JP2013045343A - Navigation system, navigation device, and operation method of navigation system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To offer a technique capable of improving accuracy of an information to be conveyed to the user in a subsequent vehicle.SOLUTION: A navigation system can detect a first congestion start point (first congestion end point) on the basis of travel history information TRKof an information offering vehicle Atraveling a traffic lane, and the system includes: a congestion point detection part capable of detecting a second congestion start point (second congestion end point) on the basis of travel history information TRKof an information offering vehicle Atraveling after the information offering vehicle A; a congestion situation predicting part for calculating the amount of change in the congestion start point by using the first congestion start point and second congestion start point and for acquiring a predicted congestion start point of which the congestion start point temporally later than the second congestion start point is predicted on the basis of the amount of change; and information offering means for offering the information by using the predicted congestion start point (predicted congestion end point) in the vehicle subsequent to the information offering vehicle A.

Description

  The present invention relates to a traffic information acquisition technique.

  Generally, means for transmitting traffic jam information to vehicles such as automobiles include means such as VICS and beacons. However, with these information transmission means, traffic jam information cannot be obtained in areas where sensors are not installed, and even if traffic jam information is obtained in areas where sensors are installed, the obtained traffic jam information is Since it is information on a limited range on the map, in order to obtain information on a desired range outside the range, traffic information in the desired range is obtained unless the traffic information in the desired range is received. The real-time nature of information was bad.

  Thus, in order to improve the real-time property of information, means for obtaining information through communication between vehicles has been proposed.

  For example, Patent Document 1 proposes a means for transmitting information by communicating with front and rear vehicles.

  Patent Document 2 proposes a means for transmitting traffic information to a vehicle traveling on the opposite lane and transmitting traffic information to a subsequent vehicle traveling behind the vehicle.

JP 2007-148901 A JP 2007-147307 A

  However, in the technology of Patent Document 1, traffic congestion information in the traveling direction can be obtained. However, when the traffic volume is low and the vehicle is not traveling within the communication range, or the front and rear vehicles are separated by an intersection or a signal wait When the distance between the vehicles is out of the communication distance, the traffic jam information is not transmitted to the rear vehicle.

  On the other hand, according to the technique of Patent Document 2, the traffic jam information can be transmitted to the following vehicle even when the vehicles are separated from each other. However, in Patent Document 2, the travel history information is received from the vehicle in the traffic jam. Thus, since only the travel history information is transmitted to the following vehicle in the traffic lane, the accuracy of the information transmitted to the user in the subsequent vehicle is low.

  Accordingly, an object of the present invention is to provide a technique capable of improving the accuracy of information transmitted to the user in the following vehicle.

  The navigation system according to the present invention can detect the first traffic state based on the first traveling history information of the first vehicle traveling in the lane, and the second traveling of the second vehicle traveling after the first vehicle. A change amount of the traffic state in the lane is calculated using detection means capable of detecting the second traffic state based on the history information, the first traffic state and the second traffic state, and based on the change amount Providing a prediction means for obtaining a predicted traffic state in which the traffic state in the lane after the second traffic state is predicted in time, and providing information using the predicted traffic state in a succeeding vehicle of the second vehicle Information providing means.

  The navigation device according to the present invention includes communication means capable of communicating with an oncoming vehicle traveling in an oncoming lane, and first travel history information acquired from the first oncoming vehicle traveling on the oncoming lane using the communication means. And detecting the second traffic state based on the second travel history information acquired from the second oncoming vehicle traveling after the first oncoming vehicle using the communication means. The amount of change in the traffic state in the opposite lane is calculated using the detection means that performs the first traffic state and the second traffic state, and based on the amount of change, the amount of change in time is greater than that in the second traffic state. Prediction means for obtaining a predicted traffic state obtained by predicting a traffic state in the subsequent oncoming lane, and the communication means transmits the predicted traffic state to a succeeding vehicle of the second oncoming vehicle.

  In addition, the operation method of the navigation system according to the present invention includes: a) detecting a first traffic state based on first traveling history information of a first vehicle traveling in a lane; and b) after the first vehicle. Detecting a second traffic state based on second travel history information of the second vehicle traveling; and c) using the first traffic state and the second traffic state to determine the amount of change in the traffic state in the lane. Calculating a predicted traffic state in which a traffic state in the lane after the second traffic state is predicted based on the amount of change, and d) in a succeeding vehicle of the second vehicle, Providing information using the predicted traffic state.

  According to the present invention, it is possible to improve the accuracy of information transmitted to the user in the following vehicle.

It is a figure which shows the structure of the navigation apparatus which concerns on embodiment. It is a figure which shows the content of driving history information. It is the schematic of the navigation system using the navigation apparatus concerning this embodiment. It is a flowchart which shows operation | movement of the navigation apparatus at the time of acquiring traffic jam start point information. It is a figure which shows the travel history information acquired from an information provision vehicle, and the travel history information acquired from an information provision vehicle. It is a figure which illustrates the distance difference on a driving | running route. It is a flowchart which shows operation | movement of the navigation apparatus at the time of acquiring traffic jam end point information. It is a figure which shows the exception pattern of the driving | running route of an information provision vehicle. It is a figure which shows the exception pattern of the driving | running route of an information collection vehicle.

  Hereinafter, embodiments will be described with reference to the drawings.

