TW201732231A - Navigation method, navigation system and recording medium - Google Patents

Abstract

A navigation method and a navigation system are disclosed here. The navigation method includes: receiving a route plan requirement; selecting a plurality of historical routes according to an origin and destination condition of the route plan requirement; classifying the historical routes to generate a plurality of route groups according to route coordinate information of the historical routes; tagging the historic times, historic environment conditions, the real-time time and the real-time environment condition on an orthogonal coordinate diagram to generate coordinates of the historical routes and a coordinate of the route plan requirement; calculating a distance between each of coordinates of the historical routes and the coordinate of the route plan requirement; averaging the distances of each of route groups respectively to acquire a plurality of average distances; calculating a historical route amounts and an average distance corresponding to one of the route groups according to a calculating module respectively to generate a corresponding calculating value for each of the route groups; and selecting one of the route groups corresponding to a biggest calculating value as at least one best route.

Description

Navigation method, navigation system, and recording medium

The content of the embodiment in the present invention relates to a navigation technology, and in particular to a navigation method, a navigation system, and a recording medium.

With the development of mobile devices and vehicle devices, the habit of users receiving suggested routes through navigation systems has gradually evolved. However, existing navigation systems only provide suggested routes based on the distance between the starting point of the route and the origin of the route or the road. That is to say, the suggested route generated by the above method is not necessarily the best route for the user.

In view of this, the present disclosure proposes a navigation method and a navigation system to solve the problems described in the prior art.

One embodiment of the present disclosure relates to a navigation method. The navigation method includes: receiving a route planning requirement, the route planning requirement includes a point-and-point condition, an immediate time, and an immediate environmental condition; and selecting a plurality of historical routes according to the starting and ending point conditions, each historical route includes a path coordinate Information, historical time and historical environment conditions; classify these historical routes according to path coordinate information to generate complex group route groups; historical time and historical environmental conditions of each historical route, and immediate time and immediate environment for route planning needs Conditions are indicated by orthogonal coordinate maps with environmental conditions and time as axes respectively to generate coordinates corresponding to each historical route and route planning requirements; and calculate a straight line distance between coordinates of each historical route and coordinates of route planning requirements; The average distance of each route group is averaged according to each route group; the number of historical routes and the average distance of each route group are calculated according to a calculation model to generate a calculation result of each route group. a value; and a route group corresponding to the largest calculated result value as at least one optimal route.

One embodiment of the present disclosure is directed to a navigation system. The navigation system includes a transmission unit, a storage unit, and a processing unit. The processing unit is electrically connected to the transmission unit and the storage unit. The transmission unit is configured to receive a route planning requirement, and the route planning requirement includes a point-and-point condition, an immediate time, and an immediate environmental condition. The storage unit is configured to store a plurality of historical routes, each historical route including a path coordinate information, a historical time, and a historical environmental condition. The processing unit is configured to select the historical routes that meet the conditions of the starting and ending points. The processing unit is further configured to classify the selected historical routes according to the path coordinate information to generate a plurality of group route groups. The processing unit is further configured to mark the historical time and the historical environmental condition of each selected historical route, and the real-time and immediate environmental conditions of the route planning requirement, respectively, in an orthogonal coordinate graph with one of the environmental conditions and the time axis. To generate coordinates corresponding to each selected historical route and route planning demand, and calculate each selected historical road The straight line distance between the coordinates of the line and the coordinates required for route planning. The processing unit is further configured to average the linear distances according to each route group to obtain an average distance of each route group. The processing unit is further configured to calculate a historical route number and an average distance of each route group according to a calculation model to generate a calculation result value of each route group, and use the route group corresponding to the maximum calculation result value. As at least one best route.

