship, and one person needs to monitor multiple management objects at the same time. Too much monitoring information is too miscellaneous, so that the conditions of inaccurate monitoring, manual errors and the like are easy to occur, and the related loss of the monitoring is caused.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a transportation management monitoring method based on vehicle driving record visualization, which at least achieves the purpose of using real-time monitoring based on position information to monitor a management object, displaying the current position of a vehicle on a map, and reminding by assistance of text information if an abnormal condition needing to be noted. If the information on the spatial position and the time dimension is to be grasped simultaneously, a plurality of charts are usually used to display the information on different dimensions respectively, and an analyst needs to cross-compare the plurality of charts to extract effective information so as to help decision making.
The aim of the invention is realized by the following technical scheme:
a method for monitoring transportation management based on visualization of vehicle running records comprises the following steps,
step S1: according to the actual demand of transportation management monitoring, selecting a corresponding date range, and importing historical data of the date range, wherein the historical data comprises a time tag and speed information;
step S2: on the basis of the step S1, data cleaning is carried out on historical data, wherein the data cleaning comprises the steps of removing redundant time labels and abnormal speed information, and sorting the speed information after data cleaning according to the sequence of the time labels;
step S3: on the basis of the step S2, extracting features of a time tag, determining a corresponding time window unit according to actual requirements, and generating two columns of features of an actual date and time window unit from the time tag;
step S4: on the basis of the step S3, when the vehicle is in a running state, calculating the average speed of the vehicle in each time window unit;
step S5: generating a data table on the basis of the step S4, wherein the row index of the data table is an actual date, the column index of the data table is a time window unit, and the numerical value in each cell is the average speed corresponding to the actual date and the time window unit;
step S6: and on the basis of the step S5, converting the data table into a thermodynamic diagram, wherein the abscissa is the actual date, the ordinate is the time window unit, the shade of each cell represents the size of the corresponding average speed, the darker the color represents the larger the average speed, and when the cell is selected, the corresponding time and average speed information can be correspondingly displayed.
Further, in step S1, the history data further includes brake pedal information and accelerator pedal information.
Further, when the vehicle is an electric vehicle, the speed information in step S1 may be replaced with current information.
Further, in step S2, the abnormal speed information includes: the speed is less than zero and the speed exceeds a maximum speed threshold.
Further, in step S3, the time window unit is set according to the requirement, and may be: hourly, every half hour, every fifteen minutes or every minute.
Further, in step S4, it may be determined that the vehicle is in a driving state and one of the following is satisfied: the speed information is not zero, and the brake pedal is away from the initial position or the accelerator pedal is away from the initial position.
Further, the specific method for judging the running state of the vehicle is as follows:
when the speed information is zero, if the brake pedal leaves the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is zero, if the brake pedal leaves the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state and is in a normal running state;
when the speed information is zero, if the brake pedal does not leave the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is not zero, if the brake pedal leaves the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is not zero, if the brake pedal does not leave the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state and is in a normal running state;
when the speed information is not zero, if the brake pedal leaves the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state, and the vehicle is in a normal running state;
when the speed information is not zero, if the brake pedal does not leave the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state, and the vehicle is in a normal running state.
Further, a plurality of date intervals parallel to the date range in the step 1 are obtained, a speed information set, a brake pedal information set, an accelerator pedal information set, a time window unit set, an average speed set and an actual date set of the plurality of date intervals are obtained in the same way, the speed information set, the brake pedal information set, the accelerator pedal information set, the time window unit set, the average speed set and the actual date set are taken as sample sets, after characteristic fusion is carried out on the speed information set, the brake pedal information set, the accelerator pedal information set and the time window unit set in the sample sets, the average speed set and the actual date set are taken as output, the sample sets are divided into a training set and a test set, the training set is trained to obtain a transportation management monitoring model, the test set is substituted into the transportation management monitoring model to obtain an optimized transportation management monitoring model, and when the date ranges recorded outside the date ranges and the plurality of date intervals in the step 1 are required to be analyzed, the speed information set, the brake pedal information set, the accelerator pedal information set and the time window unit set are taken as input into the optimized transportation management monitoring model after characteristic fusion is carried out on the speed information set, and the actual date set is taken as the corresponding optimized transportation management monitoring model, and the optimized transportation management model is output.
