CN113537682B - Real-time operation monitoring method and device for commuter vehicle - Google Patents
Real-time operation monitoring method and device for commuter vehicle Download PDFInfo
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Abstract
The invention relates to a real-time operation monitoring method and device of a commuter car, wherein the method comprises the following steps: an operation data acquisition step: acquiring operation data of the commuter car; report generation: generating a graphical report through a rendering engine according to the operation data; track playback animation generation step: track playback animation is generated according to the operation data. Compared with the prior art, the invention displays the operation condition to the operation manager more directly and conveniently, and is convenient for the operation manager to make decisions scientifically according to the operation data.
Description
Technical Field
The invention relates to the field of commuter car management, in particular to a real-time operation monitoring method and device for a commuter car.
Background
Initially, the commuter car adopts paper bills, is inconvenient to manage in a centralized manner, is difficult to count, causes unreasonable vehicle dispatching, has the conditions of overman, empty seat and the like, and is very labor-consuming to operate. Therefore, the management of the commuter car gradually develops to digitization and informatization, but the current commuter car management system is adopted to check the operation condition of the commuter car, and only boring data can be seen in the background, and the data is not analyzed, evaluated and counted and displayed in a graphical mode. The real-time position of the vehicle cannot be displayed, and the moving track of the vehicle cannot be displayed.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a real-time operation monitoring method and device for the commuter vehicle, which can more intuitively display the operation condition of the commuter vehicle.
The aim of the invention can be achieved by the following technical scheme:
a real-time operation monitoring method of a commuter car comprises the following steps:
an operation data acquisition step: acquiring operation data of the commuter car;
report generation: generating a graphical report through a rendering engine according to the operation data;
track playback animation generation step: track playback animation is generated according to the operation data.
Further, the operation data includes GPS information, and the track playback animation generating step specifically includes the steps of:
s1: analyzing the GPS information in real time, if no new GPS information is received in the preset first time, executing the step S2, otherwise, repeatedly executing the step S1;
s2: processing is started from the starting point of the GPS information, if the first piece or the second piece of GPS information is processed currently, the currently processed GPS information is skipped, otherwise, the step S3 is performed;
s3: judging whether the currently processed GPS information is the last piece of GPS information, if so, executing the step S7, otherwise, executing the step S4;
s4: calculating corresponding speed according to the currently processed GPS information, taking the position corresponding to the currently processed GPS information as a T position, acquiring the speeds of the T position, the T-1 position and the T-2 position, judging whether the speed is always increased or decreased, if so, executing a step S6, otherwise, solving variances of the speeds of the T position, the T-1 position and the T-2 position, if the variances are smaller than a preset first variance value, executing the step S6, otherwise, executing the step S5;
s5: performing variance correction on the speeds of the T position, the T-1 position and the T-2 position;
s6: starting to process the next piece of GPS information, and executing step S3;
s7: and rendering the GPS information and the speed through an animation generation engine to generate track playback animation.
Further, the step S5 is specifically to average the speeds of the T position, the T-1 position and the T-2 position, and if the speed of one of the T position, the T-1 position and the T-2 position is smaller than the average value, adding a preset first speed value to the speed of the position; if the speed of one of the T position, the T-1 position and the T-2 position is greater than the average value, subtracting a preset first speed value from the speed of the position.
Further, in step S1, the analysis process of the GPS information further includes determining whether there is missing GPS information, if so, performing comparison prediction according to the front and rear GPS information of the missing GPS information, obtaining predicted GPS information, and supplementing the predicted GPS information into the analyzed GPS information.
Further, the first time is five minutes.
Further, the operation data includes a ride record, and the report generating step includes a daily ride rendering sub-step: the number of passengers per day is shown in a line graph by a rendering engine according to the passenger record of the last week.
Further, the operation data includes a ride record, and the report generating step includes a step of rendering the number of passengers in a specified period: and counting the riding records according to a preset time period, and displaying the riding times of each time period through a rendering engine in a histogram.
Further, the operation data includes a ride record, and the report generating step includes a station ride number rendering sub-step: and counting the number of passengers corresponding to each station according to the passenger records, and displaying the number of passengers of each station by using a line graph through a rendering engine.
Further, the operation data includes a riding record and a vehicle-mounted machine number corresponding to each riding record, and the report generating step includes a carrier duty ratio rendering sub-step: and acquiring the carrier corresponding to each riding record according to the number of the vehicle-mounted machine, and displaying the duty ratio of each carrier in a pie chart through a rendering engine according to the riding record and the carrier corresponding to each riding record.
The invention also provides a real-time operation monitoring device of the commuter vehicle, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor calls the computer program to execute the steps of the method.
Compared with the prior art, the invention has the following advantages:
(1) According to the invention, the graphical report and the track playback animation are respectively generated according to the operation data, so that the operation condition is more directly and conveniently displayed to the operation manager, and the operation manager can make a decision scientifically according to the operation data.
(2) In the track playback animation generation step, the method carries out variance correction on the data which is not always increased and decreased and has overlarge variance, so that the playback process of the track playback animation is smoother.
(3) In the track playback animation generation step, the invention also judges whether the analyzed GPS information is missing or not, and predicts the missing GPS information through front and back, thereby ensuring the reliability of the subsequent track playback animation generation.
(4) In the report generation step, daily passengers are displayed through the line graph, passengers in a specified period are displayed through the column graph, passengers in a station are displayed through the line graph, the duty ratio of each carrier is displayed through the pie graph, and the like, so that operation management staff can see richer, comprehensive and visual information from operation data, and convenience is provided for operation management of commuter vehicles.
Drawings
FIG. 1 is a flow chart of the track playback animation generation steps of the present invention;
fig. 2 is a schematic diagram of the report generating step according to embodiment 1 of the present invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
Example 1
The embodiment provides a real-time operation monitoring method of a commuter vehicle, which comprises the following steps:
an operation data acquisition step: acquiring operation data of the commuter car;
report generation: generating a graphical report through a rendering engine according to the operation data;
track playback animation generation step: track playback animation is generated according to the operation data.
The steps are described in detail below.
1. Operation data acquisition step
And acquiring operation data of the commuter car, wherein the operation data comprise GPS information, riding records and vehicle-mounted machine numbers corresponding to each riding record.
2. Report generation step
The manager can view reports of various operation data: daily bus reports, site number reports, carrier month reports, company settlement month reports, recharging record month reports, month settlement reports and the like;
the report generation step is to record the current day of system operation by swiping cards, count and analyze the data of the number of passengers on the station, the position of the vehicle and the like, and generate an intuitive chart with an interface by using a rendering engine of a large data platform, so that the operation condition is directly displayed to the operation and management personnel, and the operation and management personnel can make a decision scientifically according to the operation data conveniently.
The report generating step comprises the following substeps:
a daily passenger number rendering sub-step: the number of passengers per day is shown in a line graph by a rendering engine according to the passenger record of the last week. The figure can show the floating situation of passengers in the previous week.
A sub-step of rendering the passengers in a specified period: and grouping the bus taking records of the same day according to the time of getting on the bus, and if the time of getting on the bus is not within the specified time, recording the specified time by adopting a nearby principle. Accumulating the grouped persons, rendering a histogram, wherein the histogram can reflect the change of the number of persons riding the commuter vehicles on duty and off duty, and can predict the number of passengers in the later period.
The sub-step of station passenger number rendering: the current riding data are grouped and counted according to the stations, a plurality of line diagrams of the number of the stations are generated, and rotation is carried out. Meanwhile, the data can be used for generating points with the thickness changing along with the change of the number of the site persons on the map, so that the number of the site persons can be intuitively reflected on the map, and even the distribution situation of staff can be seen according to the number of the site persons.