One embodiment of the present disclosure relates to a computer readable recording medium. The recording medium records a program that is useful for the computer to perform the following steps: receiving a route planning requirement, the route planning requirement includes a point-and-point condition, an immediate time, and an immediate environmental condition; and selecting a plurality of historical routes according to the starting and ending conditions, each The historical route includes a path coordinate information, a historical time and a historical environmental condition; the historical routes are classified according to the path coordinate information to generate a plurality of group route groups; historical time and historical environmental conditions of each historical route, and route planning The immediate time and immediate environmental conditions of the demand are indicated by orthogonal coordinate maps with environmental conditions and time as axes, to generate coordinates corresponding to the requirements of each historical route and route planning; calculation of coordinates and route planning requirements of each historical route The straight line distance between the coordinates; the average distance between the respective route groups is obtained according to the average distance of each route group; the number of historical routes and the average distance of each route group are calculated according to a calculation model, Generate a calculated result value for each route group; and maximize Route calculation result value as a group corresponding to the at least one optimal route.

In some embodiments, F = α × log (C ) - β × log (S) for the computation model. F is a calculation result value corresponding to one of the route groups. C is the number of historical routes corresponding to one of the route groups. S is the average distance corresponding to one of the route groups. α and β are each a parameter value.

In some embodiments, the processing unit is further configured to substitute the partial historical routes into the calculation model, and obtain the parameter values α and β using a cross-validation method.

In some embodiments, the processing unit is further configured to classify the historical routes into the group of route groups according to a nearest neighbor algorithm.

In summary, by applying the above embodiment, the optimal route is generated according to historical routes of other users in the past, and the number of historical routes of each route group and the average distance between each route group and the route planning requirement ( Similarity) is considered at the same time, thereby producing an optimal route that is more suitable for the user.

100‧‧‧Navigation system

110a~110f‧‧‧Electronic device

120‧‧‧Server

122‧‧‧Transportation unit

124‧‧‧Processing unit

126‧‧‧ storage unit

Starting point of P1‧‧

P2‧‧‧讫

R1~R3‧‧‧ route group

400‧‧‧ navigation method

S402, S404, S406, S408, S410, S412, S414, S416‧‧ step

The above and other objects, features, advantages and embodiments of the present invention will become more apparent and understood. 2 is a schematic diagram of a plurality of group routes according to some embodiments of the present disclosure; FIG. 3 is an orthogonal coordinate diagram of an environment condition and time axis according to some embodiments of the disclosure; And FIG. 4 is a flow chart of a navigation method according to some embodiments of the present disclosure.

The embodiments are described in detail below with reference to the accompanying drawings, but the embodiments are not intended to limit the scope of the invention, and the description of the structure operation is not intended to limit the order of execution, any component recombination The structure, which produces equal devices, is within the scope of the present invention. In addition, the drawings are for illustrative purposes only and are not drawn to the original dimensions. For the sake of understanding, the same or similar elements in the following description will be denoted by the same reference numerals.

The terms used in the entire specification and the scope of the patent application, unless otherwise specified, generally have the ordinary meaning of each term used in the field, the content disclosed herein, and the particular content.

In addition, the terms "including", "including", "having", "containing", and the like, as used herein, are all open terms, meaning, but not limited to.

FIG. 1 is a schematic diagram of a navigation system 100 in accordance with some embodiments of the present disclosure. In some embodiments, navigation system 100 includes an electronic device 110a and a server 120. The electronic device 110a is communicatively coupled to the server 120. In some other embodiments, as shown in FIG. 1, navigation system 100 includes a plurality of electronic devices 110a-110f. The electronic devices 110a-110f are, for example, portable electronic devices, wearable electronic devices, stationary electronic devices, or other various electronic devices. For example, the electronic devices 110a-110f may be smart phones of different users, but the disclosure is not limited thereto. In addition, the number of the above electronic devices is merely for illustration, and various numbers of electronic devices are within the scope of the disclosure.

As shown in FIG. 1, in some embodiments, the server 120 includes a transmission unit 122, a processing unit 124, and a storage unit 126. The processing unit 124 is electrically connected to the transmission unit 122 and the storage unit 126. The above units can be realized by a hardware or a firmware. The internal components of the server 120 are for illustrative purposes only, and various servers 120 are within the scope of the present disclosure.

In some embodiments, the electronic devices 110a-110f are connected to the server 120 via a wired network or a wireless network. For example, the electronic device 110a can be connected to the server 120 via a wired network or a wireless network by logging in an application (application; APP) installed thereon. In some embodiments, the other electronic devices 110b-110f also have the same operation.

In some embodiments, the electronic devices 110a-110f have a Global Positioning System (GPS). For example, the global positioning system of the electronic devices 110a-110f is used to record the path coordinate information of the route that the user of the electronic devices 110a-110f has traveled. In some embodiments, the path coordinate information includes a plurality of coordinates recorded by the global positioning system, the coordinates corresponding to a plurality of locations in one of the routes.

Then, the electronic devices 110a-110f transmit the path coordinate information to the server 120 through the transmission unit 122 to store the path coordinate information in the storage unit 126. As such, the storage unit 126 stores a plurality of path coordinate information.

In addition to the path coordinate information, in some embodiments, the server 120 can simultaneously take the user of the electronic device 110a~110f to walk. The time of the time (called the historical time in the latter paragraph) and the environmental conditions when the user walks in the future (referred to as the historical environmental condition in the latter paragraph). These historical times and these historical environmental conditions may be stored in the storage unit 126 of the server 120 corresponding to the corresponding path coordinate information to form a plurality of historical routes.

In other words, the storage unit 126 stores a plurality of historical routes, and each of the historical routes includes a path coordinate information, a corresponding historical time, and a corresponding historical environmental condition.

In some embodiments, historical environmental conditions may be, for example, weather conditions, traffic flow values, terrain, road type, shelter location, or other various environmental conditions. Weather conditions can be, for example, temperature, weather patterns (sunny, rainy or cloudy), rainfall, humidity, or other various weather conditions.

It should be noted that the disclosure does not limit the way in which the server 120 obtains historical time and historical environmental conditions. For example, historical time may be transmitted to the server 120 by the electronic devices 110a-110f, or provided by the central standard time, and matched with the path coordinate information. If the historical environmental condition is a historical weather condition, the historical weather condition may be directly obtained from the website of the weather bureau by the server 120 and stored in the storage unit 126 in conjunction with the corresponding path coordinate information, or firstly from the website of the meteorological bureau by the electronic device 110a~110f. After being acquired, it is transmitted to the server 120 together with the corresponding path coordinate information. If the historical environmental condition is the historical traffic value, the historical traffic value can be directly obtained from the website of the government road survey unit by the server 120 and stored in the storage unit 126 in conjunction with the corresponding path coordinate information, or first by the electronic device 110a~110f. After being obtained from the website of the government road survey unit, it is transmitted to the server 120 together with the corresponding path coordinate information. Other kinds of history Environmental conditions can be obtained through similar operational methods and will not be repeated here.

After the electronic device 110a having the navigation requirement is connected to the server 120, the user of the electronic device 110a can input the user information through the user interface provided by the application installed in the electronic device 110a (for example: User account or user age, etc., and starting conditions to provide user information and starting conditions to the server 120 via a wired or wireless network. At the same time, the server 120 can automatically obtain the instant time of the current time point as well as the immediate environmental conditions. The server 120 provides an optimal route to the electronic device 110a according to the starting point condition, the corresponding instant time, and the corresponding immediate environmental condition input by the user of the electronic device 110a. In other words, the route planning requirement of the electronic device 110a includes the starting point condition input by the user, the corresponding instant time, and the corresponding immediate environmental condition.

Similarly, the disclosure does not limit the ways and means of obtaining immediate time and immediate environmental conditions. For example, the instant time may be from the electronic device 110a or provided by the central standard time. If the immediate environmental condition is an immediate weather condition, the immediate weather condition may be obtained directly from the weather station website or other system by the server 120, or may be transmitted from the website of the weather station or other system by the electronic device 110a before being transmitted to the server 120. . Other types of real-time environmental conditions can be obtained through similar operations, and will not be described here.

