JP2000113364A - Traffic information processing system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the prediction precision of a traffic condition in respective positions in a road network. SOLUTION: The traffic information processing system is provided with a traffic flow pattern memory 34 storing a traffic flow pattern containing the predicted shunt rate of vehicles passing through respective branch points in a road network, a prediction operation part 32 executing a prediction operation by using a traffic flow pattern stored in the traffic flow pattern memory against respective traffic quantities detected in vehicle detectors 1 installed in the respective positions of the road network and calculating the predicted traffic condition in the respective positions after prescribed time in the road network, predicted information supply means 35 and 36 supplying predicted information to the respective vehicles based on the calculated predicted traffic condition, a route reading means 19 reading a route, from a navigation device loaded on the vehicle 13, to the destination of the vehicle 13 by radio and a traffic flow pattern correction means 33 correcting the traffic flow pattern stored in the traffic flow pattern memory based on route information which is read.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention predicts traffic conditions at each position on a road network and provides traffic information for providing accurate prediction information to each vehicle on the road network based on the prediction result. Regarding the processing system.

[0002]

2. Description of the Related Art For example, in a traffic information processing system for providing accurate information to each vehicle so that each vehicle can pass smoothly on each road of a complicated road network as shown in FIG. The vehicle detector 1 is installed at each position on each road. Each of the vehicle detectors 1 constantly monitors vehicles passing through the position. For example, vehicle traffic, vehicle speed, vehicle density, degree of congestion, and the like per unit time at the position at a constant period T such as 5 minutes. The traffic volume is detected and transmitted to the management center 3.

In the management center 3, a traffic condition prediction device 4
And a traffic control device 5.

[0004] The traffic condition predicting device 4 includes traffic volumes I ₁ , I ₂ , I which are sequentially input from the vehicle detectors 1 at a constant period T.
_3, ..., I _n (each suffix indicating the information of each position)
, A prediction operation is performed using a prediction program set in advance, and each time (t + T) after a lapse of a predetermined time Td such as 30 minutes from each input time t of the constant period T, for example.
Predicted traffic situation J at each position on the road network in d)
₁ , J ₂ , J ₃ ,..., J _n (each suffix indicates information on each position) are sequentially obtained and transmitted to the next traffic control device 5.

The predicted traffic conditions J ₁ , J at each position
₂ , J ₃ ,..., J _n include a predicted traffic amount, a predicted vehicle speed, a predicted vehicle density, a predicted congestion degree, and the like at the corresponding position.

The traffic control device 5 predicts traffic conditions J ₁ , J ₂ , J at each position sequentially input from the traffic condition predicting device 4.
_{Based on 3} ,..., J _n , traffic jam information is displayed and output on the electronic display panel 6 shown in FIG. 6 and various traffic regulations such as closing an entrance gate are performed.

As described above, the traffic condition prediction device 4 performs a prediction calculation using a preset prediction program. However, as shown in FIG. In order to improve the prediction accuracy, for example, as shown in FIG.
Out of all vehicles entering the section B, a shunt ratio α _B (0 <α _B <1), which is a ratio of the number of vehicles heading to section _B , and a shunt ratio α _C (0 <, which is a ratio of the number of vehicles heading to section C) α _C <1)
Is predicted in advance (α _B + α _C = 1).

[0008] As described above, by setting the predicted branch ratio α (α _B, α _C ) at the branch point 2 in advance, A
Based on the traffic I detected by the vehicle detector 1 installed in the section, the traffic situation J in the section B and the section C can be predicted to some extent accurately. Then, based on the prediction result, the traffic control device 5 displays an alarm such as, for example, “B section traffic jam occurrence forecast” on the electric display panel 6 installed before the branch point 2 if necessary.

As described above, the branch ratios α ₁ , α ₂ , α ₃ ,..., Α at all the branch points 2 in the road network of FIG.
_By setting _n in advance in the traffic flow pattern memory as the traffic flow pattern as the direction in which each vehicle is heading, it is possible to further improve the prediction accuracy of the traffic situation at each position on the road network.

[0010]

However, the traffic situation prediction device 4 for predicting the traffic situation at each position of the road network using the traffic flow pattern preset in the traffic flow pattern memory should also be improved. There were the following issues.

