TW201545133A - An abnormal vehicle detecting device, an abnormal vehicle detection method, and an abnormal vehicle detection program - Google Patents

Abstract

An abnormal vehicle detecting device including; a traffic state value calculating unit which calculates the traffic state value indicating traffic conditions within a predetermined target area in a predetermined target time zone, based on the vehicle information indicating the position and traveling speed of the vehicle obtained from the on-board vehicle-mounted device on a vehicle; and an abnormal vehicle extraction unit which extracts abnormal vehicles based on the running condition in the vehicle information acquired from the vehicle-mounted device of the vehicle.

Description

Abnormal vehicle detection device, abnormal vehicle detection method and program

The present invention relates to an abnormal vehicle detecting device, an abnormal vehicle detecting method, and a program.

The present application claims priority based on Japanese Patent Application No. 2014-033875, filed on Feb. 25, 2014, the disclosure of which is incorporated herein.

There is a detection result based on the received signal and the acceleration sensor obtained by the satellite positioning system to specify the position of the vehicle, and based on the map information prepared in advance, the map corresponding to the specific position is obtained. A vehicle-mounted device of a vehicle position (for example, refer to Patent Document 1). In such a vehicle-mounted device, for example, when there is a case where it is determined that the vehicle is traveling on a toll road based on the position of the vehicle on the map, the toll of the toll road is charged. In addition, there is also information for transmitting the information of the vehicle position on the representative map obtained by the vehicle-mounted device to the central server, and causing the central server or the like to generate traffic representing the congestion state of the traffic jam or the vehicle based on the received information. Information person. In this way, by the vehicle-mounted device The acquired information representing the location of the vehicle is utilized in various processes.

[Previous Technical Literature] [Patent Literature]

[Patent Document 1] Japanese Patent Laid-Open Publication No. 2009-115588

However, when the vehicle position acquired by the vehicle-mounted device is falsified by some methods, there is a problem that the processing is performed based on information that is not the actual vehicle position and an incorrect processing result is generated.

The present invention has been made in view of such a situation, and an object thereof is to provide an abnormal vehicle capable of detecting that the information obtained by the vehicle-mounted device is different from the actual vehicle condition. Abnormal vehicle detection device, abnormal vehicle detection method, and program.

According to the first aspect of the present invention, the abnormal vehicle detecting device is characterized in that the traffic state value calculating unit is based on a position of the vehicle that is obtained from the vehicle-mounted device mounted on the vehicle and Vehicle information of the traveling speed to calculate a traffic state value representing a traffic state in a specific target area in a specific object time zone; and an abnormality The vehicle detection unit is based on the traffic state value calculated by the traffic state value calculation unit and the vehicle information acquired from the vehicle-mounted device of each vehicle, and the traveling state of the vehicle displayed by the vehicle information is The vehicle traveling in the object area is detected by an abnormal vehicle.

With this configuration, it is possible to distinguish the possibility that the information acquired by the vehicle-mounted device differs from the actual vehicle condition based on the relationship with the other vehicles traveling on the same road. The vehicle is detected.

According to a second aspect of the present invention, in the first aspect, the abnormal vehicle detecting unit acquires a speed in the target area as the traffic state value calculated by the traffic state value calculating unit. When the amount of deviation between the speed in the target area and the traveling speed of the vehicle exhibited by the vehicle information exceeds a specific allowable range, it is determined that the traveling state of the vehicle is abnormal.

According to this configuration, it is possible to make the vehicle that does not correspond to the traffic state in the target area, that is, to have a height in the target area, and to become a vehicle that cannot travel at the traveling speed included in the vehicle information. , detected as an abnormal vehicle. Therefore, it is possible to tamper with the vehicle information and detect itself as if it is traveling in the target area.

According to a third aspect of the present invention, in the second aspect, the abnormal vehicle detecting unit acquires a density of a vehicle in the target area as the traffic state value calculated by the traffic state value calculating unit. When the density of the vehicle in the aforementioned object area is more than the threshold When the amount of deviation is higher than a specific allowable range, it is determined that the traveling state of the vehicle is abnormal.

