CN114333336A - Method for detecting and managing traffic flow among expressway cells - Google Patents
Method for detecting and managing traffic flow among expressway cells Download PDFInfo
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- CN114333336A CN114333336A CN202210262452.1A CN202210262452A CN114333336A CN 114333336 A CN114333336 A CN 114333336A CN 202210262452 A CN202210262452 A CN 202210262452A CN 114333336 A CN114333336 A CN 114333336A
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Abstract
The invention belongs to the technical field of highway traffic control, and particularly relates to a method for detecting and managing traffic flow among highway cells. Selecting a detection road section from a section of highway lane without a branch road, dividing the detection road section into a large section and a small section, and arranging a small section detection station at each small section detection node, wherein the small section detection station is fixed at a guardrail of the small section detection node; the method comprises the steps of obtaining the actual vehicle speed and the information of a driving lane of a vehicle of a cell detection node, and screening and storing the actual vehicle speed information according to the set confidence coefficient and the set confidence interval. Factors which have influences on the speed limit of the large-interval road sections include the actual speed of vehicles, the road characteristics of each large-interval road section, the natural environment, the road congestion condition of the adjacent large-interval road sections, the quantity of vehicles entering and exiting from a high-speed entrance and a high-speed exit and the like, and the quantity of vehicles entering the high-speed entrance is restrained to realize the balance of road pressure.
Description
Technical Field
The invention belongs to the technical field of highway traffic control, and particularly relates to a method for detecting and managing traffic flow among highway cells.
Background
Because the speed of vehicles on different sections of the highway is not only affected by weather factors such as rain and snow, but also affected by accidents, holidays and section characteristics, a more detailed traffic flow speed detection method is needed to be designed so as to conveniently manage the high-speed traffic flow.
Disclosure of Invention
In order to solve the problem that the speed of a highway cannot be measured finely and fine management cannot be realized in the prior art, the scheme provides a method for detecting and managing traffic flow among cells of the highway.
The technical scheme adopted by the invention is as follows:
a method for detecting traffic flow among expressway cells comprises the following steps:
step A1: selecting a detection road section from a section of expressway lane without branch road, dividing the detection road section into a plurality of continuous large interval road sections according to road characteristics, and taking the terminal point of each large interval road section as the starting point of the next large interval road section;
step A2: each large inter-cell road section is divided into a plurality of continuous inter-cell road sections at equal distances; the terminal point of each section between the cells is used as the starting point of the section between the next cells; selecting the starting point position of each section between the cells as a cell detection node, and arranging a cell detection station at each cell detection node, wherein the cell detection station is fixed at a guardrail of the cell detection node;
the cell detection station comprises an image collector, a vehicle speed detector and a cell controller; the image collector is used for collecting images of passing vehicles, and the cell controller judges the driving lanes of the vehicles according to the number of lane isolation lines between the vehicles and the cell detection station in the collected images; the vehicle speed detector is used for detecting the vehicle speed;
step A3: and a vehicle detection station is arranged at the starting point of each large interval road section, a station manager is configured at each vehicle detection station, and the station managers are in communication connection with all the cell controllers in the corresponding large interval road sections so as to acquire the actual vehicle speed and the information of the driving lane of the vehicle of the cell detection node, and screen and store the actual vehicle speed information according to the set confidence degree and confidence interval.
Optionally: a vehicle detection station is arranged at the starting point of each large section road section; this vehicle detection station is including door type support and camera, door type support spanes all lanes of highway one-way direction, and the camera sets up on door type support, all corresponds directly over every lane and sets up a camera, and the equal vertical downwards of pointing of camera to be used for the vehicle quantity in each lane in this large compartment road section of statistics respectively.
Optionally: the road characteristics include tunnels, bridges, number of lanes, curves, uphill slopes, or downhill slopes.
Optionally: the cell detection station also comprises a post rod, an annular binding band and a C-shaped positioner; the post rod is vertically arranged, two C-shaped positioners are arranged at the lower part of the post rod, and the two C-shaped positioners are arranged one above the other; a guardrail is arranged at the edge of the section between the communities and comprises a pile; the C-shaped positioner can be meshed with the outer side wall of the pile column and is magnetically attracted and positioned by a magnet arranged on the inner side of the C-shaped positioner; the outer side of the C-shaped positioner is provided with a groove, and an annular binding band can be embedded into the groove and binds and fixes the C-shaped positioner to the pile; the image collector, the vehicle speed detector and the cell controller are all fixed on the upper portion of the post rod and are all higher than the guardrail.
