KR101042811B1 - Method for planning path in navigation system - Google Patents

Abstract

The present invention relates to a route determination method of a navigation system, comprising: a first process of generating a plurality of route candidates from the origin to a destination in response to a route request from a predetermined origin to a destination; A second process of accumulating the average driving times of all links included in each of the path candidates using the traffic statistics information in the elapsed time, and calculating a predicted driving time of the corresponding path candidate group; and the prediction calculated in the second process And a third process of determining a route candidate group having a minimum driving time as an optimal route. Accordingly, the present invention has an advantage of minimizing time and logistics costs due to traffic congestion by efficiently using repeated statistical information on traffic congestion.

Navigation system, route determination, predicted driving time, time-varying weighted fusion technique, TVWF

Description

METHOD FOR PLANNING PATH IN NAVIGATION SYSTEM}             

1 is an exemplary view of the configuration of a navigation system according to an embodiment of the present invention;

2 is a diagram illustrating a path determination process according to an embodiment of the present invention;

3 is a diagram illustrating a path determination algorithm parameter according to an embodiment of the present invention;

4 is a diagram illustrating a processing procedure in a server for determining an optimal path according to an embodiment of the present invention;

5 is a diagram illustrating a processing procedure in a terminal for determining an optimal path according to an embodiment of the present invention.

The present invention relates to a route determination method of a navigation system, and more particularly, to an optimal route determination method using statistical information.

Typically, the navigation system determines the optimal route from the origin to the destination at the request of the user and provides the result to the user. To this end, in the prior art, a navigation server (also known as an information center) determines a route using starting and destination information of a navigation vehicle and current traffic information at the time of departure. However, when performing the route guidance from the departure point to the arrival point using the traffic information at the departure point, the traffic information after the lapse of the driving time cannot be taken into consideration, and therefore, the dynamic route guidance cannot be performed, and due to the possibility of changing traffic conditions during the driving. The disadvantage is that the accuracy of the estimated arrival time is poor.

Conventionally, in order to make up for the shortcomings, a route planning and driving change are periodically used by using updated traffic information such as accidents and weather. That is, a method of performing route planning of a driving vehicle by using updated traffic information at each request point by manual triggering of a client or automatic triggering of a server for each node or time. Was used. As such, when route planning is performed using updated traffic information at the time required for service requests by time or node, it is possible to cope with traffic congestion situations such as accidents or construction during driving in a relatively real time. However, there is an inefficiency in data traffic increase due to an increase in computation amount and real-time traffic information transmission, and it is highly likely that the route change determination at the triggering time for each event will not be effective. For example, if some of the routes derived by the initial route plan pass through congested areas due to surrounding traffic after a period of time, the route calculated by the new demand will avoid an increase in travel time due to congestion in the area already entered. Can't. Therefore, the route planning technique which can bring about the delay in the whole driving time is inefficient in terms of the shortest time required compared to the route planning technique which can avoid and predict the congested area in advance.

On the other hand, the conventional congestion route search method for estimating congestion after a running time using traffic statistics information and avoiding it has not been able to effectively use traffic information and past statistical information at a more reliable start time. In addition, the traffic information search result using the congestion avoidance route search method may be referred to as a local route search algorithm for avoiding a congestion point, rather than a route plan for the entire search space between a departure point and a destination. Therefore, there is a disadvantage that the range of utilization of the search results is narrow.

As such, researches on a method of guiding a route that can travel in the shortest time at the time of a route request are being conducted, rather than simply providing a route guidance service for unknown routes. For example, a study is being conducted on a route guidance method for avoiding a congestion section when a user requests a route.

The present invention has been made to solve the above shortcomings, and the first objective of the present invention is to more efficiently determine the optimal route between the starting point and the destination using traffic statistics information such as section, season, day of the week, time zone, weather, etc. in the navigation system. To provide a method that can be performed by.

The second object of the present invention is to estimate the driving time of the entire route by estimating the traffic statistics information after the estimated driving time has elapsed for each node included in the route from the starting point to the destination as well as the current traffic information, and determining the optimal route using the same. By providing a way to improve the path guidance performance.

The third object of the present invention is to improve the reliability of the predicted time by applying Time-Varying Weighted Fusion (TVWF) to the traffic information data at the initial route planning time and past traffic statistics data on the link. In providing a method of determination.

In order to achieve the above object, a route determination method of a navigation system provided by the present invention includes a first process of generating a plurality of route candidate groups from a departure point to a destination in response to a route request from a predetermined departure point to a destination; A second process of accumulating the average driving times of all links included in each of the route candidates using the traffic statistics information at the predicted elapsed time predicted to be calculated, and calculating the predicted driving time of the corresponding route candidate group; And a third process of determining the path candidate group having the smallest predicted driving time as the optimal path.                     