FIG. 2 is a schematic diagram of a plurality of group route groups according to some embodiments of the present disclosure. First, the processing unit 124 selects, according to the starting point condition input by the user of the electronic device 110a, a plurality of pieces of history from the storage unit 126 that have the same starting point as the starting point entered by the user. route. For example, if the starting point condition of the electronic device 110a is from the starting point P1 to the point P2, the processing unit 124 will select the starting and ending point conditions from the storage unit 126 as a plurality of historical routes from the starting point P1 to the point P2. A total of 9 historical routes, as shown in Figure 2.

Since even the same user walks the same road, the path coordinate information generated by each walk may still have some errors. Therefore, in some embodiments, the processing unit 124 may use the nearest neighbor (K-nearest neighbors) algorithm or other kinds of algorithms to group the path coordinate information of the historical routes to generate a plurality of group routes, thereby generating Corresponds to the number of historical routes for each route group. Taking FIG. 2 as an example, nine historical routes are classified into a route group R1, a route group R2, and a route group R3. In other words, after the nearest neighbor algorithm is calculated, the path coordinate information of the two historical routes is relatively similar to each other, and thus is classified into the route group R1. The number of historical routes of route group R1 is 2. The path coordinate information of the other two historical routes is relatively similar to each other, and thus is classified into the route group R2. The number of historical routes of route group R2 is 2. The path coordinate information of the other five historical routes is similar to each other, and is therefore classified into the route group R3. The number of historical routes for route group R3 is 5. The number of historical routes corresponding to each route group is as follows:

It should be noted that the number of historical routes of each of the above route groups is only for illustration and is not intended to limit the content of the disclosure.

In addition to calculating the number of historical routes of each route group, the processing unit 124 calculates the average distance of each route group according to the route planning requirement and the historical route, and the average distance is used to indicate between each route group and the route planning requirement. Similarity. The calculation of the average distance is detailed as follows.

FIG. 3 is an orthogonal coordinate diagram showing one of environmental conditions and time as an axis according to some embodiments of the present disclosure. In some embodiments, processing unit 124 produces an orthogonal coordinate map in FIG. This orthogonal coordinate plot is based on ambient conditions and time. The horizontal axis is used to represent time and the vertical axis is used to represent environmental conditions. Taking Figure 3 as an example, the horizontal axis shows different time points throughout the day, such as 00:00, 02:00, 04:00, and so on. The vertical axis shows different humidity levels, for example: 10%, 20%, etc. It should be noted that time may correspond to the same or different dates. For example, the historical time of historical route B may be more than eight o'clock in the morning of a certain day, while the historical time of historical route G may be more than four o'clock in the afternoon of the same day or another day.

The two axes of this orthogonal coordinate map further contain corresponding coordinate scales. The coordinate scales of the horizontal axis correspond to different times. The coordinate scales of the vertical axis correspond to different humidity levels, respectively. For example, time 02:00 corresponds to coordinate scale 1 and time 04:00 corresponds to coordinate scale 2. The humidity 10% corresponds to the coordinate scale 1 and the humidity 20% corresponds to the coordinate scale 2.

It should be particularly noted that although the orthogonal coordinate graph in FIG. 3 includes two dimensions (environmental conditions and time), in some other embodiments, when the environmental conditions are plural, the orthogonal coordinate graph may include three Dimensions or more Three dimensions. For example, if weather conditions and road patterns are considered at the same time. Two environmental conditions (weather conditions and road type) plus time will form an orthogonal coordinate map with three dimensions.

As shown in FIG. 3, the processing unit 124 will mark the route planning requirement A in the orthogonal coordinate map according to the instantaneous time of the route planning requirement A and the immediate environmental conditions to generate corresponding coordinates. For example, the immediate time for route planning requirement A is 08:01 in the morning, and its immediate environmental condition is 75.4% humidity. Therefore, its corresponding coordinates are (4.03, 7.54). The selected 9 historical routes B~J are also marked in the orthogonal coordinate map according to their respective historical time and historical environmental conditions to generate their respective coordinates.

