CN116776046B - Map data updating method applied to navigation system - Google Patents
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Abstract
The application discloses a map data updating method applied to a navigation system, and relates to the technical field of map updating, wherein the method comprises the steps of collecting map data in an area, preprocessing the data and extracting characteristics to establish a data set; calculating a traffic thermodynamic value Thv in the area and a road network density value Dr in the area, thereby obtaining a traffic thermodynamic index Thi in the area; calculating a current region endophytic generated active heat value Phv and a region road network density value Dr, and further correlating to obtain a current region endophytic generated active heat index Phi; and (3) integrating the traffic heat index Thi and the production and life heat index Phi of the current area, analyzing the integrated heat index Chi of the current area, comparing the integrated heat index Chi with a preset first heat threshold and a preset second heat threshold, and making corresponding measures according to different comparison results. According to the application, different priorities are allocated to the updating of the maps of different areas, so that the efficiency is improved and more resources are saved.
Description
Technical Field
The application relates to the technical field of map updating, in particular to a map data updating method applied to a navigation system.
Background
With the rapid development of modern society and the increasing demand of navigation services, navigation systems have become an integral part of daily life. However, due to the continuous change of the road network and the limited update speed of various top map data sources, the existing navigation system often has the problems of inaccurate map information, wrong route planning and the like.
In the chinese application of application publication No. CN101319911a, a client, a server of a navigation system, and a method for performing map update thereof are disclosed, where the method for requesting map update from the client to the server includes: the client obtains the area needing to be updated currently, and sends an updating request of the designated area and version information capable of reflecting the current updating state of the requested area to the server; the client receives and analyzes the data returned by the server to obtain the map element data of the corresponding area updated in the server, and updates the map data and version information of the corresponding area of the client according to the map element data.
In the above application, since the client transmits the update request and version information of the designated area to the server, the server transmits only the updated information determined from the version information in the designated area to the client, and after the client analyzes the updated information, the map data of the client is updated according to the updated information. However, urban road networks and buildings are evolving, but map data updates may lag these changes. Therefore, when new roads, new areas and new buildings appear, the map data of the navigation system can lose relevant information, and the problem of untimely updating exists.
To this end, the present application provides a map data updating method applied to a navigation system.
Disclosure of Invention
Aiming at the defects of the prior art, the application provides a map data updating method applied to a navigation system, which aims at optimizing the allocation of resources by allocating different priorities to the updating of maps of different areas and avoiding the condition that the updating of the maps is not timely in the areas with frequent human activities.
In order to achieve the above purpose, the application is realized by the following technical scheme: a map data updating method applied to a navigation system, comprising the steps of:
dividing a map into a plurality of areas, collecting map data in the areas through different channels, preprocessing the data and extracting features, and establishing a data set;
analyzing traffic conditions in the area, correlating the traffic flow Pt and the traffic flow Tr to obtain an in-area traffic thermodynamic value Thv, calculating an in-area road network density value Dr through the number of roads Nr and the area Aa, and analyzing the in-area traffic thermodynamic value Thv and the in-area road network density value Dr to obtain an in-area traffic thermodynamic index Thi;
analyzing living production activities in the area to obtain the number Sn of shops, the number Hn of residences and the number Cn of enterprises and institutions, calculating the current in-area generated living heat value Phv, calculating the number Nr of roads in the area and the area Aa of the area to obtain an in-area road network density value Dr, and correlating the current in-area generated living heat value Phv with the in-area road network density value Dr to obtain the current in-area generated living heat index Phi;
and integrating the traffic heat index Thi and the production and life heat index Phi of the current area, further analyzing the integrated heat index Chi of the current area, presetting a first heat threshold and a second heat threshold, comparing the first heat threshold with the heat threshold, and carrying out corresponding measures according to different comparison results.
