An intelligent traffic information management system based on 5G

Abstract

The present invention belongs to the technical field of intelligent analysis and management of traffic information, and specifically discloses an intelligent traffic information management system based on 5G, including: locating traffic congestion areas by identifying the vehicle retention status of corresponding driving sections and turning intersections of each lane on each branch route of the vehicle owner's driving path; determining the expected congestion duration of each control area on each branch route for the vehicle owner to determine a recommended turning lane by detecting the activity time of congestion sources, the proportion of large vehicles, and the proportion of vehicles in each speed interval within the traffic congestion areas on each branch route of the vehicle owner's driving path; analyzing the traffic order obstruction and smoothness rate of each control area and its adjacent sections on each branch route by identifying the lane change directions of each passing vehicle within each control area on each branch route and the traffic flow of adjacent sections of each lane during the congestion period, and evaluating the traffic flow mitigation effect index within each control area on each branch route accordingly.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent analysis and management of traffic information, and relates to an intelligent traffic information management system based on 5G. Background Art

[0002] With the trend of a sharp increase in urban traffic flow, in many large cities, road congestion during peak hours has become the norm. Traditional traffic information management means are unable to cope with the huge and complex traffic flow, making the urban traffic congestion problem increasingly serious. As a result, the society's demand for improving traffic efficiency and reducing traffic congestion is becoming increasingly urgent.

[0003] In the prior art, there are already some solutions related to the intelligent analysis and management of traffic information. For example, the patent with the Chinese patent publication number CN116453360B discloses a traffic management system based on big data. By analyzing traffic information, it determines future traffic congestion situations, and then uses a navigation information push module to send navigation diversion suggestions based on future traffic congestion situations, enabling navigation users to change their navigation routes in advance, thereby reducing road congestion.

[0004] Another patent with the Chinese patent publication number CN116721550B discloses a traffic management system based on grid computing. It collects specified state parameter values through collection means, processes the data and analyzes to obtain a traffic road accident occurrence index and a traffic road safety passing index, further analyzes to obtain a traffic management safety evaluation coefficient, and conducts corresponding processing after comparative analysis, thereby realizing the ability of autonomous decision-making and intelligent management of traffic, helping managers monitor the system in real time to obtain the latest data and make corresponding adjustments, improving the efficiency of traffic management.

[0005] Although the above solutions propose some solutions for the intelligent analysis and management of traffic information, there are still the following limitations: When the prior art recommends routes to navigation users based on traffic information, it is only limited to positioning and monitoring congested sections, and does not predict and analyze the congestion situations of adjacent sections corresponding to the congested sections, making the route recommendation for navigation users lack comprehensiveness. In addition, when the prior art predicts and analyzes the congestion characteristics during vehicle driving, it is more inclined to analyze the probability of road accidents, and lacks the problem of predicting the congestion duration by identifying traffic congestion source events, which will affect the analysis of traffic congestion causes and the formulation of solutions, and at the same time affect the accuracy of the optimized route recommendation for car owners. Summary of the Invention

[0006] In view of this, to solve the problems proposed in the above background art, an intelligent traffic information management system based on 5G is proposed.

[0007] The object of the present invention can be achieved by the following technical solutions: The present invention provides an intelligent traffic information management system based on 5G, which includes: a control area screening module for obtaining the target driving path of the vehicle owner, constructing each branch route on the target driving path, detecting the road congestion degree of each corresponding road in each traffic area on each branch route, screening out each control area on each branch route, numbering each branch route as 1, 2,... i..., n, and numbering each control area as 1, 2,... j..., m.

[0008] A congestion road condition analysis module for extracting the road condition data of each control area on each branch route, identifying the corresponding congestion sources in each control area on each branch route, and analyzing the expected congestion duration of each control area on each branch route.

[0009] A control rule determination module for obtaining the travel distance of each branch route, combining the expected congestion duration of each control area on each branch route, identifying the corresponding path recommendation score of each branch route, and then determining the recommended lane for the vehicle owner to turn.