Next, the processing unit 124 will calculate the linear distance between the coordinates of each historical route and the coordinates of the route planning requirement A. In the orthogonal coordinate map, it is assumed that the coordinates of the route planning requirement A are (X1, Y1) and the coordinates of the historical route B are (X2, Y2). The linear distance d1 between the route planning requirement A and the historical route B on the orthogonal coordinate map can be calculated by the following formula (1):

The straight line distance between other historical routes C~J and route planning demand A can also be calculated in the same way. The straight line distance between the historical route B~J, the corresponding route group and the route planning demand A is as follows:

Next, the processing unit 124 will further average the linear distances belonging to each route group to calculate the average distances of the route group R1, the route group R2, and the route group R3, respectively. The average distance can be used to represent the average similarity between each route group and route planning demand A. Specifically, the smaller the average distance of a route group, the higher the average similarity between the route group and the route planning demand A. The average distance of each route group is shown in Table 3 below:

In Table 3, the average distance between the route group R1 and the route planning demand A is the smallest, and the average distance between the route group R3 and the route planning demand A is the largest. In other words, the average similarity between the route group R1 and the route planning demand A is the highest, and the average similarity between the route group R3 and the route planning demand A is the lowest. That is to say, the time and environmental conditions of the route group R1 are similar to the time and environmental conditions of the route planning demand A.

After the number of historical routes and the average distance of each route group are calculated, the processing unit 124 calculates the historical route number and the average distance of each route group by using the calculation model to generate a calculation result value of each route group. The calculation model is as follows (2): F = α × log( C )- β ×log( S )...Formula (2)

C is the number of historical routes corresponding to one of the route groups, S is the average distance corresponding to the route group, α and β are respectively a parameter value, and F is a calculation result value corresponding to the route group.

In the calculation model, the number of historical routes (C) and the average distance (S) are considered at the same time. For example, if the number of historical routes of the two route groups is the same, if the average distance of one of the route groups is small, the calculation result value of the route group will be larger. Conversely, if the average distance between the two route groups is the same, if the number of historical routes of one of the route groups is large, the calculation result value of the route group will be larger. That is to say, when the calculation result value of the route group is larger, the route group may be a route that more users have traveled in the past, or the conditions (time and environmental conditions) of the historical route in the route group and The route planning needs are relatively similar.

The following describes how to generate the parameter value α and the parameter value β. First, the historical route B is first regarded as the best route, and the other historical routes C~F are taken as the historical route of the best route and substituted into the above calculation model. Next, the historical route C is regarded as the best route, and other historical routes B, D~F are taken as the historical route of the best route and substituted into the above calculation model, and so on. Finally, the cross-validation method is used to obtain the parameter value α and the parameter value β.

If the calculated parameter value α is equal to 2 and the parameter value β is equal to 1, the calculation result values calculated by the respective route groups according to the above formula (2) are as follows:

In Table 4, the calculation result value of the route group R1 is the largest. Therefore, the processing unit 124 selects the route group R1 as the best route and provides the route group R1 to the electronic device 110a through the transmission unit 122. Additionally, in other embodiments, the server 120 provides a plurality of optimal routes to the electronic device 110a. Taking the above table 4 as an example, the calculation result value of the route group R1 is the largest, and the calculation result value of the route group R3 is the second largest. Therefore, the processing unit 124 selects the route group R1 and the route group R3 as the best route, and provides the route group R1 and the route group R3 to the electronic device 110a through the transmission unit 122.

In some embodiments, the optimal route can be marked on the electronic map of the electronic device 110a. When the optimal route is plural, different optimal routes can be marked in different colors for the user to select.

According to the above, since the number of historical routes and the average distance (similarity) of each route group are simultaneously considered in the calculation model, the best route generated will be a route more suitable for the user.

Figure 4 is a diagram of some embodiments according to the present disclosure. A flowchart of the navigation method 400. In some embodiments, the navigation method 400 can be applied to the navigation system 100 in FIG. 1, but the disclosure is not limited thereto. The navigation method 400 includes at least steps S402 to S416.