Further, the analysis process of the traffic heat index Thi in the area is as follows:
extracting characteristic data from the data set, and acquiring the people flow Pt, the vehicle flow Tr, the road number Nr and the area Aa in the area;
correlating the traffic flow Pt and the traffic flow Tr in the area, performing dimensionless treatment, and obtaining the traffic thermodynamic value Thv in the area, wherein the calculation formula is as follows:
；
wherein a is 1 、a 2 Is a weight coefficient, and，/>，/>；
calculating the number Nr of roads in the area and the area Aa of the area to obtain a road network density value Dr in the area:
；
the calculation formula of the road network density value Dr in the region is shown as above;
analyzing the traffic thermodynamic value Thv in the area and the road network density value Dr in the area, performing dimensionless treatment, and further calculating the traffic thermodynamic index Thi in the area, wherein the calculation formula is as follows:
；
wherein θ is a correction coefficient, an。
Further, the in-region generated activity heat index Phi analysis process is as follows:
extracting characteristic data from the data set to obtain the number of shops Sn, the number of residences Hn and the number of enterprises and institutions Cn;
calculating a current area generated living heat value Phv according to the number Sn of shops, the number Hn of houses and the number Cn of enterprises and institutions, wherein the calculation formula is as follows:
；
wherein b 1 、b 2 、b 3 Is a weight coefficient, and，/>，/>；
calculating the number Nr of roads in the area and the area Aa of the area to obtain a road network density value Dr in the area:
；
the calculation formula of the road network density value Dr in the region is shown as above;
the production and living thermodynamic value Phv and the intra-area road network density value Dr are correlated, dimensionless treatment is carried out, and the current intra-area production activity thermodynamic index Phi is obtained, wherein the calculation formula is as follows:
；
wherein θ is a correction coefficient, an。
Further, the analysis process of the integrated heat index Chi in the region is as follows:
acquiring a traffic heat index Thi and a production life heat index Phi of a current area;
according to the traffic heat index Thi and the production and living heat index Phi, the comprehensive heat index Chi of the current area is calculated, and the calculation formula is as follows:
；
wherein c 1 、c 2 Is a weight coefficient, and，/>，/>。
further, a first thermal threshold and a second thermal threshold are preset, and compared with the comprehensive thermal index Chi of the current area, and corresponding measures are made according to different comparison results, specifically:
when the comprehensive heat index Chi is smaller than the first heat threshold, the current area map updating frequency priority is set to be low priority when the current area map updating frequency is lower;
when the first thermodynamic threshold value is smaller than or equal to the comprehensive thermodynamic index Chi and smaller than or equal to the second thermodynamic threshold value, the current artificial activity frequency degree is general, and the current area map updating frequency priority is set to be a medium priority;
and when the comprehensive heat index Chi > is higher than the second heat threshold, the current area map updating frequency priority is set to be high priority.
Further, the tourist hot spot area is singly analyzed, the annual average tourist number Anp, annual average vehicle flow Anc, network search amount Wsv and tourist light and vigorous season index Lp of the tourist hot spot area are obtained, the tourist heat index Rsi of the current tourist area is calculated, and corresponding measures are made according to different comparison results by comparing with preset tourist heat threshold values.
Further, the analysis process of the tourist heat index Rsi of the tourist area is as follows:
extracting characteristic data from the data set, and acquiring annual average tourist number Anp, annual average vehicle flow Anc, network search amount Wsv and tourist light and vigorous season index Lp of the tourist hot spot area;
judging whether the travel is off-season or traveling in a busy season according to the current season, and allocating different values according to different seasons to set the off-seasonIn the great season->；
The average annual tourist number, the average annual traffic flow, the network search amount and the tourist light and strong season index Lp are correlated, and the tourist heat index Rsi of the current tourist area is calculated according to the following calculation formula:
；
wherein alpha, beta and gamma are weight coefficients, and，/>，/>，/>is a correction coefficient, and。
further, a tourist thermal threshold value is preset, compared with a tourist thermal index Rsi, and corresponding measures are made according to different comparison results, specifically:
when the tourist heat index Rsi is smaller than the tourist heat threshold value, indicating that the heat of the current tourist area is low, setting the update frequency priority of the current tourist area to be low priority;
when the travel heat index Rsi is more than or equal to the travel heat threshold, the current travel area is indicated to be high in heat, and the update frequency priority of the current travel area is set to be high.