[0010] A control effect evaluation module for real-time tracking of the recommended lane for the vehicle owner to turn on the target driving path, detecting the vehicle conditions in each control area on each branch route of the vehicle owner's target driving path, and identifying the corresponding adjacent road conditions in each control area on each branch route, and evaluating the traffic flow mitigation effect index in each control area on each branch route.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) By identifying the vehicle retention status of each driving section and turning intersection of each lane on each branch route of the vehicle owner's driving path, the present invention locates the traffic congestion area, and then determines the recommended lane for the vehicle owner to turn according to the expected congestion duration of each branch path, so as to achieve the purpose of avoiding the congested section, and at the same time helps to relieve the vehicle driving flow of the congested section.

[0012] (2) By detecting the activity time of congestion sources, the proportion of large vehicles, and the proportion of vehicles in each speed interval in the traffic congestion area of each branch route of the vehicle owner's driving path, the present invention can provide real-time traffic condition information for the vehicle owner, and accordingly determine the expected congestion duration of each control area on each branch route, making the travel route optimization suggestions provided for the vehicle owner more accurate.

[0013] (3) By identifying the lane-changing directions of each passing vehicle in each control area on each branch route and the traffic flow of adjacent sections of each lane during congestion periods, and analyzing the traffic order obstruction and smoothness rates of each control area and its adjacent sections on each branch route, the present invention can more precisely map the occurrence and dissipation patterns of traffic congestion. At the same time, by comparing the differences in the congested vehicle flow of each lane in each control area on each branch route before and after congestion periods, the long-term trend of traffic flow changes is revealed. Based on this, the traffic flow mitigation effect indicators of each control area on each branch route are evaluated, which can reflect the effectiveness of the implementation of traffic control due to the optimization of the travel paths of vehicle owners. Furthermore, it provides decision-making support for traffic management departments. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0015] Figure 1 It is a schematic diagram of the connection of system modules of the present invention.

[0016] Figure 2 It is a schematic diagram of the corresponding intersections of the traffic areas of the present invention.

[0017] Figure 3 It is a display diagram of the adjacent sections of each lane belonging to the control area of the present invention.

[0018] Reference numerals: 1. Starting stop line on the straight signal indicator lane; 2. Target stop line; 3. Each lane at the corresponding intersection of the traffic area; 4. Adjacent section of the right-turn lane belonging to the control area. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] 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 some, rather than all, of the embodiments of the present invention. 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.

[0020] Please refer to Figure 1 As shown, the present invention provides a 5G-based intelligent traffic information management system, which includes: a control area screening module, a congested road condition analysis module, a control rule determination module, and a control effect evaluation module.

[0021] The control area screening module is connected to the congested traffic condition analysis module, the congested traffic condition analysis module is connected to the control rule determination module, and the control rule determination module is connected to the control effect evaluation module.

[0022] The control area screening module is used to obtain the target driving path of the vehicle owner, construct each branch route on the target driving path, detect the congestion degree of the corresponding roads in each traffic area on each branch route, screen out each control area on each branch route, number each branch route as 1, 2,... i..., n, and number each control area as 1, 2,... j..., m.

[0023] The target driving path of the vehicle owner is selected by the vehicle navigation.

[0024] Each control area refers to the road section area between each traffic light intersection and its adjacent traffic light intersection.

[0025] In a preferred embodiment, the construction of each branch route on the target driving path is specifically as follows: obtain the route map between the destination point and the vehicle owner's positioning point on the target driving path of the vehicle owner from the map navigator, and obtain the traffic control rules on the route map, including restricted license plate numbers and restricted road sections.

[0026] Obtain the license plate number of the vehicle of the vehicle owner, exclude the road section area where the restricted license plate number consistent with the license plate number of the vehicle of the vehicle owner is located on the route map, and exclude the area to which the restricted road section belongs, to obtain each branch route that the vehicle of the vehicle owner can pass on the route map, that is, each branch route on the target driving path. Furthermore, when the vehicle owner pre-arrives at the intersection of each traffic area on each branch route, use the intersection of the corresponding traffic area on the corresponding branch route as the new vehicle owner positioning point on the target driving path, and construct each branch route on the target driving path corresponding to the new vehicle owner positioning point in real time.

[0027] Please refer to Figure 2 As shown, in a further preferred embodiment, the screening of each control area on each branch route includes: real-time detect the parking duration of the vehicle flow in each lane belonging to each traffic area on each branch route through a road monitoring camera, and calculate the ratio of it to the set duration of the red light cycle of the signal indicator light of the corresponding lane in the corresponding traffic area on the corresponding branch route, to obtain the vehicle delay rate Re of each lane in each traffic area on each branch route. ija , a represents the number of each lane in the corresponding traffic area, a = 1, 2,..., z.