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In this case, detailed descriptions of well-known functions and configurations that may unnecessarily obscure the subject matter of the present invention will be omitted.

1 is a diagram illustrating a configuration of a navigation system according to an embodiment of the present invention. Referring to FIG. 1, a navigation system according to an embodiment of the present invention includes a telematics terminal 110, a telematics server 120, and an external server 130.

Telematics (Telematics) is a compound word of telecommunications and information (transformation) and transmits and receives location information in a car-centric environment based on the global positioning system (GPS) using wireless voice data communication and satellites Refers to a technology that can provide various application services. The telematics terminal 110 and the telematics server 120 are devices implemented for practical use of such telematics technology.

The telematics terminal 110 includes a route indicating device for indicating a driving direction by using route data obtained from a wireless transmitting / receiving unit, a positioning unit, and an information center, and is typically mounted on a mobile object to serve as an interface with a user.

The telematics server 120 is referred to as an 'information center', and communicates with the telematics terminal 110 and the external server 130 when requesting a service, and by route planning parameters (eg, departure time, departure point, destination, request waypoint, etc.). Predict the path in the shortest time.

The external server 130 receives a real-time information from a police station that can provide real-time traffic information or a weather center that provides weather information, and provides a traffic statistics information database for providing traffic statistics information to the telematics server 120. Save Data Base). In addition, the external server 130 obtains traffic statistics information for each section from the probe car 140 that operates a specific section.

An example of such an operation process of the navigation system of the present invention is illustrated in FIG. 2. 2 is a diagram illustrating a path determination process according to an embodiment of the present invention. Referring to FIG. 2, first, the telematics terminal 110 requests a path from the telematics server 120 (S205). At this time, the telematics terminal 110 transmits current and destination information to the telematics server 120. In addition, the telematics terminal 110 calculates location information necessary for route determination using sensors such as a GPS receiver, a gyro, an accelerometer, and a vehicle speedometer mounted on the telematics terminal 110, and transmits the result to the telematics server 120. do.

Then, the telematics server 120 generates a route candidate group using basic route planning parameters such as the location information of the telematics terminal 110 transmitted from the telematics terminal 110 and a starting point, an arrival point, and a departure time (S210). Then, after receiving traffic information (including traffic statistics information) and weather information from the external server 130 (S215), the estimated travel time of the route candidate groups is calculated using the traffic information and the weather information (S220). At this time, the telematics server 120 calculates the predicted travel time of the route candidate groups by using the traffic statistics information and fusing time-varying weights for improving the required time prediction. As described above, it is common for the telematics server 120 to calculate the predicted driving time of the route candidate groups by fusion of time-varying weights, in the case of a metropolitan city where traffic congestion is severe and the need for route guidance increases. Historical traffic statistics are usually due to the nature of repetition. In other words, by accumulating and storing such reliable information of the past to effectively use it from the initial route plan, it is possible to provide improved route guidance in the current road traffic situation.

In addition, the telematics server 120 derives the shortest path as a result (S225) and provides the result to the telematics terminal 110 (S230). At this time, the external server 130 receives continuous traffic information from the probe car 140 and continuously updates the traffic statistics information database.

The telematics terminal 110 then receives the shortest path and provides the driver with the information. To this end, the route market value of the telematics terminal 110 may be implemented to be displayed visually (eg, a map, etc.) or output as voice information by using a geographic information system (GIS).

3 is a diagram illustrating a path determination algorithm parameter according to an embodiment of the present invention. Referring to FIG. 3, path determination algorithm parameters stored in the telematics server 120 to determine an optimal path according to an embodiment of the present invention are as follows.

)(예컨대, 각 구간별 예측교통정보)과, 출발 시점시의 노드별 교통정보(

)(예컨대, 실시간 교통정보)와, 상기 두 데이터의 융합을 위한 시변 가중치 정보(

)와, 구간별 소요시간 계산을 위한 거리정보(

)를 포함한다. 이 때, 상기 거리정보(

)는 GIS 지리정보 또는 실측정보이다. 도 3에서 'SP'는 출발지(SP: Start Point)를 나타내고, 'A','D' 및 'G'는 도착지(DP: Destination Point) 까지 경유하게 되는 노드 점을 나타낸다. In other words, the path determination algorithm parameter is a velocity information matrix (

) (For example, predicted traffic information for each section) and traffic information for each node at the time of departure (

(E.g., real-time traffic information) and time-varying weight information for fusion of the two data (

), And distance information for calculating the time required for each section (

). At this time, the distance information (

) Is GIS geographic information or actual information. In FIG. 3, 'SP' represents a start point (SP), and 'A', 'D' and 'G' represent node points passing through to a destination point (DP).

