CN111723169A - Map display method and device, electronic equipment and storage medium - Google Patents

Map display method and device, electronic equipment and storage medium Download PDF

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Publication number
CN111723169A
CN111723169A CN202010273418.5A CN202010273418A CN111723169A CN 111723169 A CN111723169 A CN 111723169A CN 202010273418 A CN202010273418 A CN 202010273418A CN 111723169 A CN111723169 A CN 111723169A
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road
congestion
target time
time period
probability
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Chinese (zh)
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张勇
孙立光
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Tencent Technology Shenzhen Co Ltd
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Tencent Technology Shenzhen Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services

Abstract

The application discloses a map display method, a map display device, electronic equipment and a storage medium; according to the method and the device, each road in the geographic area can be divided into a plurality of road sections, and the congestion probability of each road in the target time interval is calculated based on the length of each road section on each road and the congestion information in the target time interval; adjusting the congestion probability based on the historical congestion information of each road to obtain the adjusted congestion probability of each road; determining a congested road in a target time period from the plurality of roads based on the adjusted congestion probability; and displaying a map of the geographic area, wherein the map is marked with congested roads. The method and the device only limit the calculation of the congestion probability of the road in the target time period, divide each road into a plurality of road sections, and simply calculate the congestion probability of the road based on the congestion information of the road sections to determine the congested road.

Description

Map display method and device, electronic equipment and storage medium
Technical Field
The present application relates to the field of computer technologies, and in particular, to a map display method and apparatus, an electronic device, and a storage medium.
Background
With the rapid development of economy, the process of traffic motorization is accelerated, and road traffic congestion becomes an important problem in the development of modern cities, which seriously affects the normal operation of urban traffic.
In the current related technology, a road condition spatiotemporal distribution map is generally obtained according to historically issued road condition information and road network data recorded in an electronic map service, and then congestion clusters in the road condition spatiotemporal distribution map are determined through a spatial clustering algorithm to mine road sections which are frequently congested.
Disclosure of Invention
The embodiment of the application provides a map display method, a map display device, electronic equipment and a storage medium, which can simplify the process of determining congested roads, facilitate the reduction of calculation complexity and enable calculation results to reflect the real situation more directly.
The embodiment of the application provides a map display method, which comprises the following steps:
dividing each road in a geographic area into a plurality of road sections to obtain a plurality of road sections of each road;
calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period;
based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road;
determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability;
displaying a map of the geographic area, wherein the map is marked with the congested road.
Accordingly, an embodiment of the present application provides a map display device, including:
the dividing unit is used for dividing each road in the geographic area into a plurality of road sections to obtain a plurality of road sections of each road;
the calculating unit is used for calculating the congestion probability of each road in the target time interval based on the length of each road section on each road and the congestion information in the target time interval;
the adjusting unit is used for adjusting the congestion probability of each road based on the historical congestion information of each road to obtain the adjusted congestion probability of each road;
the determining unit is used for determining the congested road in the target time period from a plurality of roads according to the adjusted congestion probability;
and the display unit is used for displaying a map of the geographic area, wherein the map is marked with the congestion road.
Optionally, in some embodiments of the present application, the calculating unit may include a weighting subunit and a first calculating subunit, as follows:
the weighting subunit is configured to perform weighting operation on the congestion information of each road segment in the target time interval on each road by using the length of each road segment in each road as a weight, so as to obtain the congestion information of each road in the target time interval;
and the first calculating subunit is used for calculating the congestion probability of each road in the target time interval based on the congestion information of each road in the target time interval.
Optionally, in some embodiments of the present application, the congestion information of each road segment in the target time period includes a congestion time length of each road segment in the target time period; the weighting subunit may be specifically configured to perform a weighting operation on the congestion time of each road segment in the target time period by using the length of each road segment on each road as a weight, so as to obtain the congestion information of each road in the target time period.
Optionally, in some embodiments of the present application, the adjusting unit may include a second calculating subunit and a fusing subunit, as follows:
the second calculating subunit is configured to calculate a historical congestion probability of each road based on the historical congestion information of each road;
and the fusion subunit is used for obtaining the adjusted congestion probability of each road according to the congestion probability and the historical congestion probability of each road.
Optionally, in some embodiments of the present application, the determining unit may include a sorting subunit and a determining subunit, as follows:
the sorting subunit is configured to sort the roads according to the adjusted congestion probability;
and the determining subunit is used for determining the congested road in the target time interval from a plurality of roads based on the sequencing positions of the roads.
Optionally, in some embodiments of the application, the sorting subunit may be specifically configured to pre-sort the roads according to the adjusted congestion probability; and when the difference value of the adjusted congestion probabilities of the two pre-sequenced adjacent roads is smaller than a preset value, adjusting the sequencing positions of the two adjacent roads based on the lengths of the two adjacent roads and the adjusted congestion probabilities.
Optionally, in some embodiments of the present application, the display unit may include a first display subunit and a second display subunit, as follows:
the first display subunit is configured to, when receiving a first viewing instruction for the congested road, display road condition information of the congested road on a map of the geographic area;
and the second display subunit is used for displaying the congested road in an enlarged manner on the map of the geographic area by taking the congested road as a center when a second viewing instruction of the congested road is received.
The electronic device provided by the embodiment of the application comprises a processor and a memory, wherein the memory stores a plurality of instructions, and the processor loads the instructions to execute the steps in the map display method provided by the embodiment of the application.
