CN104990559B - A kind of path recommendation method, system and client based on taxi empirical data - Google Patents

Abstract

The present invention provides a route recommendation method, system and client based on taxi experience data, including: a preset node module presets nodes, and acquires the route between two nodes; the second acquisition module, based on the experience data, Obtain the recommended weight of any of the paths in the preset time period, and store the recommended weight; the third acquisition module obtains the user's current location and target location, and obtains the current location corresponding to the nearest initial node, and the target location corresponds to the nearest the target node; select more than one path between the initial node and the target node; the fourth obtaining module obtains the current time of the user, and obtains the recommended weight value of the current time of the path within the preset time period ; The recommendation module recommends a preset number of paths corresponding to the recommended weights.

Description

A route recommendation method, system and client based on taxi experience data

technical field

The invention relates to the field of electronic navigation, in particular to a route recommendation method, system and client based on taxi experience data.

Background technique

With the development of science and technology and the improvement of living standards, route navigation has become an indispensable step for people to travel. The patent document with application number 200610105972.2 discloses a navigation system for route search based on predetermined conditions, providing starting point and end point A navigation route between trips, the navigation system includes: a display unit for displaying a navigation route and/or a candidate navigation route with an associated condition name, wherein the predetermined condition with an associated condition name generates a plurality of candidate navigation path.

The above scheme searches for the itinerary navigation path between the start point and the end point based on the name correlation and the distance. However, in the complex road conditions of the city, especially in the case of frequent traffic jams in large cities, the road conditions are different in different time periods and different road sections. For example, going to work Road sections where businesses are concentrated during peak hours and road sections where scenic spots are located during holidays are often congested. The short-distance path obtained by using the above scheme cannot guarantee smooth traffic on the road section, so the optimal navigation path cannot be accurately obtained.

In addition, under the complex road conditions in the city, experienced taxi drivers can best understand the congestion of the road conditions, and will find the fastest and smoothest route. Provided to the user according to the user's needs, the user's travel provides a smoother path, improves the user's travel comfort, and is also of great significance to the smooth operation and utilization efficiency of the entire urban road network.

Contents of the invention

The technical problem to be solved by the present invention is to recommend the best driving route to the user under the complicated urban road conditions.

In order to solve the problems of the technologies described above, the technical solution adopted in the present invention is:

The present invention provides a route recommendation method based on taxi experience data, including:

preset nodes, and obtain a path between two said nodes;

Acquiring the recommendation weight of any of the paths in a preset time period according to empirical data, and storing the recommendation weight;

Obtaining the user's current location and target location, and obtaining the current location corresponding to the nearest initial node, and the target location corresponding to the nearest target node; selecting more than one path between the initial node and the target node;

Acquiring the current time of the user, and obtaining the recommendation weight within the preset time period of the current time of the path;

A preset number of paths corresponding to the recommended weights are recommended.

The above-mentioned path recommendation method based on taxi experience data has the beneficial effects of: preset nodes, and obtain the recommended weight value of the path between any two nodes in the preset time period, so as to obtain the path between any two nodes in different time periods. The optimal path obtains the path of the initial node and the target node corresponding to the user's current position and target position respectively, and obtains the recommended weight of the path between the initial node and the target node through the user's current time, so as to obtain the optimal recommended path , so it can effectively avoid congested road sections.

The present invention also provides a route recommendation system based on taxi experience data, including:

Preset node module, used for presetting nodes;

A first obtaining module, configured to obtain a path between two nodes;

The second obtaining module is used to obtain the recommended weight value of any of the paths in the preset time period according to the empirical data; the storage module is used to store the recommended weight value;

The third obtaining module is used to obtain the user's current location and target location, and obtains that the current location corresponds to the nearest initial node, and the target location corresponds to the nearest target node; the selection module is used to select a node between the initial node and the target node the above path;

The fourth obtaining module is used to obtain the current time of the user, and obtain the recommendation weight of the current time of the path within the preset time period;

A recommendation module, configured to recommend a preset number of paths corresponding to the recommended weights.