Optionally: a support table is arranged at the upper end of the post rod, and the cell controller is positioned below the support table and fixed on the post rod; the image collector and the vehicle speed detector are both arranged on the supporting platform, the supporting platform is also provided with a solar panel, and the solar panel can charge a storage battery arranged in the cell controller.
The traffic flow management method based on the inter-cell traffic flow detection method of the expressway comprises an inter-cell speed limit management method, wherein the inter-cell speed limit management method comprises the following steps of:
step B1: a plurality of LED display panels are arranged on the door-shaped bracket; the upper part of each lane corresponds to one LED display panel, and each LED display panel respectively displays the speed limit value of the corresponding lane;
step B2: and each LED display panel is in communication connection with the site manager, and the site manager modifies the speed limit value of each lane of the large interval road section according to the actual speed of each inter-cell detection point in the corresponding large interval road section and displays the speed limit value by the LED display panels.
Optionally: the method also comprises a large-interval speed limit management method, and the large-interval speed limit management method comprises the following steps:
step C1: the method comprises the steps that site managers at all vehicle detection sites in a detection road section are connected with a cloud server in a communication mode; the cloud server collects the number of vehicles in any large interval road section on the detection road section, and compares the number of vehicles in adjacent large interval road sections;
step C2: when the number of vehicles in any one large interval road section continuously increases and exceeds a threshold value or/and exceeds a specified time, the cloud server controls one or more vehicle detection stations of the large interval road section in front of the large interval road section to modify the speed limit value.
Optionally: the door-shaped bracket is also provided with an environment detector, and the environment detector comprises a raindrop sensor, a light intensity sensor and a wind speed and direction sensor; the raindrop sensor, the light intensity sensor and the wind speed and direction sensor are electrically connected with the station manager; a database is arranged in the cloud server, a road surface friction model, a visibility model and a natural wind influence model of the road characteristics of each large section of road are stored in the database, the raindrop sensor is used for detecting rainfall conditions to enable the cloud server to be matched with the road surface friction model, the light intensity sensor is used for detecting illumination intensity to enable the cloud server to be matched with the visibility model, and the wind speed and direction sensor is used for detecting wind speed and wind direction to enable the cloud server to be matched with the natural wind influence model; and the cloud server modifies the speed limit value of each large section according to the road surface friction model, the visibility model and the natural wind influence model.
Optionally: the method for detecting the speed limit of the road section comprises the following steps:
step D1: the cloud server associates the number of vehicles in the detected road section with the number of vehicles entering the adjacent high-speed entrance toll stations according to the estimated arrival time, and artificially gives an association degree, wherein the association degree is the ratio of the number of vehicles passing through the high-speed entrance and the detected road section to the number of all vehicles entering the high-speed entrance;
step D2: and the cloud server modifies the speed limit value of each large section road section according to the association degree and the number of vehicles passing through the high-speed entrance toll station.
Optionally: the method also comprises a road section detection current limiting method, and the road section detection current limiting method comprises the following steps:
step E1: the cloud server marks the large road sections with the number of vehicles continuously increasing and exceeding a threshold value or/and exceeding specified time as the pre-congestion road sections;
step E2: the cloud server counts the number of pre-jammed road sections on the same detection road section, and performs scheduling control on the number of channels of the toll station at the high-speed entrance with the relevance degree with the detection road section according to the number of the pre-jammed road sections so as to limit the speed of entering the vehicle from the high-speed entrance.