<1. Embodiment>
[1-1. Configuration and Overview]
FIG. 1 is a diagram illustrating a configuration of a navigation device 1 according to the embodiment. FIG. 2 is a diagram showing the contents of the travel history information.

  As shown in FIG. 1, the navigation device 1 performs a display unit 11 for displaying images such as a map, a route, and traffic information, a control unit 12 that performs overall control of the navigation device 1, and performs overall control. And a control program storage unit 13 storing the control program.

  The display unit 11 functions as information providing means for providing information to the user. Note that voice information means (not shown) that provides information to the user by voice may be included in the information provision means.

  The control program storage unit 13 is composed of, for example, a ROM. The control program storage unit 13 includes a travel history information acquisition program 131 for acquiring and storing travel information, a traffic congestion point detection program 132 for detecting a traffic jam start point and end point from the travel history information, and , A traffic jam condition determination program 133 for determining the traffic jam situation from the traffic jam spot information, and a traffic jam situation prediction program 134 for calculating a traffic jam start point and a traffic jam end point at the current time from the traffic jam situation information. .

  These programs 131 to 134 are read by the control unit 12 and executed by the central processing unit (CPU) 121 of the control unit 12.

  For example, when the traveling history information acquisition program 131 is executed by the CPU 121, the traveling history information acquisition unit 122 is functionally realized in the control unit 12. The travel history information acquisition unit 122 acquires travel history information using detection results of the host vehicle position detection unit 14 and the host vehicle moving speed detection unit 15 described later. As shown in FIG. 2, the travel history information is information including the time, the vehicle position information at that time, and the moving speed, and is obtained at predetermined intervals (for example, 2 seconds).

  Further, for example, when the traffic congestion point detection program 132 is executed by the CPU 121, the traffic congestion point detection unit (detection means) 123 is functionally realized in the control unit 12. The traffic jam point detection unit 123 detects a traffic jam start point and a traffic jam end point based on the travel history information.

  For example, when the traffic situation determination program 133 is executed by the CPU 121, the traffic situation determination section 124 is functionally realized in the control unit 12. The traffic congestion status determination unit 124 determines and calculates the traffic congestion status based on information (congestion point information) regarding the start point and end point of the traffic jam.

  Further, for example, when the traffic jam situation prediction program 134 is executed by the CPU 121, the traffic jam situation prediction unit (prediction unit) 125 is functionally realized in the control unit 12. The traffic jam situation prediction unit 125 predicts and calculates a traffic jam start point and a traffic jam end point at the current time from the traffic jam point information.

  Further, the navigation device 1 includes a host vehicle position detection unit 14, a host vehicle moving speed detection unit 15, an inter-vehicle communication control unit 16, a map data storage unit 17, and a travel history information storage unit 18. .

  The own vehicle position detection unit 14 includes a GPS (Global Positioning System) device, a yaw rate sensor, an acceleration sensor, and the like, and detects information on the position of the own vehicle (own vehicle position) (also referred to as “own vehicle position information”). . The own vehicle position detection unit 14 detects, for example, a position on absolute coordinates represented by longitude and latitude as own vehicle position information.

  The own vehicle moving speed detection unit 15 acquires a vehicle speed pulse corresponding to the rotational speed of the wheel, and detects information (speed information) related to the moving speed of the own vehicle based on the vehicle speed pulse.

  The inter-vehicle communication control unit 16 functions as a communication unit that performs wireless communication with navigation devices of other vehicles.

  The map data storage unit 17 includes a hard disk drive, a DVD, and the like, and stores map data.

  The travel history information storage unit 18 includes a hard disk drive, a flash memory, an SDRAM, and the like, and stores the travel history information acquired by the travel history information acquisition unit 122. The travel history information stored in the travel history information storage unit 18 is transmitted by the inter-vehicle communication control unit 16 to the vehicle traveling on the oncoming lane.

  Here, it is assumed that the navigation device 1 having the above configuration is mounted on each vehicle traveling on a road. FIG. 3 is a schematic diagram of a navigation system using the navigation device 1 according to the present embodiment.

FIG. 3 shows a state in which each vehicle equipped with the navigation device 1 is traveling on the road. Specifically, the first vehicle A _N , the second vehicle A _{N + 1,} and the third vehicle C travel in the same lane (congestion lane) where traffic congestion occurs, and the fourth vehicle B travels in the opposite lane. Running.

In this case, the first vehicle A _N and the second vehicle A _{N + 1} serve as an information providing vehicle that provides travel history information to the fourth vehicle B traveling in the oncoming lane, and the fourth vehicle B passes by. It plays a role as an information collecting vehicle that collects travel history information from the first vehicle A _N and the second vehicle A _{N + 1} . That is, the information collecting vehicle (fourth vehicle) B sequentially travels from the first vehicle A _N and the second vehicle A _{N + 1} that travel opposite to each other, the traveling history information TRK _N and the second vehicle A of the first vehicle A _{N. N + 1} travel history information TRK _{N + 1} is acquired.

Note that the second vehicle A _{N + 1} is one of a fleet of travel after the first vehicle A _N, after the fourth vehicle B receives the travel history information from the first vehicle A _N, the following running history information means a vehicle for receiving, but is not limited to vehicles traveling immediately after the first vehicle a _N on.

