CN108985506A - Driving path recommendation method, driving path prediction method, driving path acquisition method and driving path acquisition device - Google Patents

Abstract

The invention provides a driving path recommendation method, a prediction method, an acquisition method and a device thereof, wherein the recommendation method comprises the following steps: the client generates request information according to an input instruction and sends the request information to the server, wherein the request information comprises information of a starting point, information of an end point and specified time; the server receives the request information, and calculates a recommendation result according to the request information and by using the alternative paths comprising the plurality of sub-paths and the standard time of each sub-path, wherein the recommendation result comprises the shortest driving time and a target path in the specified time, and the target path is the alternative path corresponding to the shortest driving time; the server sends the recommendation result to the client; and the client receives the recommendation result and selectively displays the recommendation result. The invention can improve the accuracy of predicting the driving time, is convenient for a user to reach the terminal point in the shortest time, avoids the problem of traffic jam as much as possible, and is beneficial to better travel arrangement of people.

Description

Driving route recommendation method, prediction method, acquisition method and device thereof

technical field

The invention belongs to the technical field of driving route prediction, and specifically provides a driving route recommendation method, a prediction method, an acquisition method and a device thereof.

Background technique

Traveling is one of people's daily activities. Before traveling, people can query the travel service system in order to plan travel time and activities. The estimated time of arrival (Estimated Time of Arrival, ETA) is crucial for some travel service systems, because accurate ETA prediction can effectively support the scheduling of tasks, resources, and personnel, enabling the system to perform more optimally . At present, the services about ETA are basically divided into two categories: first, real-time ETA service, based on current traffic conditions, weather and other information, giving the time it takes to specify a driving route; second, predictive ETA service, which is based on For the historical driving route, under the same day of the week, the same time period, and the same starting position and ending position, the ETA in the historical driving trajectory is used as the prediction result.

For the real-time ETA service, because the scheduling service for a certain period in the future is performed based on the forecast of this period, it is difficult for the real-time ETA service to perform the above-mentioned scheduling service; and for the forecast ETA service, at the same starting point, Under the conditions of the same end point and the same period of time, the data of the historical trajectory is often very sparse, so it cannot give an accurate result very well.

Correspondingly, there is a need in the art for a method capable of accurately predicting ETA under specified conditions to solve the above problems.

Contents of the invention

In order to solve the above problems in the prior art, that is, in order to solve the problem of low accuracy in predicting future driving time in the prior art, the present invention provides a driving route recommendation method, which includes: the client generates request information according to the input instructions, and sending the request information to a server, wherein the request information includes starting point information, end point information, and specified time; the server receives the request information, and according to the request information, utilizes a backup path that includes at least two sub-paths Select the route and the standard time of each sub-route, calculate the recommendation result, the recommendation result includes the shortest travel time and the target route under the specified time, and the target route is the alternative corresponding to the shortest travel time path; the server sends the recommendation result to the client; the client receives the recommendation result and selectively displays the recommendation result.

In the preferred technical solution of the above-mentioned recommendation method, the step of "calculating the recommendation result by using the alternative routes including multiple sub-paths and the standard time of each of the sub-paths" includes: fetching the road network from the pre-established road network database Image, the road network image includes a plurality of nodes and the sub-paths connecting adjacent nodes; select the node closest to the starting point as the first node, select the node closest to the end point as the second node, and generate At least one alternative path, the alternative path takes the first node and the second node as endpoints and is composed of at least two sub-paths sequentially connected; the target data is retrieved from a pre-established historical database , the target data includes the standard time of each of the sub-paths having the same time attribute as the specified time, and the time attribute refers to a certain period of time in a certain day in a week; sum the standard times of each of the sub-paths in each of the alternative routes to calculate the travel time of each of the alternative routes, and compare each of the travel times to obtain the The shortest driving time, using the alternative route corresponding to the shortest driving time as the target route; generating the recommendation result, the recommendation result including the shortest driving time and the target route.

In the preferred technical solution of the above recommendation method, the candidate path is generated by using Dijkstra algorithm, bi-directional Dijkstra algorithm or Astar algorithm.

In the preferred technical solution of the above recommendation method, the recommendation result further includes non-target routes, and the travel time of the non-target routes is arranged in ascending order.

In the preferred technical solution of the above recommendation method, the operation of establishing the road network database is as follows: acquiring an original image, the original image including a plurality of historical driving paths; The driving route is divided into at least two sub-paths; the nodes and the sub-paths are extracted to form the road network image, and the road network image is stored to establish the road network database.

In the preferred technical solution of the above recommendation method, the operation of establishing the historical database is specifically: acquiring historical driving data, the historical driving data includes historical driving time, and the historical driving time is the actual time of passing through the sub-path; Carry out weighted average calculation of the historical driving time of the same sub-path under the same time attribute to obtain the sub-time, and use the sub-time to obtain the standard time; classify the standard time according to the time attribute And store it to build the historical database.

In the preferred technical solution of the above recommendation method, the driving route recommendation method further includes: the server obtains weather forecast information, and the weather forecast information includes the weather attributes at the specified time; the target data and the specified time have the same weather properties.

In the preferred technical solution of the above recommended method, the operation of "establishing the historical database" further includes: after obtaining the standard time and before storing the standard time, setting the standard time according to the weather attribute Classification.

In the preferred technical solution of the above recommended method, the historical database is a database based on distributed file storage.

In the preferred technical solution of the above recommendation method, the sub-path includes a first sub-path, and the first sub-path is a sub-path that is only included in one of the candidate paths under one of the time attributes, " The step of using the sub-time to obtain the "standard time" includes: using the sub-time of the first sub-path as the standard time of the first sub-path.

In the preferred technical solution of the above recommendation method, the sub-path includes a second sub-path, and the second sub-path is a sub-path included in at least two of the candidate paths under one of the time attributes, The step of "obtaining the standard time by using the sub-time" includes: performing a weighted average of the sub-times of the second sub-path in each of the candidate paths to calculate the standard time of the second sub-path time.

In the preferred technical solution of the above recommended method, the at least two sub-paths include at least one third sub-route, and the third sub-route does not have the historical driving time under at least one of the time attributes, "using the sub-path The step of obtaining the standard time" includes: taking infinity as the standard time of the third sub-path under the at least one time attribute; or calculating the time under the other time attributes The average value of the standard time of the third sub-path, and use the average value as the standard time of the third sub-path.