The invention has the beneficial effects that:
1. according to the scheme, the highway is divided into a plurality of large-interval road sections according to the characteristics of the road sections, and the large-interval road sections are also divided into a plurality of small-interval road sections, so that the vehicle speed can be conveniently detected according to the characteristics of an actual road, the accuracy of vehicle speed detection can be effectively improved by using a big data measurement mode, and further the road pressure can be conveniently improved;
2. the scheme is provided with a vehicle detection station and a cell detection station, wherein the vehicle detection station is provided with a vertically downward camera to count the number of vehicles, and a door-shaped support is adopted for supporting, so that the road surface is not required to be damaged in the construction process; the community detection station can be arranged on a guardrail at the roadside of the highway, so that the community detection station can be simply and conveniently arranged, and the identity of the installation height of the community detection station can be effectively ensured;
3. in the scheme, the speed limit is adjusted to ensure the balance of road pressure in the driving process of the vehicles on the expressway, and factors influencing the speed limit of the large-interval road section comprise the actual speed of the vehicles in each small interval, the road characteristics of each large-interval road section, the natural environment, the road congestion condition of the adjacent large-interval road sections, the number of vehicles entering and exiting from a high-speed inlet and a high-speed outlet and the like; in addition, the number of vehicles entering a high-speed entrance can be restrained by predicting the congestion condition of the large-area road section, and the road pressure can be balanced.
Drawings
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 invention.
FIG. 1 is a view of a division structure between a large area and a small area of a highway;
fig. 2 is a block diagram of a cell detection station;
FIG. 3 is a state diagram of a highway collocated vehicle detection station;
FIG. 4 is a communication diagram of a vehicle inspection station, a cell inspection station, and a cloud server;
fig. 5 is a traffic flow intelligent management model of a highway.
Description of the drawings: 1-a highway lane; 101-a high-speed outlet; 102-a high speed inlet; 2-a vehicle inspection station; 201-site manager; 202-an environment detector; 203-a camera; 204-LED display panel; 205-a projection device; 3-cell detection station; 301-solar panel; 302-an image collector; 303-vehicle speed detector; 304-a post; 305-a cell controller; 306-a loop strap; 307-C-shaped locators; 4-cloud server.
Detailed Description
The technical solution in the present embodiment will be clearly and completely described below with reference to the accompanying drawings.
In the scheme, a highway lane 1 is selected as a detection road section, the detection road section has no branch between the detection road sections, the detection road section is divided into a plurality of continuous large interval road sections according to road characteristics, as shown in fig. 1, two large interval road sections are shown, in an actual segmentation, k (1) -k (m) can be included, m large interval road sections are counted, the terminal point of each large interval road section is used as the starting point of the next large interval road section, the road characteristics comprise a tunnel, a bridge, the number of lanes, curves, an ascending slope or a descending slope, and the speed of the same vehicle on the road section with the same characteristics on an expressway is not greatly different on the road section, so that the measured speed of the vehicle can represent the running speed of the vehicle on the road section. Furthermore, each large inter-cell segment is equally spaced into a plurality of consecutive inter-cell segments, k (1, 1) -k (1, n); the end point of each inter-cell segment serves as the starting point of the next inter-cell segment.
Example 1
As shown in fig. 2, the present embodiment designs a cell inspection station 3, and the cell inspection station 3 includes an image collector 302, a vehicle speed detector 303, a cell controller 305, a post 304, a ring-shaped strap 306, and a C-shaped locator 307. The community detection station 3 can be installed on a guardrail arranged on the edge of the expressway at the section between communities, so that the lane where the vehicle runs and the speed of the vehicle where the vehicle runs can be conveniently and quickly detected, and the lane information and the speed information of the vehicle on the expressway can be quickly sampled.
A guardrail is often arranged at the edge of the expressway, and comprises piles; the district detects station 3 through the stake of fixing to the guardrail, not only can make things convenient for in unifying the mounting height to district detects station 3, can also borrow current structure, improves the convenience of installation.
The posts 304 are vertically arranged, and in use, the posts 304 serve as vertical supports.
Two C-shaped locators 307 are provided at the lower portion of the post 304, the two C-shaped locators 307 being arranged one above the other, the C-shaped locators 307 being able to engage the outer sidewall of the post and being magnetically positioned by magnets provided inside the C-shaped locators 307.
A groove is provided on the outside of the C-shaped retainer 307, and a circular strap 306 can be inserted into the groove and tie the C-shaped retainer 307 to the pile. The C-shaped positioner 307 can facilitate the adjustment of the detection heights of the image collector 302 and the vehicle speed detector 303, and prevent the exposed dog from shifting during the binding process with the circular strap 306.