Further, after obtaining the actual average speed set and the actual date set, a verification step is further included, specifically:
when the optimized transportation management monitoring model outputs a corresponding actual average speed set and an actual date set, calculating a verification average speed set corresponding to the actual date set according to a method of the step S4 by using a corresponding speed information set, a brake pedal information set, an accelerator pedal information set and a time window unit;
comparing and judging the actual average speed set with the verification average speed set;
if the actual average speed set is equal to the verification average speed set in one-to-one correspondence, the output result of the optimized transportation management monitoring model is correct;
and if not, the output result of the optimized transportation management monitoring model is abnormal, and meanwhile, an abnormal output alarm is carried out, and the verification average speed set is used for replacing the actual average speed set output by the optimized transportation management monitoring model.
The beneficial effects of the invention are as follows: 1. the single chart is used for supporting the analysis and understanding of the rapid and large-capacity time space dimension information, and the longitudinal comparison of the business rules of the same vehicle in the time dimension and the transverse of business forms among different vehicles can be realized. The interactive (ECharts is used here) visual design can provide specific time and speed information of each node while presenting visual panoramic information contrast, so that further deep analysis by analysts is facilitated. In addition, the technology has low requirements on vehicle-mounted data acquisition equipment, only needs information of two dimensions of time and speed, indirectly reflects the similarity of path or transportation service scenes through speed reflecting working conditions, and reduces the requirements on the accuracy of data of each time point by using the average speed within a given time window length (for example, per hour).
2. The method can realize rapid analysis of vehicle transportation by adopting the neural network model, is convenient for management and monitoring intellectualization, and simultaneously reduces the influence of human error on analysis and monitoring results to a great extent.
3. Through the verification and inspection steps, the accuracy verification and inspection can be effectively carried out on the vehicle transportation analysis and monitoring process, the speed of obtaining the actual average speed set by optimizing the transportation management and monitoring model is far faster than that of the calculation process of the accuracy verification and inspection steps, the former normally acts, the actual average speed set is obtained by optimizing the transportation management and monitoring model, the latter also carries out the accuracy verification and inspection steps, the two steps do not influence each other at the same time, the latter has a slow speed, the result of the former is provided with corresponding guarantee, abnormal analysis results can be found in time, and management staff of vehicle transportation can find and process in time; is a powerful verification tool for optimizing the transportation management monitoring model.
Drawings
FIG. 1 is a flow chart illustrating the operation of one embodiment of the present invention;
FIG. 2 is a schematic illustration of an application of an embodiment of the present invention;
FIG. 3 is a flow chart illustrating the steps according to an embodiment of the present invention.
Detailed Description
The technical solution of the present invention will be described in further detail with reference to the accompanying drawings, but the scope of the present invention is not limited to the following description.
Examples:
with the popularization of electronic informatization in modern transportation industry, the time, geography, driving mode (acceleration, deceleration, etc.) and vehicle state information of the vehicle running process can be tracked. In the aspect of business scenes, the urban distribution process and the electronic commerce are prosperous, the urban and inter-urban distribution demands are remarkably increased, and the characteristics of complex and changeable distribution scenes, frequent logistics activities, numerous logistics nodes and the like are presented. This type of transportation need is mainly accomplished by distribution companies (having multiple vehicles), and individual carriers (owned or leased vehicles). Accordingly, the distribution company service personnel need to manage and dispatch a plurality of vehicles simultaneously, or the vehicle renting company needs to monitor the use condition of a plurality of rented vehicles so as to reduce the risk of escaping renting or improper use. All the above scenarios belong to one-to-many relationship, and one person needs to monitor multiple management objects at the same time. Too much monitoring information is too miscellaneous, so that the conditions of inaccurate monitoring, manual errors and the like are easy to occur, and the related loss of the monitoring is caused. Therefore, a transportation management monitoring method based on vehicle running record visualization is provided, so that at least the real-time monitoring based on position information is used for monitoring a management object, the current position of the vehicle is displayed on a map, and if an abnormal condition needing to be noted is reminded by assistance of text information. If the information on the spatial position and the time dimension is to be grasped simultaneously, a plurality of charts are usually used to display the information on different dimensions respectively, and an analyst needs to cross-compare the plurality of charts to extract effective information so as to help decision making. The specific content of the method is as follows,
as shown in fig. 1 and 3, the transportation management monitoring method based on the visualization of the vehicle running record, includes the steps of,
step S1: according to the actual demand of transportation management monitoring, selecting a corresponding date range, and importing historical data of the date range, wherein the historical data comprises a time tag and speed information;
step S2: on the basis of the step S1, data cleaning is carried out on historical data, wherein the data cleaning comprises the steps of removing redundant time labels and abnormal speed information, and sorting the speed information after data cleaning according to the sequence of the time labels;
step S3: on the basis of the step S2, extracting features of a time tag, determining a corresponding time window unit according to actual requirements, and generating two columns of features of an actual date and time window unit from the time tag;
step S4: on the basis of the step S3, when the vehicle is in a running state, calculating the average speed of the vehicle in each time window unit;
based on the above scheme, there is also a certain limitation, which is in the following three aspects:
1) For the same vehicle, it is inconvenient to view the track in a longer time dimension (such as three hours and more), and the track overlap is caused by the round trip passing of a main node or a road section or similar transportation paths every day, so that on one hand, the previous history information can be covered, and on the other hand, the change process in the time dimension cannot be provided.