In the preferred technical solution of the above recommendation method, the step of "the client generates request information according to the input instruction" includes: obtaining the input instruction, the instruction includes the start position, the end position and the specified time; the client uses The global positioning system obtains the GPS information of the starting point position as the starting point information, and obtains the GPS information of the ending point as the ending point information; the client uses the starting point information, the ending point information and the specified time to generate The requested information.

In the preferred technical solution of the above recommendation method, the client is a mobile terminal or a vehicle-mounted terminal.

In another aspect, the present invention provides a method for predicting a driving route, including: receiving request information, the request information including starting point information, end point information, and specified time; route and the standard time of each sub-route, and calculate the recommendation result, wherein the recommendation result includes the shortest travel time and the target route under the specified time, and the target route is the backup corresponding to the shortest travel time Selecting a path; sending the recommendation result to the client.

In the preferred technical solution of the above-mentioned prediction method, the step of "computing the recommended result by using the alternative route comprising at least two sub-paths and the standard time of each of the sub-paths" includes: fetching the route from the pre-established road network database Network image, the road network image includes a plurality of nodes and sub-paths connecting the nodes; select the node closest to the starting point as the first node, select the node closest to the end point as the second node, and generate multiple an alternative path, the alternative path takes the first node and the second node as endpoints and is composed of at least two sub-paths sequentially connected; the target data is retrieved from a pre-established historical database, The target data includes the standard time of each of the sub-paths having the same time attribute as the specified time, and the time attribute refers to a certain period of time in a certain day in a week; summing the standard times of each of the sub-paths in the candidate routes to calculate the travel time of each of the candidate routes, and comparing each of the travel times to obtain the shortest travel time Time, using the alternative route corresponding to the shortest driving time as the target route; generating the recommendation result, the recommendation result including the shortest driving time and the target route.

In the preferred technical solution of the above prediction method, the candidate path is generated by using Dijkstra algorithm, bi-directional Dijkstra algorithm or Astar algorithm.

In the preferred technical solution of the above prediction method, the recommendation result further includes non-target routes, and the travel time of the non-target routes is arranged in ascending order.

In the preferred technical solution of the above prediction method, the operation of establishing the road network database is specifically: acquiring an original image, the original image including multiple historical driving paths; The driving route is divided into at least two sub-paths; the nodes and the sub-paths are extracted to form the road network image, and the road network image is stored to establish the road network database.

In the preferred technical solution of the above prediction method, the operation of establishing the historical database is specifically: acquiring historical driving data, the historical driving data includes historical driving time, and the historical driving time is the actual time of passing through the sub-path; Carry out weighted average calculation to the described historical driving time of the same described sub-path under the same described time attribute, obtain sub-time, and use described sub-time to obtain described standard time; Described standard time according to described Time attributes are categorized and stored to create the historical database.

In the preferred technical solution of the above prediction method, the driving route prediction method further includes: obtaining weather forecast information, the weather forecast information includes the weather attributes at the specified time, wherein the target data has the same relationship with the specified time Same weather properties.

In the preferred technical solution of the above prediction method, the operation of "establishing the historical database" further includes: after obtaining the standard time and before storing the standard time, classifying the standard time according to weather attributes.

In a preferred technical solution of the above prediction method, the historical database is a distributed file storage database.

In the preferred technical solution of the above prediction method, the sub-path includes a first sub-path, and the first sub-path is a sub-path that is only included in one of the candidate paths under one of the time attributes, " The step of using the sub-time to obtain the "standard time" includes: using the sub-time of the first sub-path as the standard time of the first sub-path.

In the preferred technical solution of the above prediction method, the sub-path includes a second sub-path, and the second sub-path is a sub-path included in at least two of the candidate paths under one of the time attributes, The step of "obtaining the standard time by using the sub-time" includes: performing a weighted average of the sub-times of the second sub-path in each of the candidate paths to calculate the standard time of the second sub-path time.

In the preferred technical solution of the above prediction method, the at least two sub-paths include at least one third sub-path, and the third sub-path does not have the historical driving time under at least one of the time attributes, "using the sub-path The time to obtain the standard time" is specifically: taking infinity as the standard time of the third sub-path under the at least one time attribute; or, calculating the time under the other time attributes The average value of the standard time of the third sub-path, and use the average value as the standard time of the third sub-path.

In yet another aspect, the present invention provides a method for obtaining a driving route, comprising: generating request information according to an input instruction, wherein the request information includes starting point information, end point information, and specified time; sending the request information to a server ; Receive recommendation results, and selectively display the recommendation results.

In the preferred technical solution of the above obtaining method, the step of "generating request information according to the input instruction" includes: obtaining the input instruction, the instruction includes the start position, the end position and the specified time; using the global positioning system to obtain the The GPS information of the starting point is used as the starting point information, and the GPS information of the ending point is obtained as the ending point information; the request information is generated by using the starting point information, the ending point information and the designated time.

In yet another aspect, the present invention provides a server, the server includes a processor and a memory, a plurality of instructions are stored in the memory, and the processor is adapted to load the instructions to perform any of the above-mentioned Driving path prediction method.

In yet another aspect, the present invention provides a client, the client includes a processor and a memory, a plurality of instructions are stored in the memory, and the processor is adapted to load the instructions to perform any of the above-mentioned The method for obtaining the driving route.

In the preferred technical solution of the above client, the client is a mobile terminal or a vehicle-mounted terminal.

Those skilled in the art can understand that, in the technical solution of the present invention, use the alternative routes including multiple sub-paths and the standard time of each sub-path to calculate the travel time of each alternative route, which can effectively improve the predicted travel time. The accuracy enables the user to travel according to the recommended route, arrive at the destination in the shortest time, avoid traffic jams as much as possible, and help people make better travel arrangements; at the same time, the technical solution of the present invention can also be used for Organizations that provide novelty check services provide forecast information so that agencies that provide novelty check services can better schedule traffic demands.

Option 1, a driving route recommendation method, is characterized in that comprising:

The client generates request information according to the input instruction, and sends the request information to the server, wherein the request information includes start point information, end point information and designated time;

The server receives the request information, and according to the request information, calculates a recommendation result using an alternative path including at least two sub-paths and a standard time of each of the sub-paths, and the recommendation result includes The shortest travel time and the target route, the target route is the alternative route corresponding to the shortest travel time;

The server sends the recommendation result to the client;

The client receives the recommendation result, and selectively displays the recommendation result.