[0028] The numerator of the ratio is the parking duration of the vehicle flow in each lane belonging to each traffic area on each branch route, and the denominator is the set duration of the red light cycle of the signal indicator light of the corresponding lane in the corresponding traffic area on each branch route.

[0029] The vehicle flow parking duration refers to the total duration that vehicles stop and wait according to the signal indicator lights on the road sections belonging to the traffic area. For example, at a busy intersection, the red light cycle of the signal indicator light for a certain lane is set to 60 seconds. During this 60-second red light cycle setting duration, the vehicle flow parking duration of the vehicles waiting in this lane will increase by 60 seconds. If the vehicles waiting in a certain lane do not pass through the road section belonging to the traffic area within the full cycle setting duration of the red and green lights of the lane signal indicator light, then the vehicle flow parking duration belonging to this lane may need to increase by another 60 seconds.

[0030] The vehicle delay rate of each lane corresponding to each traffic area on each branch route represents the congestion condition of the road section belonging to the traffic area.

[0031] Extract the traffic images of the corresponding intersections of each traffic area on each branch route through the road monitoring cameras, locate the number of blocked vehicles in each lane of the corresponding intersections of each traffic area on each branch route through image recognition technology, multiply the ratio of the number of blocked vehicles to the preset reference number of blocked vehicles, and obtain the corresponding vehicle cross-traffic rate Cr of each traffic area on each branch route ij 。

[0032] The blocked vehicles refer to the vehicles that have passed the starting stop line but not passed the target stop line on the lane corresponding to the signal indicator light when the straight or turning signal indicator light changes from green to red.

[0033] The corresponding vehicle cross-traffic rate of each traffic area on each branch route represents the congestion condition of the intersection belonging to the traffic area.

[0034] Based on the vehicle delay rate of each lane corresponding to each traffic area on each branch route and the corresponding vehicle cross-traffic rate of each traffic area on each branch route, analyze the congestion degree of the corresponding roads of each traffic area on each branch route z represents the number of lanes corresponding to the traffic area. Compare the congestion degree of the corresponding roads of each traffic area on each branch route with the preset road congestion degree index, and screen out the traffic areas on each branch route where the road congestion degree exceeds the preset road congestion degree index, which are recorded as each control area on each branch route.

[0035] The congestion road condition analysis module is used to extract the road condition data of each control area on each branch route through the road monitoring cameras, identify the corresponding congestion sources of each control area on each branch route, and analyze the expected congestion duration of each control area on each branch route.

[0036] In a preferred implementation manner, the road condition data of each control area on each branch route includes historical road condition data and real-time measured road condition data.

[0037] The historical road condition data includes the regular traffic flow and the driving behavior data of passing vehicles at the positioning time.

[0038] The measured road condition data at that time includes the measured traffic flow and the proportion of large vehicles, and the proportion of vehicles in each speed range at the positioning time.

[0039] In a further preferred embodiment, the analysis of the estimated congestion travel duration of each control area on each branch route includes: obtaining the positioning time when the vehicle owner travels to each control area on each branch route

[0040] Obtain the corresponding congestion sources and their activity time regions in each control area on each branch route through the large-scale event service platform in the city. The congestion sources are such as passenger flow sources at stations and concert activity sources, and the corresponding activity time regions of the congestion sources are such as peak passenger flow periods at stations and concert activity periods, and then extract the congestion boundary times of the corresponding congestion sources in each control area on each branch route Determine the estimated congestion travel duration of the corresponding congestion sources in each control area on each branch route Where tp1 indicates that the congestion boundary time of the corresponding congestion source in the control area is after the positioning time, and tp2 indicates that the congestion boundary time of the corresponding congestion source in the control area is before the positioning time. represents the preset congestion buffer duration of the corresponding congestion source in the jth control area on the ith branch route.

[0041] The congestion boundary time refers to the corresponding estimated end time of the activity time region of the congestion source.

