Traffic management system and method based on big data, storage medium and equipment

Abstract

The invention discloses a traffic management system and method based on big data, a storage medium and equipment, and relates to the technical field of traffic management. Comprising a lane recognition module, a traffic flow recognition module, a pedestrian flow recognition module, a traffic indication assembly recognition module, an accident handling module, a master control platform and a management module which are connected in sequence. According to the invention, on the basis of monitoring the road condition information, the congestion condition is judged, and the management strategy is generated in a targeted manner, so that the human flow and the traffic flow are managed, congestion is effectively prevented, and efficient traffic management is realized; meanwhile, the accident handling efficiency can be improved, and traveling is more efficient.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic management, and in particular, to a traffic management system, method, storage medium and device based on big data. Background Art

[0002] The application of new-generation information technologies such as big data and artificial intelligence has promoted the development of cities and is also changing people's ways of life and work. Nowadays, people are using technologies such as big data to solve problems such as traffic in cities.

[0003] In recent years, with the rapid development of China's urbanization process, the popularization process of automobiles has also accelerated, and various traffic problems brought about by this have gradually emerged. Problems such as traffic congestion, road accidents and urban air pollution have become common problems in major cities. Hohhot is making efforts to build a national comprehensive transportation hub. The railway construction has maintained rapid growth, the highway network has been further improved, and its radiation capacity in the regional comprehensive transportation network has been gradually enhanced. The comprehensive three-dimensional traffic and logistics network in Hohhot has basically taken shape. In terms of highways, the large number of automobiles makes traffic management in the Hohhot area relatively difficult.

[0004] Therefore, it is an urgent problem for those skilled in the art to propose a traffic management system, method, storage medium and device based on big data to solve the difficulties existing in the prior art. Summary of the Invention

[0005] In view of this, the present invention provides a traffic management system, method, storage medium and device based on big data. Based on the monitoring of road condition information, the congestion situation is judged, and corresponding management strategies are generated to manage the flow of people and vehicles, effectively prevent congestion, realize efficient management of traffic, and at the same time improve the efficiency of accident handling and make travel more efficient.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A traffic management system based on big data includes a lane recognition module, a vehicle flow recognition module, a pedestrian flow recognition module, a traffic indication component recognition module, an accident handling module, a general control platform and a management module connected in sequence; wherein,

[0008] The lane recognition module is used to recognize the lane identification information of the monitoring area;

[0009] The vehicle flow recognition module is used to recognize the vehicle flow information;

[0010] The pedestrian flow recognition module is used to recognize the pedestrian flow information;

[0011] The traffic indication component recognition module is used to recognize the road traffic state;

[0012] An accident handling module, used to identify the accident occurrence location and occurrence status information;

[0013] A general control platform, used to receive lane identification information, vehicle flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information, and generate traffic flow management strategies;

[0014] A management module, used to conduct traffic management according to traffic flow management strategies.

[0015] For the above system, optionally, the lane identification module includes a camera, a line type identification unit, and a color identification unit connected in sequence;

[0016] The camera is used to identify the contour shape and quantity of the detected lane lines;

[0017] The line type identification unit is used to identify the line type of the lane lines according to the contour shape and quantity of the lane lines;

[0018] The color identification unit is used to determine the color of the lane lines according to the lane line pixel values and color intervals.

[0019] For the above system, optionally, the vehicle flow identification module uses a vehicle flow monitoring and identification camera to monitor the road vehicle flow in real time.

[0020] For the above system, optionally, the pedestrian flow identification module builds in the PaddleDetection algorithm to achieve pedestrian flow statistics.

[0021] For the above system, optionally, the traffic indication component identification module includes a road traffic sign unit and a traffic light status unit connected in sequence;

[0022] The road traffic sign unit is used to identify road facilities that convey guiding, restrictive, warning, or indicating information in words or symbols;

[0023] The traffic light status unit is used to identify the traffic light status, including the light color information and remaining time information of the signal lights.

[0024] A traffic management method based on big data, implementing a traffic management system based on big data as described in any one of the above, includes the following steps:

[0025] Obtain lane identification information, vehicle flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information of the monitoring area;

[0026] Based on the lane identification information, vehicle flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information, generate traffic flow management strategies;

[0027] Traffic management is achieved based on traffic flow management strategies.

[0028] A storage medium includes stored instructions. When the instructions run, they control the device where the storage medium is located to execute the above-mentioned traffic management method based on big data.

[0029] An electronic device includes a memory and one or more instructions. One or more instructions are stored in the memory and are configured to be executed by one or more processors to execute the above-mentioned traffic management method based on big data.