Scheme 2, according to the driving route recommendation method described in scheme 1, it is characterized in that the step of "calculating the recommendation result using the alternative route comprising a plurality of sub-paths and the standard time of each said sub-path" includes:

Retrieving a road network image from a pre-established road network database, the road network image including a plurality of nodes and the sub-paths connecting adjacent nodes;

Selecting the node closest to the starting point as the first node, selecting the node closest to the end point as the second node, and generating at least one alternative path, the alternative path is based on the first node and the second node The node is an endpoint and is composed of at least two sub-paths connected in sequence;

Call the target data from the pre-established historical database, the target data is the standard time of each sub-path with the same time attribute as the specified time, the time attribute refers to the time in a week a certain period of time in a certain day;

Summing the standard times of each of the sub-paths in each of the candidate routes to calculate the travel time of each of the candidate routes, and comparing each of the travel times to obtain the The shortest travel time, the alternative route corresponding to the shortest travel time as the target route;

The recommendation result is generated, and the recommendation result includes the shortest driving time and the target route.

Scheme 3. The driving route recommendation method according to scheme 2, characterized in that the alternative route is generated using Dijkstra algorithm, bi-directional Dijkstra algorithm or Astar algorithm.

Solution 4. The driving route recommendation method according to solution 3, wherein the recommendation result further includes non-target routes, and the driving time of the non-target routes is arranged in ascending order.

Scheme 5, according to the driving route recommendation method described in Scheme 2, it is characterized in that, the operation of establishing the road network database is specifically:

Acquiring an original image, the original image includes a plurality of historical driving paths;

dividing each historical driving path in the original image into at least two sub-paths by using the nodes;

Extracting the nodes and the sub-paths to form the road network image, and storing the road network image to establish the road network database.

Scheme 6, according to the driving route recommendation method described in Scheme 5, it is characterized in that the operation of establishing the historical database is specifically:

Acquiring historical driving data, the historical driving data includes historical driving time, and the historical driving time is the actual time of passing through the sub-path;

Performing weighted average calculation on the historical travel time of the same sub-path under the same time attribute to obtain the sub-time, and using the sub-time to obtain the standard time;

The standard time is classified and stored according to the time attribute, so as to establish the historical database.

Solution 7. The driving route recommendation method according to solution 6, wherein the driving route recommendation method further includes: the server obtains weather forecast information, and the weather forecast information includes the weather attributes at the specified time, wherein , the target data has the same weather attribute as the specified time.

Solution 8. The driving route recommendation method according to solution 7, characterized in that the operation of "establishing the historical database" also includes: after obtaining the standard time and before storing the standard time, storing the Standard times are categorized by the weather attributes described.

Solution 9. The driving route recommendation method according to any one of solutions 6-8, wherein the historical database is a database based on distributed file storage.

Solution 10. The driving route recommendation method according to any one of solutions 6-8, characterized in that at least two of the sub-paths include a first sub-path, and the first sub-path is the time attribute For sub-paths that are only included in one of the alternative paths, the step of "using the sub-time to obtain the standard time" includes: using the sub-time of the first sub-path as the first sub-path standard time.

Solution 11. The driving route recommendation method according to any one of solutions 6-8, characterized in that at least two of the sub-paths include a second sub-path, and the second sub-path is at one of the time attributes Under the sub-paths included in at least two of the candidate paths, the step of "using the sub-time to obtain the standard time" includes: for the second sub-path in each of the candidate paths The weighted average of the sub-times is performed to calculate the standard time of the second sub-path.

Solution 12. The driving route recommendation method according to any one of solutions 6-8, characterized in that, the two sub-paths include a third sub-path, and the third sub-path has no The step of "using the sub-time to obtain the standard time" for the historical driving time includes: taking infinity as the standard time of the third sub-path under the at least one time attribute; or, Calculate the average value of the standard time of the third sub-path under each of the other time attributes, and use the average value as the standard time of the third sub-path.

Scheme 13. According to the driving route recommendation method described in Scheme 1, the step of "the client generates request information according to the input instruction" includes:

Obtaining an input instruction, the instruction including the start position, the end position and the specified time;

The client uses the Global Positioning System to obtain the GPS information of the starting point as the starting point information, and obtains the GPS information of the ending point as the ending point information;

The client generates the request information by using the starting point information, the ending point information and the specified time.

Solution 14. The driving route recommendation method according to solution 1, wherein the client is a mobile terminal or a vehicle-mounted terminal.

Scheme 15, a driving route prediction method, is characterized in that comprising:

receiving request information, the request information including starting point information, end point information and designated time;

According to the request information, a recommendation result is calculated by using an alternative route including at least two sub-routes and a standard time for each of the sub-routes, wherein the recommendation result includes the shortest travel time and a target route under the specified time, The target route is an alternative route corresponding to the shortest driving time;

Send the recommendation result to the client.

Solution 16, the driving route prediction method according to solution 15, characterized in that the step of "calculating the recommendation result using the alternative route comprising at least two sub-paths and the standard time of each of the sub-paths" includes:

Retrieving a road network image from a pre-established road network database, the road network image including a plurality of nodes and sub-paths connecting adjacent nodes;

Selecting the node closest to the starting point as the first node, selecting the node closest to the end point as the second node, and generating a plurality of alternative paths, the alternative paths are based on the first node and the second node The node is an endpoint and is composed of at least two sub-paths connected in sequence;

Retrieve the target data from the pre-established historical database, the target data refers to the standard time of each sub-path with the same time attribute as the specified time, and the time attribute refers to the time in a week. a certain period of time on a certain day;

Summing the standard times of each of the sub-paths in each of the candidate routes to calculate the travel time of each of the candidate routes, and comparing each of the travel times to obtain the The shortest travel time, the alternative route corresponding to the shortest travel time as the target route;

The recommendation result is generated, and the recommendation result includes the shortest driving time and the target route.

Solution 17. The driving route prediction method according to solution 16, characterized in that the candidate route is generated by using Dijkstra algorithm, bi-directional Dijkstra algorithm or Astar algorithm.

Solution 18. The driving route prediction method according to solution 16, wherein the recommendation result further includes non-target routes, and the driving times of the non-target routes are arranged in ascending order.

Scheme 19. The driving route prediction method according to scheme 16, wherein the operation of establishing the road network database is specifically:

Acquiring an original image, the original image includes a plurality of historical driving paths;

dividing each historical driving path in the original image into at least two sub-paths by using the nodes;

Extracting the nodes and the sub-paths to form the road network image, and storing the road network image to establish the road network database.

Scheme 20. The driving route prediction method according to scheme 19, wherein the operation of establishing the historical database is specifically:

Acquiring historical driving data, the historical driving data includes historical driving time, and the historical driving time is the actual time of passing through the sub-path;

Performing weighted average calculation on the historical travel time of the same sub-path under the same time attribute to obtain the sub-time, and using the sub-time to obtain the standard time;

The standard time is classified and stored according to the time attribute, so as to establish the historical database.