The application provides a map data updating method applied to a navigation system, which has the following beneficial effects:
(1) The same building group, landmark buildings, intersections and road sections are divided into one area, so that statistics and analysis are facilitated, and inaccurate data statistics caused by splitting the same building group into different areas is avoided; by preprocessing the data and extracting the characteristics, unnecessary data interference is reduced, relevant effective information is extracted, the quality and the integrity of the data are improved, and the subsequent analysis is facilitated;
(2) The traffic heat index Thi and the production and life heat index Phi of the current area are comprehensively analyzed to obtain the comprehensive heat index Chi of the current area, the comprehensive heat index Chi is compared with a preset first heat threshold and a preset second heat threshold, corresponding measures are taken according to the comparison result, so that resources are better regulated, the situation that map updating is not timely in the area with frequent artificial activities is avoided, the efficiency is greatly improved, and more resources are saved;
(3) The travel heat index Rsi of the current travel area is obtained by analyzing the related data of the current travel area, and compared with the preset travel heat threshold, and higher priority is allocated to the area with higher travel heat according to the comparison result, so that the allocation of resources is optimized, the map updating efficiency is improved, and the user experience is improved.
Drawings
Fig. 1 is a flow chart of a map data updating method of the navigation system of the present application.
Detailed Description
The following description of the embodiments of the present application 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 application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, the present application provides a map data updating method applied to a navigation system, comprising the following steps:
step one: dividing a map into a plurality of areas, collecting map data in the areas through different channels, preprocessing the data and extracting features, and establishing a data set;
the first step comprises the following steps:
step 101: dividing the map into a plurality of areas, and enabling the same building group, landmarks, intersections and road sections to belong to one area;
step 102: map data in the area are collected through channels such as official websites, statistical data and market research, and preprocessing operations such as data cleaning, data deduplication and data deletion filling are carried out on the data;
step 103: and extracting features of the preprocessed data, extracting required feature data, and establishing a data set.
It should be noted that the number of buildings, landmarks, intersections and road segments in the area greatly affect the activities in the area, which may result in an increase or decrease in the traffic flow, so that it is necessary to divide these into areas as much as possible so as not to affect the analysis result.
Combining the contents of steps 101 to 103:
the same building group, landmark buildings, intersections and road sections are divided into one area, so that statistics and analysis are facilitated, and inaccurate data statistics caused by splitting the same building group into different areas is avoided; by preprocessing the data and extracting the characteristics, unnecessary data interference is reduced, relevant effective information is extracted, the quality and the integrity of the data are improved, and the subsequent analysis is facilitated.
Step two: analyzing traffic conditions in the area, correlating the traffic flow Pt and the traffic flow Tr to obtain an in-area traffic thermodynamic value Thv, calculating an in-area road network density value Dr through the number of roads Nr and the area Aa, and analyzing the in-area traffic thermodynamic value Thv and the in-area road network density value Dr to obtain an in-area traffic thermodynamic index Thi;
the second step comprises the following steps:
step 201: extracting characteristic data from the data set, and acquiring the people flow Pt, the vehicle flow Tr, the road number Nr and the area Aa in the area;
step 202: correlating the traffic flow Pt and the traffic flow Tr in the area, performing dimensionless treatment, and obtaining the traffic thermodynamic value Thv in the area, wherein the calculation formula is as follows:
；
wherein a is 1 、a 2 Is a weight coefficient, and，/>，/>；
step 203: calculating the number Nr of roads in the area and the area Aa of the area to obtain a road network density value Dr in the area:
；
the calculation formula of the road network density value Dr in the region is shown as above;
step 204: analyzing the traffic thermodynamic value Thv in the area and the road network density value Dr in the area, performing dimensionless treatment, and further calculating the traffic thermodynamic index Thi in the area, wherein the calculation formula is as follows:
；
wherein θ is a correction coefficient, an。
It should be noted that, when the traffic flow and the traffic flow in the area are larger, the number of roads in the area is larger, and the traffic heat index in the area is larger, otherwise, the traffic heat index in the area is smaller, and when the traffic heat index in the area is larger, the production and living activities in the area are more frequent, and the map updating frequency is required to be faster.