In addition, the embodiment of the present application further provides a storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the steps in the map display method provided by the embodiment of the present application.
The embodiment of the application provides a map display method, a map display device, electronic equipment and a storage medium, wherein each road in a geographic area can be divided into a plurality of road sections, and the plurality of road sections of each road are obtained; calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period; based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road; determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability; displaying a map of the geographic area, wherein the map is marked with the congested road. The method and the device only limit the calculation of the congestion probability of the road in the target time period, divide each road into a plurality of road sections, and simply calculate the congestion probability of the road based on the congestion information of the road sections, so as to determine the congested road, and do not introduce a complex algorithm, thereby reducing the calculation complexity.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1a is a scene schematic diagram of a map display method provided in an embodiment of the present application;
fig. 1b is a flowchart of a map display method provided in an embodiment of the present application;
fig. 1c is a schematic illustration showing a map display method according to an embodiment of the present application;
fig. 1d is another schematic illustration showing a map displaying method according to an embodiment of the present disclosure;
fig. 2 is another flowchart of a map display method provided in an embodiment of the present application;
fig. 3a is a schematic structural diagram of a map display device according to an embodiment of the present application;
fig. 3b is another schematic structural diagram of a map display device according to an embodiment of the present application;
fig. 3c is another schematic structural diagram of a map display device according to an embodiment of the present application;
fig. 3d is another schematic structural diagram of a map display device according to an embodiment of the present application;
fig. 3e is another schematic structural diagram of a map display device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiment of the application provides a map display method and device, electronic equipment and a storage medium. Specifically, the embodiment of the present application provides a map display device suitable for an electronic device, where the electronic device may be a terminal or a server.
It is understood that the map display method of the present embodiment may be executed on the terminal, may be executed on the server, or may be executed by both the terminal and the server.
Referring to fig. 1a, a method for displaying a map by a terminal and a server is taken as an example. The map display system provided by the embodiment of the application comprises a terminal 10, a server 11 and the like; the terminal 10 and the server 11 are connected via a network, for example, a wired or wireless network connection, wherein the map display device may be integrated in the terminal, for example, in the terminal 10 in the form of a client, which may be an application client or the like.
A terminal 10 operable to: dividing each road in a geographic area into a plurality of road sections to obtain a plurality of road sections of each road; calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period; based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road; determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability; displaying a map of the geographic area, wherein the map is marked with the congested road. The terminal 10 may include a mobile phone, a tablet Computer, a notebook Computer, a Personal Computer (PC), or the like.
When detecting that the application client is started, the terminal 10 may send a congested road display request to the server 11, where the congested road display request may include a geographic location of the terminal 10, so as to trigger the server 11 to determine a geographic area based on the geographic location, and calculate congested roads in the geographic area, and the terminal 10 further receives data of the congested roads sent by the server 11, and displays a map of the geographic area based on the congested road data, where the map is marked with the congested roads.
The server 11 may be configured to calculate a congested road in a geographic area when receiving a congested road display request transmitted by the terminal 10, and transmit data of the calculated congested road to the terminal 10. The server 11 may be a single server or a server cluster including a plurality of servers.
The specific process of calculating the congested road in the geographic area may include: dividing each road in a geographic area into a plurality of road sections to obtain a plurality of road sections of each road; calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period; based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road; and determining the congested road in the target time period from a plurality of roads according to the adjusted congestion probability.
The above-described process of calculating the congested road by the server 11 may be executed by the terminal 10.
The following are detailed below. It should be noted that the following description of the embodiments is not intended to limit the preferred order of the embodiments.
The embodiment of the present application will be described from the perspective of a map display apparatus, which may be specifically integrated in an electronic device, where the electronic device may be a server or a terminal.
The map display device provided by the embodiment of the application can be applied to various scenes needing to display congested roads to display the congested roads. For example, the method can be applied to relevant scenes of electronic map services, such as vehicle navigation and network appointment business, and displays a map after a relevant application program client is opened, wherein the map is marked with congested roads.
As shown in fig. 1b, the specific flow of the map display method is as follows:
101. each road in the geographic area is divided into a plurality of road sections, and a plurality of road sections of each road are obtained.
The geographic area may be a certain area range including the current location, and the area range may be set according to an actual situation, which is not limited in this embodiment, for example, the geographic area may be set to be within 5 kilometers of the current location.
Optionally, in this embodiment, the road section refers to a road section identifier in the electronic map, and the road section may be a road section of several tens to kilometers, and is usually a part of a real road; a road refers to a road sign in an electronic map, and a road can be understood as being composed of a plurality of road segments, which can be a series of road segment sets between two adjacent intersections.
102. And calculating the congestion probability of each road in the target time interval based on the length of each road section on each road and the congestion information in the target time interval.
The target time period can be customized by the user, which is not limited in this embodiment, for example, the target time period can be defaulted to an on-duty early peak time period and an off-duty late peak time period, and the user can adjust the target time period according to the actual on-duty and off-duty situation. In addition, each road may be composed of a series of segments, the lengths of the segments may not be consistent, and the factor of the lengths of the segments may be considered when calculating the congestion probability of the road.
Optionally, in some embodiments, the step "calculating a congestion probability of each road in the target time period based on the length of each road segment on each road and the congestion information in the target time period" may include:
taking the length of each road section on each road as a weight, and carrying out weighted operation on the congestion information of each road section on each road in a target time interval to obtain the congestion information of each road in the target time interval;
and calculating the congestion probability of each road in the target time period based on the congestion information of each road in the target time period.