As described above, the traffic situation prediction device 4
Each traffic I ₁ , which is input at a constant period T such as every 5 minutes from each vehicle detector 1 provided at each position on the road network,
I _2, I _3, ..., each predicted traffic situation for I _n J _1, J
_2, J _3, ..., seeking a J _n.

Therefore, each of the branching ratios α ₁ , α ₂ , α ₃ ,..., Α _n of each branch point 2 included in the traffic flow pattern set in the traffic flow pattern memory is determined by referring to the actual measurement results and the like. For example, as shown by a solid line pattern in FIG.
It changes every 24 hours a day.

This is because, in many cases, the traveling direction differs between morning and evening or the route differs depending on commuting or the like. Further, between weekdays and holidays, the split ratio α
In some cases.

As described above, by changing the pattern of the branching ratio α at each branching point 2 according to the road use conditions such as the time zone and the day of the week, the prediction accuracy of the traffic situation can be greatly improved.

However, the pattern of each branching ratio α corresponding to the use condition of each road set in the traffic flow pattern memory is a fixed value written in advance by the administrator of the traffic situation prediction device 4. .

Therefore, when a special condition other than the above-mentioned plural kinds of use conditions specified in advance occurs, the predicted value obtained by the traffic condition predicting device 4 is greatly different from the actual traffic condition. Become.

For example, when a large entertainment is held along a specific road, as shown by a broken line pattern in FIG. 7, the shunt ratio α to the road leading to the entertainment venue is temporarily set before the holding time. When the time of the event ends, the shunt ratio α greatly decreases.

Such a situation can be predicted to some extent at the time when the event is planned to be held, and a vehicle not related to the event bypasses another route to avoid traffic congestion that may occur near the event site. A guidance recommending that the user should take action should be displayed on the electronic display panel 6 just before the branch point 2.

However, there is a high probability that a large number of unique conditions that cannot be predicted in advance occur in addition to the above-mentioned event. In this way, it is not possible to previously set the pattern of the diversion ratio α in the traffic flow pattern memory for the condition that cannot be predicted in advance.

As a result, it was not possible to accurately predict the traffic condition including the prediction of the occurrence of traffic congestion under the conditions of use of the road where the probability of congestion occurring on a specific route (road) in the road network is high.

[0021] The present invention has been made in view of the above-described circumstances. For example, by using a route to a destination of a corresponding vehicle in a navigation device mounted on each vehicle traveling on a road network, prediction can be performed. Provide a traffic information processing system that can accurately predict traffic conditions including traffic congestion prediction, provide correct predicted traffic conditions to each vehicle, and greatly improve reliability even when road use conditions that cannot be used occur. The purpose is to do.

[0022]

In order to solve the above problems, in the traffic information processing system of the present invention, a traffic flow pattern including at least a predicted shunt ratio of a vehicle passing through each branch point in a road network is stored. A traffic flow pattern memory and a traffic flow pattern stored in a traffic flow pattern memory are used to perform a prediction calculation for each traffic volume detected by a vehicle detector installed at each position of the road network, A prediction calculation unit that calculates a predicted traffic situation at each position after a predetermined time in; a prediction information providing unit that provides prediction information to each vehicle based on the predicted traffic situation calculated by the prediction calculation unit; Route reading means for wirelessly reading a route from a navigation device mounted on a traveling vehicle to a destination of the vehicle; and a route reading unit for reading a route based on the route information read by the route reading unit. And a traffic flow pattern modification means for modifying the traffic flow pattern stored in the traffic flow pattern memory Te.

In the traffic information processing system thus configured, a route from a navigation device mounted on a vehicle traveling on a road network to a destination of the vehicle is wirelessly read.

That is, in recent years, many vehicles are equipped with a navigation device. This navigation device receives a radio wave from a GPS satellite and calculates a current position including its own latitude and longitude. Then, the current position is displayed on the map read from the map memory on the display screen.

Further, in the navigation device,
When the operator (driver) specifies the destination of the vehicle on, for example, a display screen, an automatic route from the current position to the destination is displayed on the display screen with, for example, a red line. More specifically, information on which road travels in which direction from the current position to the destination and which branch point travels in which direction are displayed graphically.

Therefore, the driver only has to drive along the displayed red line. When the car goes off the course,
You notice immediately because the displayed current position deviates from the red line.

In the present invention, a route composed of the road (section) to be traveled, the branching point and the traveling direction of the branching point to the destination of the vehicle created by the navigation device is read wirelessly. . In this case, an individual route is read from each vehicle.