2) The transverse comparison among vehicles is not supported, and the multi-vehicle multi-path display is carried out on the same drawing page, so that on one hand, the comparison in the time dimension is not supported, and on the other hand, the sensitivity of analysts to information is reduced due to node crossing or coverage.
3) Longitudinal contrast in the time dimension is not supported to reflect the regularity and variation in its use. The multiple charts respectively display information of different dimensions, and the limitation is that the mutual correlation among the dimensions cannot be intuitively reflected, and the requirements on the information comparison and integration capability of analysts are high.
Step S5: generating a data table on the basis of the step S4, wherein the row index of the data table is an actual date, the column index of the data table is a time window unit, and the numerical value in each cell is the average speed corresponding to the actual date and the time window unit;
step S6: and on the basis of the step S5, converting the data table into a thermodynamic diagram, wherein the abscissa is the actual date, the ordinate is the time window unit, the shade of each cell represents the size of the corresponding average speed, the darker the color represents the larger the average speed, and when the cell is selected, the corresponding time and average speed information can be correspondingly displayed. Each row of the thermodynamic diagram reflects the departure time and the receiving time of the vehicle on the date and the working condition of the transportation route; the rules and changes of the traffic pattern or the transportation route of the vehicle are reflected among each column (see the example of fig. 2 for details). The darker the corresponding cell color represents the greater the average speed at that time. For vehicle number 1, an analyst may find the relative regularity of the vehicle transportation traffic. The vehicle is driven out every morning, the vehicle is driven for 1-2 hours (corresponding to the pick-up point of the distributed warehouse) through a high-speed driving road section (such as a winding city and a high-speed), then the vehicle is driven again through the high-speed driving road section, and after the vehicle is on the sky, the vehicle is driven at a low speed (corresponding to the distribution in the city), and the vehicle is received at noon. Wherein, during 8 months of 2018, there is no vehicle record for a period of time, possibly due to rest or failure of vehicle-mounted equipment, and related personnel can further analyze reasons against other recorded information. In the case of vehicle No. 2, by comparing the velocity profile map with the corresponding map of vehicle No. 1, it can be seen that the traffic pattern of vehicle No. 2 is greatly different from that of vehicle No. 1. The dynamic state of the No. 2 vehicle is disordered and has no certain rule, but the related information of the No. 2 vehicle can still be seen through the corresponding thermodynamic diagram, and the vehicle transportation management and monitoring process can be carried out as usual.
The single chart is used for supporting the analysis and understanding of the rapid and large-capacity time space dimension information, and the longitudinal comparison of the business rules of the same vehicle in the time dimension and the transverse of business forms among different vehicles can be realized. The interactive (ECharts is used here) visual design can provide specific time and speed information of each node while presenting visual panoramic information contrast, so that further deep analysis by analysts is facilitated. In addition, the technology has low requirements on vehicle-mounted data acquisition equipment, only needs information of two dimensions of time and speed, indirectly reflects the similarity of path or transportation service scenes through speed reflecting working conditions, and reduces the requirements on the accuracy of data of each time point by using the average speed within a given time window length (for example, per hour).
Further, in step S1, the history data further includes brake pedal information and accelerator pedal information.
Further, when the vehicle is an electric vehicle, the speed information in step S1 may be replaced with current information. The current information can reflect the speed information of the electric automobile.
Further, in step S2, the abnormal speed information includes: the speed is less than zero, the speed exceeds a maximum speed threshold value and the like, and the speed information which obviously does not accord with the actual situation is abnormal speed information and needs to be completely removed, otherwise, larger errors are caused for subsequent analysis.
Further, in step S3, the time window unit is set according to the requirement, and may be: hourly, every half hour, every fifteen minutes or every minute, etc.
Further, in step S4, it may be determined that the vehicle is in a driving state and one of the following is satisfied: the speed information is not zero, and the brake pedal is separated from the initial position or the accelerator pedal is separated from the initial position, and the three situations are discussed in detail according to actual driving situations.
