Checkpoint flow early warning method based on mobile police affairs
A traffic and policing technology, which is applied in the field of checkpoint traffic early warning based on mobile policing, can solve the problem that traffic police cannot be deployed to abnormal road sections in time, and achieve the effects of improving referenceability, improving work efficiency, and simplifying the configuration process
Inactive Publication Date: 2021-02-05
TRAFFIC MANAGEMENT RES INST OF THE MIN OF PUBLIC SECURITY
View PDF9 Cites 5 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0003] In order to solve the problem that traffic police cannot be deployed to abnormal road sections in time in the existing traffic management methods, the present invention provides a checkpoint flow early warning method based on mobile policing, which can ensure that traffic police can timely Discover abnormal road sections, simplify the traffic police’s configuration process of checkpoint flow warning parameters, and then ensure that the traffic police can optimize the checkpoint layout and improve the operation and maintenance level of checkpoint equipment
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0041] Such as figure 1 As shown, the present invention is a mobile police-based checkpoint traffic early warning method, which includes the following steps.
[0042] S1: Construct differential autoregressive moving average model ARIMA.
[0043] S2: Confirm the main road to be monitored; obtain the specific date of the forecast day.
[0044] S3: Set: the forecast day is week τ, and set the period number ξ selected by the observation data;
[0045] Collect all the historical traffic flow data of all checkpoints on the arterial road to be monitored within the ξ week before the forecast day and every week τ in the whole day; after preprocessing the collected historical traffic flow data, record it as after this preprocessing Sample data L i , where ξ is a positive integer; preprocess the collected historical traffic flow data, and the preprocessing content includes:
[0046] a1: Keep the checkpoint data for which the average daily number of vehicles in one direction is greate...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more PUM
Login to view more Abstract
The invention provides a Checkpoint flow early warning method based on mobile police affairs, which can ensure that traffic polices can discover abnormal road sections in time, simplify the configuration process of Checkpoint flow early warning parameters by the traffic polices, and further ensure that the traffic polices can optimize Checkpoint distribution points and improve the operation and maintenance level of Checkpoint equipment. In the technical scheme of the invention, the traffic flow of the prediction day is predicted through the differential autoregressive moving average model ARIMA, and the traffic police can receive the early warning information before the traffic abnormality occurs once the traffic abnormality occurs by setting the early warning threshold, so that the traffic police can arrive at an abnormal place in time, and the problem is solved in time; based on historical data, a differential autoregressive moving average model ARIMA is established for a main trunkroad to be monitored on the basis of each day of a week, and it is ensured that a traffic flow passing predicted value predicted by the differential autoregressive moving average model ARIMA conformsto the characteristics of the peak value and valley value of the Checkpoint daily flow of each day in urban life.
Description
technical field [0001] The invention relates to the technical field of intelligent traffic monitoring, in particular to a checkpoint flow early warning method based on mobile police. Background technique [0002] In the existing traffic management methods, the traffic police are often dispatched to respond to traffic abnormalities when traffic abnormalities occur on a certain road section. The arrival of the traffic police is often later than the time of the accident; although there are also managers who will predict in advance because of their experience The road section where the problem occurs, but because it relies too much on personal experience, it is not possible to accurately determine specific parameters such as time and location. Contents of the invention [0003] In order to solve the problem that traffic police cannot be deployed to abnormal road sections in time in the existing traffic management methods, the present invention provides a checkpoint flow early ...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more Application Information
Patent Timeline
Login to view more Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06F17/18
CPCG06F17/18G06Q10/04
Inventor 陆杨张亚洲陆伟佳张长辉季晨琦黄辉莫子兴
Owner TRAFFIC MANAGEMENT RES INST OF THE MIN OF PUBLIC SECURITY
Who we serve
- R&D Engineer
- R&D Manager
- IP Professional
Why Eureka
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Social media
Try Eureka
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap