CN111024110B - 5G-based intelligent traffic path planning and navigation system and working method thereof - Google Patents
5G-based intelligent traffic path planning and navigation system and working method thereof Download PDFInfo
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- CN111024110B CN111024110B CN201911409366.3A CN201911409366A CN111024110B CN 111024110 B CN111024110 B CN 111024110B CN 201911409366 A CN201911409366 A CN 201911409366A CN 111024110 B CN111024110 B CN 111024110B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3461—Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
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Abstract
The invention provides an intelligent traffic path planning and navigation system based on 5G and a working method thereof. According to the intelligent travel route planning method and the intelligent travel route planning device, the user intelligent terminal is used for sending a route request to the navigation server, receiving route information and displaying a dynamic navigation process, the navigation server is used for calculating the route and pushing settlement results to the user intelligent terminal, the edge calculation service MAP intelligent terminal is used for providing information such as congestion, route deviation correction and flow early warning, data support is provided for the nearby intelligent terminals, intelligent travel route planning is conducted depending on edge calculation, intelligent recommended route is achieved, traffic information is obtained through implementation, and therefore intelligent travel is achieved.
Description
Technical Field
The invention relates to the technical field of intelligent traffic, in particular to an intelligent traffic path planning and navigation method and system based on 5G and a working method thereof.
Background
In modern intelligent traffic environments, traffic systems are required to have the ability to reasonably distribute traffic flow, thereby reducing road congestion, reducing traffic accidents, reducing time costs for traffic participants, reducing economic costs for traffic participants, and the like. The optimal path planning is an important component of intelligent traffic and is necessarily the key research content of a navigation system. The current route planning of the main stream navigation system generally only considers a single factor, such as a journey or a time or a traffic fee, and other factors are not added into the decision of the route planning, especially the strong supporting capability of edge calculation is not utilized, so that a real-time autonomous decision navigation system is provided for traffic participants. The main working flow is as follows: the user inputs a destination request-the navigation system performs route planning and recommendation-the user selects a route-the user travels to the destination according to the navigation route.
The main drawbacks of the above method are:
(1) The change of the path condition is not timely displayed, and the traffic flow and the change trend of the preset path cannot be displayed in real time.
(2) The intelligent recommended route cannot be achieved, and only after a user runs according to the selected route and a traffic department or the users with the same route manually report the traffic condition, the navigation server can push the traffic condition, and the user often cannot change the route because the user enters a congested road section.
Disclosure of Invention
Aiming at the technical problems that the change of the route condition in the existing navigation system is not timely displayed and the intelligent recommended route cannot be achieved, the invention provides an intelligent traffic route planning and navigation method and system based on 5G and a working method thereof.
In order to solve the problems, the technical scheme of the invention is realized as follows:
the intelligent traffic path planning and navigation method and system based on 5G comprises a user intelligent terminal, wherein the user intelligent terminal is respectively connected with an edge service device and a navigation server, and the edge service device is connected with the navigation server.
Preferably, the edge service device comprises an edge computing service MAP intelligent terminal, and the edge computing service MAP intelligent terminal is respectively connected with the user intelligent terminal and the navigation server.
An intelligent traffic path planning and navigation method and a working method of a system based on 5G comprise the following steps:
s1, a user enters a navigation system through a user intelligent terminal;
s2, acquiring the current position of the user intelligent terminal as a starting point;
s3, inputting end position information by a user;
s4, the navigation server performs path planning according to the starting point position and the end point position;
s5, pushing navigation information of the planned path to the intelligent user terminal by the navigation server;
s6, the user intelligent terminal receives the navigation information and analyzes the navigation route information pushed by the navigation server;
and S7, the user intelligent terminal starts navigation until the user reaches the destination or the user initiatively ends navigation.
Preferably, the path planning method in step S4 includes the following steps:
s401, initially selecting a navigation path, and performing preliminary planning on the path by a navigation server according to starting and ending point information of a user;
s402, acquiring a time cost weight, and giving the time cost weight by the navigation server according to the speed limit information of the planned route and the big data analysis information;
s403, obtaining a distance cost weight, and giving the distance cost weight by the navigation server according to the total travel distance of the planned route;
s404, acquiring a cost weight of the expense, and calculating the cost weight of the expense by the navigation server according to the charging condition of the planned route;
s405, acquiring flow data, and calculating the flow condition of each planned route by the edge calculation service MAP intelligent terminal according to the real-time condition of each road section of the planned route;
s406, acquiring traffic data, and identifying traffic conditions by the edge computing service MAP intelligent terminal according to road condition information issued by traffic departments and feedback of route planning navigation users;
s407, generating an edge computing service MAP index according to the steps S402-S406, and generating different index information by the navigation server according to different planned routes;
s408, the navigation server forms a recommended planning path, and the navigation server provides at least three recommended paths for the user to select according to different weights by integrating the flow condition, the traffic condition, the time cost weight, the distance cost weight and the expense cost weight.
Preferably, the index information in step S407 includes a user intelligent terminal that has performed navigation in the planned route; in step 407, the planned route is divided into different road segments, and the user intelligent terminal IDs in the road segments are counted according to the different road segments, and an index table is formed.
Preferably, the method for calculating the traffic situation in step S406 includes the following steps:
s801, an edge computing service MAP intelligent terminal acquires speed limit information of a current road section;
s802, the navigation server acquires the speed information of the current user from the user intelligent terminal and then sends the user speed information to the edge computing service MAP intelligent terminal;
s803, calculating a pass value according to the corresponding relation between the speed and the speed of the user and the speed limit information received by the MAP intelligent terminal;
s804, when the traffic value is higher than the creep threshold, comparing the traffic value with the congestion threshold;
s805, when the traffic value is lower than the creep threshold, generating a fluency mark 0;
s806, when the traffic value is higher than the creep threshold value but does not reach the congestion threshold value, generating a creep mark 1;
s807, when the traffic value is higher than the congestion threshold value, generating a congestion identification 2; and the smooth mark, the creep mark and the congestion mark generated in the calculation process are fed back to the user intelligent terminal as calculation parameters.
Preferably, in the step S802, when the vehicle speed varies by more than 20%, the edge calculation service MAP intelligent terminal initiates a calculation.
Preferably, the method for calculating the flow condition in step S405 includes the following steps:
s901, an edge computing service MAP intelligent terminal reads the edge computing service MAP;
s902, the edge computing service MAP intelligent terminal acquires various information about a road section n in MAP;
s903, according to the updated data of the edge computing service MAP, comparing the quantity change condition of the user intelligent terminals in the road section n, and according to the quantity increase and decrease, generating different weights;
s904, the edge computing service MAP intelligent terminal compares the average speed change condition of the user intelligent terminal in the road section n according to the update data of the edge computing service MAP, and generates different weights according to the increase and decrease of the average speed;
s905, integrating and calculating the acquired quantity weight and average speed weight by the edge computing service MAP intelligent terminal;
s906, according to the step S905, when the MAP intelligent terminal for the edge computing service generates a variable flow identifier 1 through integration computation, actively early warning is carried out on a user through a navigation system;
s907, according to step S905, when the MAP intelligent terminal is integrated and calculated to generate a flow unchanged identifier 0, no feedback is made to the navigation process;
s908, according to the step S905, when the edge computing server generates the flow reducing mark 2, the edge computing service MAP intelligent terminal integrates and computes, and sends a passing notification to a user through the navigation system.
Preferably, in the step S903, the number of the user intelligent terminals is compared with the number of the intelligent terminals of the service MAP calculated according to the current edge and the number of the intelligent terminals of the historical version of the service MAP calculated according to the edge within a fixed time, and different weight values are given according to the change trend.
The invention has the beneficial effects that: according to the intelligent travel route planning method and the intelligent travel route planning device, the user intelligent terminal is used for sending a route request to the navigation server, receiving route information and displaying a dynamic navigation process, the navigation server is used for calculating the route and pushing settlement results to the user intelligent terminal, the edge calculation service MAP intelligent terminal is used for providing information such as congestion, route deviation correction and traffic early warning, data support is provided for the nearby intelligent terminals, the edge calculation service MAP intelligent terminal is utilized for providing edge calculation service in the process of navigating by a user, the problem of overlarge calculation pressure caused by the aid of a single navigation server is solved, intelligent travel route planning is conducted by integral navigation depending on edge calculation, intelligent recommended route is achieved, traffic information is obtained through implementation, and intelligent travel is achieved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a frame structure of a navigation system according to the present invention.
FIG. 2 is a navigation workflow diagram of the present invention.
FIG. 3 is a flow chart illustrating a navigation path generation process according to the present invention.
Fig. 4 is a schematic diagram of an edge computing service MAP index traffic situation participating terminal according to the present invention.
In the figure, 10 is a user intelligent terminal, 11 is a navigation server, and 12 is an edge computing service MAP intelligent terminal.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without any inventive effort, are intended to be within the scope of the invention.
Example 1: as shown in fig. 1, the 5G-based intelligent traffic path planning and navigation method and system include a user intelligent terminal 10, wherein the user intelligent terminal 10 is respectively connected with an edge service device and a navigation server 11, the edge service device is connected with the navigation server 11, the edge service device includes an edge computing service MAP intelligent terminal 12, the edge computing service MAP intelligent terminal 12 is respectively connected with the user intelligent terminal 10 and the navigation server 11, and information wireless transmission is realized among the edge computing service MAP intelligent terminal, the navigation server and the intelligent terminal through a mobile communication network.
The user intelligent terminal is used for loading navigation software, sending a path application request to the navigation server, calculating flow change and traffic situation change according to data calculated by the edge calculation service MAP intelligent terminal, and feeding back all the identifiers calculated by the user intelligent terminal to the edge calculation service MAP intelligent terminal as participants of edge calculation, and the user intelligent terminal also receives parameters of the navigation server, performs calculation and analysis, presents the parameters to a user, and guides the travelling direction of the user in a mode of voice, graphic display and animation display.
The navigation server is used for receiving the path application request of the intelligent terminal, sending the path calculation result to the intelligent terminal of the user, generating an edge calculation service MAP according to the path information, sending the edge calculation service MAP to all intelligent terminals in the edge calculation service MAP, updating MAP information according to the dynamic change process, and feeding back the road condition information acquired from the traffic management department to the intelligent terminal.
The edge computing service MAP intelligent terminal is used for providing edge computing service, the edge computing service MAP intelligent terminal is provided with an edge computing service component, the edge computing service MAP intelligent terminal gives a flow change weight (0=constant flow, 1=variable flow, 2=variable flow) and a traffic situation weight (0=smooth, 1=slow, 2=congestion) according to the running condition of the edge computing service MAP intelligent terminal, the edge computing service MAP intelligent terminal is an assembly of all intelligent terminals in the current edge computing service MAP, and indexes different intelligent terminals according to path information and road section information contained in the path information, so that the number of the intelligent terminals providing the edge computing service can change, namely, when the intelligent terminal 10 performs different types of computation, a required computing result can be obtained from different edge computing service MAP intelligent terminals 12, the edge computing service MAP can change according to time progress, and a navigation server can update the edge computing service MAP in real time according to the changing condition of the intelligent terminals participating in traffic in the navigation process. The computing service of the edge computing service MAP intelligent terminal 12 is in an active form, does not need the intelligent terminal to initiate application, calculates various parameters in real time only according to the change of the self traveling state, and updates the weights of the different parameters.
As shown in fig. 2, a working method of the 5G-based intelligent traffic path planning and navigation method and system includes the following steps:
s1, a user enters a navigation system by starting navigation software in a user intelligent terminal 10, wherein the user intelligent terminal comprises terminal equipment such as a smart phone, a pad and the like, and needs to have computing capacity, network communication capacity and GPS positioning function;
s2, the navigation software acquires the current position of the user intelligent terminal 10 as a starting point, and the user can manually change the starting point position according to the self requirement;
s3, inputting end position information by a user through a visual section, and sending the start point information and the end point information to a navigation server;
s4, the navigation server 11 performs path planning according to the starting point position and the end point position, generates basic navigation path information according to the received path planning request information and the prefabricated electronic map in the navigation system, adds and optimizes the weights of different paths leading to the end point position through an algorithm (such as a fox elimination method) when the path planning is performed, so as to calculate the shortest time path, the shortest distance path, the least cost path, the recommended path and the like in the road network information of the navigation system, and perform routine path screening when the model path planning is performed;
then, according to the flow weight and the passing weight of each preselected path, the passing condition is provided by the navigation server and the edge computing service equipment in a cooperative way, the navigation server acquires traffic notification information of traffic departments and congestion information reported by users on the paths, real-time information of the passing condition is provided with basic information by intelligent terminals in MAP indexes of the edge computing service, the real-time passing information is confirmed according to the weight of each terminal, the confirmation of the passing condition is confirmed according to the speed per hour and the speed limit information of road sections of the intelligent terminals, a creep mark is generated to reach a creep threshold, whether the traffic is congested or not is further judged, wherein the creep mark or the congestion mark of a single terminal is only used as a calculation basis, the calculation weight is provided, and the user intelligent terminal calculates whether a certain road section is slowly or congested or not;
the traffic situation is divided into real-time traffic and traffic variation trend, and is provided by a user intelligent terminal in the same navigation path according to an edge computing service MAP, and is predicted according to each road section in the navigation path, and a final recommended path is generated, meanwhile, intelligent terminals in the same path and similar paths are generated into an edge computing service MAP, and information in the recommended path and the edge service MAP is pushed to the user intelligent terminal, and the terminals in the edge computing service MAP comprise the same-direction intelligent terminal of the current path and the intelligent terminals of adjacent road sections;
s5, pushing the planned path navigation information to the user intelligent terminal by the navigation server 11;
s6, the user intelligent terminal 10 receives the navigation information and analyzes the navigation route information pushed by the navigation server;
s7, the user intelligent terminal 10 starts navigation until the user reaches the destination or the user actively ends navigation.
Example 2: as shown in fig. 3, a working method of an intelligent traffic route planning and navigation method and system based on 5G, the navigation server 11 in step S4 performs a route planning method according to a start position and an end position, and includes the following steps:
s401, initially selecting a navigation path, and performing primary planning of the path by the navigation server 11 according to starting and ending point information of a user;
s402, acquiring a time cost weight, and giving the time cost weight by the navigation server 11 according to the speed limit information of the planned route and the big data analysis information;
s403, obtaining a distance cost weight, and the navigation server 11 gives the distance cost weight according to the total travel distance of the planned route;
s404, acquiring a cost weight, and calculating the cost weight by the navigation server 11 according to the charging condition of the planned route;
s405, acquiring flow data, and calculating the flow condition of each planned route by the edge calculation service MAP intelligent terminal 12 according to the real-time condition of each road section of the planned route;
s406, acquiring traffic data, and identifying traffic conditions by the edge computing service MAP intelligent terminal 12 according to road condition information issued by traffic departments and feedback of route planning navigation users;
s407, generating an edge computing service MAP according to the steps S402-S406, dividing the planned route into different road sections, wherein the road sections are the minimum units for dividing the route, and a user can only change the route or adjust the required travelling directions such as turning around at the nodes of the road sections; counting the user intelligent terminal IDs in the road sections according to different road sections, forming an index table, and generating different index information by the navigation server 11 according to different planned routes, wherein the index information comprises the user intelligent terminals 10 which have performed navigation in the planned routes;
s408, the navigation server 11 forms a recommended planning path, and the navigation server 11 provides at least three recommended paths for the user to select according to different weights by integrating the flow condition, the traffic condition, the time cost weight, the distance cost weight and the expense cost weight.
Preferably, the method for calculating the traffic situation in step S406 includes the following steps:
s801, the edge computing service MAP intelligent terminal 12 obtains speed limit information of a current road section from road network information of a navigation server;
s802, the navigation server 11 acquires the speed information of the current user from the user intelligent terminal 10 and then sends the user speed information to the edge computing service MAP intelligent terminal 12; when the vehicle speed variation exceeds 20%, the edge computing service MAP intelligent terminal 12 initiates a computation, the computation process is a computation process performed by the edge computing service MAP intelligent terminal, and each intelligent terminal in the edge computing service MAP performs autonomous computation;
s803, calculating a pass value according to the corresponding relation between the speed and the speed limit by the edge calculation service MAP intelligent terminal 12 and the speed limit information of the user;
s804, when the traffic value is higher than the creep threshold, comparing the traffic value with the congestion threshold;
s805, when the traffic value is lower than the creep threshold, generating a fluency mark 0;
s806, when the traffic value is higher than the creep threshold value but does not reach the congestion threshold value, generating a creep mark 1;
s807, when the traffic value is higher than the congestion threshold value, generating a congestion identification 2; the smooth mark, the creep mark and the congestion mark generated in the calculation process are fed back to the user intelligent terminal 10 as calculation parameters and are not used for reflecting the actual traffic conditions; after receiving various identifiers of the edge computing service MAP intelligent terminal 12 of different road sections, the user intelligent terminal 10 calculates actual traffic conditions, and presents calculation results to an electronic MAP for navigation, wherein different identifiers are distinguished by different colors, green represents the calculation result of the smooth identifier 0, yellow represents the calculation result of the creep identifier 1, red represents the calculation result of the congestion identifier 2, the colors are only used for distinguishing different calculation results, and the optional color scheme is not unique.