Carrier duty cycle rendering sub-step: and the carrier of each riding record is obtained according to the number of the vehicle-mounted machine, a pie chart is generated according to the statistics of the carrier, the duty ratio of each carrier can be reflected, and a decision maker can reasonably adjust the carrying proportion of the carrier according to the duty ratio.
The total number of people on the same day is rendered in the substep of: and counting the number of passengers in the month, and calculating the ratio of the total number of passengers in the day by combining the total number of passengers in the day.
Fig. 2 is a schematic diagram of the results generated in the report generating step according to this embodiment.
3. Track playback animation generation step
As shown in fig. 1, the track playback animation generation step specifically includes the steps of:
s1: analyzing GPS information in real time, judging whether missing GPS information exists, if so, comparing and predicting according to the front and rear GPS information of the missing GPS information, obtaining predicted GPS information, supplementing the predicted GPS information into the analyzed GPS information, and enabling a background operator to see the position of the vehicle in the background in real time;
if no new GPS information is received within the preset first time, executing the step S2, otherwise, repeatedly executing the step S1; in this embodiment, the first time is five minutes;
s2: processing is started from the starting point of the GPS information, if the first piece or the second piece of GPS information is processed currently, the currently processed GPS information is skipped, otherwise, the step S3 is performed;
s3: judging whether the currently processed GPS information is the last piece of GPS information, if so, executing the step S7, otherwise, executing the step S4;
s4: calculating corresponding speed according to the currently processed GPS information, taking the position corresponding to the currently processed GPS information as a T position, acquiring the speeds of the T position, the T-1 position and the T-2 position, judging whether the speed is always increased or decreased, if so, executing a step S6, otherwise, solving variances of the speeds of the T position, the T-1 position and the T-2 position, if the variances are smaller than a preset first variance value, executing the step S6, otherwise, executing the step S5;
s5: performing variance correction on the speeds of the T position, the T-1 position and the T-2 position;
the method comprises the steps of obtaining average values of speeds of a T position, a T-1 position and a T-2 position, and adding a preset first speed value to the speed of one of the T position, the T-1 position and the T-2 position if the speed of the position is smaller than the average value; if the speed of one of the T position, the T-1 position and the T-2 position is greater than the average value, subtracting a preset first speed value from the speed of the position.
S6: starting to process the next piece of GPS information, and executing step S3;
s7: and rendering the GPS information and the speed through an animation generation engine to generate track playback animation.
The embodiment also provides a real-time operation monitoring device of the commuter vehicle, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor calls the computer program to execute the steps of the method.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the person skilled in the art according to the inventive concept shall be within the scope of protection defined by the claims.
Claims (7)
1. The real-time operation monitoring method of the commuter car is characterized by comprising the following steps of:
an operation data acquisition step: acquiring operation data of the commuter car;
report generation: generating a graphical report through a rendering engine according to the operation data;
track playback animation generation step: generating track playback animation according to the operation data;
the operation data comprises GPS information, and the track playback animation generation step specifically comprises the following steps:
s1: analyzing the GPS information in real time, if no new GPS information is received in the preset first time, executing the step S2, otherwise, repeatedly executing the step S1;
s2: processing is started from the starting point of the GPS information, if the first piece or the second piece of GPS information is processed currently, the currently processed GPS information is skipped, otherwise, the step S3 is performed;
s3: judging whether the currently processed GPS information is the last piece of GPS information, if so, executing the step S7, otherwise, executing the step S4;
s4: calculating corresponding speed according to the currently processed GPS information, taking the position corresponding to the currently processed GPS information as a T position, acquiring the speeds of the T position, the T-1 position and the T-2 position, judging whether the speed is always increased or decreased, if so, executing a step S6, otherwise, solving variances of the speeds of the T position, the T-1 position and the T-2 position, if the variances are smaller than a preset first variance value, executing the step S6, otherwise, executing the step S5;
s5: performing variance correction on the speeds of the T position, the T-1 position and the T-2 position;
s6: starting to process the next piece of GPS information, and executing step S3;
s7: rendering the GPS information and the speed through an animation generation engine to generate a track playback animation;
step S5 is specifically to calculate average values of the speeds of the T position, the T-1 position and the T-2 position, and if the speed of one position among the T position, the T-1 position and the T-2 position is smaller than the average value, adding a preset first speed value to the speed of the position; if the speed of one of the T position, the T-1 position and the T-2 position is greater than the average value, subtracting a preset first speed value from the speed of the position;
in step S1, the process of analyzing the GPS information further includes determining whether there is missing GPS information, if so, performing comparative prediction according to the front and rear GPS information of the missing GPS information, obtaining predicted GPS information, and supplementing the predicted GPS information into the analyzed GPS information.
2. A method of monitoring real time operation of a commuter car as claimed in claim 1 wherein said first time is five minutes.
3. The method for monitoring real-time operation of a commuter car according to claim 1, wherein the operation data comprises a bus record, and the report generation step comprises a sub-step of daily bus number rendering: the number of passengers per day is shown in a line graph by a rendering engine according to the passenger record of the last week.
4. The method for monitoring real-time operation of a commuter car according to claim 1, wherein the operation data comprises a bus record, and the report generation step comprises a bus number rendering sub-step in a specified period: and counting the riding records according to a preset time period, and displaying the riding times of each time period through a rendering engine in a histogram.
5. The method for monitoring real-time operation of a commuter car according to claim 1, wherein the operation data comprises a bus record, and the report generation step comprises a station bus number rendering sub-step: and counting the number of passengers corresponding to each station according to the passenger records, and displaying the number of passengers of each station by using a line graph through a rendering engine.
6. The method for monitoring real-time operation of a commuter vehicle according to claim 1, wherein the operation data includes a bus record and a vehicle number corresponding to each bus record, and the report generating step includes a carrier duty ratio rendering sub-step: and acquiring the carrier corresponding to each riding record according to the number of the vehicle-mounted machine, and displaying the duty ratio of each carrier in a pie chart through a rendering engine according to the riding record and the carrier corresponding to each riding record.
7. A real-time operation monitoring device of a commuter vehicle, characterized by comprising a memory and a processor, the memory storing a computer program, the processor invoking the computer program to perform the steps of the method according to any of claims 1-6.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105005839A (en) * | 2015-01-07 | 2015-10-28 | 泰华智慧产业集团股份有限公司 | GPS monitoring system for urban management and operating method of system |
| CN105550789A (en) * | 2016-02-19 | 2016-05-04 | 上海果路交通科技有限公司 | Method for predicting bus taking passenger flow |
| CN106529754A (en) * | 2016-06-27 | 2017-03-22 | 江苏智通交通科技有限公司 | Taxi operation condition assessment method based on big data analysis |
| CN107273819A (en) * | 2017-05-26 | 2017-10-20 | 毛亦炜 | A kind of bus passenger number statistics application method |
| CN107741944A (en) * | 2017-08-09 | 2018-02-27 | 成都路行通信息技术有限公司 | A kind of electronic map simulation track back method and system |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105005839A (en) * | 2015-01-07 | 2015-10-28 | 泰华智慧产业集团股份有限公司 | GPS monitoring system for urban management and operating method of system |
| CN105550789A (en) * | 2016-02-19 | 2016-05-04 | 上海果路交通科技有限公司 | Method for predicting bus taking passenger flow |
| CN106529754A (en) * | 2016-06-27 | 2017-03-22 | 江苏智通交通科技有限公司 | Taxi operation condition assessment method based on big data analysis |
| CN107273819A (en) * | 2017-05-26 | 2017-10-20 | 毛亦炜 | A kind of bus passenger number statistics application method |
| CN107741944A (en) * | 2017-08-09 | 2018-02-27 | 成都路行通信息技术有限公司 | A kind of electronic map simulation track back method and system |
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