[0030] As can be seen from the above technical solutions, compared with the prior art, the present invention provides a traffic management system, method, storage medium and device based on big data, which has the following beneficial effects: Based on the monitoring of road condition information, the present invention judges the congestion situation and generates targeted management strategies, thereby managing the traffic flow of people and vehicles, effectively preventing congestion, achieving efficient traffic management, and at the same time improving the accident handling efficiency and making travel more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0032] Figure 1 It is a block diagram of a traffic management system based on big data provided by the present invention;

[0033] Figure 2 It is a flowchart of a traffic management method based on big data provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0035] Refer to Figure 1 As shown, the present invention discloses a traffic management system based on big data, including a lane recognition module, a traffic flow recognition module, a pedestrian flow recognition module, a traffic indication component recognition module, an accident handling module, a general control platform and a management module connected in sequence; wherein,

[0036] A lane recognition module for recognizing lane identification information in a monitoring area;

[0037] A traffic flow recognition module for recognizing traffic flow information;

[0038] A pedestrian flow recognition module for recognizing pedestrian flow information;

[0039] A traffic indication component recognition module for recognizing the road traffic status;

[0040] An accident handling module for recognizing the accident occurrence location and occurrence status information;

[0041] A total control platform for receiving lane identification information, traffic flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information, and generating a traffic flow management strategy;

[0042] A management module for traffic management according to the traffic flow management strategy.

[0043] Furthermore, the lane recognition module includes a camera, a line type recognition unit, and a color recognition unit connected in sequence;

[0044] The camera is used to recognize the contour shape and quantity of the detected lane lines;

[0045] The line type recognition unit is used to recognize the line type of the lane lines according to the contour shape and quantity of the lane lines;

[0046] The color recognition unit is used to determine the color of the lane lines according to the lane line pixel values and color ranges.

[0047] Specifically, the specific content of the lane recognition module for recognizing lane identification information in the monitoring area is as follows:

[0048] Obtain a road image dataset based on the camera;

[0049] Divide the road image into grids, and perform lane line detection on each row of grids along the road direction;

[0050] Aggregate the lane line detection results of each row of grids to obtain a lane line monitoring area;

[0051] Adopt a row-level based lane line detection method, divide the picture into grids, then predict the position of the lane lines in each row, and finally aggregate the results of each row together to obtain several lane lines;

[0052] Perform refined processing on the lane line monitoring area to obtain lane lines with accurate positions;

[0053] After performing morphological filtering on the lane line monitoring area, binaryzation processing is carried out; then edge detection is performed on the region of interest for lane line detection after binaryzation processing to extract the lane line contour, obtaining lane lines with accurate positions.

[0054] Analyze the lane line type according to conditions such as the shape and quantity of the lane line contour, such as solid lines and dashed lines.

[0055] Then, according to the lane line pixel values and color intervals, determine the color of the lane line. Lane lines are mainly divided into white and yellow. The main content of color discrimination is as follows:

[0056] Convert the original road image to the HSV color model;

[0057] Analyze the pixel value distributions of white and yellow to find the corresponding intervals;

[0058] According to the accurate position of the lane line, extract the color interval of the lane line in the converted road image;

[0059] Determine the color of the lane line according to the lane line pixel values and the threshold values of yellow and white color intervals.

[0060] Furthermore, the traffic flow recognition module uses a traffic flow monitoring and recognition camera for real-time monitoring of road traffic flow.

[0061] Furthermore, the pedestrian flow recognition module builds in the PaddleDetection algorithm to achieve pedestrian flow statistics.

[0062] Specifically, the specific steps for the PaddleDetection algorithm to perform pedestrian flow statistics are as follows:

[0063] Data preparation, obtaining data from the Caltech Pedestyain dataset and the CityPersons dataset;

[0064] Select the FairMOT model and train the FairMOT model to obtain a trained FairMOT model;

[0065] Implement pedestrian flow statistics based on the FairMOT model.

[0066] Furthermore, the traffic indication component recognition module includes a road traffic sign unit and a traffic light status unit connected in sequence;

[0067] The road traffic sign unit is used to recognize road facilities that convey guiding, restrictive, warning, or indicating information in the form of words or symbols;

[0068] The traffic light status unit is used to recognize the status of traffic lights, including the light color information and remaining time information of the signal lights.

[0069] In a specific embodiment, the following is included:

[0070] Start the system, and obtain lane identification information, traffic flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information through the lane recognition module, traffic flow recognition module, pedestrian flow recognition module, traffic indication component recognition module and accident handling module, and transmit them to the general control platform;

[0071] The general control platform analyzes and processes the received lane identification information, traffic flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information, and generates a traffic flow management strategy; the management module conducts traffic management according to the traffic flow management strategy.

[0072] Among them, the traffic flow management strategy includes road planning and layout, traffic signal control, traffic demand management (public transportation priority), traffic control and restriction, traffic information release and navigation system.