Solution 21. The driving route prediction method according to solution 20, characterized in that the driving route prediction method further includes: acquiring weather forecast information, the weather forecast information including the weather attributes at the specified time, wherein the The target data has the same weather attribute as the specified time.

Solution 22. The driving route prediction method according to solution 21, characterized in that the operation of "establishing the historical database" further includes: after obtaining the standard time and before storing the standard time, storing the Standard times are categorized by weather attributes.

Solution 23. The driving route prediction method according to any one of claims 20-22, wherein the historical database is a distributed file storage database.

Solution 24. The driving route prediction method according to any one of solutions 20-22, characterized in that the sub-paths include a first sub-path, and the first sub-path is only determined under one time attribute For a sub-path included in one of the alternative paths, the step of "using the sub-time to obtain the standard time" includes: using the sub-time of the first sub-path as the standard time of the first sub-path .

Solution 25. The driving path prediction method according to any one of solutions 20-22, wherein the sub-path includes a second sub-path, and the second sub-path is included under one of the time attributes For the sub-paths in at least two of the alternative paths, the step of "using the sub-time to obtain the standard time" includes: calculating the sub-time of the second sub-path in each of the alternative paths A weighted average is performed to calculate the standard time of the second sub-path.

Solution 26. The driving route prediction method according to any one of solutions 20-22, wherein the at least two sub-paths include at least a third sub-path, and the third sub-path is at least one of the time attributes If there is no said historical driving time, "use said sub-time to obtain said standard time" specifically: take infinity as said standard time of said third sub-path under said at least one said time attribute; or , calculating an average value of the standard time of the third sub-path under each of the other time attributes, and using the average value as the standard time of the third sub-path.

Scheme 27. A method for obtaining a driving route, characterized in that it comprises:

Generate request information according to the input instruction, wherein the request information includes start point information, end point information and designated time;

Send the request information to the server;

Receive recommendation results, and selectively display the recommendation results.

Scheme 28. The method for obtaining the driving route according to scheme 27, wherein the step of "generating request information according to the input instruction" includes:

Obtaining an input instruction, the instruction including the start position, the end position and the specified time;

Obtaining the GPS information of the starting point position by using a global positioning system as the starting point information, and obtaining the GPS information of the ending point as the ending point information;

The request information is generated by using the start point information, the end point information and the designated time.

Solution 29. A server, including a processor and a memory, wherein a plurality of instructions are stored in the memory, wherein the processor is adapted to load the instructions to execute the instructions described in any one of solutions 15-26. The driving path prediction method.

Solution 30, a client, including a processor and a memory, wherein a plurality of instructions are stored in the memory, wherein the processor is adapted to load the instructions to execute the instructions described in any one of solutions 27-29. The method for obtaining the driving route described above.

Solution 31. The client according to solution 30, wherein the client is a mobile terminal or a vehicle-mounted terminal.

Description of drawings

FIG. 1 is a schematic flowchart of a driving route recommendation method in an embodiment of the present invention.

Fig. 2 is a flow chart of the client generating request information according to the input instruction in the embodiment of the present invention.

FIG. 3 is a schematic flow chart of calculating recommendation results using alternative paths and standard time of each sub-path in an embodiment of the present invention.

Fig. 4 is a flowchart of establishing a road network database in an embodiment of the present invention.

Figure 5 is a partial map of the Huangpu River area in Shanghai.

Fig. 6 is a road network image corresponding to some areas in Fig. 5 .

Fig. 7 is a flow chart of establishing a historical database in the embodiment of the present invention.

FIG. 8 is a schematic flowchart of a method for predicting a driving route in an embodiment of the present invention.

FIG. 9 is a flowchart of a method for obtaining a driving route in an embodiment of the present invention.

Fig. 10 is a schematic diagram of a connection structure between a driving route prediction device and a driving route acquisition device in an embodiment of the present invention.

FIG. 11 is a schematic diagram of the connection structure between another driving route prediction device and the driving route acquisition device in an embodiment of the present invention.

Detailed ways

Preferred embodiments of the present invention are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention, and are not intended to limit the protection scope of the present invention. Those skilled in the art can make adjustments as needed so as to adapt to specific applications.

People usually make travel plans before traveling, and the current travel service system does not have high prediction accuracy for the ETA of future travel time. For predicting ETA services, under the conditions of the same starting point, the same end point, and the same time period, the data of historical trajectories is often very sparse. Therefore, an accurate result cannot be given well, which affects people's travel arrangements.

In order to solve the above technical problems, an embodiment of the present invention provides a driving route recommendation method. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention.

FIG. 1 is a schematic flowchart of a driving route recommendation method in an embodiment of the present invention. Please refer to Figure 1, the recommended method for the driving route includes the following steps:

Step S11: the client generates request information according to the input instruction, and sends the request information to the server, wherein the request information includes start point information, end point information and specified time. In this embodiment, the first instruction is the information input by the user. For example, the user designates the Shanghai Municipal Library as the starting point and the Huadu Building as the end point, and departs at the current moment. Then the starting point information is the location information of the Shanghai Municipal Library , the end point information is the location information of Huadu Building, the designated time may be the current time information, or the designated time may be a future time input by the user.

Step S12: The server receives the request information, and according to the request information, uses the alternative routes including at least two sub-routes and the standard time of each sub-route to calculate the recommendation result, the recommendation result includes the shortest driving time under the specified time and the target route, target The route is the alternative route corresponding to the shortest travel time.

Step S13: the server sends the recommendation result to the client.

Step S14: the client receives the recommendation result, and selectively displays the recommendation result. "Selectively" in the present invention means that the client can display the recommendation results, or directly use the recommendation results for navigation without displaying the recommendation results.

In this embodiment, using the alternative routes including at least two sub-routes and the standard time of each sub-route, the driving time of each alternative route is calculated, which can effectively improve the accuracy of the predicted driving time, so that the user can Route travel, to reach the destination in the shortest time, can avoid traffic jams as much as possible, and help people to make better travel arrangements; at the same time, this embodiment can also be used to provide forecast information for institutions that provide novelty checking services, so as to facilitate Organizations that provide novelty checking services can better schedule driving needs.

It should be noted that the steps in the driving route recommendation method provided by the present invention can be split, combined and adjusted in order. For example, step S12 can be split into "the server receives the request information" and "the server utilizes the information including at least Alternative paths of the two sub-paths and the standard time of each sub-path, and calculate the recommended results", step S14 can be split into two steps: "the client receives the recommended results" and "the client selectively performs the recommendation on the recommended results". Show" these two steps; of course, step S12 and step S13 can also be combined into one step.