[0042] Based on the measured road condition data to which the road condition data of each control area on each branch route belongs, analyze the estimated congestion travel duration of the measured road conditions in each control area on each branch route

[0043] Determine the estimated congestion travel duration of each control area on each branch route

[0044] The estimated congestion travel duration of the corresponding congestion sources in each control area on each branch route and the estimated congestion travel duration of the measured road conditions in each control area on each branch route are two influencing factors of the congestion duration on the congestion route. Compare them and select the maximum value as the finally determined estimated congestion travel duration. The purpose of the analysis is to shorten the impact of the total congestion travel time on the selection of the congestion route when determining the recommended lane for the vehicle owner to turn.

[0045] In a further preferred embodiment, the analysis of the estimated congestion travel duration of the measured road conditions in each control area on each branch route includes: extracting the measured traffic flow in each control area on each branch route at the positioning time, and extracting the normal traffic flow in each control area on each branch route at the positioning time, and obtaining the estimated traffic flow delay rate b of each control area on each branch route by taking the ratioij 。

[0046] Extract the proportion of large vehicles and the proportion of vehicles in each speed interval in each control area on each branch route at the positioning time, denoted as K′ ij 、K ij→v , and denote the corresponding median speed of each speed area as sp v , and calculate the vehicle type delay rate in each control area on each branch route at the positioning time where sp 0 represents the preset appropriate reference speed, v represents the number of the speed interval, v = 1, 2,..., x.

[0047] Analyze the predicted congestion travel duration of the real-time measured road conditions in each control area on each branch route where T 0 represents the congestion travel duration corresponding to the preset unit delay rate.

[0048] By detecting the activity time of congestion sources, the proportion of large vehicles, and the proportion of vehicles in each speed interval in the traffic congestion areas of each branch route on the owner's driving path, the present invention can provide real-time traffic condition information for the owner, determine the predicted congestion travel duration of each control area on each branch route accordingly, and make the travel route optimization suggestions provided for the owner more accurate. At the same time, by analyzing the congestion-related data of each control area on each branch route, it can provide a basis for the planning and construction of traffic facilities. For example, if it is found that a certain area is often congested due to a high proportion of large vehicles and the congestion time is long, it can be considered to widen the road, build a dedicated lane for large vehicles, or improve the bearing capacity of the road; for the situation where the proportion of vehicles in the speed interval is unreasonable, such as traffic congestion caused by a too high proportion of low-speed vehicles, a reasonable speed limit area can be set or the flatness of the road can be improved to increase the driving speed of vehicles.

[0049] The control rule determination module is used to obtain the travel distance of each branch route, combine the predicted congestion travel duration of each control area on each branch route, identify the corresponding path recommendation score of each branch route, and then determine the recommended lane for the owner to turn.

[0050] The determination of the recommended lane for the owner to turn is to relieve the vehicle flow on the congested section and help the owner avoid the congested section at the same time, so as to make the driving road condition smoother.

[0051] In a preferred embodiment, the determination of the recommended lane for the owner to turn includes: obtaining the travel distance L of each branch route from the route map i , and extracting the driving speed of the owner Calculate the corresponding travel duration of each branch route according to the basic path time

[0052] Accumulate the estimated congestion travel times of each control area on each branch route to obtain the corresponding estimated cumulative congestion time T' of each branch route. i Based on this, calculate the corresponding path recommendation scores for each branch route. Among them represents the preset reference travel time, and e is the natural constant.

[0053] Compare the corresponding path recommendation scores of each branch route with each other, select the branch route to which the maximum path recommendation score belongs, and then obtain the pre-turning direction of the intersection of the branch route to which the maximum path recommendation score belongs from the route map. Use the lane to which the pre-turning direction of the intersection belongs as the lane recommended for the vehicle owner to turn.

[0054] The present invention locates the traffic congestion area by identifying the vehicle detention status of the corresponding driving sections and turning intersections of each lane on each branch route of the vehicle owner's driving path, and then determines the lane recommended for turning for the vehicle owner according to the estimated congestion travel time of each branch path, so as to achieve the purpose of avoiding congested sections, and at the same time helps to relieve the vehicle traffic flow of congested sections.

[0055] The control effect evaluation module is used to track in real time the lane recommended for turning of the vehicle owner on the target driving path, detect the vehicle conditions in each control area on each branch route of the vehicle owner's target driving path, identify the corresponding adjacent road conditions in each control area on each branch route, and evaluate the traffic flow relief effect index in each control area on each branch route.

[0056] In a preferred embodiment, the content of detecting the vehicle conditions in each control area on each branch route includes: identifying the lane-changing directions of each passing vehicle in each control area on each branch route, including the road-turning along-the-road direction and the road-turning against-the-road direction, and statistically obtaining the proportion of the number of passing vehicles in the road-turning against-the-road direction in each control area on each branch route, and then using it as the traffic order obstruction relief compensation factor M of each control area on each branch route. ij .

[0057] The road-turning along-the-road direction refers to turning from the straight lane to the left or right lane in the slow-moving section of the signal indicator light, and the road-turning against-the-road direction refers to turning from the left or right lane to the straight lane in the slow-moving section of the signal indicator light.

[0058] Extract the driving behavior data of the passing vehicles in each control area on each branch route, including the lane-changing frequency and the sharp speed-changing frequency, denoted as D ij 、S ij , and calculate the traffic order obstruction rate of each control area on each branch route Among them, D' and S' respectively represent the preset reference frequencies corresponding to the frequent lane-changing frequency and the sharp speed-changing frequency.

[0059] Specifically, the corresponding identification objective of the traffic order obstruction and facilitation compensation factors for each control area on each branch route is to focus on increasing the influence weight of the vehicle lane-changing situation in the reverse direction along the road turn.

[0060] The lane-changing frequency refers to the weight of the number of lane-changing vehicles when passing through the control area on the branch route.

[0061] The sharp speed change frequency refers to the weight of the number of suddenly accelerating vehicles or the weight of the number of suddenly decelerating vehicles when passing through the control area on the branch route.

[0062] Please refer to Figure 3 As shown, in a further preferred implementation manner, the identification of the corresponding adjacent road conditions for each control area on each branch route includes: extracting the congestion periods of each control area on each branch route through the traffic information recording terminal, and extracting the traffic flow q' of the adjacent sections of each lane to which each control area on each branch route belongs during the congestion period. ij→h 。

[0063] The congestion period refers to the maintenance period when the road congestion degree of the control area is in a state exceeding the preset road congestion degree index.

[0064] The adjacent sections of each lane to which the control area belongs are such as the adjacent sections of the right-turn lane to which the control area belongs, the adjacent sections of the left-turn lane to which the control area belongs, and the adjacent sections of the straight-through lane to which the control area belongs.

[0065] Extract the corresponding preset full-load traffic flow of the adjacent sections of each lane to which each control area on each branch route belongs, denoted as Analyze the traffic order obstruction and facilitation rate of the corresponding adjacent sections of each control area on each branch route Among them represents the preset overflow deviation permitted traffic flow, h represents the number of each lane corresponding to the control area, h = 1, 2,..., u.

[0066] In a further preferred implementation manner, the evaluation index of the traffic flow relief effect in each control area on each branch route is specifically: extracting the congested traffic flow q of each lane in each control area on each branch route during the congestion period through the traffic information recording terminal ij→h , and obtaining the congestion sources of each control area on each branch route, and extracting the historical congested traffic flow q' of each lane in the corresponding control area on the corresponding branch route under the corresponding congestion source situation ij ′ →h 。

[0067] Set the traffic flow deviation compensation weight B corresponding to the congestion source of each control area on each branch route ij , and evaluate the traffic flow relief effect index in each control area on each branch route u represents the number of lanes in each control area corresponding to the branch route.

[0068] Specifically, the traffic flow deviation compensation weights of the congestion sources in each control area on each branch route are determined by the differences of the congestion sources. For example, when the congestion source in a certain control area on a certain branch route is a concert of a certain celebrity, its corresponding traffic flow deviation compensation weight is determined by the online popularity of the celebrity, that is, there is a positive mapping relationship between the online popularity and the setting of the traffic flow deviation compensation weight.