Meanwhile, FIG. 4 is a diagram illustrating a processing process in a server for determining an optimal path according to an embodiment of the present invention. Referring to Figures 3 and 4 will be described the path determination process in the server according to an embodiment of the present invention.

When a path is requested from the terminal to the destination (DP) to the destination (DP) (S302), the server first checks information such as whether the user is registered, validity of the current location information, origin, destination, and departure time, and provides a service to the user. Authentication is performed (S304).

If it is determined that the service is not possible as a result of the authentication, the server provides a service unavailable guide message to the corresponding user (S336). At this time, it is preferable to use at least one of a visible or audible method for providing a service unavailable guide message.

As a result, if it is determined that the service is possible (S306), the server generates 'I' path candidate groups from the source SP to the destination DP (S308). The candidate group generated at this time may include all paths connecting the terminal nodes representing the starting point SP and the destination DP, and are reduced to a set of geographic paths which are adjacent to the shortest path around the shortest path. May be generated. In this case, parameters for determining an optimal path for each candidate group are as illustrated in FIG. 3.                     

Then, the prediction driving time calculation processes S310 to S330 of the respective path candidate groups are performed.

That is, after initializing an algorithm variable for each path candidate group using a parameter of the type illustrated in FIG. 3, 'I' path candidate groups are sequentially selected one by one (S312) and the path candidate groups using statistical information. The average travel time for each section on the link included in the calculation is calculated and accumulated (S314 to S324).

At this time, the initial value of the travel time at the start point is set to t ₀ .

The average driving time (eg, driving prediction time) of the link using the statistical information calculated in step S318 may be implemented as shown in Equation 1 using the prediction average speed information for each section.

)는 수학식 2와 같이 미래 예측 시간의 값과 출발시점에서의 값의 가중 함수로 주어진다.
At this time, the predicted average speed in the k-th section (

) Is given as a weighting function of the value of the future prediction time and the value at the starting point as shown in Equation 2.

'과 '

'는 도 3에 예시된 바와 같이 '통계자료에 의한 속도 정보 행렬'과 '출발 시점시의 노드별 교통정보'를 각각 나타낸다.In equation (2)

'And'

3 denotes a 'speed information matrix based on statistical data' and 'traffic information for each node at the time of departure', respectively, as illustrated in FIG. 3.

The cumulative result of Equation 1 in step S320 is equal to Equation 3.

In this case, Equation 3 is a predicted driving time for a specific route candidate group.

The processes S314 to S322 are repeatedly performed on the 'I' path candidate groups while storing the estimated driving time for each path candidate group (S326).

When the predicted driving time for all of the 'I' path candidate groups generated in step S308 is calculated as described above, the path candidate group having the shortest predicted driving time among the path candidate groups is selected as the optimal driving path (S332). The optimal driving route is provided to the terminal (S334).                     

The variable 'i' used in the above process is a variable for sequentially selecting 'I' path candidate groups one by one, and 'k' is a variable for selecting one link included in the selected path candidate group one by one.

Equation 4 illustrates a performance index function for obtaining the shortest time path among 'I' path candidate groups. That is, equation (4) represents the minimum time lapse (t_ _STP) to fuse the statistical information and the real-time information TVWF prediction.

)는 통계정보와 출발시의 교통정보의 융합치로 획득되며, 이와 같이 미래에 주행할 것으로 기대되는 경로상에서의 예측 평균속도를 시간적으로 변하는 가중치 정보(w_k)로서, 융합, 연산하여 주행시간을 예측하는 것이 기존의 경로 계획 기법과는 상이한 본 발명의 차별적 개념인 것이다. 데이터 융합을 위한 시변 가중치(w_k)는 서비스 요청 일시, 전체 경로의 거리, 통계적 구간 속도와 실시간 교통정보와의 차이량 등 여러 요소에 따라 다르게 실시될 수 있다. 상기 시변 가중치는 시간이 경과할 수록 실시간의 정보의 오차가 커지는 것을 고려하여 단조 증가열(strictly increasing sequence)로 표현할 수 있으므로 도 3에 예시된 바와 같이 수학식 5를 이용하여 구현하는 것이 바람직하다.
In Equation 4, the average speed in the driving section for predicting the elapsed time (

) Is obtained as a fusion value of statistical information and traffic information at the time of departure.In this way, weight information (w _k ) that changes temporally the predicted average speed on a route expected to be driven in the future is converged and calculated to calculate the driving time. Predicting is a differential concept of the present invention that is different from existing path planning techniques. The time-varying weight w _k for data fusion may be implemented differently depending on various factors such as the date and time of service request, the distance of the entire route, the amount of difference between the statistical section speed and the real-time traffic information. Since the time-varying weight may be represented as a monotonically increasing sequence in consideration of the error of information in real time as time passes, it is preferable to implement it using Equation 5 as illustrated in FIG. 3.