Then, the predicted branching ratio of the corresponding branch point stored in the traffic flow pattern memory for each of the read routes is corrected. The degree of correction of the predicted shunt ratio may correspond to the number of samples of the route read from each vehicle.

That is, when the number of samples is large, the degree of correction may be increased, and the predicted branching ratio of the corresponding branch point stored in the traffic flow pattern memory may be replaced with the branching ratio obtained from the read path. Conversely, if the number of samples is small, the predicted branching ratio of the corresponding branch point stored in the traffic flow pattern memory is corrected to slightly approach the branching ratio obtained on the read route.

As described above, the traffic flow patterns including the predicted shunt ratios of the vehicles passing through the respective branch points stored in the traffic flow pattern memory are obtained from the respective vehicles going to the corresponding branch points. Corrected by route.

Therefore, even if an unusual car flow such as an event occurs, the traffic flow pattern changes in accordance with the flow of the car. Also, it is possible to accurately predict traffic conditions including prediction of occurrence of traffic congestion.

Further, in the traffic information processing system of another invention, a route reading means for wirelessly reading a route from a navigation device mounted on a vehicle traveling on a road network to a destination of the vehicle, and the route reading means A shunt ratio calculating means for calculating a predicted shunt ratio of a vehicle passing through each branch point in the road network based on the route information read in step 1, and a traffic flow pattern including at least the predicted shunt ratio calculated by the shunt ratio calculating means And a traffic flow pattern stored in the traffic flow pattern memory, and performs a prediction calculation for each traffic volume detected by a vehicle detector installed at each position of the road network. A prediction operation unit that calculates a predicted traffic condition at each position after a predetermined time in the road network; and a predicted traffic condition calculated by the prediction calculation unit. And a prediction information providing means for providing a prediction information to the vehicle.

In the thus constructed traffic information system, the traffic pattern memory includes a traffic pattern including only the predicted ratio calculated based on the route read from the navigation device of each vehicle. It is memorized. Naturally, this traffic pattern is updated with each newly read route.

Therefore, the same operation and effect as those of the traffic information processing system according to the above invention can be obtained.

According to still another invention, the route reading means in the traffic information processing system of each invention is provided at each tollgate in the road network, and at least a corresponding charge rate is applied to a vehicle-mounted device of a vehicle entering the road network. It is incorporated in an automatic toll collection device that wirelessly writes information specifying a place.

[0036] In the traffic information processing system thus configured, the route reading means is provided in an automatic toll collection device that enables vehicles to pass through toll booths installed at toll road interchanges (ICs) without stopping. It is built in. This automatic toll collection device has a function of wirelessly writing at least information specifying a corresponding tollgate to an in-vehicle device of a vehicle entering a road network.

Therefore, it is easy to add a function of wirelessly reading the route from the navigation device mounted on the vehicle to the destination of the vehicle to the automatic toll collection device.

According to still another aspect of the present invention, the route reading means in the traffic information processing system according to each of the above aspects is arranged along each road of the road network, and is incorporated in a wireless beacon for providing various information to the navigation device. I have.

In the traffic information processing system configured as described above, the wireless beacon originally has a function of providing various information including traffic information to the navigation device of each vehicle.

Therefore, for this radio beacon,
It is easy to add the function of wirelessly reading the route from the navigation device mounted on the vehicle to the destination of the vehicle.

[0041]

Embodiments of the present invention will be described below with reference to the drawings.

(First Embodiment) FIG. 1 is a schematic diagram showing a part of the traffic network shown in FIG. 5 to which a traffic information processing system according to a first embodiment of the present invention is applied. 5 and 6
The same reference numerals are given to the same parts. For simplicity of description, it is assumed that the road network to which the traffic information processing system according to the first embodiment is applied is a toll road expressway network.

In FIG. 1, each road 1 constituting the road network
1 is provided with a plurality of interchanges 12.
In front of the junction 2 of the road 11, an antenna 15 for wirelessly providing various kinds of prediction information to the electric bulletin board 6 and each vehicle 13 passing the corresponding position is provided. Road 1
The vehicle detector 1 is disposed at each of the positions 1.

Each of the vehicle detectors 1 outputs a traffic volume I ₁ , I ₂ , I such as a vehicle traffic volume, a vehicle speed, a vehicle density, and a degree of congestion per unit time at a corresponding position at a constant period T such as a 5-minute interval. ₃ ,
... detects the I _n, to the management center.