Information collection vehicle B is traffic condition (e.g. traffic jam starting point, congestion end point) in the congested lane on the basis of the running history information TRK _N of the first vehicle A _N detects the second vehicle A _{N + 1} of the running history Based on the information TRK _{N + 1} , the traffic state in the traffic lane is detected. And the information collection vehicle B acquires the prediction traffic state which predicted the traffic state in a traffic jam lane using the said traffic state.

Thereafter, the information collecting vehicle B sends information including the predicted traffic state (predicted traffic state information) to the subsequent third vehicle C traveling behind the information providing vehicles A _N and A _{N + 1.} 16 is used for transmission.

  In the third vehicle C, information using the predicted traffic state is provided to the user (passenger). Note that the third vehicle C is also referred to as an information collection vehicle because it collects information acquired based on the travel history information of a vehicle traveling in the same lane.

  In this way, in the navigation system, the travel history information of the own vehicle is transmitted from the inter-vehicle communication control unit 16 to the vehicle traveling on the oncoming lane (oncoming vehicle), and the vehicle travels behind the own vehicle using the oncoming vehicle. The predicted traffic condition information is transmitted to the following vehicle.

  Since all vehicles may be information providing vehicles, information collecting vehicles, and information collecting vehicles, each vehicle may have all of an information providing function, an information collecting function, and an information collecting function. preferable.

  The navigation device 1 includes a car navigation device mounted on a vehicle or a mobile device (for example, a mobile phone, a PDA, etc.) having a navigation function.

[1-2. Operation]
Next, operation | movement of the navigation apparatus 1 which acquires a predicted traffic state is explained in full detail. The navigation device 1 acquires the predicted traffic jam start point and the predicted traffic jam end point as the predicted traffic state. First, the operation of the navigation device 1 (acquisition of the predicted traffic jam start point) when acquiring the predicted traffic jam start point. explain. FIG. 4 is a flowchart showing the operation of the navigation device 1 when acquiring the predicted traffic jam start point. Figure 5 is a diagram showing the running history information TRK _N acquired from the information providing vehicle A _N, and travel history information TRK N + _1, which is acquired from the information providing vehicle A _{N + 1.} FIG. 6 is a diagram illustrating a distance difference on the travel route.

In operation of obtaining the predicted traffic jam starting point, as shown in FIG. 4, the running history information TRK _N from the information providing vehicle A _N is obtained, in step SP11, the congestion point detecting unit 123, the travel history information TRK _A traffic jam start point is detected using _N , and traffic jam start point information _SN is extracted.

Further, when the travel history information TRK _{N + 1} is acquired from the information providing vehicle A _{N + 1} , in step SP12, the traffic congestion start point is determined by the traffic congestion point detection unit 123 using the travel history information TRK _{N + 1.} It is detected, and traffic jam start point information S _{N + 1} is extracted.

FIG. 5, in step SP11, the information providing vehicle A _N running history information TRK _N traffic jam starting point information is extracted using S _N of, in step SP 12, the travel information provided vehicle A _{N + 1} historical information TRK _{N + 1} and the traffic jam starting point information S _{N + 1,} which is extracted with is shown.

As a method for detecting a traffic jam start point, for example, a certain threshold speed (also referred to as “traffic jam judgment speed”) is set, and a moving speed included in the travel history information (V _N (K) in the travel history information TRK _N ). In the travel history information TRK _{N + 1} , a method of detecting a point where V _{N + 1} (K)) is equal to or higher than the threshold speed and lower than or equal to the threshold speed can be adopted as a traffic jam start point.

  In addition, as another detection method of the traffic jam start point, for example, a certain threshold travel distance (also referred to as “congestion judgment distance”) is set, and the travel distance for a certain period (a certain time) obtained from the travel history information is You may employ | adopt the method of detecting the point which became the threshold value movement distance more than the said threshold value movement distance as a traffic congestion start point.

  Alternatively, when information on the traffic jam start point input by the user when the traffic jam occurs is included in the travel history information, information on the traffic jam start point by the user input may be extracted from the travel history information. .

Next, in step SP13, the traffic jam condition determination unit 124 compares the traffic jam start point information S _N and S _{N + 1} to determine whether or not the traffic jam start points match. Specifically, the position information included in the traffic jam starting point information S _N and _{(LAT N (K), LON} N (K)), the position information included in the traffic jam starting point information _{S N + 1 (LAT N +} 1 ( It is determined whether or not K) and LON _{N + 1} (K)) match. In addition, since it is unlikely that the position information completely matches, here, if the distance difference between the two position information is less than or equal to a certain value (for example, 5 m or less), it is determined that the two position information match. It is preferable. If the traffic jam start point information S _{N + 1} is not extracted from the travel history information TRK _{N + 1} , it is determined that the traffic jam has been eliminated, and the operation for acquiring the predicted traffic jam start point is terminated.

  In step SP13, when it is determined that the traffic congestion start points coincide, the operation process moves to step SP14.

  In step SP14, the traffic jam situation prediction unit 125 identifies either one of the traffic jam start points as the predicted traffic jam start point (predicted traffic jam start point).

  On the other hand, when it is determined in step SP13 that the congestion start points do not match, the operation process moves to step SP15. In subsequent steps SP15 to SP20, the traffic jam situation prediction unit 125 calculates the predicted position of the traffic jam start point.

Specifically, in step SP15, a distance difference (change amount) ΔD _S (K) on the travel route between the two traffic jam start points is calculated. The distance difference ΔD _S (K) on the travel route between the two traffic jam start points is obtained when the two traffic jam start points PS _N and PS _{N + 1} are connected along the travel route, as shown in FIG. Distance, calculated with reference to map data.