Wherein, in some embodiments, the target time period may refer to an early peak time period, a late peak time period, and the like. In the embodiment, the accurate positioning of congestion in time is not concerned, and the calculation of the congestion probability of each road in a specified scene is only limited, wherein the specified scene can be the congestion situation of the road at the peak early on duty or the peak late on duty, the calculation amount is greatly reduced because the statistics of all time periods is not required, and the calculation result more directly reflects the real situation. For example, the congestion probability of the road in the early peak time period or the late peak time period is calculated by using the data (i.e., congestion information) of the early peak time period or the late peak time period, so that the calculated result can better reflect the actual congestion state of the road in the early peak time period and the late peak time period.
The congestion information of the road segment may include a congestion time length of the road segment, an average speed of the road segment, and the like. The link average speed is the average speed of travel of the vehicle for the link over the target time period. Optionally, in some embodiments, if the average speed of the road segment is lower than 10 kilometers per hour in a target time period of N consecutive days, the road segment may be determined as a congested road segment, where N is a positive integer, for example, N may be 5, 10, or 15, and the present embodiment does not limit this.
Optionally, in some embodiments, the congestion information of each road segment in the target time period includes a congestion time length of each road segment in the target time period; the step of performing a weighted operation on the congestion information of each road segment in the target time interval by using the length of each road segment on each road as a weight to obtain the congestion information of each road in the target time interval may include:
and taking the length of each road section on each road as a weight, and carrying out weighted operation on the congestion time of each road section on each road in the target time interval to obtain the congestion information of each road in the target time interval.
In this embodiment, a road may be denoted as c, a link may be denoted as link (traffic route), the road c may be a set of links in a series of links between two adjacent intersections, and the link may be a linear link of several tens to kilometers. The congestion time of each link in the target time period can be obtained, and then the congestion probability of each road c in the target time period is calculated based on the length of each link. The specific calculation process may be that the sum of weighted values of the congestion durations of all the links in the road in the target time period and the space length of the links in the target time period is divided by the total length of the road c multiplied by the duration of the total amount of the target time period, wherein the duration of the total amount of the target time period refers to the time length of the target time period.
Optionally, there are various ways to obtain the congestion time and the length of each road segment in the target time period. For example, the congestion duration and the link length of each link in the target time period may be obtained by other devices, and then provided to the map display apparatus, that is, the map display apparatus may specifically receive the congestion duration and the link length of the link in the target time period, which are sent by other devices, such as other terminals or servers. For another example, the congestion duration and the link length of the link in the target time period may be obtained from a local database of the electronic device, and specifically, the congestion duration and the link length of the link in the target time period are stored in the local database of the electronic device, so that when an instruction for obtaining the congestion duration and the link length data of the link in the target time period is received, the congestion duration and the link length data of the link in the target time period may be directly extracted from the local database of the electronic device, where the local location refers to the electronic device.
For example, in a specific embodiment, the congestion probability of the morning peak of a certain day needs to be acquired, that is, the target time interval is the morning peak time period, the time from 7 am to 10 am can be set as the morning peak time period, and the total time length of the target time interval is 180 minutes. It is understood that another time period may be set as the early peak time period, which is not limited by the embodiment. The calculation process of the road congestion probability is shown as formula (1):
Figure BDA0002443945590000081
wherein r represents the congestion probability of a road in a target time period, n is the number of road segments in the road, i represents the ith road segment of the road, i is more than or equal to 1 and less than or equal to n, i is a positive integer, liIndicates the length of the ith road section, tiIndicating the congestion time of the ith road section in the target time period, tiIn units of minutes,. lcThe length of the whole road is expressed, and the numerator in the formula (1) represents the length weighted sum of the congestion time lengths of each road section of one road in the target time interval, namely the total congestion weighted value of the total length of the road, that is, the numerator is the congestion information of one road, wherein the length of each road section is the weight, and the denominator is the product of the total length of the road and the total time length.
103. And adjusting the congestion probability of each road based on the historical congestion information of each road to obtain the adjusted congestion probability of each road.
The historical congestion information of each road may be the historical congestion probability of each road, or the historical congestion information of each road section of each road, and the historical congestion information may be the historical congestion duration of each road section in the target time period. For example, in a scenario in which the adjusted congestion probability of the early peak time period road is calculated, the adjusted congestion probability of the road may be calculated by counting the congestion situations of the road in the early peak time period on the last month working day (generally, monday to friday). Specifically, the congestion probability of the road in the early peak time period of more than 20 consecutive working days in a month can be obtained based on the congestion information of each road segment in the early peak time period every day, and then the congestion probability of the consecutive working days is averaged, where the average is the adjusted congestion probability of the road. Through the mode, data of a single day can be smoothed, the influence caused by data abnormity is reduced, meanwhile, the condition of the latest month is counted, and the timeliness of the calculation result can be guaranteed.
Based on the historical congestion information of each road, there may be many ways to adjust the congestion probability of each road, which is not limited in this embodiment. For example, the historical congestion probability of each road may be calculated based on the historical congestion information of each road, and the historical congestion probability may include congestion probabilities in a target time period of multiple days, and the congestion probability of the road may be added, so that a median or an average of all the congestion probabilities may be taken as the adjusted congestion probability of the road.
Optionally, in some embodiments, the step "adjusting the congestion probability of each road based on the historical congestion information of each road to obtain the adjusted congestion probability of each road" may include:
calculating the historical congestion probability of each road based on the historical congestion information of each road;
and obtaining the adjusted congestion probability of each road according to the congestion probability and the historical congestion probability of each road.