Each vehicle 13 is equipped with a navigation device 16 shown in FIG. 2 and constantly receives radio waves from GPS satellites 14.

As shown in FIG. 2, the interchange 12 is provided with an IC (interchange) device 19 in which an automatic toll collection device 17 and a route information transmitting section 18 are incorporated. This IC device 19 is used for the interchange 12
It is provided at the entrance gate inside.

The automatic toll collection device 17 provides a navigation device 16 mounted on a vehicle 13 which enters the road 11 non-stop at the entrance gate of the interchange 12 to the navigation device 16 which also serves as an on-vehicle device.
Information for calculating a toll at an exit gate of another IC 12 consisting of an IC number specifying a (tollgate), an entry time, etc., is wirelessly written, and the navigation device 16 is used.
Similarly, the route to the destination of the vehicle 13 is wirelessly read. The route read wirelessly by the automatic toll collection device 17 is transmitted by a route information transmitting unit 18 to a management center that manages the entire road network via a communication line.

In the navigation device shown in FIG.
The radio wave from the S satellite 14 is received by the receiving unit 20 and transmitted to the position calculating unit 21. The position calculation unit 21 receives the received GP
Using the S signal, the current position of the vehicle 13 is calculated,
It is sent to the display 22 and the route calculation unit 25. Display 22
Displays a map of the area read from the map memory 23, and the current position received from the position calculation unit 21 is displayed on the map.

The destination inputted by the operator via the destination input unit 24 is sent to the route calculating unit 25. Specifically, the operator indicates a destination on the map displayed on the display 22 with, for example, a finger or a touch pen. The map from the map memory 23 is input to the route calculation unit 25. Then, the route calculation unit 25 calculates a route from the current position to the destination using the input map.

The route calculating section 25 displays the calculated route on the display 2
8 is displayed on the map displayed by, for example, a red line to the destination, and the calculated route is stored in the route memory 2.
Write to 6. Specifically, the route written in the route memory 26 includes each of the principles 11 to the destination, each of the branch points 2 to pass, and the traveling direction at each of the branch points 2.

The navigation device 16 includes a vehicle I including a vehicle number for identifying the vehicle 13.
A vehicle ID memory 28 for storing D is provided. Further, the navigation device 16 includes an antenna 31, a transmission unit 27, and a reception unit 3 for wirelessly transmitting and receiving various information to and from the automatic toll collection device 17 of the IC device 19.
0, and a reception memory 29 are provided.

When the vehicle 13 equipped with such a navigation device 16 passes through the entrance gate of the interchange 12, the automatic toll collection device 17 of the IC device 19 is used.
Transmits an IC number and an entry time and a route transmission request to the vehicle 13.

The receiver 30 of the navigation device 16 of the vehicle 13 stores the received IC number and the entry time in the reception memory 29.
And transmits the received route transmission request to the transmission unit 27.
Transfer to The transmission unit 27 transmits the route stored in the route memory 26 wirelessly to the automatic toll collection device 1 of the IC device 19.
Send to 7.

Note that this vehicle 13 is the interchange 1
When exiting from the exit gate 2, the transmission unit 27 transmits the IC number and the entry time stored in the reception memory 29 and the vehicle ID read from the vehicle ID memory 28 to the automatic toll collection device 17.

FIG. 3 is a block diagram showing the overall configuration of the traffic information processing system according to the first embodiment.

[0056] Each traffic I ₁ sequentially input at a predetermined period T from the vehicle detector _{1, I 2, I 3,} ..., I n is input to the prediction computation unit 32. On the other hand, each of the routes K ₁ , K ₂ , K ₃ ,..., K _n that are input each time the vehicle 13 enters the road 11 from each IC device 19 of each interchange 12 (the suffix is an IC number specifying the interchange 12) Is input to the traffic flow pattern correction unit 33.

In the traffic pattern memory 34, the predicted shunt ratios α ₁ , α ₂ , α ₃ ,..., Α _{n at} all the branch points 2 in the road network shown in FIG. It is stored as a traffic flow pattern. However, the shunt ratio alpha of the branching point 2, as shown in FIG. 6 includes a shunt ratio alpha _C for predicting shunt ratio alpha _B and another road for one of the road [alpha (alpha _B,
α _C )].