Next, in step SP16, a traffic difference start time difference ΔT _S (K) is calculated. The traffic difference start time difference ΔT _S (K) is obtained by subtracting the time T _N (K) included in the traffic jam start point information S _N from the time T _{N + 1} (K) included in the traffic jam start point information S _{N + 1.} Can be obtained by: That is, the time difference ΔT _S (K) at the start of traffic jam is expressed as in equation (1).

In step SP17, the fluctuation speed ΔV _S (K) at the traffic jam start point is calculated. The fluctuation speed ΔV _S (K) of the traffic jam start point is obtained by dividing the distance difference ΔD _S (K) between the two traffic jam start points on the travel route by the traffic jam start time difference ΔT _S (K). Can do. That is, the fluctuation speed ΔV _S (K) at the traffic jam start point is expressed as in Expression (2).

In the next step SP18, the current time Tc and the time included in the traffic congestion start point information extracted from the latest travel history information among the travel history information acquired by the information collecting vehicle B (here, the traffic congestion start point information S time T _{N + 1} (K)) the difference between the ΔTc included in _{N + 1} (K) is calculated. The traffic jam start point information extracted from the latest travel history information among the travel history information acquired by the information collecting vehicle B is also referred to as “latest traffic jam start point information”. The included time is also referred to as “latest traffic jam start time”.

In step SP19, a predicted fluctuation distance ΔDc (K) of the traffic jam start point that is predicted to change between the latest traffic jam start time and the current time Tc is calculated. The predicted fluctuation distance ΔDc (K) of the traffic jam start point is obtained by multiplying the fluctuation speed ΔV _S (K) of the traffic jam start point by the difference ΔTc (K) between the current time Tc and the latest traffic jam start time. Can do. That is, the predicted fluctuation distance ΔDc (K) at the traffic jam start point is expressed as in Expression (3).

In step SP20, it is specified by position information included in the latest congestion start point information (here, position information LAT _{N + 1} (K), LON _{N + 1} (K) included in the congestion start point information S _{N + 1} )). A point that has moved by the predicted fluctuation distance ΔDc (K) on the travel route from the point to be acquired is acquired as the predicted position of the traffic jam start point (predicted traffic jam start point).

Thus, by calculating the predicted position of the traffic congestion start point at the current time Tc from the travel history information TRK _N and TRK _{N + 1} of the information providing vehicles A _N and A _{N + 1} , the information providing vehicles A _N , a N _{+ 1} of the running history information TRK _N, as compared with the case of obtaining directly TRK N + ₁ traffic jam starting point information from the composed information high traffic jam starting point accuracy can be provided to the user.

More specifically, in the case of a configuration in which traffic jam start point information is directly extracted from the travel history information TRK _N and TRK _{N + 1} of the information providing vehicles A _N and A _{N + 1} , the extracted traffic jam start point information is collected as information collection When the vehicle C acquires, the traffic jam start point information is old information. On the other hand, by calculating the predicted position of the traffic jam start point at the current time Tc from the travel history information TRK _N and TRK _{N + 1} of the information providing vehicles A _N and A _{N + 1} as in this embodiment. Thus, it is possible to provide the user with highly accurate information on the traffic jam start point.

Note that the predicted position of the traffic jam start point at the current time Tc indicates a traffic state that is later in time than the traffic jam start point extracted directly from the travel history information TRK _N and TRK _{N + 1} .

  In addition, although each operation process of step SP11-step SP20 was taken as the aspect performed in the information collection vehicle B above, it is not limited to this.

Specifically, as shown in FIG. 4, the operation process of step SP11 may be executed in any of the information providing vehicle A _N , the information collection vehicle B, and the information collection vehicle C. The operation process may be executed in any of the information providing vehicle A _{N + 1} , the information collecting vehicle B, and the information collecting vehicle C. Moreover, you may perform each operation | movement process of step SP11-step SP20 in which vehicle among the information collection vehicle B and the information collection vehicle C.

  For example, in the information collection vehicle C, if the operation steps of steps SP11 to SP20 are executed, the time immediately before the information on the traffic jam start point is provided to the user may be the current time Tc used in step SP18. Therefore, it is possible to provide the user with more accurate information on the traffic jam start point.

  Further, for example, if the information collecting vehicle B is configured to execute the operation steps of step SP11 to step SP20, the information collecting vehicle C can be accurately transmitted to the user by simply transmitting the calculated predicted position of the traffic jam start point. Therefore, it is possible to reduce the amount of information transmitted to the information collection vehicle C.

Further, for example, perform the operation process of step SP11 in the information providing vehicle A _N, the information providing vehicle A _{N + 1} According to performing the operation process of step SP 12, the information collection vehicle B, the travel history information TRK _Since the traffic jam start point information S _N and S _{N + 1} may be transmitted instead of _{N 1} and TRK _{N + 1} , the amount of information to be transmitted can be reduced.

Further, for example, if the information collecting vehicle B executes the operation process up to step SP17, the amount of information transmitted to the information collecting vehicle C can be reduced. Further, it is possible to accumulate travel history information from more information-providing vehicles and update it to newer information, or to calculate the fluctuation speed ΔV _S (K) of the traffic jam starting point with high accuracy. Even if traveling history information is collected from each, the amount of information transmitted to the information collecting vehicle C can be suppressed.