The step of obtaining the adjusted congestion probability of each road according to the congestion probability and the historical congestion probability of each road may specifically include: and fusing the congestion probability and the historical congestion probability of each road to obtain the adjusted congestion probability of each road. The fusion mode may be an averaging mode, specifically, an averaging mode is performed on all the congestion probabilities corresponding to each road, that is, the adjusted congestion probability of each road.
The specific process of calculating the historical congestion probability of each road based on the historical congestion information of each road may refer to the calculation process of the congestion probability in step 102.
Optionally, in some embodiments, the historical congestion information of each road may be historical congestion time of each road segment of each road; the step of calculating the historical congestion probability of each road based on the historical congestion information of each road may specifically include:
taking the length of each road section on each road as a weight, and carrying out weighted operation on the historical congestion duration of each road section on each road to obtain the historical congestion information of each road;
and calculating the historical congestion probability of each road in a target time period based on the historical congestion information of each road.
Optionally, in some embodiments, if the congestion probability of the road for half of the days in the target time period of the past N days exceeds a preset value, the road may be determined as a congested road, and the preset value may be set according to an actual situation, which is not limited in this embodiment.
104. And determining the congested road in the target time period from a plurality of roads according to the adjusted congestion probability.
Optionally, in some embodiments, a road with the adjusted congestion probability being greater than a preset congestion probability may be determined as the congested road in the target time period, where the preset congestion probability may be set according to an actual situation, and this embodiment does not limit this.
Optionally, in some embodiments, the step "determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability" may include:
sorting the roads according to the adjusted congestion probability;
and determining the congested road in the target time period from a plurality of roads based on the sequencing positions of the roads.
The roads can be sorted from big to small or from small to big according to the adjusted congestion probability.
If the roads are ranked from large to small based on the adjusted congestion probability, specifically, the step "determining the congested road in the target time interval from the multiple roads based on the ranked positions of the roads" may include:
determining the first A roads as congested roads in the target time period based on the sorting positions of the roads, wherein A is a positive integer not exceeding the total number of the roads; or the like, or, alternatively,
and determining the first B roads as the congested roads in the target time period based on the sorted positions of the roads, wherein B is a positive number which is greater than 1 and does not exceed the total number of the roads.
The values of a and B may be set according to actual situations, and this embodiment does not limit this.
Optionally, the roads are arranged from large to small mainly based on the adjusted congestion probability, and if the adjusted congestion probability is not very different, a road with a longer road length may be arranged in front of a road with a shorter road length.
For example, in some embodiments, the step of "ordering the roads according to the magnitude of the adjusted congestion probability" may include:
pre-sequencing the roads according to the adjusted congestion probability;
and when the difference value of the adjusted congestion probabilities of the two pre-sequenced adjacent roads is smaller than a preset value, adjusting the sequencing positions of the two adjacent roads based on the lengths of the two adjacent roads and the adjusted congestion probabilities.
For example, the preset value may be set to 0.1, and if the difference between the adjusted congestion probabilities of two pre-sorted adjacent roads is smaller and less than 0.1, it may be considered that a road with a longer road length is ranked before a road with a shorter road length. Specifically, in one embodiment, the roads are arranged from large to small based on the adjusted congestion probability; and when the difference of the adjusted congestion probability is within 20%, arranging the products of the adjusted congestion probability and the road length, and arranging the higher product of the adjusted congestion probability and the road length in front.
105. Displaying a map of the geographic area, wherein the map is marked with the congested road.
Alternatively, the congested roads may be marked in the map in various ways. For example, the congested road may be marked in red to distinguish it from other roads. Further, in some embodiments, in the case of a zoomed-out display of the map, the congested road may be marked with dots; in the case of a map enlarged display, the congested road may be marked with a thick line.
For example, referring to FIG. 1c, a road with congestion ranking 20 top is shown during a target time period, which may be an early peak time period or a late peak time period, with congested roads marked with dots and dark lines.
Optionally, in some embodiments, the step of "displaying a map of the geographic area" may include:
when a first viewing instruction of the congested road is received, displaying road condition information of the congested road on a map of the geographic area;
and when a second viewing instruction for the congested road is received, magnifying and displaying the congested road on the map of the geographic area by taking the congested road as a center.
The first viewing instruction may specifically be a click operation or a slide operation on a congested road on a map, and based on the click operation or the slide operation on the congested road, road condition information of the congested road may be displayed on the map, where the road condition information may include information such as a congestion length of the congested road, a direction of the congested road, an average speed of vehicles on the congested road, and a length of the congested road. Based on the road condition information of the congested road, the user can quickly know the specific congestion condition of the road.
The second viewing instruction may specifically be a double-click operation (i.e., two continuous click operations in a short time) in a certain area around the congested road on the map page, and the like, which is not limited in this embodiment. Based on the second viewing instruction, the map page can be displayed in an enlarged manner, and the congested road is taken as the center.
For example, as shown in fig. 1d, the image is an enlarged display image with the congested road as the center, and the direction information of the congested road is displayed in the image.
The complex algorithm in the prior art has large calculation amount, and a large amount of calculation is spent on the accurate positioning problem of the jam time. The method only limits the calculation of the congestion probability of the road in the target time period, namely the calculated congestion probability in the specific time period concerned by the user; the method can better meet the actual requirements of users while reducing the calculation complexity.