According to this configuration, the abnormal vehicle is detected based on the traffic state in a state where the density of the vehicle traveling in the target area is higher than the threshold. In the traffic state where the density of the vehicle is high, it is possible to obtain most of the vehicle information acquired from the vehicle-mounted device. Therefore, it is possible to calculate the traffic state value representing the average traffic state based on the plurality of vehicle information. Further, in a traffic state in which the density of the vehicle is high, it is conceivable that the interval with other vehicles is narrow, and there is no space that can travel at a faster speed than the average speed in the target area. Therefore, the speed that can be traveled in the target area depends on the traffic state and is close to the speed of the traffic state in the representative target area. In this way, since the abnormal vehicle can be detected based on the traffic state value in a state in which the traveling speed of the vehicle traveling in the target area is restricted to some extent, it is possible to make the abnormal vehicle Detection accuracy is improved.

According to a fourth aspect of the present invention, in any one of the first to third aspects, the traveling speed calculation unit is obtained from the same vehicle-mounted device at a timing different from each other. The vehicle speed is calculated based on the position information of at least two points of the vehicle represented by the vehicle information, and the abnormal vehicle detecting unit determines the vehicle information based on the traveling speed calculated by the traveling speed calculating unit. The displayed driving state of the vehicle is regarded as abnormality in the vehicle traveling in the aforementioned target area.

By this configuration, it is possible to base on a vehicle included in the vehicle information. The position is calculated based on the position of the vehicle. When the position of the vehicle included in the vehicle information has been tampered with, it is conceivable that the traveling speed of the vehicle calculated based on the position of the vehicle may deviate from the actual traveling speed. Therefore, it is possible to detect a vehicle having a high possibility that the position of the vehicle included in the vehicle information has been tampered with as an abnormal vehicle.

According to a fifth aspect of the present invention, in any one of the first to third aspects, the traffic state estimation unit is configured to be a specific object in a specific target time zone. When the density of the vehicle information in the area is less than the threshold value, the traffic state in the specific target area in the specific target time zone is estimated, and the traffic state value calculation unit is the density of the vehicle information. When the threshold value is equal to or greater than the threshold value, the traffic state value is calculated, and the abnormal vehicle detecting unit determines the traveling state of the vehicle displayed by the vehicle information based on the traffic state estimated by the traffic state estimating unit. Whether the vehicle traveling in the aforementioned object area is abnormal.

With this configuration, when the vehicle information in the specific target area in the specific target time zone is small, the traffic state of the specific target area in the specific target time is estimated. Here, when the density of the vehicle information is low, since only a small amount of vehicle information can be acquired, it is possible to evaluate the traffic state based on the biased vehicle information or to be in a special state according to chance. The state of the vehicle is used to evaluate the traffic status. However, when the density of the vehicle information is lower than the threshold, by not based on the object The vehicle information obtained in the intervening zone is used to extract the traffic state value, and the traffic state is estimated, and the traffic state value is calculated based on the estimated traffic state, even if the vehicle information density is low. An abnormal vehicle can be detected based on the average traffic state.

According to a sixth aspect of the present invention, in any one of the first to third aspects, the report unit further includes a vehicle that is determined to be abnormal by the abnormal vehicle detecting unit.

With this configuration, it is possible to provide information on the abnormal vehicle, a manager who manages the payment for the toll road, a monitor that monitors the traffic situation based on the vehicle information, or a vehicle that is determined to be an abnormal vehicle. Drive and report.

According to a seventh aspect of the present invention, in any one of the first to third aspects, the correction unit is configured to detect that the abnormal vehicle detecting unit is abnormal. Information on the correction of the vehicle's levy status.

According to this configuration, the correction unit generates information for correcting the correction status to be corrected, and the processing for correcting the situation can be performed.

According to the eighth aspect of the present invention, the abnormal vehicle detecting device includes an abnormal vehicle detecting unit that is based on a position and a traveling speed of the vehicle obtained from the vehicle-mounted device mounted on the vehicle. Determining, in the vehicle information, the vehicle information in the specific target area in the specific object time zone, determining whether the vehicle traveling state exhibited by the vehicle information is the vehicle traveling in the target area Abnormal.