Fig. 2 is a flow chart of the client generating request information according to the input instruction in the embodiment of the present invention. Please refer to Figure 2, the steps of "the client generates request information according to the input instructions" include:

Step S111: Acquiring an input command, the command includes a start position, an end position and a specified time.

Step S112: the client uses the global positioning system to acquire GPS information of the starting point as starting point information, and obtains GPS information of the ending point as end point information.

Step S113: the client generates request information using the start point information, end point information and specified time.

In this embodiment, the GPS information generated by the global positioning system installed on the client is used as the starting point information and the ending point information, the method of generating the request information is simple, and the positioning is accurate.

FIG. 3 is a schematic flow chart of calculating recommendation results using alternative paths and standard time of each sub-path in an embodiment of the present invention. Referring to Fig. 3, the steps of "computing the recommendation result by using the alternative paths including multiple sub-paths and the standard time of each sub-path" include:

Step S121: Retrieving road network images from a pre-established road network database. A road network image includes multiple nodes and sub-paths connecting adjacent nodes.

Step S122: Select the node closest to the starting point as the first node, select the node closest to the end point as the second node, and generate multiple candidate paths, the candidate paths take the first node and the second node as endpoints, and consist of at least The two sub-paths are sequentially connected to form. For example, using node A as the first node and node B as the second node, there are multiple travel modes from node A to node B, and each travel mode can be used as an alternative path, and each alternative path has It is composed of at least two sub-paths connected in sequence.

Step S123: Retrieve the target data from the pre-established historical database. The target data has the standard time of each sub-path with the same time attribute as the specified time. The time attribute refers to a certain day of the week where the time is located time period. That is, the number of days in a week is 7 days. If the specified time is Tuesday, then the time attribute of the target data is also Tuesday; and each day has different time periods, for example, morning peak time, evening peak time, and less travel time at night. Optionally, a day can be divided into 24 time periods according to hours. At this time, there are 7*24 (7 days a week, 24 hours a day) time attributes.

Step S124: Sum the standard time of each sub-path in each candidate route to calculate the travel time of each candidate route, and compare each travel time to obtain the shortest travel time, and the shortest travel time The alternative path corresponding to the time is used as the target path.

Step S125: Generate recommendation results, the recommendation results include the shortest travel time and the target route.

In the method for calculating the recommendation result in this embodiment, the road network image is retrieved from the pre-established road network database to generate an alternative path, the target data is retrieved from the pre-established historical database, and each child in the alternative path The standard time of the route is summed to calculate the driving time of each alternative route, and the calculation result is more accurate; the network image and historical data are stored separately, and the corresponding network image and data are called when calculating the recommendation result, which can reduce the system cost. load, and at the same time help to improve the speed of computing recommendation results.

Fig. 4 is a flowchart of establishing a road network database in an embodiment of the present invention. Please refer to Figure 4, the specific operation of establishing the road network database is as follows:

Step S1211: Acquire the original image, which includes multiple historical driving paths. The original image can be a map of a certain city, region, or province. For example, Figure 5 is a partial map of the Huangpu River area in Shanghai. On both sides of the Huangpu River, there are famous business districts such as Shanghai World Financial Center and famous scenic spots such as Yu Garden, which are areas prone to traffic congestion.

Step S1212: using nodes to divide each historical driving route in the original image into at least two sub-paths, and extracting nodes and sub-paths to form a road network image. Further, it may be selected at the intersection of the physical path, the landmark building, the ramp of the expressway, the entire kilometer of the road, etc., and the sub-path is a section of road between two nodes. For example, Figure 6 is the road network image corresponding to some areas in Figure 5. Please refer to Figure 6. The dots in Figure 6 are nodes, and the line segments in Figure 6 are sub-paths. Circles, scenic spots, etc. are relatively dense.

Step S1213: Store the road network image to establish a road network database.

In this embodiment, by dividing the physical path into at least two sub-paths, since the distance of the sub-paths is relatively short, the historical data obtained on each sub-path is relatively sufficient; at the same time, dividing the physical path into at least two sub-paths can facilitate The standard time of each sub-path is counted; and the above-mentioned advantages are all conducive to improving the accuracy of predicting the ETA.

Fig. 7 is a flow chart of establishing a historical database in the embodiment of the present invention. Please refer to Figure 7, the specific operation of establishing the historical database is as follows:

Step S1231: Obtain historical driving data. The historical driving data includes historical driving time, and the historical driving time is the actual time of passing through the sub-route. Historical driving time can be obtained through statistics.

Step S1232: Perform weighted average calculation on the historical driving time of the same sub-route under the same time attribute to obtain the sub-time, and use the sub-time to obtain the standard time. For example, for a sub-route, a total of 100 historical driving times have been counted during the Monday morning rush hour, then the average value of the 100 historical driving times is obtained as the sub-time, and then the sub-time is used to obtain the standard time of the sub-route .

Step S1233: classify and store the standard time according to the time attribute, so as to establish a historical database.

In this embodiment, the standard time of each sub-route is calculated by making statistics on the historical driving time, and the standard time is stored according to the time attribute, so that the standard time can be extracted according to the time attribute.

Optionally, a candidate path is generated by using the Dijkstra algorithm, the bidirectional Dijkstra algorithm or the Astar algorithm. The applicant tested the network image of Shanghai (the number of nodes and sub-paths is at the level of one million), and the above-mentioned methods can complete the calculation of the shortest driving time and the target route within 30 seconds.

Optionally, the recommendation result also includes non-target routes, and the travel time of the non-target routes is arranged in ascending order. In this way, users can learn multiple recommended routes and choose according to their own travel arrangements. For example, if they want to arrive at the fastest speed, they can choose the recommended route; The recommended route with a short distance to a shopping mall.

Optionally, in the present invention, the historical database may be a database based on distributed file storage. Using a database based on distributed file storage can facilitate data storage and query.

In the present invention, due to the different conditions of the sub-paths, "obtaining the standard time by calculating the sub-time" has different calculation methods, which will be described in detail below.

In some optional implementations, at least two sub-paths include a first sub-path, and the first sub-path is a sub-path that is only included in one alternative path under a time attribute, "Using sub-times to obtain standard time " includes: using the sub-time of the first sub-path as the standard time of the first sub-path.