Combining the contents of steps 201 to 204:
by analyzing the traffic flow Pt, the traffic flow Tr, the road number Nr and the area Aa of the area, the traffic heat index Thi of the current area is obtained, and whether the human activities of the current area are frequent or not and the degree of the current area is luxury can be rapidly judged, so that the determination of the map updating frequency of the current area is more accurately evaluated.
Step three: analyzing living production activities in the area to obtain the number Sn of shops, the number Hn of residences and the number Cn of enterprises and institutions, calculating the current in-area generated living heat value Phv, calculating the number Nr of roads in the area and the area Aa of the area to obtain an in-area road network density value Dr, and correlating the current in-area generated living heat value Phv with the in-area road network density value Dr to obtain the current in-area generated living heat index Phi;
the third step comprises the following steps:
step 301: extracting characteristic data from the data set to obtain the number of shops Sn, the number of residences Hn and the number of enterprises and institutions Cn;
step 302: calculating a current area generated living heat value Phv according to the number Sn of shops, the number Hn of houses and the number Cn of enterprises and institutions, wherein the calculation formula is as follows:
；
wherein b 1 、b 2 、b 3 Is a weight coefficient, and，/>，/>；
step 303: calculating the number Nr of roads in the area and the area Aa of the area to obtain a road network density value Dr in the area:
；
the calculation formula of the road network density value Dr in the region is shown as above;
step 304: the production and living thermodynamic value Phv and the intra-area road network density value Dr are correlated, dimensionless treatment is carried out, and the current intra-area production activity thermodynamic index Phi is obtained, wherein the calculation formula is as follows:
；
wherein θ is a correction coefficient, an。
When the number of businesses Sn, the number of residences Hn, and the number of enterprises and institutions Cn in the area are larger, the higher the production/life heat index Phi in the current area is, the more frequent the human activities in the current area are, and therefore, the faster the map update frequency in the current area is required.
Combining the contents of steps 301 to 304:
the production and life heat power indexes Phi of the current area are obtained by analyzing the number of shops Sn, the number of residences Hn, the number of enterprises and public institutions Cn, the number of roads Nr and the area Aa in the current area, and the frequency of the artificial activities of the current area can be rapidly estimated, so that the map updating frequency of the current area can be rapidly judged.
Step four: the traffic heat index Thi and the production and living heat index Phi of the current area are synthesized, the comprehensive heat index Chi in the current area is further analyzed, a first heat threshold value and a second heat threshold value are preset, the comparison is carried out with the heat threshold values, and corresponding measures are carried out according to different comparison results;
the fourth step comprises the following steps:
step 401: acquiring a traffic heat index Thi and a production life heat index Phi of a current area;
step 402: according to the traffic heat index Thi and the production and living heat index Phi, the comprehensive heat index Chi of the current area is calculated, and the calculation formula is as follows:
；
wherein c 1 、c 2 Is a weight coefficient, and，/>，/>；
step 403: the method comprises the steps of presetting a first thermal threshold and a second thermal threshold, comparing the first thermal threshold with a comprehensive thermal index Chi of a current area, and making corresponding measures according to different comparison results, wherein the measures specifically comprise:
when the comprehensive heat index Chi is smaller than the first heat threshold, the current area map updating frequency priority is set to be low priority when the current area map updating frequency is lower;
when the first thermodynamic threshold value is smaller than or equal to the comprehensive thermodynamic index Chi and smaller than or equal to the second thermodynamic threshold value, the current artificial activity frequency degree is general, and the current area map updating frequency priority is set to be a medium priority;
and when the comprehensive heat index Chi > is higher than the second heat threshold, the current area map updating frequency priority is set to be high priority.
It should be noted that, the higher the traffic heat index Thi and the production heat index Phi of the current area are, the higher the comprehensive heat index Chi is, and the lower the comprehensive heat index Chi is, and the higher the comprehensive heat index Chi is, the more frequent the artificial activity of the current area is directly reflected, and the faster the map updating frequency is required for the area with the higher frequent artificial activity.