In step S402, the transmission unit 122 of the server 120 receives a route planning requirement. The route planning requirements include a set-point condition, an immediate time, and an immediate environmental condition.

In step S404, the processing unit 124 of the server 120 selects, from the storage unit 126, a historical route that meets the start and end point conditions of the route planning requirement. Each historical route contains a path coordinate information, a historical time, and a historical environmental condition.

In step S406, the processing unit 124 of the server 120 classifies the historical routes according to the path coordinate information of each historical route to generate a plurality of group routes. In some embodiments, processing unit 124 utilizes a nearest neighbor algorithm to group the path coordinate information to correspondingly classify the historical routes.

In step S408, the processing unit 124 of the server 120 marks the historical time and historical environmental conditions of each historical route, and the instantaneous time and immediate environmental conditions of the route planning requirement, respectively, which are orthogonal to one of the environmental conditions and the time axis. Coordinate maps to generate coordinates for each historical route and route planning needs.

In step S410, the processing unit 124 of the server 120 calculates the linear distance between the coordinates of each historical route and the coordinates of the route planning requirements. The calculation method of the straight line distance has been described in detail in the above embodiments, and details are not described herein again.

In step S412, the processing unit 124 of the server 120 averages the linear distances belonging to each route group to obtain an average distance of each route group.

In step S414, the processing unit 124 of the server 120 calculates the historical route number and the average distance of each route group according to the calculation model to generate a calculation result value of each route group. The calculation method of the calculation result value has been described in detail in the above embodiment, and details are not described herein again.

In step S416, the processing unit 124 of the server 120 takes the route group corresponding to the maximum calculation result value as at least one optimal route. Next, the transmission unit 122 of the server 120 will provide this optimal route to the electronic device 110a.

The details of the navigation method 400 are described in the foregoing description of the embodiments, and will not be described again.

In addition, it should be particularly noted that the above examples include sequential steps, but the steps are not necessarily performed in the order shown. Performing these steps in a different order is within the scope of this case. In addition, within the spirit and scope of the embodiments of the present disclosure, the steps may be added, replaced, changed, and/or omitted as appropriate.

In some embodiments, the navigation method disclosed above can be implemented as a computer program. The implemented computer program can be stored in a computer readable recording medium, and the computer can read the recorded medium and execute the disclosed navigation method. The computer readable recording medium can be read-only memory, flash memory, floppy disk, hard disk, optical disk, flash drive, tape, network accessible database or familiar with the art. Functional computer readable record media.

In summary, by applying the above embodiment, the optimal route is generated according to historical routes of other users in the past, and the number of historical routes of each route group and the average distance between each route group and the route planning requirement ( Similarity) is considered at the same time, thereby producing an optimal route that is more suitable for the user.

The present disclosure has been disclosed in the above embodiments, and is not intended to limit the disclosure. Any one of ordinary skill in the art can make various changes and refinements without departing from the spirit and scope of the disclosure. The scope of protection is subject to the definition of the scope of the patent application.

400‧‧‧ navigation method

S402~S416‧‧‧Steps

Claims (12)