In some optional implementation manners, at least two sub-paths include a second sub-path, and the second sub-path is a sub-path included in at least two alternative paths under a time attribute, "Using sub-time to find the criterion The step of "time" includes: performing a weighted average of the sub-times of the second sub-path in each candidate path to calculate the standard time of the second sub-path. That is, the second sub-path is included in at least two candidate paths. At this time, when calculating the standard time, it is necessary to carry out a weighted average of the corresponding sub-times of all the candidate paths including the second sub-path, so as to obtain get standard time. For example, the sub-time of the second sub-path in the first candidate path is a, and the sub-time of the second sub-path in the second candidate path is b, wherein the first candidate path is in the history The utilization rate of the second alternative path is 60%, and the historical utilization rate of the second alternative path is 40%, then the standard time is 60%a+40%b.

In some optional embodiments, at least two sub-paths include a third sub-path, and the third sub-path has no historical driving time under at least one time attribute, and the step of "obtaining the standard time by using sub-times" includes: using infinity as The standard time of the third sub-path under at least one time attribute; or, calculate the average value of the standard time of the third sub-path under other time attributes, and use the average value as the standard time of the third sub-path. For the case that the sub-path under some time attributes has no historical driving time, infinity can be used as the standard time, that is, the alternative path passing through this sub-path is not recommended; the third sub-path under other time attributes can also be selected The average of the standard time of the path is used as the standard time of the third sub-path under this time attribute.

Because different weather conditions may cause the standard time of some sub-paths to be different, therefore, in order to increase the accuracy of the forecast, optionally, the server also receives weather forecast information, which includes weather attributes at a specified time; the target data and The specified time has the same weather attribute. Weather attributes include sunny, cloudy, cloudy, rain, snow, wind, and haze.

Based on the impact of weather factors on travel, in order to facilitate the extraction of target data, optionally, establishing a historical database, after obtaining the standard time and storing the standard time, also includes: classifying the standard time according to weather attributes. Specifically, a folder named with the time attribute can be established, and subfolders named with the weather attribute can be set in the folder named with the time attribute, and the standard time stored in each subfolder named with the weather attribute, the The Weather property for Standard Time has the same name as the subfolder it is in, and the Time property for Standard Time has the same name as the folder it is in. Specifically, it is also possible to establish a folder named after the weather attribute, and set subfolders named after the time attribute in the folder named after the weather attribute, and each subfolder named after the time attribute stores the standard time, The time attribute of the standard time has the same name as the subfolder it is located in, and the weather attribute of the standard time has the same name as the folder it is located in.

Optionally, the client mentioned in the present invention may be a mobile terminal or a vehicle-mounted terminal, wherein the mobile terminal may be a smart phone, a tablet computer, etc., and the vehicle-mounted terminal mainly refers to a vehicle machine of a smart car.

In order to solve the above technical problem, an embodiment of the present invention also provides a driving route prediction method. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention.

FIG. 8 is a schematic flowchart of a method for predicting a driving route in an embodiment of the present invention. Referring to Figure 8, the method for predicting the driving route is executed by the server and includes the following steps:

Step S21: Receive request information, the request information includes start point information, end point information and designated time. In this embodiment, the first instruction is the information input by the user. For example, the starting point information can be the Shanghai Municipal Library, the end point information can be Huadu Building, the specified time can be the current moment, and the specified time can also be the future input by the user. at some point.

Step S22: According to the request information, calculate the recommendation result by using the alternative route including at least two sub-route and the standard time of each sub-route, wherein the recommendation result includes the shortest driving time and the target route under the specified time, and the target route is the shortest driving time The corresponding alternative path.

Step S23: Send the recommendation result to the client.

In this embodiment, using the alternative routes including at least two sub-routes and the standard time of each sub-route, the driving time of each alternative route is calculated, which can effectively improve the accuracy of the predicted driving time, so that the user can Route travel, to reach the destination in the shortest time, can avoid traffic jams as much as possible, and help people make better travel arrangements.

FIG. 3 is a schematic flow chart of calculating recommendation results using alternative paths and standard time of each sub-path in an embodiment of the present invention. Please refer to Figure 3, the method for calculating the recommendation result is executed by the server, including the following steps:

Step S121: Retrieving road network images from a pre-established road network database. A road network image includes multiple nodes and sub-paths connecting adjacent nodes.

Step S122: Select the node closest to the starting point as the first node, select the node closest to the end point as the second node, and generate multiple candidate paths, the candidate paths take the first node and the second node as endpoints, and consist of at least The two sub-paths are sequentially connected to form. For example, using node A as the first node and node B as the second node, there are multiple travel modes from node A to node B, and each travel mode can be used as an alternative path, and each alternative path has It is composed of multiple sub-paths connected in sequence.

Step S123: Retrieve the target data from the pre-established historical database. The target data has the standard time of each sub-path with the same time attribute as the specified time. The time attribute refers to a certain day of the week where the time is located time period. That is, the number of days in a week is 7 days. If the specified time is Tuesday, then the time attribute of the target data is also Tuesday; and each day has different time periods, for example, morning peak time, evening peak time, and less travel time at night. Optionally, a day can be divided into 24 time periods according to hours. At this time, there are 7*24 (7 days a week, 24 hours a day) time attributes.

Step S124: Sum the standard time of each sub-path in each candidate route to calculate the travel time of each candidate route, and compare each travel time to obtain the shortest travel time, and the shortest travel time The alternative path corresponding to the time is used as the target path.

Step S125: Generate recommendation results, the recommendation results include the shortest travel time and the target route.

In the method for calculating the recommendation result in this embodiment, the road network image is retrieved from the pre-established road network database to generate an alternative path, the target data is retrieved from the pre-established historical database, and each child in the alternative path The standard time of the route is summed to calculate the driving time of each alternative route, and the calculation result is more accurate; the network image and historical data are stored separately, and the corresponding network image and data are called when calculating the recommendation result, which can reduce the system cost. load, and at the same time help to improve the speed of computing recommendation results.

Fig. 4 is a flowchart of establishing a road network database in an embodiment of the present invention. Please refer to Figure 4, the operation of establishing the road network database is as follows:

Step S1211: Acquire the original image, which includes multiple historical driving paths. The original image can be a map of a certain city, region, or province. For example, Figure 5 is a partial map of the vicinity of the Huangpu River in Shanghai. On both sides of the Huangpu River, there are famous business districts such as Shanghai World Financial Center and famous scenic spots such as Yu Garden, which are areas prone to traffic congestion.