Combining the contents of steps 401 to 403:
the traffic heat index Thi and the production and life heat index Phi of the current area are comprehensively analyzed to obtain the comprehensive heat index Chi of the current area, the comprehensive heat index Chi is compared with a preset first heat threshold and a preset second heat threshold, corresponding measures are taken according to the comparison result, so that resources are better regulated, the maps of different areas are updated, the situation that the map is not updated timely in the areas with frequent artificial activities is avoided, the efficiency is greatly improved, and the waste of the resources is avoided.
Step five: and (3) carrying out independent analysis on the tourist hot spot area, obtaining the annual average tourist number Anp, the annual average vehicle flow Anc, the network search amount Wsv and the tourist light and vigorous season index Lp of the tourist hot spot area, calculating the tourist heat index Rsi of the current tourist area, comparing with a preset tourist heat threshold value, and carrying out corresponding measures according to different comparison results.
The specific content of the fifth step comprises:
step 501: extracting characteristic data from the data set, and acquiring annual average tourist number Anp, annual average vehicle flow Anc, network search amount Wsv and tourist light and vigorous season index Lp of the tourist hot spot area;
step 502: judging whether the travel is off-season or traveling in a busy season according to the current season, and allocating different values according to different seasons to set the off-seasonIn the great season->；
Step 503: the average annual tourist number, the average annual traffic flow, the network search amount and the tourist light and strong season index Lp are correlated, and the tourist heat index Rsi of the current tourist area is calculated according to the following calculation formula:
；
wherein alpha, beta and gamma are weight coefficients, and，/>，/>，/>is a correction coefficient, and；
step 504: the method comprises the steps of presetting a tourist thermal threshold value, comparing with a tourist thermal index Rsi, and making corresponding measures according to different comparison results, wherein the steps are as follows:
when the tourist heat index Rsi is smaller than the tourist heat threshold value, indicating that the heat of the current tourist area is low, setting the update frequency priority of the current tourist area to be low priority;
when the travel heat index Rsi is more than or equal to the travel heat threshold, the current travel area is indicated to be high in heat, and the update frequency priority of the current travel area is set to be high.
It should be noted that, when the average annual tourist number, the average annual traffic flow and the web search amount are higher, the tourist heat index of the current tourist area is higher, otherwise, the lower the tourist heat index of the current tourist area is, the higher the heat of the current tourist area is reflected, and the map needs to be updated more quickly in the tourist area with higher heat.
Combining the contents of steps 501 to 504:
the travel heat index Rsi of the current travel area is obtained by analyzing the related data of the current travel area, and compared with the preset travel heat threshold, and higher priority is allocated to the area with higher travel heat according to the comparison result, so that the allocation of resources is optimized, the map updating efficiency is improved, and the user experience is improved.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.
Claims (7)
1. A map data updating method applied to a navigation system, comprising the steps of:
dividing a map into a plurality of areas, collecting map data in the areas through different channels, preprocessing the data and extracting features, and establishing a data set;
analyzing traffic conditions in the area, correlating the traffic flow Pt and the traffic flow Tr to obtain an in-area traffic thermodynamic value Thv, calculating an in-area road network density value Dr through the number of roads Nr and the area Aa, and analyzing the in-area traffic thermodynamic value Thv and the in-area road network density value Dr to obtain an in-area traffic thermodynamic index Thi;
the analysis process of the traffic heat index Thi in the area is as follows:
analyzing the traffic thermodynamic value Thv in the area and the road network density value Dr in the area, performing dimensionless treatment, and further calculating the traffic thermodynamic index Thi in the area, wherein the calculation formula is as follows:
；
wherein θ is a correction coefficient, an；
Analyzing living production activities in the area to obtain the number Sn of shops, the number Hn of residences and the number Cn of enterprises and institutions, calculating the current in-area generated living heat value Phv, calculating the number Nr of roads in the area and the area Aa of the area to obtain an in-area road network density value Dr, and correlating the current in-area generated living heat value Phv with the in-area road network density value Dr to obtain the current in-area generated living heat index Phi;
the in-region generated activation heat index Phi analysis process is as follows:
the production and living thermodynamic value Phv and the intra-area road network density value Dr are correlated, dimensionless treatment is carried out, and the current intra-area production activity thermodynamic index Phi is obtained, wherein the calculation formula is as follows:
；
wherein θ is a correction coefficient, an；
The traffic heat index Thi and the production and living heat index Phi of the current area are synthesized, the comprehensive heat index Chi of the current area is further analyzed, and the analysis process of the comprehensive heat index Chi in the area is as follows:
acquiring a traffic heat index Thi and a production life heat index Phi of a current area;
according to the traffic heat index Thi and the production and living heat index Phi, the comprehensive heat index Chi of the current area is calculated, and the calculation formula is as follows:
；
wherein c 1 、c 2 Is a weight coefficient, and，/>，/>；
the method comprises the steps of presetting a first thermal threshold and a second thermal threshold, comparing the first thermal threshold with a comprehensive thermal index Chi of a current area, and making corresponding measures according to different comparison results, wherein the measures specifically comprise:
when the comprehensive heat index Chi is smaller than the first heat threshold, setting the current area map updating frequency priority to be low;
when the first thermodynamic threshold value is less than or equal to the comprehensive thermodynamic index Chi and less than or equal to the second thermodynamic threshold value, setting the current area map updating frequency priority as a medium priority;
when the integrated heat index Chi > the second heat threshold, the current area map update frequency priority is set to a high priority.