The above-mentioned path recommendation method based on taxi experience data has the beneficial effects of: the preset node module presets the node, and obtains the recommendation weight of any two nodes in the preset time period through the first acquisition module and the second acquisition module. Value, so that the best path between any two nodes in different time periods can be obtained, the third acquisition module obtains the path of the initial node and target node corresponding to the user's current position and target position respectively, and obtains through the fourth acquisition module The user's current time and the recommended weight of the path between the initial node and the target node at the current time can obtain the optimal recommended path, so it can effectively avoid congested road sections.

The present invention also provides a route recommendation client based on taxi experience data, including:

The third obtaining module is used to obtain the target position of the user's current position, and obtains the nearest initial node corresponding to the current position, and the nearest target node corresponding to the target position; the selection module is used to select the initial node and the target node between more than one path;

The fourth obtaining module is used to obtain the current time of the user, and obtain the recommendation weight of the current time of the path within the preset time period;

A recommendation module, configured to recommend a preset number of paths corresponding to the recommended weights.

The beneficial effect of the above client is that the user obtains the path between the initial node and the target node respectively corresponding to the current position and the target position through the third acquisition module, and obtains the current time and the current time between the initial node and the target node through the fourth acquisition module. The recommended weight of the path can be used to obtain the best path between the initial node and the target node, which effectively solves the problem of driving difficulties caused by road congestion; the above client node data and the recommended weight of the path between any two nodes in different time periods are preset It is installed in the client, so the client does not need to carry out other communication, and it can effectively avoid congested road sections even when there is no communication signal or no network connection.

The present invention further provides a route recommendation client based on taxi experience data, including:

The fifth obtaining module is used to obtain the target position of the user's current position;

The first receiving module is used to receive the nearest initial node corresponding to the current position, and the nearest target node corresponding to the target position; and receive more than one path between the initial node and the target node;

The sixth obtaining module is used to obtain the current user time;

The second receiving module is configured to receive the recommended weight value within the preset time period of the current time of the path;

The third receiving module is configured to receive a preset number of paths corresponding to the recommended weights.

The beneficial effect of the above client is that: the user receives the path between the initial node and the target node which are respectively closest to the current position and the target position through the first receiving module, and receives the recommendation weight of the path between the initial node and the target node at the current time through the second receiving module. Value, through the third receiving module to receive the path corresponding to the recommended weight; the above client node data, recommended weights in different time periods, and the path corresponding to the recommended weight are received by the client through communication, and do not need to be stored in the client , which saves the storage space of the client.

Description of drawings

1 is a flowchart of a route recommendation method based on taxi experience data in Embodiment 1 of the present invention;

Fig. 2 is the preset node flowchart of the route recommendation method based on taxi experience data in Embodiment 1 of the present invention;

FIG. 3 is a schematic structural diagram of a route recommendation system based on taxi experience data in Embodiment 2 of the present invention;

4 is a schematic structural diagram of a route recommendation client based on taxi experience data according to Embodiment 3 of the present invention;

FIG. 5 is a schematic structural diagram of a route recommendation client based on taxi experience data according to Embodiment 4 of the present invention.

Label description:

1. Preset node module; 2. Second acquisition module; 3. Third acquisition module; 4. Fourth acquisition module; 5. Recommendation module; 6. Seventh acquisition module; 7. Calculation module; 8. Superposition module; 9. The fifth acquiring module; 10. The first receiving module; 11. The sixth acquiring module; 12. The second receiving module; 13. The third receiving module; 14. The first acquiring module.

Detailed ways

In order to describe the technical content, achieved goals and effects of the present invention in detail, the following descriptions will be made in conjunction with the embodiments and accompanying drawings.

The most critical idea of the present invention is: according to empirical data, obtain the recommendation weight of any path in the preset time period, and make recommendations according to the path included in the current position and the target position and the current time in the preset time period weights to get the optimal path.

Please refer to Figure 1 to Figure 5,

A route recommendation method based on taxi experience data, including:

S1. Preset nodes, and obtain a path between two nodes;

S2. According to empirical data, obtain the recommended weight value of any one of the paths in a preset time period, and store the recommended weight value;

S3. Obtain the user's current location and target location, and obtain the current location corresponding to the nearest initial node, and the target location corresponding to the nearest target node; select more than one path between the initial node and the target node;

S41. Obtain the current time of the user, and obtain the recommendation weight within the preset time period of the current time of the path;

S5. Recommending a preset number of paths corresponding to the recommended weights.