The rest of the structure and the working method are the same as those of the embodiment 1.
Example 3: as shown in fig. 4, in the working method of the 5G-based intelligent traffic path planning and navigation method and system, in the step S405, the edge computing service MAP intelligent terminal 12 computes the flow condition of each planned route according to the real-time condition of each road segment of the planned route, and includes the following steps:
s901, the edge computing service MAP intelligent terminal 12 reads the edge computing service MAP;
s902, the edge computing service MAP intelligent terminal 12 acquires various information about a road section n in a MAP index;
s903, according to the update data of the edge computing service MAP (the update data is actively pushed by the navigation server, when the change of the edge computing service MAP information stored in the navigation server exceeds 5%, the push update is carried out once), the change condition of the number of the user intelligent terminals 10 in the road section n is compared, and different weights are generated according to the increase and decrease of the number; the comparison of the number of the user intelligent terminals 10 is that the number of the intelligent terminals for calculating the service MAP according to the current edge is compared with the number of the intelligent terminals for calculating the historical version of the service MAP within fixed time, different weight values are given according to the change trend, and the more severe the change trend, the higher the weight value;
s904, the edge computing service MAP intelligent terminal 12 compares the average speed change condition of the user intelligent terminal 10 in the road section n according to the update data of the edge computing service MAP, and generates different weights according to the increase and decrease of the average speed;
s905, the edge computing service MAP intelligent terminal 12 integrates and computes the acquired quantity weight and average speed weight;
s906, according to the step S905, when the edge computing service MAP intelligent terminal 12 integrates and computes to generate a flow variable identifier 1, actively early warning is carried out to a user through a navigation system;
s907, according to step S905, the edge computing service MAP intelligent terminal 12 does not feed back the navigation process when integrating and computing to generate a flow unchanged identifier 0; under different traffic conditions, the early warning grades of users are different, the navigation system strongly recommends the users to adjust the travelling path in a way of early warning under the condition of congestion, re-plans the path is carried out, and only provides early warning prompts for the process change under the condition of the process, so as to prompt the users to reasonably determine whether to continue travelling according to the current path;
s908, according to step S905, when the edge computing service MAP intelligent terminal 12 integrates and computes the edge computing server to generate the traffic decrease identifier 2, a traffic notification is sent to the user through the navigation system.