As can be seen from the above, in the present embodiment, each road in the geographic area may be divided into a plurality of road segments, so as to obtain a plurality of road segments of each road; calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period; based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road; determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability; displaying a map of the geographic area, wherein the map is marked with the congested road. The method and the device only limit the calculation of the congestion probability of the road in the target time period, divide each road into a plurality of road sections, and simply calculate the congestion probability of the road based on the congestion information of the road sections, so as to determine the congested road, reduce the calculation complexity, and simultaneously, because other algorithms and parameters set manually are not introduced, the calculation result can more directly reflect the real situation.
The method described in the foregoing embodiment will be described in further detail below with an example in which the map display apparatus is specifically integrated in a server.
An embodiment of the present application provides a map display method, and as shown in fig. 2, a specific process of the map display method may be as follows:
201. the method comprises the steps that a server receives a congested road display request sent by a terminal, wherein the congested road display request comprises a geographical area needing to display a congested road.
The geographic area may be a certain area range including a current location of the terminal, and the area range may be set according to an actual situation, which is not limited in this embodiment, for example, the geographic area may be set to be within a range of 5 kilometers around the current location.
202. The server divides each road in the geographic area into a plurality of road sections to obtain a plurality of road sections of each road.
Optionally, in this embodiment, the road section refers to a road section identifier in the electronic map, and the road section may be a road section of several tens to kilometers, and is usually a part of a real road; a road refers to a road sign in an electronic map, and a road can be understood as being composed of a plurality of road segments, which can be a series of road segment sets between two adjacent intersections.
203. The server calculates the congestion probability of each road in the target time period based on the length of each road section on each road and the congestion information in the target time period.
Optionally, in some embodiments, the step "the server calculates the congestion probability of each road in the target time period based on the length of each road segment on each road and the congestion information in the target time period" may include:
taking the length of each road section on each road as a weight, and carrying out weighted operation on the congestion information of each road section on each road in a target time interval to obtain the congestion information of each road in the target time interval;
and calculating the congestion probability of each road in the target time period based on the congestion information of each road in the target time period.
In some embodiments, the target time period may refer to an early peak time period, a late peak time period, and the like, and the user may adjust the target time period according to the actual work attendance situation of the user. In the embodiment, the accurate positioning of congestion in time is not concerned, and the calculation of the congestion probability of each road in a specified scene is only limited, wherein the specified scene can be the congestion situation of the road at the peak early on duty or the peak late on duty, the calculation amount is greatly reduced because the statistics of all time periods is not required, and the calculation result more directly reflects the real situation. For example, the congestion probability of the road in the early peak time period or the late peak time period is calculated by using the data (i.e., congestion information) of the early peak time period or the late peak time period, so that the calculated result can better reflect the actual congestion state of the road in the early peak time period and the late peak time period.
The congestion information of the road segment in the target time period may include congestion time of the road segment in the target time period, average speed of the road segment, and the like. The link average speed is the average speed of travel of the vehicle for the link over the target time period.
Optionally, in some embodiments, the congestion information of each road segment in the target time period includes a congestion time length of each road segment in the target time period; the step of performing a weighted operation on the congestion information of each road segment in the target time interval by using the length of each road segment on each road as a weight to obtain the congestion information of each road in the target time interval may include:
and taking the length of each road section on each road as a weight, and carrying out weighted operation on the congestion time of each road section on each road in the target time interval to obtain the congestion information of each road in the target time interval.
204. And the server adjusts the congestion probability of each road based on the historical congestion information of each road to obtain the adjusted congestion probability of each road.
The historical congestion information of each road may be the historical congestion probability of each road, or the historical congestion information of each road section of each road, and the historical congestion information may be the historical congestion duration of each road section in the target time period. For example, in a scenario in which the adjusted congestion probability of the early peak time period road is calculated, the adjusted congestion probability of the road may be calculated by counting the congestion situations of the road in the early peak time period on the last month working day (generally, monday to friday). Specifically, the congestion probability of the road in the early peak time period of more than 20 consecutive working days in a month can be obtained based on the congestion information of each road segment in the early peak time period every day, and then the congestion probability of the consecutive working days is averaged, where the average is the adjusted congestion probability of the road. Through the mode, data of a single day can be smoothed, the influence caused by data abnormity is reduced, meanwhile, the condition of the latest month is counted, and the timeliness of the calculation result can be guaranteed.
Optionally, in some embodiments, the step "the server adjusts the congestion probability of each road based on the historical congestion information of each road to obtain the adjusted congestion probability of each road" by using the server may include:
calculating the historical congestion probability of each road based on the historical congestion information of each road;
and obtaining the adjusted congestion probability of each road according to the congestion probability and the historical congestion probability of each road.
The step of obtaining the adjusted congestion probability of each road according to the congestion probability and the historical congestion probability of each road may include: and fusing the congestion probability and the historical congestion probability of each road to obtain the adjusted congestion probability of each road. The fusion mode may be an averaging mode, specifically, an averaging mode is performed on all the congestion probabilities corresponding to each road, that is, the adjusted congestion probability of each road.
Optionally, in some embodiments, the historical congestion information of each road may be historical congestion time of each road segment of each road; the step of calculating the historical congestion probability of each road based on the historical congestion information of each road may specifically include:
taking the length of each road section on each road as a weight, and carrying out weighted operation on the historical congestion duration of each road section on each road to obtain the historical congestion information of each road;
and calculating the historical congestion probability of each road in a target time period based on the historical congestion information of each road.