A navigation method includes: receiving a route planning requirement, where the route planning requirement includes a point-and-point condition, an immediate time, and an immediate environmental condition; selecting a plurality of historical routes according to the starting and ending point conditions, each of the historical routes including a path coordinate Information, a historical time, and a historical environmental condition; classifying the historical routes according to the path coordinate information to generate a plurality of group route groups; the historical time of the historical route and the historical environmental conditions, and the route planning requirements The instant time and the real-time environmental condition are marked on an orthogonal coordinate map which is one of an environmental condition and a time axis respectively, to generate coordinates corresponding to each of the historical route and the route planning requirement; calculating coordinates of each of the historical routes a straight line distance between the coordinates of the route planning demand; according to each of the route groups, the linear distances are averaged to obtain an average distance of each route group; a historical route to each route group according to a calculation model Calculating the quantity and the average distance to generate a calculated result value of each route group; The route to the maximum value of the calculation result as the corresponding group of at least one optimal route. The navigation method of claim 1, wherein the calculation model is: F = α × log( C ) - β × log( S ), where F is a calculation result value corresponding to one of the route groups, C is the number of historical routes corresponding to the one of the route groups, S is the average distance corresponding to the one of the route groups, and α and β are respectively a parameter value. The navigation method of claim 2, wherein obtaining the parameter values comprises: substituting the historical routes into the calculation model, and obtaining the parameter values by a cross-validation method. The navigation method of claim 1, wherein the historical routes are classified into the group of route groups according to a nearest neighbor algorithm. A navigation system includes: a transmission unit for receiving a route planning requirement, the route planning requirement includes a return-to-point condition, an immediate time, and an immediate environmental condition; and a storage unit configured to store a plurality of historical routes, each of which The historical route includes a path coordinate information, a historical time, and a historical environmental condition; and a processing unit electrically connected to the transmission unit and the storage unit, the processing unit is configured to select the historical routes that meet the conditions of the origin and destination The processing unit is further configured to classify the selected historical routes according to the path coordinate information to generate a plurality of group route groups, and the processing unit is further configured to use the historical time and the historical environment of each of the selected historical routes. Conditions, and the immediate time of the route planning requirement and the immediate environmental conditions are indicated in Correlating coordinate graphs with environmental conditions and time as axes respectively to generate coordinates corresponding to each selected historical route and the route planning requirements, and calculating coordinates of each selected historical route and the route planning requirements The straight line distance between the coordinates, the processing unit is further configured to average the linear distances according to each of the route groups to obtain an average distance of each route group, and the processing unit is further configured to use the calculation model for each of the route groups. The number of historical routes of the group and the average distance are calculated to generate a calculated result value of each route group, and the route group corresponding to the maximum calculated result value is used as at least one optimal route. The navigation system of claim 5, wherein the calculation model is: F = α × log( C ) - β × log( S ), where F is a calculation result value corresponding to one of the route groups, C is the number of historical routes corresponding to the one of the route groups, S is the average distance corresponding to the one of the route groups, and α and β are respectively a parameter value. The navigation system of claim 6, wherein the processing unit is further configured to substitute the selected historical routes into the calculation model, and obtain the parameter values by using a cross-validation method. The navigation system of claim 5, wherein the processing unit is further configured to classify the selected historical routes into the group of route groups according to a nearest neighbor algorithm. A computer readable recording medium recording a program for causing a computer to perform the following steps: receiving a route planning requirement, the route planning requirement including a point-and-point condition, an instant time, and an immediate environmental condition; Selecting a plurality of historical routes according to the starting and ending conditions, each of the historical routes includes a path coordinate information, a historical time, and a historical environmental condition; and classifying the historical routes according to the path coordinate information to generate a plurality of group routes; The historical time of the historical route and the historical environmental condition, and the immediate time of the route planning requirement and the immediate environmental condition are indicated by orthogonal coordinate maps respectively on an environmental condition and time axis to generate corresponding a coordinate of the historical route and the route planning demand; calculating a straight line distance between the coordinates of each of the historical routes and the coordinates of the route planning demand; and averaging the linear distances according to each of the route groups to obtain each of the route groups An average distance; a historical route to each of the route groups based on a calculation model and The average distance calculation, the calculation result to generate a value for each route group; and the route of the group to the maximum value corresponding to the calculation result as the at least one optimal route. The recording medium of claim 9, wherein the calculation model is: F = α × log( C ) - β × log( S ), where F is a calculation result value corresponding to one of the route groups, C is the number of historical routes corresponding to the one of the route groups, S is the average distance corresponding to the one of the route groups, and α and β are respectively a parameter value. The recording medium of claim 10, wherein obtaining the parameter values comprises: substituting the historical routes into the calculation model, and obtaining the parameter values by a cross-validation method. The recording medium of claim 9, wherein the historical routes are classified into the group of route groups according to a nearest neighbor algorithm.