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Traffic condition prediction method and device, electronic equipment and storage medium

A technology of traffic conditions and traffic, applied in the computer field, can solve problems such as poor data availability and poor accuracy

Pending Publication Date: 2022-02-18
BEIJING AUTONAVI YUNMAP TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the above method can only count the cross-city or cross-country trips that have occurred based on the user's location changes, and the data availability is poor, resulting in poor accuracy of traffic condition prediction based on these data

Method used

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  • Traffic condition prediction method and device, electronic equipment and storage medium
  • Traffic condition prediction method and device, electronic equipment and storage medium
  • Traffic condition prediction method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0022] Figure 1A It is a flow chart of the steps of a traffic condition prediction method according to Embodiment 1 of the present application; Figure 1A shown, which includes:

[0023] S101. Obtain first traffic data within a first preset time period, wherein the first traffic data includes: first actual data used to indicate the actual traffic flow of the traffic route, and / or used to indicate the purpose of the traffic The second actual data of the actual vehicle inflow to the ground.

[0024] In this embodiment, the first preset period of time may be set according to user requirements. For example, if the forecast of traffic conditions is carried out by day, the first preset time period can be the time period (one day) from the last forecast to this forecast; or, if the forecast is specifically to predict the May Day holiday traffic conditions, the first preset time period may be the time period corresponding to the previous May Day holiday. It should be understood tha...

Embodiment 2

[0055] figure 2 It is a flow chart of the steps of a method for predicting traffic conditions according to Embodiment 2 of the present application; figure 2 shown, which includes:

[0056] S201. Acquire first actual data for indicating the actual traffic flow of the traffic route, and acquire first forecast data for indicating the expected traffic flow of the traffic route.

[0057] For the specific implementation of this step, refer to the foregoing embodiments, and details are not repeated here.

[0058] S202. Based on the first preset condition, filter the traffic route corresponding to the first actual data to obtain the first hotspot traffic route; based on the second preset condition, filter the traffic route corresponding to the first estimated data , to obtain the second hotspot traffic path.

[0059] In this embodiment, screening is performed based on the first preset condition to obtain the first popular traffic route, and screening is performed based on the sec...

Embodiment 3

[0079] For the specific implementation of this step, refer to the foregoing embodiments, and details are not repeated here.

[0080] S302. Based on the third preset condition, filter the traffic destinations corresponding to the second actual data to obtain the first hot traffic destination; based on the fourth preset condition, filter the traffic destinations corresponding to the second estimated data Screening to obtain the second hottest traffic destination.

[0081] In this embodiment, by filtering based on the third preset condition, the first popular traffic destination can be obtained, and by filtering based on the fourth preset condition, the second popular traffic destination can be obtained. The hot traffic destinations are generally places that attract more attention, such as popular tourist cities, cities with a large flow of people, etc., and then based on the traffic matching data of the first hot traffic destination and the second hot traffic destination, the ...

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Abstract

The embodiment of the invention provides a traffic condition prediction method and device, electronic equipment and a storage medium. The traffic condition prediction method comprises the steps that: first traffic data in a first preset time period are acquired, wherein the first traffic data comprise first actual data used for indicating the actual traffic flow of a traffic path and / or second actual data used for indicating the actual vehicle inflow amount of a traffic destination; second traffic data determined based on the navigation planning data in a second preset time period is obtained, wherein the second traffic data comprises first predicted data used for indicating predicted traffic flow of the traffic path and / or second predicted data used for indicating predicted vehicle inflow of the traffic destination; and traffic matching data in the first traffic data and the second traffic data are determined, and traffic condition prediction is performed on a traffic path and / or a traffic destination corresponding to the traffic matching data in a third preset time period according to the traffic matching data.

Description

technical field [0001] The embodiments of the present application relate to the field of computer technology, and in particular, to a traffic condition prediction method, device, electronic equipment, and storage medium. Background technique [0002] With the gradual development of transportation, users' travel is becoming more and more convenient. For example, they can easily travel from one city to another city, or from one country to another country by car, plane, train, high-speed rail, etc. [0003] Usually, in order to count users’ cross-city or transnational travel, etc., after authorization by the user, the city where the user is historically located can be determined according to the user’s historical location information, and then the user’s current city can be determined according to the user’s real-time location. By comparing the historical location The city and the city where the user is currently located can determine whether the user has traveled across cities...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G08G1/01
CPCG06Q10/04G08G1/0125
Inventor 王宇静苏岳龙李屹董振宁
Owner BEIJING AUTONAVI YUNMAP TECH CO LTD
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