A support base is provided at the upper end of the mast 304, and the cell controller 305 is located below the support base and fixed to the mast 304.
The image collector 302 is arranged on the support platform, the image collector 302 is used for collecting images of passing vehicles, and the cell controller 305 judges the driving lanes of the vehicles according to the number of lane isolation lines between the vehicles and the cell detection station 3. A vehicle speed detector 303 is provided on the support base, and the vehicle speed detector 303 detects a vehicle speed. The cell controller 305 is fixed to the upper part of the column 304, and the solar panel 301 provided above the support stand can charge a battery provided in the cell controller 305. After the cell detection station 3 is installed, the image collector 302, the vehicle speed detector 303 and the cell controller 305 are all fixed on the upper part of the post 304 and are all higher than the guard rail, and all face to the expressway.
When the cell detection station 3 in this embodiment is used, the starting point position of each inter-cell road section is selected as a cell detection node, one cell detection station 3 is arranged at each cell detection node, and the cell detection station 3 is fixed at a guardrail of the cell detection node. The cell detection node is a sampling point for sampling the vehicle speed of the vehicle on each lane, and can assist workers in obtaining more actual vehicle speed information, so that big data analysis and balanced management of road pressure are facilitated.
Through the setting of district detection station, can make and carry out the multiple spot in the highway section of large interval and test the speed to can improve the accuracy that tests the speed.
Example 2
As shown in fig. 3, the present embodiment is designed with a vehicle inspection station 2, and the vehicle inspection station 2 is provided at the starting point of each large inter-zone segment and is connected in communication with the cell inspection stations 3 of all inter-zone segments within the large inter-zone segment. The method comprises the steps of obtaining the actual vehicle speed and the information of a driving lane of a vehicle of a cell detection node, and screening and storing the actual vehicle speed information according to the set confidence coefficient and the set confidence interval.
The vehicle inspection station 2 comprises a door-shaped bracket, a camera 203, an LED display panel 204, a station manager 201, a projection device 205 and the like, wherein the vehicle inspection station 2 comprises the structure. The site manager 201 may be an existing computer, server, or industrial personal computer, which mainly implements functions of receiving, storing, and forwarding data of the camera 203, and implements display control of the LED display panel 204, and on/off control of the projection device 205 or/and switching control of a projection model pre-stored in the projection device, and all existing devices capable of implementing the above functions may be regarded as the site manager 201 of the embodiment.
The door type support crosses all lanes in the one-way direction of the expressway, the cameras 203 are arranged on the door type support, one camera 203 is correspondingly arranged right above each lane, the direction of the camera 203 is vertical downward, and the cameras 203 are respectively used for counting the number of vehicles in each lane in the large-interval road section and collecting the speed of the vehicles passing through the detection node. One camera 203 corresponds to the number of vehicles passing by which one lane is detected. Through vertical camera 203 down, make statistics of the quantity of vehicle to the door type support of adoption supports, thereby need not to destroy the road surface in the work progress, thereby can reduce the application cost, and its installation can not influence highway's use yet.
An LED display panel 204 is arranged above each lane, and the LED display panel 204 is used for prompting speed limit; each LED display panel 204 is communicatively coupled to site manager 201; the station managers 201 at all the vehicle detection stations 2 are in communication connection with a cloud server 4; the cloud server 4 collects the number of vehicles in all the large-interval road sections, so that the vehicle speed limit value of each large interval can be adjusted according to the number of vehicles in all the large-interval road sections.
Each vehicle detection station 2 is provided with a station manager 201, the station manager 201 is in communication connection with all corresponding cell controllers 305 to acquire the actual vehicle speed and the information of the driving lane of the vehicle of the cell detection node, and the actual vehicle speed information is screened and stored according to the set confidence and confidence interval. The confidence level and confidence interval can be artificially designated according to the requirement or can be artificially analyzed according to historical data.