2. The map data updating method applied to a navigation system according to claim 1, wherein the analysis process of the traffic heating value Thv in the area is as follows:
extracting characteristic data from the data set, and acquiring the people flow Pt, the vehicle flow Tr, the road number Nr and the area Aa in the area; correlating the traffic flow Pt and the traffic flow Tr in the area, performing dimensionless treatment, and obtaining the traffic thermodynamic value Thv in the area, wherein the calculation formula is as follows:
；
wherein a is 1 、a 2 Is a weight coefficient, and，/>，/>。
3. the map data updating method applied to a navigation system according to claim 1, wherein the analysis process of the intra-area road network density value Dr is as follows:
calculating the number Nr of roads in the area and the area Aa of the area to obtain a road network density value Dr in the area:
；
the calculation formula of the road network density value Dr in the region is shown as above.
4. A map data updating method applied to a navigation system as recited in claim 1, wherein,
the analytical process of generating the activation heat value Phv in the region is as follows:
extracting characteristic data from the data set to obtain the number of shops Sn, the number of residences Hn and the number of enterprises and institutions Cn; calculating a current area generated living heat value Phv according to the number Sn of shops, the number Hn of houses and the number Cn of enterprises and institutions, wherein the calculation formula is as follows:
；
wherein b 1 、b 2 、b 3 Is a weight coefficient, and，/>，/>。
5. the map data updating method for a navigation system according to claim 1, wherein the tourist hot spot area is individually analyzed to obtain the annual average tourist number Anp, the annual average traffic flow Anc, the web search Wsv and the tourist light and vigorous season index Lp, the tourist heat index Rsi of the current tourist area is calculated, and the tourist heat index Rsi of the current tourist area is compared with a preset tourist heat threshold value to make corresponding measures according to different comparison results.
6. A map data updating method applied to a navigation system as claimed in claim 5, wherein the analysis process of the tourist heat index Rsi of the tourist area is as follows:
extracting characteristic data from the data set, and acquiring annual average tourist number Anp, annual average vehicle flow Anc, network search amount Wsv and tourist light and vigorous season index Lp of the tourist hot spot area; judging whether the travel is off-season or traveling in a busy season according to the current season, and allocating different values according to different seasons to set the off-seasonIn the great season->；
The average annual tourist number, the average annual traffic flow, the network search amount and the tourist light and strong season index Lp are correlated, and the tourist heat index Rsi of the current tourist area is calculated according to the following calculation formula:
；
wherein alpha, beta and gamma are weight coefficients, and，/>，/>，/>is a correction coefficient, and。
7. the map data updating method for a navigation system according to claim 6, wherein a tour heat threshold is preset, and compared with a tour heat index Rsi, and corresponding measures are made according to different comparison results, specifically:
when the travel heat index Rsi < the travel heat threshold, the update frequency priority of the current travel area is set to be low priority;
when the travel heat index Rsi is greater than or equal to the travel heat threshold, the update frequency priority of the current travel area is set to be high.
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