[0058] traffic flow pattern modifying unit 33, the path K ₁ input, K _2, K _3, ..., based on K _n, each prediction shunt at each branching point 2 stored in the traffic pattern memory 34 Correct the ratios α ₁ , α ₂ , α ₃ ,..., Α _n . Specifically, for example, each time a fixed period T such as 5 minutes elapses, each of the paths K ₁ , K ₂ ,
K _3, ..., the traveling direction in each branch point 2 contained in K _n, over all the branch points 2 in the road network shown in FIG. 5, by summing at each branch point 2, each branch point 2 It predicted shunt ratio beta _{1 of, β 2, β 3, ...} , and calculates the beta _n.

The traffic pattern is stored in the traffic pattern memory 34.
Predicted shunt ratio α₁, Α_Two, Α_Three,…, Α_nWhen
Each deviation (α₁―Β₁), (Α_Two―Β_Two), (Α_Three―Β
_Three),…, (Α_n―Β_n), And for each of these deviations
Multiplied by a preset correction rate P (0 <P <1)
Each deviation P (α₁―Β₁), P (α_Two―Β_Two), P (α _Three
―Β_Three) ..., P (α_n-Α_n) Is the original predicted shunt ratio α
₁, Α_Two, Α_Three,…, Α_nIs added to.

Therefore, the predicted shunt ratios α ₁ , α ₂ , α ₃ ,..., Α _{n at the} respective branch points 2 stored in the traffic flow pattern memory 34 are determined by the vehicle 1 at regular intervals T.
3 is updated to the latest value according to the route to be taken.

The prediction calculation unit 32 calculates the traffic volumes I ₁ , I ₂ , I ₃ , and the like sequentially input from each vehicle detector 1 at a constant period T.
..., predicted shunt ratio alpha ₁ for each branch point 2 stored in the prediction program and traffic flow pattern memory 34 is previously set for the I _n, alpha _2, alpha _3, ..., traffic stream comprising alpha _n A prediction operation is performed using the pattern and a predetermined time T such as 30 minutes from each input time t of the predetermined period T.
The predicted traffic conditions J ₁ , J ₂ , J ₃ ,..., J at each position on the road network at each time (t + Td) after d has elapsed.
_n (each suffix indicates information of each position) is sequentially obtained and transmitted to the next traffic control unit 35.

The predicted traffic conditions J ₁ , J at each position
₂ , J ₃ ,..., J _n include a predicted traffic amount, a predicted vehicle speed, a predicted vehicle density, a predicted congestion degree, and the like at the corresponding position.

The traffic control section 35 predicts traffic conditions J ₁ , J ₂ , J ₃ ,
... on the basis of the J _n, if an alarm is necessary, the alarm output section 3
6 to send alarm information. The alarm output unit 36 outputs, for example, a congestion occurrence prediction that specifies the occurrence position on the electric display panel 6 installed before the junction 2. Further, the alarm output unit 36 outputs, via a transmitter 37 and the antenna 15, radio waves of the congestion occurrence prediction designating the above-described occurrence position to the vehicle 13 traveling near the installation position of the antenna 15.

In the traffic information processing system configured as described above, the navigation device 16 mounted on each vehicle 13 entering the road 11 from each interchange 12 disposed along each road 11 constituting the road network. A route K from the vehicle to the destination of the vehicle 13 is read wirelessly.

That is, in the navigation device 16, when the operator (driver) specifies the destination of the vehicle 13 on, for example, a display screen, the vehicle travels on which road 11 and which branch point 2 and which direction. Information on whether to proceed to is displayed graphically on the display 22.

Each of the routes K ₁ and K ₁ read from each vehicle 13 entering the road 11 from each interchange 12
_2, K _3, ..., based on the K _n, traffic pattern memory 3
Each predicted shunt ratio alpha ₁ at each branching point 2 stored in the _{4, α 2, α 3,} ..., α n is automatically corrected. In this case, the degree of correction is determined based on a preset correction rate P (0 <P <1). That is, when the route collection cycle T is long and the number of route samples is large, the degree of correction may be increased. When the route collection cycle T is short and the number of route samples is small, the correction level may be reduced.

Note that, even when the ratio of the vehicles 13 equipped with the navigation device 16 is small, the correction rate P (0 <P <
1) may be set low.