[0069] By identifying the lane-changing directions of each passing vehicle in each control area on each branch route, analyzing the traffic order smoothness rate of each control area on each branch route, identifying the traffic volume of the approaching sections of the lanes belonging to each control area on each branch route during the congestion period, and analyzing the traffic order smoothness rate of the corresponding approaching sections of each control area on each branch route, the present invention can more meticulously map the occurrence and dissipation patterns of traffic congestion. At the same time, by comparing the differences in the congestion traffic volume of each lane in each control area on each branch route before and after the congestion period, the long-term trend of traffic flow changes is revealed. Based on this, the traffic flow mitigation effect indicators in each control area on each branch route are evaluated, which can reflect the effectiveness of the implementation of traffic control by optimizing the travel paths of vehicle owners, and thus provide decision-making support for the traffic management department.

[0070] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of the present technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all belong to the protection scope of the present invention.

Claims

1. A 5G-based intelligent traffic information management system, characterized in that: The system includes: The control area screening module is used to obtain the owner's target driving path, construct each branch route on the target driving path, detect the corresponding road congestion level of each traffic area on each branch route, screen out each control area on each branch route, and number each branch route. , and number each control area as ; The traffic congestion analysis module is used to extract the traffic condition data of each control area on each branch route, identify the corresponding congestion source of each control area on each branch route, and analyze the expected congestion duration of each control area on each branch route; The control rule determination module is used to obtain the travel distance of each branch route, combine the estimated congestion duration of each control area on each branch route, identify the corresponding path recommendation score of each branch route, and then determine the recommended lane for the driver to turn to; The control effect evaluation module is used to track the recommended lanes that the driver turns to on the target driving route in real time, detect the vehicle conditions in each control area on each branch route on the driver's target driving route, identify the corresponding adjacent road conditions of each control area on each branch route, and evaluate the traffic relief effect indicators in each control area on each branch route; The traffic condition data of each control area on each branch route includes historical traffic condition data and real-time traffic condition data; The historical traffic data includes regular traffic flow and driving behavior data of passing vehicles at the positioning time; The real-time road condition data includes the real-time vehicle flow, the proportion of large vehicles, and the proportion of vehicles in each speed range at the positioning time; The analysis of the estimated congestion duration of each control area on each branch route includes: Get the positioning time of the vehicle owner to each control area on each branch route ; Obtain the corresponding congestion sources and their activity time areas in each control area on each branch route, and then extract the congestion limit time of the corresponding congestion sources in each control area on each branch route , determine the expected congestion duration of the congestion source in each control area on each branch route ,in Indicates that the congestion limit time of the corresponding congestion source in the control area is after the positioning time. Indicates that the congestion limit time of the corresponding congestion source in the control area is before the positioning time. Indicates On the branch route The preset congestion buffer time of the corresponding congestion source in each control area; Based on the real-time traffic data of each controlled area on each branch route, the estimated congestion duration of each controlled area on each branch route is analyzed. ; Determine the expected congestion duration for each control area on each branch route .

2. According to claim 1, a 5G-based intelligent traffic information management system is characterized in that: The construction of each branch route on the target driving path is specifically as follows: obtaining a route map between a destination point on the target driving path of the vehicle owner and the vehicle owner's positioning point from a map navigator, and obtaining traffic control rules on the route map, including restricted license plate numbers and restricted road sections; The license plate number of the vehicle owner is obtained, the road section area where the restricted license plate number that is consistent with the license plate number of the vehicle owner is located on the route map is eliminated, and the area belonging to the restricted section is eliminated, and the branch routes that the vehicle owner's vehicle can pass on the route map are obtained, which are the branch routes on the target driving path. Then, when the vehicle owner pre-travels to the intersections of the traffic areas on the branch routes, the intersections of the corresponding traffic areas on the corresponding branch routes are used as the newly created vehicle owner positioning points on the target driving path, and the branch routes on the target driving path corresponding to the newly created vehicle owner positioning points are constructed in real time.

3. According to claim 1, a 5G-based intelligent traffic information management system is characterized in that: The control areas on each branch route are screened out, including: The vehicle stagnation rate of each lane in each traffic area on each branch route is obtained by detecting the stagnation time of the traffic flow in each lane in each traffic area on each branch route in real time through the road monitoring camera, taking it as the numerator and comparing it with the red light cycle setting time of the signal indicator light in the corresponding lane in the corresponding traffic area on the corresponding branch route; Extract the traffic images of the corresponding intersections in each traffic area on each branch route, locate the number of blocked vehicles in each lane at the corresponding intersections in each traffic area on each branch route through image recognition technology, multiply it with the preset reference blocked vehicle number ratio, and obtain the corresponding vehicle crossing rate in each traffic area on each branch route; Based on the vehicle deceleration rate of each lane corresponding to each traffic area on each branch route and the vehicle crossing rate of each traffic area on each branch route, the road congestion degree of each traffic area on each branch route is analyzed and compared with the preset road congestion degree index, and the traffic areas on each branch route whose road congestion degree exceeds the preset road congestion degree index are screened out and recorded as the controlled areas on each branch route.