The projection device 205 is arranged on the door-shaped support, points vertically downwards and can project a speed bump and a driving direction prompt; when the speed limit prompt changed by the vehicle detection station 2 is smaller than the standard speed limit, the projection device 205 projects a deceleration strip mark, thereby prompting the vehicle to decelerate; when the vehicle needs to perform the prompt diversion from the exit 101 of the highway lane 1, the projection device 205 may project a diversion indication arrow, so as to guide a part of the vehicle to leave the highway from the exit 101 of the highway, thereby reducing traffic pressure on the highway. The projection device 205 can be used for more clearly prompting a driver of a vehicle, so that the driver can conveniently decelerate, and the road pressure of each road section of the expressway can be balanced. Since the deceleration sign of the projection device 205 is a non-material deceleration strip, even if the vehicle is overspeed or the speed limit value is temporarily changed, the driving safety of the highway is not affected. In addition, the speed is limited by changing the speed limit value, the principle is that the speed of the non-compliant vehicles is limited by using the lanes complying with the speed limit requirement, when most vehicles run according to the speed limit value requirement, more vehicles are forced or the speed of the vehicles is reduced to the range of the speed limit value, and therefore the effect of managing the speed of the expressway in different sections is achieved.
Example 3
As shown in fig. 1 to 4, with the structures of embodiment 1 and embodiment 2, this embodiment designs a method for detecting traffic flow between expressway cells, including the following steps:
step A1: selecting a detection road section from a section of expressway lane without branch road, dividing the detection road section into a plurality of continuous large interval road sections according to road characteristics, and taking the terminal point of each large interval road section as the starting point of the next large interval road section;
step A2: each large inter-cell road section is divided into a plurality of continuous inter-cell road sections at equal distances; the terminal point of each section between the cells is used as the starting point of the section between the next cells; selecting the starting point position of each section between the cells as a cell detection node, and arranging a cell detection station at each cell detection node, wherein the cell detection station is fixed at a guardrail of the cell detection node;
step A3: and a vehicle detection station is arranged at the starting point of each large interval road section, a station manager is configured at each vehicle detection station, and the station managers are in communication connection with all the cell controllers in the corresponding large interval road sections so as to acquire the actual vehicle speed and the information of the driving lane of the vehicle of the cell detection node, and screen and store the actual vehicle speed information according to the set confidence degree and confidence interval. Specifically, each cell controller 305 performs vehicle speed sampling and image acquisition on a vehicle passing through a cell detection node, judges a driving lane of the vehicle according to the number of lane isolation lines between the vehicle and the cell detection station 3, uploads information of the driving lane of the vehicle and the real-time vehicle speed of the vehicle to a station manager 201 at the vehicle detection station 2 after acquiring the information, and screens the information by the station manager 201 according to a set confidence interval and confidence degree, so that a large amount of corresponding information of the lane and the vehicle speed can be obtained, and reference can be provided for the balance and analysis of road pressure.
Example 4
As shown in fig. 1 to 4, with the structures of embodiment 1 and embodiment 2, this embodiment designs a traffic flow management method for an expressway, which includes an inter-cell speed limit management method, a large-cell speed limit management method, and a road section speed limit detection method. The boundaries between the different highway lanes in fig. 1 and 3 are indicated by dashed lines parallel to the highway, while the solid lines in fig. 1 and 3 represent isolated solid lines or traffic boundaries of the highway and the arrows represent traffic directions; the boundaries between inter-cell road segments are indicated by dashed lines perpendicular to the highway.
The inter-cell speed limit management method comprises the following steps:
step B1: a plurality of LED display panels 204 are arranged on the door-shaped bracket; the upper part of each lane corresponds to one LED display panel 204, and each LED display panel 204 respectively displays the speed limit value of the corresponding lane;
step B2: each LED display panel 204 is connected in communication with the site manager 201, and the site manager 201 modifies the speed limit value of each lane of the large block road section according to the actual vehicle speed of each inter-cell detection point in the corresponding large block road section, and the speed limit value is displayed by the LED display panel 204.
The large-compartment speed limit management method comprises the following steps:
step C1: the station managers 201 at all the vehicle detection stations 2 in a detection road section are commonly connected with a cloud server 4 in a communication mode; the cloud server 4 collects the number of vehicles in any large interval road section on the detection road section, and compares the number of vehicles in adjacent large interval road sections;
step C2: when the number of vehicles in any one large section of road continuously increases and exceeds a threshold value or/and exceeds a specified time, the cloud server 4 controls the vehicle detection stations 2 of one or more large sections of road in front of the coming direction of the large section of road to modify the speed limit value.