From the above description, it can be seen that the beneficial effect of this route recommendation method based on taxi experience data is: preset nodes, and get the recommended weight of any two nodes in the preset time period, so that any path in different time periods can be obtained. The best path between one or two nodes, obtain the path of the initial node and target node corresponding to the user's current position and target position respectively, and obtain the recommended weight of the path between the initial node and the target node through the user's current time, so as to obtain The optimal recommended route, so it can effectively avoid congested road sections.

Further, the "preset node" is specifically:

S11, traversing the taxi's initial position or target position;

S12. Sort the frequency of taxis at the initial location or the target location within the preset time period;

S13. According to the sorting, extract a preset number of initial positions or target positions as preset nodes.

From the above description, it can be known that the preset nodes extracted by sorting the taxi frequency of the initial location and the target location can represent most of the initial location and the target location of the taxi.

Further, the "recommendation weight of the preset time period" is specifically: according to holidays, weekdays, weekends, common time periods and peak hours, combined with the taxi speed and frequency information of a route in the above time period, to obtain the recommendation weight value.

From the above description, it can be seen that the speed and frequency information of taxis in different time periods reflect the traffic conditions of the route in different time periods, so that the obtained recommendation weights can effectively avoid congested road sections.

Further, the route recommendation method based on taxi experience data also includes:

S42. Obtain the path from the current location to the initial node, and obtain the path from the target location to the target node, calculate the recommended weight of the path, superimpose the recommended weight with the recommended weight between nodes, and superimpose the superimposed The recommendation weight is used as the recommendation weight.

It can be seen from the above description that the total path also considers the path from the initial position to the initial node and the position from the target position to the target node.

A route recommendation system based on taxi experience data, including:

The preset node module 1 is used to preset a node; the first acquisition module 14 is used to acquire a path between two nodes;

The second obtaining module 2 is used to obtain the recommended weight value of any of the paths in the preset time period according to empirical data; the storage module is used to store the recommended weight value;

The third obtaining module 3 is used to obtain the user's current location and target location, and obtains the current location corresponding to the nearest initial node, and the target location corresponds to the nearest target node; the selection module is used to select between the initial node and the target node more than one path;

The fourth obtaining module 4 is used to obtain the current time of the user, and obtain the recommendation weight of the current time of the path within the preset time period;

The recommending module 5 is configured to recommend a preset number of paths corresponding to the recommended weights.

As can be seen from the above description, the beneficial effects of this route recommendation system based on taxi experience data are: the preset node module 1 presets the node, and obtains the path between any two nodes through the first acquisition module 14 and the second acquisition module 2. The recommended weight of the preset time period, so that the best path between any two nodes in different time periods can be obtained, and the third acquisition module 3 obtains the path of the initial node and the target node corresponding to the user's current position and target position respectively , and obtain the current time of the user and the recommended weight of the path between the initial node and the target node through the fourth acquisition module 4, so as to obtain the optimal recommended path, so that congested road sections can be effectively avoided.

A route recommendation client based on taxi experience data, including;

The third obtaining module 3 is used to obtain the target position of the user's current position, and obtains the nearest initial node corresponding to the current position, and the nearest target node corresponding to the target position; the selection module is used to select the initial node and the target node between more than one path;

The fourth obtaining module 4 is used to obtain the current time of the user, and obtain the recommendation weight of the current time of the path within the preset time period;

The recommending module 5 is configured to recommend a preset number of paths corresponding to the recommended weights.

It can be seen from the above description that the beneficial effect of the route recommendation client based on taxi experience data is that the user obtains the path between the initial node and the target node respectively corresponding to the current position and the target position through the third acquisition module 3, and through the fourth acquisition module 3 Obtaining module 4 obtains the current time, and the recommended weight of the path between the initial node and the target node at the current time, thereby obtaining the optimal path between the initial node and the target node, effectively solving the problem of driving difficulties caused by road congestion; the above-mentioned client The node data and the recommended weight of the path between any two nodes in different time periods are preset in the client, so the client does not need to communicate any more, and can effectively avoid congestion even when there is no communication signal or no network connection road section.

Further, said route recommendation client based on taxi experience data also includes:

The seventh obtaining module 6 is used to obtain the path from the current position to the initial node, and obtain the path from the target position to the target node;

Calculation module 7, for calculating the recommended weight of the path;

A superimposing module 8, configured to superimpose the recommended weights and recommended weights between nodes.