205. And the server determines the congested road in the target time period from a plurality of roads according to the adjusted congestion probability.
Optionally, in some embodiments, a road with the adjusted congestion probability being greater than a preset congestion probability may be determined as the congested road in the target time period, where the preset congestion probability may be set according to an actual situation, and this embodiment does not limit this.
Optionally, in some embodiments, the step "the server determines a congested road in the target time period from a plurality of roads according to the adjusted congestion probability" may include:
sorting the roads according to the adjusted congestion probability;
and determining the congested road in the target time period from a plurality of roads based on the sequencing positions of the roads.
The roads can be sorted from big to small or from small to big according to the adjusted congestion probability.
If the roads are ranked from large to small based on the adjusted congestion probability, specifically, the step "determining the congested road in the target time interval from the multiple roads based on the ranked positions of the roads" may include:
determining the first A roads as congested roads in the target time period based on the sorting positions of the roads, wherein A is a positive integer not exceeding the total number of the roads; or the like, or, alternatively,
and determining the first B roads as the congested roads in the target time period based on the sorted positions of the roads, wherein B is a positive number which is greater than 1 and does not exceed the total number of the roads.
The values of a and B may be set according to actual situations, and this embodiment does not limit this.
Optionally, the roads are arranged from large to small mainly based on the adjusted congestion probability, and if the adjusted congestion probability is not very different, a road with a longer road length may be arranged in front of a road with a shorter road length.
For example, in some embodiments, the step of "ordering the roads according to the magnitude of the adjusted congestion probability" may include:
pre-sequencing the roads according to the adjusted congestion probability;
and when the difference value of the adjusted congestion probabilities of the two pre-sequenced adjacent roads is smaller than a preset value, adjusting the sequencing positions of the two adjacent roads based on the lengths of the two adjacent roads and the adjusted congestion probabilities.
For example, the preset value may be set to 0.1, and if the difference between the adjusted congestion probabilities of two pre-sorted adjacent roads is smaller and less than 0.1, it may be considered that a road with a longer road length is ranked before a road with a shorter road length. Specifically, in one embodiment, the roads are arranged from large to small based on the adjusted congestion probability; and when the difference of the adjusted congestion probability is within 20%, arranging the products of the adjusted congestion probability and the road length, and arranging the higher product of the adjusted congestion probability and the road length in front.
206. And the server sends the data of the congested road to the terminal.
The data of the congested road may include specific location information of the congested road, congestion length, average speed of the vehicle, and the like. The congested road is a road with a high congestion probability in the target time period, and is not a road which is congested currently.
207. And the terminal receives the data of the congested roads and displays a map of the geographic area, wherein the congested roads are marked in the map.
Optionally, the terminal may mark the congested road in the map based on the data of the congested road, and the marking manner may be multiple. For example, the congested road may be marked in red to distinguish it from other roads. Further, in some embodiments, in the case of a zoomed-out display of the map, the congested road may be marked with dots; in the case of a map enlarged display, the congested road may be marked with a thick line.
Optionally, in some embodiments, the step of "displaying a map of the geographic area" may include:
when a first viewing instruction of the congested road is received, displaying road condition information of the congested road on a map of the geographic area;
and when a second viewing instruction for the congested road is received, magnifying and displaying the congested road on the map of the geographic area by taking the congested road as a center.
The first viewing instruction may specifically be a click operation or a slide operation on a congested road on a map, and based on the click operation or the slide operation on the congested road, road condition information of the congested road may be displayed on the map, where the road condition information may include information such as a congestion length of the congested road, a direction of the congested road, an average speed of vehicles on the congested road, and a length of the congested road. Based on the road condition information of the congested road, the user can quickly know the specific congestion condition of the road.
The second viewing instruction may specifically be a double-click operation (i.e., two continuous click operations in a short time) in a certain area around the congested road on the map page, and the like, which is not limited in this embodiment. Based on the second viewing instruction, the map page can be displayed in an enlarged manner, and the congested road is taken as the center.
The embodiment can calculate the congestion probability of the road according to the target time period, and determine the congested road. Because no complex algorithm is introduced in the embodiment, the calculation complexity is low, and effective reference information can be provided for urban congestion control.
As can be seen from the above, in the embodiment, a congested road display request sent by a terminal may be received by a server, where the congested road display request includes a geographic area where a congested road needs to be displayed; the method comprises the steps that a server divides each road in a geographic area into a plurality of road sections to obtain the plurality of road sections of each road; calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period; based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road; determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability; the server sends the data of the congested road to a terminal; and the terminal receives the data of the congested roads and displays a map of the geographic area, wherein the congested roads are marked in the map. The method and the device only limit the calculation of the congestion probability of the road in the target time period, divide each road into a plurality of road sections, and simply calculate the congestion probability of the road based on the congestion information of the road sections, so as to determine the congested road, reduce the calculation complexity, and simultaneously, because other algorithms and parameters set manually are not introduced, the calculation result can more directly reflect the real situation.
In order to better implement the above method, an embodiment of the present application further provides a map display apparatus, as shown in fig. 3a, which may include a dividing unit 301, a calculating unit 302, an adjusting unit 303, a determining unit 304, and a display unit 305, as follows:
(1) a dividing unit 301;
the dividing unit 301 is configured to divide each road in the geographic area into a plurality of road segments, so as to obtain a plurality of road segments of each road.