Such as: the vehicle detection station 2 of the k (4) road section detects the vehicle input amount of the k (4) road section, the detection result can be used as the output amount of the vehicle of the k (3) road section, the input amount minus the output amount of the vehicle of the k (3) road section is the vehicle quantity of the k (3) road section, when the vehicle quantity of the k (3) road section is continuously increased for a specified time or the vehicle quantity reaches a set threshold value, the cloud server 4 is used for controlling the k (2) road section in front of the vehicle coming direction of the k (3) road section to reduce the speed limit value, so that the vehicle quantity of the vehicle entering the k (3) road section is reduced, in addition, the speed limit value of the k (1) road section can be controlled to be linked with the speed limit value of the k (2) road section according to a set rule, and the probability that the k (2) road section is not blocked is reduced.
In addition, the speed limit management of a highway large interval can be carried out by detecting the environment, an environment detector 202 is also arranged on the door-shaped bracket, and the environment detector 202 comprises a raindrop sensor, a light intensity sensor and a wind speed and direction sensor; the raindrop sensor, the light intensity sensor and the wind speed and direction sensor are electrically connected with the station manager 201; a database is arranged in the cloud server 4, a road surface friction model, a visibility model and a natural wind influence model of each vehicle detection station 2 are stored in the database, the raindrop sensor is used for detecting rainfall conditions to enable the cloud server to be matched with the road surface friction model, the light intensity sensor is used for detecting illumination intensity to enable the cloud server to be matched with the visibility model, and the wind speed and direction sensor is used for detecting wind speed and wind direction to enable the cloud server to be matched with the natural wind influence model; and the cloud server 4 modifies the speed limit value of each large section according to the road surface friction model, the visibility model and the natural wind influence model. The road surface friction model is a corresponding relation curve of a road surface friction coefficient and a vehicle speed limit value, the visibility model is a corresponding relation curve of a vehicle visibility distance and a vehicle speed limit value, and the natural wind influence model is a corresponding relation curve of a wind speed and a risk and the vehicle speed limit value.
The method for detecting the speed limit of the road section comprises the following steps:
step D1: the cloud server 4 associates the number of vehicles in the detected road section with the number of vehicles entering the toll stations of the adjacent high-speed entrances 102 according to the estimated arrival time, and artificially gives an association degree, wherein the association degree is a ratio of the number of vehicles passing through the high-speed entrances and the detected road section to the number of all vehicles entering from the high-speed entrances, such as: if the degree of association is 0.5, it is considered that 50% of the vehicles entering from the high-speed entrance will pass through the vehicle inspection section;
step D2: the cloud server 4 may estimate the number of vehicles entering the detection road section according to the association degree, the number of vehicles passing through the high-speed entrance 102 toll station, and the distance from the high-speed entrance to the detection road section, so as to reduce the probability that the vehicles arrive at the same large-interval road section at the same time by modifying the speed limit value of each large-interval road section.
Example 5
As shown in fig. 1 to 4, with the structures of embodiment 1 and embodiment 2 and the existing toll booth structure of the highway entrance 102, this embodiment designs a traffic flow management method for a highway, and the traffic flow management method further includes a method for detecting a road section current limit, where the method for detecting a road section current limit includes the following steps:
step E1: the cloud server 4 marks the large road sections with the number of vehicles continuously increasing and exceeding a threshold value or/and exceeding a specified time as the pre-congestion road sections;
step E2: the cloud server 4 counts the number of pre-congested road sections on the same detected road section, and performs scheduling control on the number of channels of the toll station at the high-speed entrance 102 having a correlation with the detected road section according to the number of pre-congested road sections so as to limit the speed of entering the vehicle from the high-speed entrance. When the number of channels of the toll station is reduced, the number of vehicles entering the high-speed entrance can be reduced; and when the number of lanes at the toll booth increases, the number of vehicles entering the high-speed entrance can be increased.
A projection device 205 can be further arranged on the door-shaped bracket of the vehicle detection station 2, points vertically downwards and is used for projecting a speed bump and a driving direction prompt; when the vehicle needs to perform the prompt diversion from the exit 101 of the highway lane 1, the projection device 205 may project a diversion indication arrow, so as to guide a part of the vehicle to leave the highway from the exit 101 of the highway, thereby reducing and equalizing traffic pressure on the highway.