Step S1212: using nodes to divide each historical driving route in the original image into at least two sub-paths, and extracting nodes and sub-paths to form a road network image. Further, it may be selected at the intersection of the physical path, the landmark building, the ramp of the expressway, the entire kilometer of the road, etc., and the sub-path is a section of road between two nodes. For example, Figure 6 is the road network image corresponding to some areas in Figure 5. Please refer to Figure 6. The dots in Figure 6 are nodes, and the line segments in Figure 6 are sub-paths. Circles, scenic spots, etc. are relatively dense.

Step S1213: Store the road network image to establish a road network database.

In this embodiment, the physical path is divided into at least two sub-paths, so as to make statistics on the standard time of each sub-path, thereby improving the accuracy of predicting the ETA.

Fig. 7 is a flow chart of establishing a historical database in the embodiment of the present invention. Please refer to Figure 7, the operation of establishing the historical database is as follows:

Step S1231: Obtain historical driving data. The historical driving data includes historical driving time, and the historical driving time is the actual time of passing through the sub-route. Historical driving time can be obtained through statistics.

Step S1232: Perform weighted average calculation on the historical driving time of the same sub-route under the same time attribute to obtain the sub-time, and use the sub-time to obtain the standard time. For example, for a sub-route, a total of 100 historical driving times have been counted during the Monday morning rush hour, then the average value of the 100 historical driving times is obtained as the sub-time, and then the sub-time is used to obtain the standard time of the sub-route .

Step S1233: classify and store the standard time according to the time attribute, so as to establish a historical database.

In this embodiment, the standard time of each sub-route is calculated by making statistics on the historical driving time, and the standard time is stored according to the time attribute, so that the standard time can be extracted according to the time attribute.

Optionally, a candidate path is generated by using the Dijkstra algorithm, the bidirectional Dijkstra algorithm or the Astar algorithm. Tested by the applicant on the network image of Shanghai (the number of nodes and sub-paths is at the level of one million), the above-mentioned methods can complete the calculation of the shortest driving time and the target route within 30 seconds.

Optionally, the recommendation result also includes non-target routes, and the travel time of the non-target routes is arranged in ascending order. In this way, users can learn multiple recommended routes and choose according to their own travel arrangements. For example, if they want to arrive at the fastest speed, they can choose the recommended route; The recommended route with a short distance to a shopping mall.

Optionally, in the present invention, the historical database may be a database based on distributed file storage. Using a database based on distributed file storage can facilitate data storage and query.

In the present invention, due to the different conditions of the sub-paths, "obtaining the standard time by calculating the sub-time" has different calculation methods, which will be described in detail below.

In some optional implementations, at least two sub-paths include a first sub-path, and the first sub-path is a sub-path that is only included in one alternative path under a time attribute, "Using sub-times to obtain standard time " includes: using the sub-time of the first sub-path as the standard time of the first sub-path.

In some optional implementation manners, at least two sub-paths include a second sub-path, and the second sub-path is a sub-path included in at least two alternative paths under a time attribute, "Using sub-time to find the criterion The step of "time" includes: performing a weighted average of the sub-times of the second sub-path in each candidate path to calculate the standard time of the second sub-path. That is, the second sub-path is included in at least two candidate paths. At this time, when calculating the standard time, it is necessary to carry out a weighted average of the corresponding sub-times of all the candidate paths including the second sub-path, so as to obtain get standard time. For example, the sub-time of the second sub-path in the first candidate path is a, and the sub-time of the second sub-path in the second candidate path is b, wherein the first candidate path is in the history The utilization rate of the second alternative path is 60%, and the historical utilization rate of the second alternative path is 40%, then the standard time is 60%a+40%b.

In some optional embodiments, at least two sub-paths include a third sub-path, and the third sub-path has no historical driving time under at least one time attribute, and the step of "obtaining the standard time by using sub-times" includes: using infinity as The standard time of the third sub-path under at least one time attribute; or, calculate the average value of the standard time of the third sub-path under other time attributes, and use the average value as the standard time of the third sub-path. For the case that the sub-path under some time attributes has no historical driving time, infinity can be used as the standard time, that is, the alternative path passing through this sub-path is not recommended; the third sub-path under other time attributes can also be selected The average of the standard time of the path is used as the standard time of the third sub-path under this time attribute.

Because different weather conditions may cause the standard time of some sub-paths to be different, therefore, in order to increase the accuracy of the forecast, optionally, the server also receives weather forecast information, which includes weather attributes at a specified time; the target data and The specified time has the same weather attribute. Weather attributes include sunny, cloudy, cloudy, rain, snow, wind, and haze.

Based on the impact of weather factors on travel, in order to facilitate the extraction of target data, optionally, establishing a historical database, after obtaining the standard time and storing the standard time, also includes: classifying the standard time according to weather attributes. Specifically, a folder named with the time attribute can be established, and subfolders named with the weather attribute can be set in the folder named with the time attribute, and the standard time stored in each subfolder named with the weather attribute, the The Weather property for Standard Time has the same name as the subfolder it is in, and the Time property for Standard Time has the same name as the folder it is in. Specifically, it is also possible to establish a folder named after the weather attribute, and set subfolders named after the time attribute in the folder named after the weather attribute, and each subfolder named after the time attribute stores the standard time, The time attribute of the standard time has the same name as the subfolder it is located in, and the weather attribute of the standard time has the same name as the folder it is located in.

In order to solve the above technical problem, an embodiment of the present invention provides a method for acquiring a driving route. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention.

FIG. 9 is a flowchart of a method for obtaining a driving route in an embodiment of the present invention. Referring to FIG. 9, the method for obtaining the driving route provided by this embodiment is executed by the client and includes the following steps:

Step S31: Generate request information according to the input instruction, wherein the request information includes start point information, end point information and specified time.

Step S32: Send the request information to the server.

Step S33: Receive recommendation results, and selectively display the recommendation results. "Selectively" in the present invention means that the client can display the recommendation results, or not display the recommendation results but directly use the recommendation results for navigation.

The driving route acquisition method provided in this embodiment can obtain highly accurate driving time prediction results, and selectively display the prediction results, so that the user can travel according to the recommended route, reach the destination in the shortest time, and be able to Avoid traffic jams as much as possible, and help people make travel arrangements better.

Fig. 2 is a flow chart of the client generating request information according to the input instruction in the embodiment of the present invention. Please refer to Figure 2, the steps of "generating request information according to the input instruction" include:

Step S111: Acquiring an input command, the command includes a start position, an end position and a designated time.

Step S112: The client is equipped with a global positioning system, and uses the global positioning system to obtain GPS information of the starting point as information of the starting point, and obtain GPS information of the ending point as information of the ending point.

Step S113: the client generates request information using the start point information, end point information and specified time.