The geographic area may be a certain area range including the current location, and the area range may be set according to an actual situation, which is not limited in this embodiment.
Optionally, in this embodiment, the road section refers to a road section identifier in the electronic map, and the road section may be a road section of several tens to kilometers, and is usually a part of a real road; a road refers to a road sign in an electronic map, and a road can be understood as being composed of a plurality of road segments, which can be a series of road segment sets between two adjacent intersections.
(2) A calculation unit 302;
the calculating unit 302 is configured to calculate a congestion probability of each road in a target time period based on the length of each road segment on each road and congestion information in the target time period.
Optionally, in some embodiments of the present application, the calculating unit 302 may include a weighting subunit 3021 and a first calculating subunit 3022, see fig. 3b, as follows:
the weighting subunit 3021 is configured to perform a weighting operation on the congestion information of each road segment in the target time period by using the length of each road segment on each road as a weight, so as to obtain the congestion information of each road in the target time period;
a first calculating subunit 3022, configured to calculate a congestion probability of each road in the target time period based on the congestion information of each road in the target time period.
Optionally, in some embodiments of the present application, the congestion information of each road segment in the target time period includes a congestion time length of each road segment in the target time period; the weighting subunit 3021 may be specifically configured to perform a weighting operation on the congestion time of each road segment in the target time period by using the length of each road segment on each road as a weight, so as to obtain the congestion information of each road in the target time period.
(3) An adjustment unit 303;
the adjusting unit 303 is configured to adjust the congestion probability of each road based on the historical congestion information of each road, so as to obtain an adjusted congestion probability of each road.
Optionally, in some embodiments of the present application, the adjusting unit 303 may include a second calculating sub-unit 3031 and a fusing sub-unit 3032, see fig. 3c, as follows:
the second calculating subunit 3031 is configured to calculate a historical congestion probability of each road based on the historical congestion information of each road;
and the fusion subunit 3032 is configured to obtain the adjusted congestion probability of each road according to the congestion probability and the historical congestion probability of each road.
(4) A determination unit 304;
a determining unit 304, configured to determine a congested road in the target time period from multiple roads according to the adjusted congestion probability.
Optionally, in some embodiments of the present application, the determining unit 304 may include a sorting subunit 3041 and a determining subunit 3042, see fig. 3d, as follows:
the sorting subunit 3041 is configured to sort the roads according to the adjusted congestion probability;
a determining subunit 3042, configured to determine, based on the sorted positions of the roads, a congested road in the target time period from the multiple roads.
Optionally, in some embodiments of the present application, the sorting subunit 3041 may be specifically configured to pre-sort the roads according to the adjusted congestion probability; and when the difference value of the adjusted congestion probabilities of the two pre-sequenced adjacent roads is smaller than a preset value, adjusting the sequencing positions of the two adjacent roads based on the lengths of the two adjacent roads and the adjusted congestion probabilities.
(5) A display unit 305;
a display unit 305, configured to display a map of the geographic area, where the map is marked with the congested road.
Optionally, in some embodiments of the present application, the display unit 305 may include a first display subunit 3051 and a second display subunit 3052, see fig. 3e, as follows:
the first display subunit 3051, configured to, when a first viewing instruction for the congested road is received, display road condition information of the congested road on a map of the geographic area;
the second display subunit 3052 is configured to, when a second viewing instruction for the congested road is received, display the congested road on the map of the geographic area in an enlarged manner with the congested road as a center.
As can be seen from the above, in this embodiment, the dividing unit 301 may divide each road in the geographic area into a plurality of road segments, so as to obtain a plurality of road segments of each road; calculating, by the calculation unit 302, a congestion probability of each road in a target time period based on a length of each road segment on each road and congestion information in the target time period; the adjusting unit 303 adjusts the congestion probability of each road based on the historical congestion information of each road to obtain the adjusted congestion probability of each road; determining, by a determining unit 304, a congested road in the target time period from a plurality of roads according to the adjusted congestion probability; a map of the geographical area is displayed by the display unit 305, wherein the map is marked with the congested roads. The method and the device only limit the calculation of the congestion probability of the road in the target time period, divide each road into a plurality of road sections, and simply calculate the congestion probability of the road based on the congestion information of the road sections, so as to determine the congested road, reduce the calculation complexity, and simultaneously, because other algorithms and parameters set manually are not introduced, the calculation result can more directly reflect the real situation.
An electronic device according to an embodiment of the present application is further provided, as shown in fig. 4, which shows a schematic structural diagram of the electronic device according to an embodiment of the present application, specifically:
the electronic device may include components such as a processor 401 of one or more processing cores, memory 402 of one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 4 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components. Wherein:
the processor 401 is a control center of the electronic device, connects various parts of the whole electronic device by various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 402 and calling data stored in the memory 402, thereby performing overall monitoring of the electronic device. Optionally, processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 401.
The memory 402 may be used to store software programs and modules, and the processor 401 executes various functional applications and data processing by operating the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to use of the electronic device, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 access to the memory 402.
The electronic device further comprises a power supply 403 for supplying power to the various components, and preferably, the power supply 403 is logically connected to the processor 401 through a power management system, so that functions of managing charging, discharging, and power consumption are realized through the power management system. The power supply 403 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
The electronic device may further include an input unit 404, and the input unit 404 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
Although not shown, the electronic device may further include a display unit and the like, which are not described in detail herein. Specifically, in this embodiment, the processor 401 in the electronic device loads the executable file corresponding to the process of one or more application programs into the memory 402 according to the following instructions, and the processor 401 runs the application program stored in the memory 402, thereby implementing various functions as follows:
dividing each road in a geographic area into a plurality of road sections to obtain a plurality of road sections of each road; calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period; based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road; determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability; displaying a map of the geographic area, wherein the map is marked with the congested road.