Meanwhile, FIG. 5 is a diagram illustrating a processing procedure in a terminal for determining an optimal path according to an embodiment of the present invention.

Referring to FIG. 5, in order to determine an optimal route according to an embodiment of the present disclosure, when a terminal requests a route from a predetermined starting point (for example, the current location) to a destination by the user (S402), the terminal may determine the starting point. The location information is detected (S404). The current location information and the destination information are transmitted to the server (S406). When the route information is received from the server (S408), the route information is output (S410). At this time, it is preferable that the output data is at least one of visible or audible.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments. Therefore, the scope of the present invention should not be defined by the described embodiments, but should be determined by the equivalent of claims and claims.

As described above, the route determination method of the present invention reliably accumulates and stores past traffic statistics according to various conditions in a large city or a frequent congestion area where traffic congestion is severe and a necessity of route guidance is increasing, By using it, the improved route guidance is possible even in the current road traffic situation. That is, the present invention has an advantage of minimizing time and logistics costs due to traffic congestion by efficiently using repeated statistical information on traffic congestion.

Claims (13)

In the path determination method of the server in the navigation system, A first process of generating a plurality of route candidate groups from the origin to the destination in response to a route request from a predetermined origin to a destination; The average driving time of the links included in each of the path candidate groups is calculated by fusing traffic statistics information at an elapsed time predicted to pass due to driving and traffic information at the time of driving departure using time varying weights. A second process of accumulating the calculated average driving time and calculating a predicted driving time of the corresponding route candidate group; And a third process of determining, as an optimal path, a route candidate group having the smallest predicted running time calculated in the second process among the plurality of route candidate groups. The method of claim 1, wherein the first process is The route determination method of the server in the navigation system, characterized in that for generating a route candidate group all routes connecting the destination from the source. The method of claim 1, wherein the first process is The method for determining a path of a server in a navigation system, characterized in that only a predetermined path geographically adjacent to the shortest path among all the paths connecting the destination to the destination is generated. delete delete The method of claim 1, wherein the time-varying weight is The method of determining a route of a server in a navigation system, characterized in that it is set differently by environmental information including a service request date and time, a distance of an entire route, a statistical section speed, and an amount of difference between real-time traffic information. The time-varying weight value corresponding to the 'k' section in the 'i' candidate path having 'n' sections between the starting point and the destination,

)

Path setting method of the server in the navigation system, characterized in that set by. In the navigation information providing method of the terminal in the navigation system, Requesting the server for route information from a predetermined origin to a destination; Receiving route information including an optimal route calculated using the traffic statistics information from the server; Outputting the received path information; The optimal path is a time-varying weight that the server generates a plurality of route candidate groups from the starting point to the destination, and changes the traffic statistics information at the elapsed time predicted to elapse due to the driving and the traffic information at the time of driving departure in time. Calculate the average travel time of the links included in each of the path candidate groups, accumulate the calculated average travel time, calculate the predicted travel time of the corresponding path candidate group, and calculate the calculation among the plurality of path candidate groups. The method of providing a route in a navigation system, characterized in that the route candidate group having the minimum predicted driving time is determined as the optimal route. The method of claim 8, wherein the path candidate group is generated. The route providing method of the terminal in the navigation system, characterized in that for generating all the routes connecting the destination from the starting point to the path candidate group. The method of claim 8, wherein the path candidate group is generated. Method of providing a path in the navigation system, characterized in that for generating a path candidate group only a predetermined path geographically adjacent to the shortest path among all the paths connecting the destination from the starting point. delete 9. The method of claim 8 wherein the time varying weight is The method of providing a route in a navigation system, characterized in that differently set by the environment information including the service request date and time, the distance of the entire route, the statistical section speed and the amount of difference between the real-time traffic information. The method of claim 8, wherein the time-varying weight corresponding to the 'k' section in the 'i' candidate path having 'n' sections between the starting point and the destination.

)

The path providing method of the terminal in the navigation system, characterized in that set by.

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