Further, the specific method for judging the running state of the vehicle is as follows:
when the speed information is zero, if the brake pedal leaves the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is zero, if the brake pedal leaves the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state and is in a normal running state;
when the speed information is zero, if the brake pedal does not leave the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is not zero, if the brake pedal leaves the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is not zero, if the brake pedal does not leave the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state and is in a normal running state;
when the speed information is not zero, if the brake pedal leaves the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state, and the vehicle is in a normal running state;
when the speed information is not zero, if the brake pedal does not leave the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state, and the vehicle is in a normal running state.
Further, a plurality of date intervals parallel to the date range in the step 1 are obtained, a speed information set, a brake pedal information set, an accelerator pedal information set, a time window unit set, an average speed set and an actual date set of the plurality of date intervals are obtained in the same way, the speed information set, the brake pedal information set, the accelerator pedal information set, the time window unit set, the average speed set and the actual date set are taken as sample sets, after characteristic fusion is carried out on the speed information set, the brake pedal information set, the accelerator pedal information set and the time window unit set in the sample sets, the average speed set and the actual date set are taken as output, the sample sets are divided into a training set and a test set, the training set is trained to obtain a transportation management monitoring model, the test set is substituted into the transportation management monitoring model to obtain an optimized transportation management monitoring model, and when the date ranges recorded outside the date ranges and the plurality of date intervals in the step 1 are required to be analyzed, the speed information set, the brake pedal information set, the accelerator pedal information set and the time window unit set are taken as input into the optimized transportation management monitoring model after characteristic fusion is carried out on the speed information set, and the actual date set is taken as the corresponding optimized transportation management monitoring model, and the optimized transportation management model is output. By adopting the mode, the rapid analysis of the vehicle transportation can be realized, the management and the monitoring are convenient to be intelligentized, and meanwhile, the influence of the artificial error on the analysis and the monitoring results is reduced to a great extent.
Further, after obtaining the actual average speed set and the actual date set, a verification step is further included, specifically:
when the optimized transportation management monitoring model outputs a corresponding actual average speed set and an actual date set, calculating a verification average speed set corresponding to the actual date set according to a method of the step S4 by using a corresponding speed information set, a brake pedal information set, an accelerator pedal information set and a time window unit;
comparing and judging the actual average speed set with the verification average speed set;
if the actual average speed set is equal to the verification average speed set in one-to-one correspondence, the output result of the optimized transportation management monitoring model is correct;
and if not, the output result of the optimized transportation management monitoring model is abnormal, and meanwhile, an abnormal output alarm is carried out, and the verification average speed set is used for replacing the actual average speed set output by the optimized transportation management monitoring model.
Through the verification and inspection steps, the accuracy verification and inspection can be effectively carried out on the vehicle transportation analysis and monitoring process, the speed of obtaining the actual average speed set by optimizing the transportation management and monitoring model is far faster than that of the calculation process of the accuracy verification and inspection steps, the former normally acts, the actual average speed set is obtained by optimizing the transportation management and monitoring model, the latter also carries out the accuracy verification and inspection steps, the two steps do not influence each other at the same time, the latter has a slow speed, the result of the former is provided with corresponding guarantee, abnormal analysis results can be found in time, and management staff of vehicle transportation can find and process in time; is a powerful verification tool for optimizing the transportation management monitoring model.
Meanwhile, on the basis of the scheme, a positioning verification step is also provided, and the method specifically comprises the following steps:
acquiring real-time geographic position information of a vehicle and map information of a vehicle passing place;
calculating a positioning average speed set of the vehicle according to the real-time geographic position information of the vehicle on the map information and the real-time movement information of the vehicle;
and verifying and checking the positioning average speed set and the actual average speed set, and judging whether the positioning average speed set and the actual average speed set are consistent.
Comparing the positioning verification step with the verification step, and if the positioning verification step and the verification step are judged to be consistent, judging that any consistent verification result is right; if the two are inconsistent, an alarm is sent to the manager, and corresponding manual verification and inspection are carried out.
The foregoing is merely a preferred embodiment of the invention, and it is to be understood that the invention is not limited to the form disclosed herein but is not to be construed as excluding other embodiments, but is capable of numerous other combinations, modifications and environments and is capable of modifications within the scope of the inventive concept, either as taught or as a matter of routine skill or knowledge in the relevant art. And that modifications and variations which do not depart from the spirit and scope of the invention are intended to be within the scope of the appended claims.