The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.
As can be seen from the above, in the present embodiment, each road in the geographic area may be divided into a plurality of road segments, so as to obtain a plurality of road segments of each road; calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period; based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road; determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability; displaying a map of the geographic area, wherein the map is marked with the congested road. The method and the device only limit the calculation of the congestion probability of the road in the target time period, divide each road into a plurality of road sections, and simply calculate the congestion probability of the road based on the congestion information of the road sections, so as to determine the congested road, reduce the calculation complexity, and simultaneously, because other algorithms and parameters set manually are not introduced, the calculation result can more directly reflect the real situation.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.
To this end, the present application provides a storage medium, in which a plurality of instructions are stored, where the instructions can be loaded by a processor to execute the steps in any one of the map display methods provided in the present application. For example, the instructions may perform the steps of:
dividing each road in a geographic area into a plurality of road sections to obtain a plurality of road sections of each road; calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period; based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road; determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability; displaying a map of the geographic area, wherein the map is marked with the congested road.
The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.
Wherein the storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
Since the instructions stored in the storage medium can execute the steps in any map display method provided in the embodiments of the present application, beneficial effects that can be achieved by any map display method provided in the embodiments of the present application can be achieved, which are detailed in the foregoing embodiments and will not be described herein again.
A map display method, a map display apparatus, an electronic device, and a storage medium provided by embodiments of the present application are described in detail above, and specific examples are applied herein to illustrate principles and implementations of the present application, and the description of the embodiments is only used to help understand the method and the core concept of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims (10)

1. A map display method, comprising:
dividing each road in a geographic area into a plurality of road sections to obtain a plurality of road sections of each road;
calculating the congestion probability of each road in a target time period based on the length of each road section on each road and the congestion information in the target time period;
based on the historical congestion information of each road, adjusting the congestion probability of each road to obtain the adjusted congestion probability of each road;
determining a congested road in the target time period from a plurality of roads according to the adjusted congestion probability;
displaying a map of the geographic area, wherein the map is marked with the congested road.
2. The method of claim 1, wherein the calculating the congestion probability of each road in the target time period based on the length of each road segment on each road and the congestion information in the target time period comprises:
taking the length of each road section on each road as a weight, and carrying out weighted operation on the congestion information of each road section on each road in a target time interval to obtain the congestion information of each road in the target time interval;
and calculating the congestion probability of each road in the target time period based on the congestion information of each road in the target time period.
3. The method of claim 2, wherein the congestion information for each road segment in the target time period comprises a congestion time period for each road segment in the target time period; the obtaining of the congestion information of each road in the target time interval by performing a weighted operation on the congestion information of each road section in the target time interval with the length of each road section in each road as a weight comprises:
and taking the length of each road section on each road as a weight, and carrying out weighted operation on the congestion time of each road section on each road in the target time interval to obtain the congestion information of each road in the target time interval.
4. The method of claim 1, wherein the adjusting the congestion probability of each road based on the historical congestion information of each road to obtain the adjusted congestion probability of each road comprises:
calculating the historical congestion probability of each road based on the historical congestion information of each road;
and obtaining the adjusted congestion probability of each road according to the congestion probability and the historical congestion probability of each road.
5. The method of claim 1, wherein determining the congested road in the target time period from a plurality of roads according to the adjusted congestion probability comprises:
sorting the roads according to the adjusted congestion probability;
and determining the congested road in the target time period from a plurality of roads based on the sequencing positions of the roads.
6. The method of claim 5, wherein the ranking the roads according to the adjusted congestion probability comprises:
pre-sequencing the roads according to the adjusted congestion probability;
and when the difference value of the adjusted congestion probabilities of the two pre-sequenced adjacent roads is smaller than a preset value, adjusting the sequencing positions of the two adjacent roads based on the lengths of the two adjacent roads and the adjusted congestion probabilities.
7. The method of claim 1, wherein said displaying the map of the geographic area comprises:
when a first viewing instruction of the congested road is received, displaying road condition information of the congested road on a map of the geographic area;
and when a second viewing instruction for the congested road is received, magnifying and displaying the congested road on the map of the geographic area by taking the congested road as a center.
8. A map display apparatus, comprising:
the dividing unit is used for dividing each road in the geographic area into a plurality of road sections to obtain a plurality of road sections of each road;
the calculating unit is used for calculating the congestion probability of each road in the target time interval based on the length of each road section on each road and the congestion information in the target time interval;
the adjusting unit is used for adjusting the congestion probability of each road based on the historical congestion information of each road to obtain the adjusted congestion probability of each road;
the determining unit is used for determining the congested road in the target time period from a plurality of roads according to the adjusted congestion probability;
and the display unit is used for displaying a map of the geographic area, wherein the map is marked with the congestion road.
9. An electronic device comprising a memory and a processor; the memory stores an application program, and the processor is configured to execute the application program in the memory to perform the operations of the map display method according to any one of claims 1 to 7.
10. A storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the steps of the map display method of any one of claims 1 to 7.
CN202010273418.5A 2020-04-09 2020-04-09 Map display method and device, electronic equipment and storage medium Pending CN111723169A (en)

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