As described above, the traffic flow pattern including the predicted shunt ratio α of the vehicle 13 passing through each branch point 2 stored in the traffic flow pattern memory 34 is converted into the traffic flow pattern from each vehicle 13 going to the corresponding branch point 2. Is corrected using the route K to be traveled obtained from the vehicle.

Therefore, even if an unusual car flow occurs, such as when an event is held, the traffic flow pattern changes in accordance with the flow of the car. Also the prediction operation unit 32
In predicted traffic conditions J ₁ of each position on the road network including congestion occurrence _{prediction, J 2, J 3, ...} , it is possible to accurately obtain the J _n.

(Second Embodiment) FIG. 4 is a block diagram showing a schematic configuration of a traffic information processing system according to a second embodiment of the present invention. The same parts as those in the traffic information processing system according to the first embodiment shown in FIG. Therefore, the detailed description of the overlapping part is omitted.

In the traffic information processing system of the second embodiment, instead of the traffic flow pattern correction unit 33 in the traffic information system of the first embodiment, a diverting ratio calculation unit 38 is provided.

The shunt ratio calculating unit 38 outputs a constant time longer than the fixed period T of the system of the first embodiment, such as 20 minutes each time the vehicle 13 enters the road 11 from the IC device 19 of each interchange 12. each time period T ₁ is passed, corresponding each path is input in the cycle T ₁ K _1, K _2,
K _3, ..., the traveling direction in each branch point 2 contained in K _n, over all the branch points 2 in the road network shown in FIG. 5, by summing at each branch point 2, each branch point 2 each predicted shunt ratio beta _{1 of, β 2, β 3, ...} , and calculates the beta _n.

The shunt ratio calculating section 38 calculates the predicted shunt ratios β ₁ , β ₂ , β ₃ , calculated for each fixed period T ₁ such as 20 minutes.
.., Β _n are transmitted to the traffic flow pattern memory 34, and each branch point 2 stored in the traffic flow pattern memory 34 is transmitted.
Each predicted shunt ratio alpha _{1 in, α 2, α 3, ...} , α each prediction diversion ratio beta _{1 n} was calculated this _{time, β 2, β 3, ...} , β
Update with _n .

That is, in the traffic flow pattern memory 34, the predicted quantity ratios α ₁ , α calculated based on the routes K ₁ , K ₂ , K ₃ ,..., K _n read from the navigation device 16 of each vehicle 13. A traffic flow pattern including only ₂ , α ₃ ,..., Α _n is stored.

Therefore, the prediction calculation unit 32 determines that each vehicle 1
3 based on the predicted volume ratios α ₁ , α ₂ , α ₃ ,..., Α _n obtained from the route to which the vehicle actually goes, J ₁ , J ₂ , J ₃ , , _Jn are calculated, so that substantially the same effects as in the traffic information processing system of the first embodiment can be obtained.

(Third Embodiment) Next, a traffic information processing system according to a third embodiment will be described.

In the traffic information processing system of the third embodiment, wireless beacons are provided at equal intervals along each road 11 of the road network. Each of the wireless beacons is transmitted to a navigation device 16 mounted on a vehicle 13 running near the road 11 on which the wireless beacon is installed.
Various information including traffic information is provided wirelessly.

The navigation device 16 mounted on the vehicle 13 outputs various kinds of information received from the radio beacon to the display 22 and outputs sound.

Further, in the radio beacon employed in the traffic information processing system of the third embodiment, in addition to the function of providing various kinds of information to the vehicle 13 described above, the radio beacon may be provided to the navigation device 16 for 5 minutes, for example. The route transmission request is wirelessly transmitted at a constant period T such as the above. Wireless beacons
Since the running vehicles 13 are installed at relatively short intervals in order to receive various information without interruption, a route transmission request is always transmitted to all the vehicles 13 at the same timing.

The receiving unit 30 of the navigation device 16 of the vehicle 13 transfers the received route transmission request to the transmitting unit 27. The transmitting unit 27 wirelessly transmits the route stored in the route memory 26 to the wireless beacon.

The wireless beacon transmits each route received from each vehicle 13 to the traffic flow pattern correction unit 33 of the first embodiment shown in FIG. 3 or the diverting ratio calculation unit 38 of the second embodiment shown in FIG. Send.

As a result, the traffic pattern in the traffic flow pattern memory 34 is always updated with each newest route, so that substantially the same effects as those of the above-described embodiments can be obtained.