The rest of the structure and the working method are the same as those of the embodiment 1.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (4)
1. The working method of the intelligent traffic path planning and navigation system based on 5G is characterized in that the system comprises a user intelligent terminal (10), wherein the user intelligent terminal (10) is respectively connected with edge service equipment and a navigation server (11), and the edge service equipment is connected with the navigation server (11);
the edge service equipment comprises an edge computing service MAP intelligent terminal (12), and the edge computing service MAP intelligent terminal (12) is respectively connected with the user intelligent terminal (10) and the navigation server (11);
the working method comprises the following steps:
s1, a user enters a navigation system through a user intelligent terminal (10);
s2, the navigation system acquires the current position of the user intelligent terminal (10) as a starting point;
s3, inputting end position information by a user;
s4, the navigation server (11) performs path planning according to the starting point position and the ending point position;
s5, pushing the planned path navigation information to the intelligent user terminal by the navigation server (11);
s6, the user intelligent terminal (10) receives the navigation information and analyzes the navigation route information pushed by the navigation server;
s7, the user intelligent terminal (10) starts navigation until the user reaches a terminal or the user actively ends navigation;
the method for path planning in the step S4 includes the following steps:
s401, initially selecting a navigation path, and performing primary planning of the path by a navigation server (11) according to starting and ending point information of a user;
s402, the navigation server (11) gives a time cost weight according to the speed limit information of the planned route and the big data analysis information;
s403, the navigation server (11) gives a distance cost weight according to the total travel distance of the planned route;
s404, the navigation server (11) calculates a cost weight according to the charging condition of the planned route;
s405, the edge computing service MAP intelligent terminal (12) computes the flow condition of each planned route according to the real-time condition of each road section of the planned route;
s406, the edge computing service MAP intelligent terminal (12) computes the traffic situation of each planned route according to the road condition information issued by the traffic management department and the traffic situation recognized by the feedback of navigation users in the planned route;
the calculation method of the traffic situation in step S406 includes the following steps:
s801, an edge computing service MAP intelligent terminal (12) acquires speed limit information of a current road section;
s802, the navigation server (11) acquires the speed information of the current user from the user intelligent terminal (10) and then sends the user speed information to the edge computing service MAP intelligent terminal (12);
s803, calculating a passing value according to the corresponding relation between the speed and the speed limit by the edge calculation service MAP intelligent terminal (12) and the speed limit information of the user;
s804, when the traffic value is higher than the creep threshold, comparing the traffic value with the congestion threshold;
s805, when the traffic value is lower than the creep threshold, generating a fluency mark 0;
s806, when the traffic value is higher than the creep threshold value but does not reach the congestion threshold value, generating a creep mark 1;
s807, when the traffic value is higher than the congestion threshold value, generating a congestion identification 2; the smooth mark, the creep mark and the congestion mark generated in the calculation process are fed back to the user intelligent terminal (10) as calculation parameters;
s407, generating an edge calculation service MAP according to the steps S402-S406, and generating different index information by the navigation server (11) according to different planned routes;
s408, the navigation server (11) forms a recommended planning path, and the navigation server (11) provides at least three recommended paths for a user to select according to different weights by integrating the flow condition, the traffic condition, the time cost weight, the distance cost weight and the cost weight;
the index information in the step S407 comprises a user intelligent terminal (10) which has performed navigation in the planned route; in step S407, the planned route is divided into different road segments, and the IDs of the user intelligent terminals in the road segments are counted according to the different road segments, and an index table is formed.
2. The method according to claim 1, wherein the edge computing service MAP intelligent terminal (12) initiates a computation when the vehicle speed varies by more than 20%.
3. The working method of the 5G-based intelligent traffic path planning and navigation system according to claim 1 or 2, wherein the calculating method of the traffic situation in step S405 comprises the following steps:
s901, an edge computing service MAP intelligent terminal (12) reads the edge computing service MAP;
s902, the intelligent terminal (12) of the edge computing service MAP acquires various information about the road section n in the edge computing service MAP;
s903, according to the update data of the edge computing service MAP, comparing the number change condition of the user intelligent terminals (10) in the road section n, and according to the number increase and decrease, generating different weights;
s904, the edge computing service MAP intelligent terminal (12) compares the average speed change condition of the user intelligent terminal (10) in the road section n according to the update data of the edge computing service MAP, and generates different weights according to the increase and decrease of the average speed;
s905, integrating and calculating the acquired quantity weight and average speed weight by the edge computing service MAP intelligent terminal (12);
s906, according to the step S905, when the edge computing service MAP intelligent terminal (12) integrates and computes to generate a flow variable identifier 1, actively early warning is carried out to a user through a navigation system;
s907, according to the step S905, when the edge computing service MAP intelligent terminal (12) integrates and computes to generate a flow unchanged identifier 0, no feedback is made to the navigation process;
s908, according to the step S905, when the edge computing service MAP intelligent terminal (12) integrates the computing to generate the flow reducing identification 2, a traffic notification is sent to the user through the navigation system.
4. The working method of the 5G-based intelligent traffic path planning and navigation system according to claim 3, wherein the number comparison of the user intelligent terminals (10) in step S903 is to compare the number of the intelligent terminals for calculating the service MAP according to the current edge with the number of the intelligent terminals for calculating the historical version of the service MAP according to the edge within a fixed time, and different weight values are given according to the change trend.
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