  Further, for example, if the operation process after step SP18 is executed in the information collection vehicle C, the predicted position of the traffic jam start point can be calculated using the newer current time Tc, so the traffic jam start can be performed with higher accuracy. It becomes possible to provide the user with point information.

  Next, the operation of the navigation device 1 (acquisition of predicted traffic jam end point) when acquiring the predicted traffic jam end point will be described. FIG. 7 is a flowchart showing the operation of the navigation device 1 when acquiring the predicted traffic jam end point.

  In the operation for acquiring the predicted traffic jam end point, almost the same operation steps as those for the operation for acquiring the predicted traffic jam start point (FIG. 4) are executed. Therefore, the operation for acquiring the predicted traffic jam end point will be briefly described below.

In operation of obtaining the predicted congestion end point, as shown in Figure 7, the running history information TRK _N from the information providing vehicle A _N is obtained, in step SP51, the congestion point detecting unit 123, the travel history information TRK _A traffic jam end point is identified using _N , and traffic jam end point information E _N is extracted.

Further, when the travel history information TRK _{N + 1} is acquired from the information providing vehicle A _{N + 1} , in step SP52, the traffic congestion end point is determined by the traffic congestion point detection unit 123 using the travel history information TRK _{N + 1.} The traffic jam end point information E _{N + 1} is extracted.

FIG. 5, in step SP51, the information providing vehicle A _N running history information TRK _N congestion end point information has been extracted using E _N of, in step SP 52, the travel information provided vehicle A _{N + 1} historical information TRK _{N + 1} and the congestion end point information E _{N + 1,} which is extracted with is shown.

As a method for detecting a traffic jam end point, for example, a certain threshold speed (a traffic jam judgment speed) is set, and a travel speed (V _N (L) in the travel history information TRK _N ) and travel history information are included in the travel history information. In TRK _{N + 1} , a method of detecting a point where V _{N + 1} (L)) is equal to or higher than the threshold speed and higher than or equal to the threshold speed as an end point of the traffic jam can be employed.

  In addition, as another detection method of the congestion end point, for example, a certain threshold moving distance (congestion determination distance) is set, and the moving distance for a certain period (constant time) obtained from the travel history information is the threshold moving distance. You may employ | adopt the method of detecting the point which became more than threshold movement distance from the following as an end point of traffic congestion.

  Alternatively, when information on the traffic jam end point input by the user when the traffic jam occurs is included in the travel history information, the information on the traffic jam end point by the user input may be extracted from the travel history information. .

Next, in step SP53, the traffic jam condition determination unit 124 compares the traffic jam end point information E _N and E _{N + 1} to determine whether or not the traffic jam end point matches. Specifically, the position information included in the traffic jam ending point information E _N and _{(LAT N (L), LON} N (L)), the position information included in the traffic jam ending point information _{E N + 1 (LAT N +} 1 ( L) and LON _{N + 1} (L)) are matched. In addition, since it is unlikely that the position information completely matches, here, if the distance difference between the two position information is less than or equal to a certain value (for example, 5 m or less), it is determined that the two position information match. It is preferable.

  When it is determined in step SP53 that the congestion end points coincide, the operation process moves to step SP54.

  In step SP54, the traffic jam situation prediction unit 125 identifies one of the traffic jam end points as the predicted position of the traffic jam end point.

  On the other hand, when it is determined in step SP53 that the congestion end points do not match, the operation process moves to step SP55. In subsequent steps SP55 to SP60, the traffic jam condition prediction unit 125 calculates the predicted position of the traffic jam end point.

Specifically, in step SP55, a distance difference ΔD _E (L) on the travel route between the two traffic jam end points is calculated.

Next, in step SP56, the time difference ΔT _E (L) at the end of the traffic jam is calculated. The time difference ΔT _E (L) of the traffic jam end time is obtained by subtracting the time T _N (L) included in the traffic jam end point information E _N from the time T _{N + 1} (L) included in the traffic jam end point information E _{N + 1.} Can be obtained by:

In step SP57, the fluctuation speed ΔV _E (L) at the congestion end point is calculated. The fluctuation speed ΔV _E (L) at the traffic jam end point is obtained by dividing the distance difference ΔD _E (L) between the two traffic jam end points on the travel route by the traffic jam end time difference ΔT _E (L). Can do.

In the next step SP58, the current time Tc and the time included in the traffic congestion end point information extracted from the latest travel history information among the travel history information acquired by the information collecting vehicle B (here, the traffic congestion end point information E time T _{N + 1} (L)) difference between the ΔTc included in _{N + 1} (L) is calculated. The traffic jam end point information extracted from the latest travel history information among the travel history information acquired by the information collecting vehicle B is also referred to as “latest traffic jam end point information”. The included time is also referred to as “latest traffic jam end time”.

In step SP59, the predicted fluctuation distance ΔDc (L) of the traffic jam end point predicted to change between the latest traffic jam end time and the current time Tc is calculated. The predicted fluctuation distance ΔDc (L) at the traffic jam end point is obtained by multiplying the fluctuation speed ΔV _E (L) at the traffic jam end point by the difference ΔTc (L) between the current time Tc and the latest traffic jam end time. Can do.