Further, in the traffic information processing system of the third embodiment, the vehicle 1
Since the traffic condition prediction is performed using the route collected from No. 3, the prediction accuracy can be further improved.

[0084]

As described above, in the traffic information processing system of the present invention, a route to a destination of a corresponding vehicle in a navigation device mounted on each vehicle traveling on a road network is read wirelessly. The predicted shunt ratio at each branch point of the road network is corrected or updated from the read route. Then, the traffic situation at each position after a predetermined time is predicted using the traffic flow pattern including the predicted split flow ratio.

Therefore, even if road use conditions that cannot be predicted occur, traffic conditions including traffic congestion prediction can be accurately predicted, correct predicted traffic conditions can be provided to each vehicle, and reliability is greatly improved. Can be improved.

[Brief description of the drawings]

FIG. 1 is an enlarged view showing a part of a road network to which an intersection information processing system according to a first embodiment of the present invention is applied;

FIG. 2 is a block diagram showing a schematic configuration of a navigation device mounted on a vehicle to which the intersection information processing system according to the first embodiment is applied;

FIG. 3 is a block diagram showing a schematic configuration of an exchange information processing system according to the first embodiment;

FIG. 4 is a block diagram showing a schematic configuration of an intersection information processing system according to a second embodiment of the present invention;

FIG. 5 is a diagram showing a general road network;

FIG. 6 is a diagram showing a situation of a branch point in a road network;

FIG. 7 is a diagram showing a pattern of a predicted shunt ratio at a branch point;

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 ... Vehicle detector 2 ... Junction point 6 ... Electric bulletin board 11 ... Road 12 ... Interchange 13 ... Vehicle 14 ... GPS satellite 15 ... Antenna 16 ... Navigation device 17 ... Automatic toll collection device 18 ... Route information transmission part 19 ... IC device 20 , 30 ... Receiving unit 21 ... Position calculating unit 22 ... Display unit 25 ... Route calculating unit 27, 37 ... Transmission unit 32 ... Prediction calculation unit 33 ... Traffic flow pattern correction unit 34 ... Traffic flow pattern memory 35 ... Traffic control unit 36 ... Alarm output unit 38: Dividing ratio calculation unit

Claims (4)

[Claims] 1. A traffic flow pattern memory for storing a traffic flow pattern including at least a predicted shunt ratio of a vehicle passing through each branch point in a road network, and a traffic flow pattern memory detected by a vehicle detector installed at each position in the road network. A prediction calculation unit that performs a prediction calculation using the traffic flow pattern stored in the traffic flow pattern memory for each traffic volume, and calculates a predicted traffic situation at each position after a predetermined time in the road network; Prediction information providing means for providing prediction information to each vehicle based on the predicted traffic situation calculated by the prediction calculation unit; and a route from a navigation device mounted on the vehicle traveling on the road network to a destination of the vehicle. Reading means for wirelessly reading the traffic flow pattern, and correcting the traffic flow pattern stored in the traffic flow pattern memory based on the route information read by the route reading means. Traffic information processing system comprising a traffic flow pattern modification means. 2. A route reading unit for wirelessly reading a route from a navigation device mounted on a vehicle traveling on a road network to a destination of the vehicle, and a road network based on the route information read by the route reading unit. A shunt ratio calculating means for calculating a predicted shunt ratio of a vehicle passing through each branch point in; a traffic flow pattern memory for storing a traffic flow pattern including at least the predicted shunt ratio calculated by the shunt ratio calculating means; For each traffic detected by the vehicle detector installed at each position of the road network, a prediction calculation is performed using the traffic flow pattern stored in the traffic flow pattern memory, and after a predetermined time in the road network, A prediction calculation unit that calculates a predicted traffic situation at each position of the vehicle; and a prediction information that provides prediction information to each vehicle based on the predicted traffic situation calculated by the prediction calculation unit. Traffic information processing system including a providing means. 3. The route reading means is provided at each tollgate of a road network, and automatically writes at least information specifying the corresponding tollgate to a vehicle-mounted device of a vehicle entering the road network by wireless. 3. The traffic information processing system according to claim 1, wherein the traffic information processing system is incorporated in a toll collection device. 4. The method according to claim 1, wherein the route reading means is provided along each road of a road network, and is incorporated in a wireless beacon for providing various information to the navigation device. The traffic information processing system as described.