With the development of artificial intelligence and the improvement and development of ETC portal monitoring in the future, in the near future, a model of an inter-cell management system can be built by means of the artificial intelligence, as shown in FIG. 5, the collection of the quantity of vehicles and traffic flow speed of each large-cell road section and each inter-cell large-cell road section, the collection and deep learning of the vehicle information obtained by monitoring the ETC portal at each expressway entrance and exit and the data of each traffic gate of the expressway are utilized, the expressway network can be gridded in the future, the minimum interval can reach 1km, and the traffic condition in each inter-cell road section is carved and predicted in real time. Under the artificial intelligence, real-time traffic flow data, vehicle type data (cars, buses, trucks and the like), road pressure values (unblocked, slow running and congestion), traffic flow analysis data (minutes, hours, days, months, years), traffic flow prediction (mainly aiming at slow running and congestion), traffic accident data, meteorological data, traffic data analysis (easy-to-block time, easy-to-occur traffic accident time, easy-to-block reasons and the like), early warning prediction (real-time congestion, prediction congestion, abnormal traffic, dangerization vehicles, extreme weather and the like) and the like in a cell are realized, refined management ideas and methods are provided for traffic managers, one-cell strategy and one-cell strategy are realized, the problem of traffic management potential safety hazard sources is solved, passive traffic management is changed into active risk identification, and the effects of early intervention, safety risk reduction and the like are achieved.
The foregoing examples are provided for clarity of illustration only and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are intended to be within the scope of the invention.
Claims (10)
1. A method for detecting traffic flow among expressway cells is characterized by comprising the following steps: the method comprises the following steps:
step A1: selecting a detection road section from a section of expressway lane (1) without branch road, dividing the detection road section into a plurality of continuous large interval road sections according to road characteristics, and taking the terminal point of each large interval road section as the starting point of the next large interval road section;
step A2: each large inter-cell road section is divided into a plurality of continuous inter-cell road sections at equal distances; the terminal point of each section between the cells is used as the starting point of the section between the next cells; the starting point position of each section between the cells is selected as a cell detection node, a cell detection station (3) is arranged at each cell detection node, and the cell detection station (3) is fixed at the guardrail of the cell detection node;
the cell detection station (3) comprises an image collector (302), a vehicle speed detector (303) and a cell controller (305); the image collector (302) is used for collecting images of passing vehicles, and the cell controller (305) judges the driving lanes of the vehicles according to the number of lane isolation lines between the vehicles and the cell detection station (3) in the collected images; the vehicle speed detector (303) is used for detecting the vehicle speed;
step A3: the method comprises the steps that a vehicle detection station (2) is arranged at the starting point of each large interval road section, a station manager (201) is arranged at each vehicle detection station (2), the station manager (201) is in communication connection with all cell controllers (305) in the corresponding large interval road section to obtain the actual vehicle speed and the information of a driving lane of a vehicle of a cell detection node, and the actual vehicle speed information is screened and stored according to the set confidence degree and the confidence interval.
2. The inter-highway-cell traffic flow detection method according to claim 1, characterized by comprising: vehicle detection station (2) is including door type support and camera (203), door type support spanes all lanes of highway one-way direction, and camera (203) set up on door type support, all corresponds directly over every lane and sets up a camera (203), and the equal vertical downwards of pointing direction of camera (203) to be used for counting the vehicle quantity in each lane in this large interval road section respectively.
3. The inter-highway-cell traffic flow detection method according to claim 2, characterized in that: the road characteristics include tunnels, bridges, number of lanes, curves, uphill slopes, or downhill slopes.
4. The inter-highway-cell traffic flow detection method according to claim 1, characterized by comprising: the cell detection station (3) further comprises a post (304), an annular band (306) and a C-shaped locator (307); the post rod (304) is vertically arranged, two C-shaped locators (307) are arranged at the lower part of the post rod (304), and the two C-shaped locators (307) are arranged one above the other; a guardrail is arranged at the edge of the section between the communities and comprises a pile; the C-shaped positioner (307) can be used for occluding the outer side wall of the pile and is magnetically attracted and positioned by a magnet arranged on the inner side of the C-shaped positioner (307); the outer side of the C-shaped positioner (307) is provided with a groove, and an annular binding band (306) can be embedded into the groove and can bind and fix the C-shaped positioner (307) on the pile; the image collector (302), the vehicle speed detector (303) and the cell controller (305) are all fixed on the upper portion of the post rod (304) and are all higher than the guardrail.