In step SP60, it is specified by position information included in the latest traffic end point information (here, position information LAT _{N + 1} (L), LON _{N + 1} (L) included in the traffic end point information E _{N + 1} ). The point moved by the predicted variation distance ΔDc (L) on the travel route is acquired as the predicted position of the traffic jam end point.

Thus, by calculating the predicted position of the traffic jam end point at the current time Tc from the travel history information TRK _N and TRK _{N + 1} of the information providing vehicles A _N and A _{N + 1} , the information providing vehicles A _N , a N _{+ 1} of the running history information TRK _N, as compared with the case of obtaining directly TRK N + ₁ congestion end point information from the composed information high congestion end point accuracy can be provided to the user.

More specifically, in the case of a configuration in which the traffic jam end point information is directly extracted from the travel history information TRK _N and TRK _{N + 1} of the information providing vehicles A _N and A _{N + 1} , the extracted traffic jam end point information is collected as information. When the vehicle C acquires, the traffic jam end point information is old information. On the other hand, by calculating the predicted position of the traffic jam end point at the current time Tc from the travel history information TRK _N and TRK _{N + 1} of the information providing vehicles A _N and A _{N + 1} as in this embodiment. Thus, it becomes possible to provide the user with highly accurate information on the end point of the traffic jam.

  In addition, although each operation process of step SP51-step SP60 was made into the aspect performed in the information collection vehicle B above, it is not limited to this.

Specifically, as shown in FIG. 7, the operation process of step SP51 may be executed in any of the information providing vehicle A _N , the information collection vehicle B, and the information collection vehicle C. The operation process may be executed in any of the information providing vehicle A _{N + 1} , the information collecting vehicle B, and the information collecting vehicle C. In addition, each operation process of step SP51 to step SP60 may be executed in any one of the information collecting vehicle B and the information collecting vehicle C.

  For example, in the information collection vehicle C, if the operation steps of step SP51 to step SP60 are performed, the time immediately before the information on the traffic jam end point is provided to the user may be the current time Tc used in step SP58. Therefore, it is possible to provide the user with more accurate information on the traffic jam end point.

  Further, for example, if the information collecting vehicle B is configured to execute the operation steps of step SP51 to step SP60, the information collecting vehicle C can be accurately transmitted to the information recovery vehicle C simply by transmitting the calculated predicted position of the traffic jam end point. Therefore, it is possible to reduce the amount of information transmitted to the information collection vehicle C.

Further, for example, perform the operation process of step SP51 in the information providing vehicle A _N, the information providing vehicle A _{N + 1} According to performing the operation process of step SP 52, the information collection vehicle B, the travel history information TRK _Since the traffic jam end point information E _N and E _{N + 1} may be transmitted instead of _{N 1} and TRK _{N + 1} , the amount of information to be transmitted can be reduced.

For example, if the information collection vehicle B performs the operation process up to step SP57, the amount of information transmitted to the information collection vehicle C can be reduced. Further, it is possible to accumulate travel history information from more information-providing vehicles and update it to newer information, or to calculate the fluctuation speed ΔV _E (L) of the congestion end point with high accuracy. Even if traveling history information is collected from each, the amount of information transmitted to the information collecting vehicle C can be suppressed.

  Further, for example, if the operation process after step SP58 is executed in the information collection vehicle C, the predicted position of the traffic jam end point can be calculated using the newer current time Tc, so the traffic jam end can be performed with higher accuracy. It becomes possible to provide the user with point information.

As described above, a navigation system using a navigation device 1 is capable of detecting first congestion start point (first congestion end point) on the basis of the running history information TRK _N information providing vehicle A _N traveling lane the information providing vehicle a _N provide information travels after the vehicle a _{N + 1} of the running history information TRK N + second traffic jam starting point on the basis of ₁ (second congestion end point) capable of detecting the congestion point detecting unit 123 And a change amount of the traffic jam start point using the first traffic jam start point and the second traffic jam start point, and based on the change amount, a traffic jam start point later in time than the second traffic jam start point is calculated. A traffic condition prediction unit 125 that acquires a predicted predicted traffic start point, and an information providing unit that provides information using a predicted traffic start point (predicted traffic end point) in a vehicle subsequent to the information providing vehicle _{AN + 1} ; Is provided.

  According to such a navigation system, information can be provided using the predicted traffic start point (predicted traffic end point) that predicts the traffic start point (traffic end point), so information to be communicated to the user in the following vehicle It becomes possible to improve the accuracy.

  Within the scope of the present invention, the present invention can be modified or omitted with any component in the present embodiment.

<2. Modification>
Although the embodiments of the present invention have been described above, the present invention is not limited to the contents described above.

  For example, in step SP18 of the above embodiment, the difference ΔTc () between the current time Tc and the time included in the traffic jam start point information extracted from the latest travel history information among the travel history information acquired by the information collecting vehicle B. K) has been calculated, but the present invention is not limited to this.

Specifically, in step SP18, the congestion start point extracted from the current time Tc and any travel history information (also referred to as “reference travel history information”) among the travel history information acquired by the information collecting vehicle B. A difference ΔTc (K) from the time included in the information (for example, time T _N (K) included in the traffic jam start point information S _N ) may be calculated. The traffic jam start point information extracted from the reference travel history information is also referred to as “reference traffic jam start point information”, and the time included in the traffic jam start point information is also referred to as “reference traffic jam start time”.