It can be seen from the above description that the total path also considers the path from the initial position to the initial node and the position from the target position to the target node.

A route recommendation client based on taxi experience data, including;

The fifth obtaining module 9 is used to obtain the target position of the user's current position;

The first receiving module 10 is configured to receive the nearest initial node corresponding to the current position, and the nearest target node corresponding to the target position; and receive more than one path between the initial node and the target node;

The sixth obtaining module 11 is used to obtain the current user time;

The second receiving module 12 is configured to receive the recommended weight value within the preset time period of the current time of the path;

The third receiving module 13 is configured to receive a preset number of paths corresponding to the recommended weights.

It can be seen from the above description that the beneficial effect of the route recommendation client based on taxi experience data is that the user receives the routes between the initial node and the target node which are respectively closest to the current position and the target position through the first receiving module 10, and through the second receiving module 10 Module 12 receives the recommended weight of the path between the initial node and the target node at the current time, and receives the path corresponding to the recommended weight through the third receiving module 13; the above-mentioned client node data, recommended weights in different time periods, and recommended weights The path is received by the client through communication and does not need to be stored in the client, which saves the storage space of the client.

Further, the described route recommendation client based on taxi experience data also includes;

The seventh obtaining module 6 is used to obtain the path from the current position to the initial node, and obtain the path from the target position to the target node;

Calculation module 7, for calculating the recommended weight of the path;

A superimposing module 8, configured to superimpose the recommended weights and recommended weights between nodes.

It can be seen from the above description that the total path also considers the path from the initial position to the initial node and the position from the target position to the target node.

Please refer to Fig. 1 and Fig. 2, embodiment one of the present invention is:

A route recommendation method based on taxi experience data, including:

S1, preset nodes, obtain the path between the two nodes; the "preset nodes" are specifically: S11, traverse the initial position or target position of the taxi; S12, set the initial position or target position within the preset time period Sorting the frequency of location taxis; S13, according to the sorting, extracting a preset number of initial positions or target positions as preset nodes; the map-based road network divides the city into multiple nodes, and the occurrence of taxis Nodes whose frequency reaches a certain amount are used as preset nodes. For example, the frequency of taxis in parks and train stations is high, and parks and train stations are used as two preset nodes;

S2. According to the experience data, that is, the historical data of taxis, obtain the recommended weight value of any of the routes in the preset time period, and store the recommended weight value; the "recommended weight value in the preset time period" is specific is: According to holidays, weekdays, weekends, normal hours and peak hours, combined with the taxi speed and frequency information of a path in the above hours, the recommended weights are obtained; the paths from the train station to the park include Lakeside East path, Lakeside South path and For the lakeside north route, during the peak hours of holidays, the recommended weight for the lakeside east route is a, the recommended weight for the lakeside south route is b, and the recommended weight for the lakeside north route is c;

S3. Obtain the user's current location and target location, and obtain the current location corresponding to the nearest initial node, and the target location corresponding to the nearest target node; select more than one path between the initial node and the target node; assume that the current location is the nearest initial starting point If it is a railway station, and the target location corresponds to the nearest target node park, then choose the shortest distance of the lakeside east path and the shortest distance of the lakeside south road as the path;

S41. Obtain the current time of the user, and obtain the recommendation weight value of the current time of the route within the preset time period; assuming that the current time is the peak period of the holiday, obtain the correspondence between the East Lake Route and the South Lake Route during this period The recommendation weights of are a and b;

S42. Obtain the path from the current location to the initial node, and obtain the path from the target location to the target node, calculate the recommended weight of the path, superimpose the recommended weight with the recommended weight between nodes, and superimpose the superimposed The recommended weight is used as the recommended weight; the recommended weights corresponding to the two paths from the current location to the initial node train station, Xinghua path and Xuefu path, are d and e respectively, and the recommended weights corresponding to a path from the target location to the target node park, Zhongshan Road The weight is f, superposition of a, d, f, superposition of a, e, f, superposition of b, d, f, and superposition of b, e, f as the recommended weight of the total path from the current position to the target position;

S5. Recommending the path corresponding to the recommended weight of the preset number; recommending the above-mentioned superimposed recommended weight of the preset number, comparing the recommended weights after the superimposition, the recommended weights of b, d, and f superimposed are the best , and finally the path corresponding to b, d, and f is Xinghua Road-Hubin South Road-Zhongshan Road is the optimal path.