5. The inter-highway-cell traffic flow detection method according to claim 4, characterized in that: a support table is arranged at the upper end of the column rod (304), and the cell controller (305) is positioned below the support table and fixed on the column rod (304); image collector (302) and speed of a motor vehicle detector (303) all set up on the brace table, still are provided with solar panel (301) on the brace table, solar panel (301) can be for setting up the battery charge in cell controller (305).
6. The traffic flow management method based on the inter-highway cell traffic flow detection method according to claim 3, characterized in that: the method comprises a method for managing the speed limit among cells, and the method for managing the speed limit among the cells comprises the following steps:
step B1: a plurality of LED display panels (204) are arranged on the door-shaped support; the upper part of each lane corresponds to one LED display panel (204), and each LED display panel (204) respectively displays the speed limit value of the corresponding lane;
step B2: each LED display panel (204) is in communication connection with the site manager (201), and the site manager (201) modifies the speed limit value of each lane of the large section road according to the actual speed of each inter-cell detection point in the corresponding large section road and displays the speed limit value by the LED display panels (204).
7. The traffic flow management method according to claim 6, characterized in that: the method also comprises a large-interval speed limit management method, and the large-interval speed limit management method comprises the following steps:
step C1: the method comprises the steps that site managers (201) at all vehicle detection sites (2) in a detection road section are connected with a cloud server (4) in a communication mode; the cloud server (4) collects the number of vehicles in any large interval road section on the detection road section, and compares the number of vehicles in adjacent large interval road sections;
step C2: when the number of vehicles in any one large section of road continuously increases and exceeds a threshold value or/and exceeds a specified time, the cloud server (4) controls the vehicle detection stations (2) of one or more large sections of road in front of the large section of road to modify the speed limit value.
8. The traffic flow management method according to claim 7, characterized in that: an environment detector (202) is further arranged on the door-shaped support, and the environment detector (202) comprises a raindrop sensor, a light intensity sensor and a wind speed and direction sensor; the raindrop sensor, the light intensity sensor and the wind speed and direction sensor are electrically connected with the station manager (201); a database is arranged in the cloud server (4), a road surface friction model, a visibility model and a natural wind influence model of the road characteristics of each large section of road are stored in the database, the raindrop sensor is used for detecting rainfall conditions to enable the cloud server to be matched with the road surface friction model, the light intensity sensor is used for detecting illumination intensity to enable the cloud server to be matched with the visibility model, and the wind speed and direction sensor is used for detecting wind speed and wind direction to enable the cloud server to be matched with the natural wind influence model; and the cloud server (4) modifies the speed limit value of each large section according to the road surface friction model, the visibility model and the natural wind influence model.
9. The traffic flow management method according to claim 7, characterized in that: the method for detecting the speed limit of the road section comprises the following steps:
step D1: the cloud server (4) associates the number of vehicles in the detected road section with the number of vehicles entering the toll stations of the adjacent high-speed entrances (102) according to the estimated arrival time, and artificially gives an association degree, wherein the association degree is the ratio of the number of vehicles passing through the high-speed entrances and the detected road section to the number of all vehicles entering from the high-speed entrances;
step D2: and the cloud server (4) modifies the speed limit value of each large section road section according to the association degree and the number of vehicles passing through the high-speed entrance (102) toll station.
10. The traffic flow management method according to claim 9, characterized in that: the method also comprises a road section detection current limiting method, and the road section detection current limiting method comprises the following steps:
step E1: the cloud server (4) marks the large section of the road with the number of vehicles continuously increasing and exceeding a threshold value or/and exceeding a specified time as a pre-congestion road section;
step E2: the cloud server (4) counts the number of the pre-jammed road sections on the same detection road section, and performs scheduling control on the number of channels of a toll station at a high-speed entrance (102) with a degree of association with the detection road section according to the number of the pre-jammed road sections so as to limit the speed of entering a vehicle from the high-speed entrance.
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