In this case, in step SP19, the predicted fluctuation distance ΔDc (K) of the traffic jam start point predicted to change between the reference traffic jam start time and the current time Tc is calculated. The predicted fluctuation distance ΔDc (K) of the traffic jam start point can be obtained by multiplying the fluctuation speed ΔV _S (K) of the traffic jam start point by the difference ΔTc (K) between the current time Tc and the reference traffic jam start time. it can.

In step SP20, the vehicle travels from the location specified by the location information (for example, location information LAT _N (K), LON _N (K) contained in the traffic jam start point information _SN ) included in the reference traffic jam start location information. The point moved by the predicted fluctuation distance ΔDc (K) on the route is acquired as the predicted position of the traffic jam start point.

  Moreover, there is a possibility that the information providing vehicle and the information collecting vehicle have passed an exceptional travel route. FIG. 8 is a diagram showing an exception pattern of the travel route of the information providing vehicle, and FIG. 9 is a diagram showing an exception pattern of the travel route of the information collecting vehicle.

Specifically, as shown in FIG. 8, when the information providing vehicle _AM is a vehicle that has entered a traffic lane (congested road) from another route, the traffic start position is different from other information providing vehicles. .

However, it can be determined whether has traveled which path from the travel history information of the information providing vehicle A _M, the use of congestion start position information of the information providing vehicle A _M to the prediction of the traffic jam starting position can be avoided.

Incidentally, the travel history information of the information providing vehicle A _M may be of use to grasp the traffic situation around the other travel route information collecting vehicle requires, travel history information of the information providing vehicle A _M leaves as It may be. Further, the information providing vehicle A _M entering from another route in traffic lanes there are a plurality, in the case where a plurality of information providing vehicle A _M was traveling the same route, the travel history information of a plurality of information providing vehicle A _M If the above-described operation for acquiring the predicted traffic jam start point and the operation for acquiring the predicted traffic jam end point are performed, it is possible to obtain the latest traffic jam information of the surrounding roads.

Further, as shown in FIG. 9, when the information collecting vehicle B _M enters the opposite lane opposite to the traffic lane from another route, the information collecting vehicle B _M may have traffic information on the surrounding roads. There is. For this reason, if the information collection vehicle C also receives the travel history information of the information collecting vehicle B _M , it is possible to grasp the traffic situation of the surrounding road on the travel route. Furthermore, the plurality of information collection vehicles B _M, if the plurality of information collection vehicles B _M was traveling the same path, using the travel history information of a plurality of information providing vehicle A _M, the above-described predictive traffic congestion If the acquisition operation of the start point and the acquisition operation of the predicted traffic jam end point are performed, it becomes possible to obtain the latest traffic information on the surrounding roads.

  Thus, the information collection vehicle C can accurately acquire not only the traffic situation on the planned travel route but also the surrounding traffic situation. For this reason, the information collection vehicle C can more accurately search the detour route based on the acquired information with the latest information, and can more reliably avoid traffic jams. In addition, a vehicle already in a traffic jam can more accurately obtain the time until the vehicle passes the traffic jam.

  In the above embodiment, the travel history information is information including the time, the own vehicle position information at that time, and the moving speed. However, the travel history information may further include the position information of the passing intersection. According to this, since the travel route of the vehicle can be specified based on the position information of the intersection, the interval for acquiring the travel history information can be increased, and the information amount of the travel history information can be reduced. Can do. Note that position information between the intersections may be used instead of the position information of the intersections.

  Moreover, you may perform in parallel with the acquisition operation of the prediction traffic start point shown in the said embodiment, and the acquisition operation of the prediction traffic end point.

  DESCRIPTION OF SYMBOLS 1 Navigation apparatus, 11 Display part, 12 Control part, 122 Traveling history information acquisition part, 123 Traffic congestion point detection part, 124 Traffic congestion state determination part, 125 Traffic congestion state prediction part, 13 Control program memory | storage part, 14 Own vehicle position detection part , 15 Self-vehicle movement speed detection unit, 16 Inter-vehicle communication control unit, 17 Map data storage unit, 18 Travel history information storage unit.

Claims (12)