4. According to claim 1, a 5G-based intelligent traffic information management system is characterized in that: The analysis of the estimated congestion duration corresponding to the measured road conditions in each control area on each branch route includes: Extract the measured traffic flow of each control area on each branch route at the positioning time, and extract the regular traffic flow of each control area on each branch route at the positioning time, and compare them to get the expected traffic delay rate of each control area on each branch route. ; Extract the proportion of large vehicles and the proportion of vehicles in each speed range in each control area on each branch route at the positioning time, and record them as , and the corresponding median speed of each speed area is recorded as , calculate the vehicle type delay rate of each control area on each branch route at the positioning time ,in Indicates the preset appropriate reference speed, Indicates the speed range number. ; Analyze the time-measured road conditions in each control area on each branch route and the corresponding estimated congestion duration ,in Indicates the preset unit delay rate corresponding to the congestion behavior duration.

5. According to claim 1, a 5G-based intelligent traffic information management system is characterized in that: The determining that the vehicle owner is turning to the recommended lane includes: Get the travel distance of each branch route, extract the vehicle owner's travel speed, and calculate the corresponding travel time of each branch route based on the basic path time ; The estimated congestion duration of each control area on each branch route is accumulated to obtain the corresponding estimated congestion cumulative duration of each branch route. , based on which the corresponding path recommendation scores of each branch route are calculated ,in represents the preset reference travel time, and e is a natural constant; The corresponding path recommendation scores of each branch route are compared with each other, and the branch route with the maximum path recommendation score is screened out, and then the predicted turning direction of the intersection of the branch route with the maximum path recommendation score is obtained, and the lane with the predicted turning direction of the intersection is used as the recommended lane for the car owner to turn to.

6. The 5G-based intelligent traffic information management system according to claim 1 is characterized in that: The detection of vehicle conditions in each control area on each branch route includes: identifying the lane change direction of each passing vehicle in each control area on each branch route, including the lane change direction of the road turning along the same side and the lane change direction of the road turning against the same side, and obtaining the proportion of the number of passing vehicles in each control area on each branch route that change lanes along the same side, and then using it as the traffic order obstruction compensation factor of each control area on each branch route. ; Extract the driving behavior data of vehicles passing through each control area on each branch route, including lane change frequency and sudden speed change frequency, recorded as , calculate the traffic order obstruction rate of each control area on each branch route ,in They respectively represent the corresponding preset reference frequencies for frequent lane changing frequency and sudden speed changing frequency.

7. A 5G-based intelligent traffic information management system according to claim 6, characterized in that: The identification of the corresponding adjacent road conditions of each controlled area on each branch route includes: extracting the congestion period of each controlled area on each branch route, and extracting the traffic volume of the adjacent road sections of each lane belonging to each controlled area on each branch route during the congestion period. ; Extract the corresponding preset full-load traffic flow of the adjacent sections of each lane in each control area on each branch route, denoted as , analyze the traffic order obstruction rate of the corresponding adjacent sections of each control area on each branch route ,in Indicates the preset overload deviation permitted vehicle flow, Indicates the lane numbers corresponding to the control area. .

8. A 5G-based intelligent traffic information management system according to claim 7, characterized in that: The indicators for evaluating the traffic relief effect in each control area on each branch route are specifically: Extract the congested traffic flow of each lane in each control area on each branch route during the congestion period , and obtain the congestion source of each control area on each branch route, and extract the historical congested traffic flow of each lane in the corresponding control area on the corresponding branch route under the corresponding congestion source ; Set the corresponding traffic flow deviation compensation weights for congestion sources in each control area on each branch route , evaluate the traffic relief effect indicators in each control area on each branch route , Indicates the number of lanes corresponding to the control area.

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