Claims (3)
1. The transportation management monitoring method based on the visualization of the vehicle running record is characterized by comprising the following steps of: comprises the steps of,
step S1: according to the actual demand of transportation management monitoring, selecting a corresponding date range, and importing historical data of the date range, wherein the historical data comprises a time tag and speed information;
step S2: on the basis of the step S1, data cleaning is carried out on historical data, wherein the data cleaning comprises the steps of removing redundant time labels and abnormal speed information, and sorting the speed information after data cleaning according to the sequence of the time labels;
step S3: on the basis of the step S2, extracting features of a time tag, determining a corresponding time window unit according to actual requirements, and generating two columns of features of an actual date and time window unit from the time tag;
step S4: on the basis of the step S3, when the vehicle is in a running state, calculating the average speed of the vehicle in each time window unit;
step S5: generating a data table on the basis of the step S4, wherein the row index of the data table is an actual date, the column index of the data table is a time window unit, and the numerical value in each cell is the average speed corresponding to the actual date and the time window unit;
step S6: converting the data table into a thermodynamic diagram on the basis of the step S5, wherein the abscissa is the actual date, the ordinate is the time window unit, the color shade of each cell represents the size of the corresponding average speed, the darker the color represents the larger the average speed, and when the cell is selected, the corresponding time and average speed information can be correspondingly displayed;
the historical data also comprises brake pedal information and accelerator pedal information;
when the vehicle is an electric vehicle, the speed information in step S1 may be replaced with current information;
in step S2, the abnormal speed information includes: the speed is less than zero, the speed exceeds a maximum speed threshold;
in step S3, the time window unit is set according to the requirement, and may be: hourly, half hour, fifteen minutes or minutes;
in step S4, it is sufficient to determine that the vehicle is in a running state and one of the following is satisfied: the speed information is not zero, and the brake pedal leaves the initial position or the accelerator pedal leaves the initial position;
the specific method for judging the running state of the vehicle is as follows:
when the speed information is zero, if the brake pedal leaves the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is zero, if the brake pedal leaves the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state and is in a normal running state;
when the speed information is zero, if the brake pedal does not leave the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is not zero, if the brake pedal leaves the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state, and the vehicle is in an abnormal running state, and an abnormal running alarm is sent out;
when the speed information is not zero, if the brake pedal does not leave the initial position and the accelerator pedal leaves the initial position, the vehicle is in a running state and is in a normal running state;
when the speed information is not zero, if the brake pedal leaves the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state, and the vehicle is in a normal running state;
when the speed information is not zero, if the brake pedal does not leave the initial position and the accelerator pedal does not leave the initial position, the vehicle is in a running state, and the vehicle is in a normal running state.
2. The vehicle travel record visualization-based transportation management monitoring method according to claim 1, wherein: obtaining a plurality of date intervals parallel to the date range in the step 1, obtaining a speed information set, a brake pedal information set, an accelerator pedal information set, a time window unit set, an average speed set and an actual date set of the plurality of date intervals in the same way, taking the speed information set, the brake pedal information set, the accelerator pedal information set, the time window unit set, the average speed set and the actual date set as sample sets, taking the sample sets as input after feature fusion of the speed information set, the brake pedal information set, the accelerator pedal information set and the time window unit set in the sample sets, taking the average speed set and the actual date set as output, dividing the sample sets into a training set and a test set, training the training set to obtain a transportation management monitoring model, substituting the test set into the transportation management monitoring model to test to obtain an optimized transportation management monitoring model, and inputting the speed information set, the brake pedal information set, the accelerator pedal information set and the time window unit set recorded outside the date ranges in the step 1 as input to the optimized transportation management monitoring model after feature fusion of the speed information set and the time window unit set as the actual date set for the actual transportation management monitoring model.
3. The vehicle travel record visualization-based transportation management monitoring method according to claim 2, wherein: after obtaining the actual average speed set and the actual date set, a verification and inspection step is further included, specifically:
when the optimized transportation management monitoring model outputs a corresponding actual average speed set and an actual date set, calculating a verification average speed set corresponding to the actual date set according to a method of the step S4 by using a corresponding speed information set, a brake pedal information set, an accelerator pedal information set and a time window unit;
comparing and judging the actual average speed set with the verification average speed set;
if the actual average speed set is equal to the verification average speed set in one-to-one correspondence, the output result of the optimized transportation management monitoring model is correct;
and if not, the output result of the optimized transportation management monitoring model is abnormal, and meanwhile, an abnormal output alarm is carried out, and the verification average speed set is used for replacing the actual average speed set output by the optimized transportation management monitoring model.
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