[0073] For road planning and layout, by reasonably planning the width, length, intersection settings, etc. of the road, the traffic capacity of the road can be improved and traffic congestion can be reduced.

[0074] For traffic signal control, by reasonably setting traffic signals and optimizing signal timing, the orderly passage of traffic flow can be achieved and traffic congestion can be reduced.

[0075] For traffic demand management (public transportation priority), by setting bus lanes, optimizing bus routes and other measures, citizens can be encouraged to use public transportation, reduce the use of private cars, and relieve traffic pressure.

[0076] In the case of serious traffic congestion, it is necessary to take traffic control and restriction measures. By restricting the passage of vehicles within a specific time period or specific area, traffic congestion can be effectively reduced and the traffic capacity of the road can be improved.

[0077] The traffic information release and navigation system can provide citizens with real-time traffic information, help them choose the best travel route, and reduce traffic congestion. Through the guidance of the intelligent navigation system, the traffic flow can be reasonably dispersed to achieve the purpose of traffic flow management.

[0078] Corresponding to Figure 1 the described system, the embodiment of the present invention also provides a traffic management method based on big data, and its flowchart is as Figure 2 shown, including the following steps:

[0079] Obtain lane identification information, traffic flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information of the monitoring area;

[0080] Generate a traffic flow management strategy based on lane identification information, traffic flow information, pedestrian flow information, road traffic conditions, accident location and occurrence status information;

[0081] Implement traffic management based on the traffic flow management strategy.

[0082] An embodiment of the present invention also provides a storage medium, which includes stored instructions. When the instructions run, the device where the storage medium is located is controlled to execute the above-mentioned traffic management method based on big data.

[0083] An embodiment of the present invention also provides an electronic device, including a memory, and one or more instructions. One or more of the instructions are stored in the memory and are configured to be executed by one or more processors to perform the traffic management method based on big data.

[0084] The various embodiments in this specification are described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. The same or similar parts among the various embodiments can be referred to each other. For the methods disclosed in the embodiments, since they correspond to the systems disclosed in the embodiments, the descriptions are relatively simple. For the relevant parts, refer to the descriptions of the system part.

[0085] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A traffic management system based on big data, characterized in that It includes a lane recognition module, a traffic flow recognition module, a pedestrian flow recognition module, a traffic indication component recognition module, an accident handling module, a general control platform, and a management module that are connected in sequence; among them, The lane recognition module is used to recognize the lane identification information of the monitoring area; The traffic flow recognition module is used to recognize the traffic flow information; The pedestrian flow recognition module is used to recognize the pedestrian flow information; The traffic indication component recognition module is used to recognize the road traffic status; The accident handling module is used to recognize the accident occurrence location and occurrence status information; The general control platform is used to receive the lane identification information, traffic flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information, and generate a traffic flow management strategy; The management module is used to conduct traffic management according to the traffic flow management strategy.

2. The traffic management system based on big data according to claim 1, characterized in that The lane recognition module includes a camera, a line type recognition unit, and a color recognition unit that are connected in sequence; The camera is used to recognize the contour shape and quantity of the detected lane lines; The line type recognition unit is used to recognize the line type of the lane lines according to the contour shape and quantity of the lane lines; The color recognition unit is used to determine the color of the lane lines according to the lane line pixel values and color ranges.

3. The traffic management system based on big data according to claim 1, characterized in that The traffic flow recognition module adopts a traffic flow monitoring and recognition camera for real-time monitoring of road traffic flow.

4. The traffic management system based on big data according to claim 1, characterized in that The pedestrian flow recognition module internally sets the PaddleDetection algorithm to achieve pedestrian flow statistics.

5. The traffic management system based on big data according to claim 1, characterized in that The traffic indication component recognition module includes a road traffic sign unit and a traffic light status unit that are connected in sequence; The road traffic sign unit is used to recognize the road facilities that convey guiding, restricting, warning, or indicating information in words or symbols; The traffic light status unit is used to recognize the traffic light status, including the light color information and remaining time information of the signal lights.

6. A traffic management method based on big data, characterized in that, Implementing the traffic management system based on big data according to any one of claims 1-5 includes the following steps: Obtain the lane identification information, traffic flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information of the monitoring area; Generate a traffic flow management strategy based on the lane identification information, traffic flow information, pedestrian flow information, road traffic status, accident occurrence location and occurrence status information; Implement traffic management based on the traffic flow management strategy.

7. A storage medium, characterized in that, The storage medium includes stored instructions, wherein when the instructions run, they control the device where the storage medium is located to execute and implement a traffic management method based on big data as described in claim 6.

8. An electronic device, characterized in that, The electronic device includes a memory, and one or more instructions, wherein one or more instructions are stored in the memory and are configured to be executed by one or more processors to implement a traffic management method based on big data as described in claim 6.

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