Please refer to Fig. 3, embodiment two of the present invention is:

A route recommendation system based on taxi experience data, including:

The preset node module 1 is used to preset a node; the first acquisition module 14 is used to acquire a path between two nodes;

The second obtaining module 2 is used to obtain the recommended weight value of any of the paths in the preset time period according to empirical data; the storage module is used to store the recommended weight value;

The third obtaining module 3 is used to obtain the user's current location and target location, and obtains the current location corresponding to the nearest initial node, and the target location corresponds to the nearest target node; the selection module is used to select between the initial node and the target node more than one path;

The fourth obtaining module 4 is used to obtain the current time of the user, and obtain the recommendation weight of the current time of the path within the preset time period;

The recommending module 5 is configured to recommend a preset number of paths corresponding to the recommended weights.

Please refer to Fig. 4, embodiment three of the present invention is:

A route recommendation client based on taxi experience data, including:

The third obtaining module 3 is used to obtain the target position of the user's current position, and obtains the nearest initial node corresponding to the current position, and the nearest target node corresponding to the target position; the selection module is used to select the initial node and the target node between more than one path;

The fourth obtaining module 4 is used to obtain the current time of the user, and obtain the recommendation weight of the current time of the path within the preset time period;

A recommendation module 5, configured to recommend a preset number of paths corresponding to the recommended weights;

The seventh obtaining module 6 is used to obtain the path from the current position to the initial node, and obtain the path from the target position to the target node;

Calculation module 7, for calculating the recommended weight of the path;

A superimposing module 8, configured to superimpose the recommended weights and recommended weights between nodes.

Please refer to Fig. 5, the fourth embodiment of the present invention is:

A route recommendation client based on taxi experience data, including:

The fifth obtaining module 9 is used to obtain the target position of the user's current position;

The first receiving module 10 is configured to receive the nearest initial node corresponding to the current position, and the nearest target node corresponding to the target position; and receive more than one path between the initial node and the target node;

The sixth obtaining module 11 is used to obtain the current user time;

The second receiving module 12 is configured to receive the recommended weight value within the preset time period of the current time of the path;

The third receiving module 13 is configured to receive a preset number of paths corresponding to the recommended weights.

The seventh obtaining module 6 is used to obtain the path from the current position to the initial node, and obtain the path from the target position to the target node;

Calculation module 7, for calculating the recommended weight of the path;

A superimposing module 8, configured to superimpose the recommended weights and recommended weights between nodes.

To sum up, the present invention provides a route recommendation method, system and client based on taxi experience data, aiming at the problem of inaccurate navigation caused by the existing navigation system only based on the starting position without considering road congestion. The preset node module and the second acquisition module preset the node and obtain the recommended weight of the path between any two nodes, and obtain the user's current location, target location and current time through the third acquisition module and the fourth acquisition module, and obtain the corresponding Recommended weights, the recommendation module recommends the corresponding path, which can effectively avoid the peak road section of vehicles and provide users with the best path.

The above description is only an embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent transformations made by using the description of the present invention and the contents of the accompanying drawings, or directly or indirectly used in related technical fields, are all included in the same principle. Within the scope of patent protection of the present invention.

Claims (8)