In this embodiment, the GPS information generated by the global positioning system installed on the client is used as the starting point and destination information, the method of generating the request information is simple, and the positioning is accurate.

In order to solve the above-mentioned technical problems, this embodiment provides a server, the server includes a processor and a memory, a plurality of instructions are stored in the memory, and the processor is adapted to load the instructions to execute any one of the above-mentioned driving route prediction methods , can achieve the beneficial effect of any one of the above-mentioned driving route prediction methods, which will not be repeated here.

In order to solve the above-mentioned technical problems, this embodiment provides a client, the client includes a processor and a memory, a plurality of instructions are stored in the memory, and the processor is adapted to load instructions to execute any one of the above-mentioned embodiments. The method for obtaining a driving route can realize the beneficial effect of any one of the above methods for obtaining a driving route, and will not be repeated here.

FIG. 10 is a schematic diagram of a connection structure between a server and a client in an embodiment of the present invention. Referring to FIG. 10 , the interaction between the server 2 and the client 1 can realize the recommendation of the driving route, wherein both the client 1 and the server 2 include a memory and a processor. In the present invention, the client may be a mobile terminal or a vehicle-mounted terminal, wherein the mobile terminal may be a smart phone, a tablet computer, etc., and the vehicle-mounted terminal mainly refers to a vehicle machine of a smart car.

Please continue to refer to Fig. 10, in the present invention, the client 1 performs the following steps: generate request information according to the input instruction, and send the request information to the server 2, wherein the request information includes starting point information, end point information and specified time; receiving Recommended results, and selectively display the recommended results.

Please continue to refer to FIG. 10. In the present invention, the server 2 performs the following steps: the server 2 receives the request information, and according to the request information, calculates the recommendation result by using the alternative paths including multiple sub-paths and the standard time of each sub-path, The recommendation results include the shortest driving time and the target route under the specified time, and the target route is the alternative route corresponding to the shortest driving time; the server 2 sends the recommendation result to the client 1.

Please continue to refer to FIG. 10, further, the memory of the server 2 includes a prediction module 201, a road network database 202 and a historical database 203, wherein the road network database 202 is used to store road network images, and the historical database is used to store the standard of each sub-path Time, so that the prediction module 201 retrieves the road network image and the standard time from the road network database 202 and the history database 203 respectively when predicting the driving time. It should be noted that the road network database 202 and the history database 203 can be databases based on distributed file storage. The database 203 only needs to be connected to the server 2 .

FIG. 11 is a schematic diagram of another connection structure between a server and a client in an embodiment of the present invention. Referring to Fig. 11, further, the memory of the server 2 also includes an offline data processing module 204, the offline data processing module 204 uses the original image to establish a road network database, utilizes historical driving data to establish a historical database, establishes a road network database and establishes a historical database. For the process, please refer to the above-mentioned embodiments, which will not be repeated here. It should be noted that although the server 2 in this embodiment includes an offline data processing module 204, in fact, the offline data processing module 204 may not be arranged in the server 2, but connected to the server 2, which does not affect this implementation Example implementation.

So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings, but those skilled in the art will easily understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

Claims (10)

1. A driving route recommendation method, characterized in that it comprises: The client generates request information according to the input instruction, and sends the request information to the server, wherein the request information includes start point information, end point information and designated time; The server receives the request information, and according to the request information, calculates a recommendation result using an alternative path including at least two sub-paths and a standard time of each of the sub-paths, and the recommendation result includes The shortest travel time and the target route, the target route is the alternative route corresponding to the shortest travel time; The server sends the recommendation result to the client; The client receives the recommendation result, and selectively displays the recommendation result. 2. The driving route recommendation method according to claim 1, characterized in that, the step of "utilizing the alternative route comprising a plurality of sub-paths and the standard time calculation recommendation result of each said sub-path" comprises: Retrieving a road network image from a pre-established road network database, the road network image including a plurality of nodes and the sub-paths connecting adjacent nodes; Selecting the node closest to the starting point as the first node, selecting the node closest to the end point as the second node, and generating at least one alternative path, the alternative path is based on the first node and the second node The node is an endpoint and is composed of at least two sub-paths connected in sequence; Call the target data from the pre-established historical database, the target data is the standard time of each sub-path with the same time attribute as the specified time, the time attribute refers to the time in a week a certain period of time in a certain day; Summing the standard times of each of the sub-paths in each of the candidate routes to calculate the travel time of each of the candidate routes, and comparing each of the travel times to obtain the The shortest travel time, the alternative route corresponding to the shortest travel time as the target route; The recommendation result is generated, and the recommendation result includes the shortest driving time and the target route. 3. The driving route recommendation method according to claim 2, characterized in that, The candidate path is generated by using the Dijkstra algorithm, the bidirectional Dijkstra algorithm or the Astar algorithm. 4. The driving route recommendation method according to claim 3, characterized in that, The recommendation result also includes non-target routes, and the travel time of the non-target routes is arranged in ascending order. 5. The driving route recommendation method according to claim 2, wherein the operation of establishing the road network database is specifically: Acquiring an original image, the original image includes a plurality of historical driving paths; dividing each historical driving path in the original image into at least two sub-paths by using the nodes; Extracting the nodes and the sub-paths to form the road network image, and storing the road network image to establish the road network database. 6. The driving route recommendation method according to claim 5, wherein the operation of establishing the historical database is specifically: Acquiring historical driving data, the historical driving data includes historical driving time, and the historical driving time is the actual time of passing through the sub-path; Performing weighted average calculation on the historical travel time of the same sub-path under the same time attribute to obtain the sub-time, and using the sub-time to obtain the standard time; The standard time is classified and stored according to the time attribute, so as to establish the historical database. 7. The driving route recommendation method according to claim 6, wherein the driving route recommendation method further comprises: The server obtains weather forecast information, and the weather forecast information includes weather attributes at the specified time, wherein the target data has the same weather attributes as the specified time. 8. The driving route recommendation method according to claim 7, wherein the operation of "establishing the historical database" also includes: After the standard time is obtained and before the standard time is stored, the standard time is classified according to the weather attribute. 9. The driving route recommendation method according to any one of claims 6-8, wherein the historical database is a database based on distributed file storage. 10. The driving route recommendation method according to any one of claims 6-8, wherein at least two of the sub-paths comprise a first sub-path, and the first sub-path is at one of the time attributes Under the sub-path that is only included in one of the alternative paths, the step of "using the sub-time to obtain the standard time" includes: The sub-time of the first sub-path is used as the standard time of the first sub-path.