The first traffic state can be detected based on the first travel history information of the first vehicle traveling in the lane, and the second traffic is based on the second travel history information of the second vehicle traveling after the first vehicle. Detection means capable of detecting the state;
The amount of change in the traffic state in the lane is calculated using the first traffic state and the second traffic state, and the traffic in the lane after the second traffic state is calculated based on the amount of change. A predicting means for obtaining a predicted traffic state in which a state is predicted;
An information providing means for providing information using the predicted traffic state in a succeeding vehicle of the second vehicle;
A navigation system comprising: The oncoming vehicle that travels in the opposite lane with respect to the lane has communication means capable of communicating with each of the first vehicle, the second vehicle, and the subsequent vehicle,
The oncoming vehicle acquires the first travel history information from the first vehicle using the communication means, and acquires the second travel history information from the second vehicle using the communication means,
The oncoming vehicle further includes the detection means and the prediction means,
The navigation system according to claim 1, wherein the oncoming vehicle transmits the predicted traffic state to the following vehicle using the communication unit. The oncoming vehicle that travels in the opposite lane with respect to the lane has communication means capable of communicating with each of the first vehicle, the second vehicle, and the subsequent vehicle,
The oncoming vehicle acquires the first travel history information from the first vehicle using the communication means, and acquires the second travel history information from the second vehicle using the communication means,
The oncoming vehicle transmits the first travel history information and the second travel history information to the following vehicle using the communication means,
The navigation system according to claim 1, wherein the following vehicle includes the detection unit and the prediction unit. The oncoming vehicle that travels in the opposite lane with respect to the lane has communication means capable of communicating with each of the first vehicle, the second vehicle, and the subsequent vehicle,
The oncoming vehicle acquires the first travel history information from the first vehicle using the communication means, and acquires the second travel history information from the second vehicle using the communication means,
The oncoming vehicle further includes the detection means,
The oncoming vehicle transmits the first traffic state and the second traffic state to the following vehicle using the communication means,
The navigation system according to claim 1, wherein the succeeding vehicle includes the prediction unit. The oncoming vehicle that travels in the opposite lane with respect to the lane has communication means capable of communicating with each of the first vehicle, the second vehicle, and the subsequent vehicle,
The first vehicle and the second vehicle have the detection means,
The first vehicle detects a first traffic state based on the first travel history information by the detecting means,
The second vehicle detects a second traffic state based on the second travel history information by the detecting means,
The oncoming vehicle acquires the first traffic state from the first vehicle using the communication means, and acquires the second traffic state from the second vehicle using the communication means,
The oncoming vehicle further includes the prediction means,
The navigation system according to claim 1, wherein the oncoming vehicle transmits the predicted traffic state to the following vehicle using the communication unit. The oncoming vehicle that travels in the opposite lane with respect to the lane has communication means capable of communicating with each of the first vehicle, the second vehicle, and the subsequent vehicle,
The first vehicle and the second vehicle have the detection means,
The first vehicle detects a first traffic state based on the first travel history information by the detecting means,
The second vehicle detects a second traffic state based on the second travel history information by the detecting means,
The oncoming vehicle acquires the first traffic state from the first vehicle using the communication means, and acquires the second traffic state from the second vehicle using the communication means,
The oncoming vehicle transmits the first traffic state and the second traffic state to the following vehicle using the communication means,
The navigation system according to claim 1, wherein the succeeding vehicle includes the prediction unit. The detection means is capable of detecting a start point of a traffic jam occurring in the lane based on the first travel history information as the first traffic state, and a start point of the traffic jam based on the second travel history information. Can be detected as the second traffic state,
The prediction means compares a traffic jam start point detected based on the first travel history information with a traffic jam start point detected based on the second travel history information, and determines a traffic jam start point. The navigation system according to any one of claims 1 to 6, wherein a change amount on a travel route is calculated, and a predicted position of a traffic jam start point is acquired as the predicted traffic state based on the change amount. The detection means is capable of detecting an end point of a traffic jam occurring in the lane based on the first travel history information as the first traffic state, and an end point of the traffic jam based on the second travel history information. Can be detected as the second traffic state,
The predicting means compares the end point of the traffic jam detected based on the first travel history information with the end point of the traffic jam detected based on the second travel history information, and determines the end point of the traffic jam. The navigation system according to any one of claims 1 to 6, wherein a change amount on a travel route is calculated, and a predicted position of a traffic jam end point is acquired as the predicted traffic state based on the change amount. A communication means capable of communicating with an oncoming vehicle traveling in an oncoming lane;
Based on the first travel history information acquired from the first oncoming vehicle traveling in the oncoming lane using the communication means, the second traffic is detected after detecting the first traffic state and travels after the first oncoming vehicle. Detection means for detecting a second traffic state based on second travel history information acquired from the vehicle using the communication means;
The amount of change in the traffic state in the opposite lane is calculated using the first traffic state and the second traffic state, and the opposite lane is temporally later than the second traffic state based on the amount of change. A predicting means for obtaining a predicted traffic state by predicting a traffic state in
With
The said communication means is a navigation apparatus which transmits the said predicted traffic state to the succeeding vehicle of the said 2nd oncoming vehicle. The detection means detects a start point of a traffic jam that has occurred in the oncoming lane based on the first travel history information as the first traffic state, and determines a start point of the traffic jam based on the second travel history information. Detecting as the second traffic state;
The prediction means compares a traffic jam start point detected based on the first travel history information with a traffic jam start point detected based on the second travel history information, and determines a traffic jam start point. The navigation device according to claim 9, wherein a change amount on a travel route is calculated, and a predicted position of a traffic jam start point is acquired as the predicted traffic state based on the change amount. The detection means detects an end point of a traffic jam occurring in the oncoming lane as the first traffic state based on the first travel history information, and determines an end point of the traffic jam based on the second travel history information. Detecting as the second traffic state;
The predicting means compares the end point of the traffic jam detected based on the first travel history information with the end point of the traffic jam detected based on the second travel history information, and determines the end point of the traffic jam. The navigation device according to claim 9, wherein an amount of change on the travel route is calculated, and a predicted position of a traffic jam end point is acquired as the predicted traffic state based on the amount of change. a) detecting a first traffic state based on first travel history information of a first vehicle traveling in a lane;
b) detecting a second traffic state based on second travel history information of a second vehicle traveling after the first vehicle;
c) A change amount of the traffic state in the lane is calculated using the first traffic state and the second traffic state, and the lane that is temporally later than the second traffic state based on the change amount Obtaining a predicted traffic condition that predicts the traffic condition in
d) providing information using the predicted traffic state in a vehicle following the second vehicle;
A method of operating a navigation system comprising:

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