1. A route recommendation method based on taxi experience data, comprising: The preset node is used to obtain the path between the two nodes; the preset node is a map-based road network that divides the city into multiple nodes, and the node whose occurrence frequency of taxis reaches a certain amount is used as the preset node. set node; According to empirical data, obtain the recommended weight value of any of the paths in the preset time period, and store the recommended weight value; the "recommended weight value in the preset time period" is specifically: according to holidays, working days, On weekends, common hours and peak hours, combined with the taxi speed and frequency information of a path in the above hours, the recommendation weights are obtained; Obtaining the user's current location and target location, and obtaining the current location corresponding to the nearest initial node, and the target location corresponding to the nearest target node; selecting more than one path between the initial node and the target node; Acquiring the current time of the user, and obtaining the recommendation weight within the preset time period of the current time of the selected path; A preset number of paths corresponding to the recommended weights are recommended. 2. a kind of route recommendation method based on taxi experience data as claimed in claim 1, is characterized in that: The "preset node" mentioned is specifically: Traverse the initial or target location of the taxi; Sort the frequency of taxis at the initial location or the target location within the preset time period; According to the sorting, a preset number of initial positions or target positions are extracted as preset nodes. 3. a kind of route recommendation method based on taxi experience data as claimed in claim 1, is characterized in that: further comprising: Obtain the path from the current location to the initial node, and obtain the path from the target location to the target node, calculate the recommended weight of the path, superimpose the recommended weight with the recommended weight between nodes, and superimpose the recommended weight value as the recommended weight. 4. A route recommendation system based on taxi experience data, including: The preset node module is used to preset nodes; the first acquisition module is used to acquire the path between the two nodes; the preset node module divides the city into multiple nodes based on the road network of the map, The node whose occurrence frequency of the taxi reaches a certain amount is used as the preset node; The second acquisition module is used to obtain the recommended weight of any of the paths in the preset time period according to empirical data; the "recommended weight of the preset time period" is specifically: according to holidays, working days, and weekends As well as normal hours and peak hours, combined with the taxi speed and frequency information of a path in the above hours, the recommendation weight is obtained; a storage module, configured to store the recommended weight; The third obtaining module is used to obtain the user's current location and target location, and obtain the current location corresponding to the nearest initial node, and the target location corresponding to the nearest target node; A selection module, used to select more than one path between the initial node and the target node; The fourth obtaining module is used to obtain the current time of the user, and obtain the recommended weight value within the preset time period of the current time of the selected path; A recommendation module, configured to recommend a preset number of paths corresponding to the recommended weights. 5. A route recommendation client based on taxi experience data, characterized in that: comprising; The third obtaining module is used to obtain the target position of the user's current position, and obtain the nearest initial node corresponding to the current position, and the nearest target node corresponding to the target position; A selecting module, configured to select more than one path between the initial node and the target node; the initial node and the target node are respectively one of preset nodes, and the preset node is a map-based path The network divides the city into multiple nodes, and the nodes whose occurrence frequency of taxis reaches a certain amount are used as preset nodes; The fourth obtaining module is used to obtain the current time of the user, and obtain the recommended weight value within the preset time period of the current time of the selected path; the recommended weight value within the preset time period is specifically: According to holidays, weekdays, weekends, normal hours and peak hours, combined with the taxi speed and frequency information of a path in the above hours, the recommendation weights are obtained; A recommendation module, configured to recommend a preset number of paths corresponding to the recommended weights. 6. A kind of route recommendation client based on taxi experience data as claimed in claim 5, it is characterized in that: also comprise, The seventh obtaining module is used to obtain the path from the current position to the initial node, and obtain the path from the target position to the target node; A calculation module, configured to calculate the recommended weight of the path; A superimposing module, configured to superimpose the recommended weights with recommended weights between nodes. 7. A route recommendation client based on taxi experience data, characterized in that: comprising, The fifth obtaining module is used to obtain the target position of the user's current position; The first receiving module is used to receive the nearest initial node corresponding to the current position, and the nearest target node corresponding to the target position; and receive more than one path between the initial node and the target node; the initial node and the The target nodes are respectively one of the preset nodes, and the preset nodes are divided into multiple nodes based on the road network of the map, and the nodes whose occurrence frequency of taxis reach a certain amount are used as the preset nodes; The sixth obtaining module is used to obtain the current user time; The second receiving module is used to receive the recommended weight value within the preset time period of the current time of the path; the recommended weight value within the preset time period is specifically: according to holidays, working days, weekends and ordinary Time period and peak time, combined with the taxi speed and frequency information of a route in the above time period, to obtain the recommendation weight; The third receiving module is configured to receive a preset number of paths corresponding to the recommended weights. 8. A kind of route recommendation client based on taxi experience data as claimed in claim 7, it is characterized in that: also comprise, The seventh obtaining module is used to obtain the path from the current position to the initial node, and obtain the path from the target position to the target node; A calculation module, configured to calculate the recommended weight of the path; A superimposing module, configured to superimpose the recommended weights with recommended weights between nodes.