According to this configuration, it is possible to detect an abnormal vehicle in which the information acquired by the vehicle-mounted device and the actual vehicle condition are different. For example, the abnormal vehicle detecting device calculates the traveling speed of the vehicle traveling on the moving trajectory obtained by connecting the position information based on the position information. At this time, when the position information of the vehicle included in the vehicle information is falsified, the calculated traveling speed of the vehicle may become an abnormally high speed (for example, 200 km/h). The abnormal vehicle detecting unit is capable of detecting such a vehicle as an abnormal vehicle in which the information acquired by the vehicle-mounted device and the actual vehicle condition are different, that is, the vehicle can If the driving speed included in the vehicle information is high, there is a possibility that it is impossible to travel in the target area, and it is most likely that the vehicle traveling on the other road is pretending to be detected in the target area. . Therefore, it is possible to detect a vehicle having a high possibility of tampering with the vehicle information as an abnormal vehicle.

According to a ninth aspect of the present invention, the abnormal vehicle detecting method includes a traffic state value calculating step based on a position and a traveling speed of the vehicle obtained from the vehicle-mounted device mounted on the vehicle. Vehicle information to calculate a traffic state value representing a traffic state in a specific target area in a specific target time zone; and an abnormal vehicle detecting step based on the aforementioned traffic calculated in the traffic state value calculating step The state value and the vehicle information acquired from the vehicle-mounted device of each vehicle are used to detect the traveling state of the vehicle displayed by the vehicle information as a vehicle having an abnormality in the vehicle traveling in the target area. Come.

With this configuration, it is possible to distinguish the possibility that the information acquired by the vehicle-mounted device differs from the actual vehicle condition based on the relationship with the other vehicles traveling on the same road. The vehicle is detected.

According to the tenth aspect of the present invention, the computer functions as a means for calculating the traffic state value calculation means based on the position of the vehicle obtained from the vehicle-mounted device mounted on the vehicle. And vehicle information of the traveling speed to calculate a traffic state value representing a traffic state in a specific target area in a specific target time zone; and an abnormal vehicle detecting means based on the traffic state value calculating means The traffic state value and the vehicle information acquired from the vehicle-mounted device of each vehicle detect the traveling state of the vehicle displayed by the vehicle information as a vehicle having an abnormality in the vehicle traveling in the target region.

With this configuration, it is possible to distinguish the possibility that the information acquired by the vehicle-mounted device differs from the actual vehicle condition based on the relationship with the other vehicles traveling on the same road. The vehicle is detected.

According to the present invention, it is possible to detect a vehicle in which the position of the vehicle acquired by the vehicle-mounted device and the position of the actual vehicle are different.

1‧‧‧Abnormal vehicle detection system

100‧‧‧Vehicle

200‧‧‧ roadside installation

201‧‧‧Road side antenna

300‧‧‧Abnormal vehicle detection device

500‧‧‧ stored value card

11‧‧‧Communication Department

12‧‧‧ clock

13‧‧‧Location Information Acquisition Department

14‧‧‧Vehicle Status Detection Department

15‧‧‧CPU

16‧‧‧Memory Department

17‧‧‧Reader

101‧‧‧Map Matching Processing Department

102‧‧‧Speed Information Calculation Department

103‧‧‧Vehicle Information Generation Department

104‧‧‧Vehicle Information Output Department

105‧‧‧Training and Processing Department

121‧‧‧Map Information

122‧‧‧Vehicle Information

123‧‧‧ Conditions of Information

31‧‧‧Communication Department

32‧‧‧Registration Department

33‧‧‧Vehicle Information DB

34‧‧‧ Speculation information DB

35‧‧‧Information Information DB

36‧‧‧CPU

37‧‧‧Reporting Department

301‧‧‧Decision Department

302‧‧‧Traffic status value calculation unit

303‧‧‧Travel speed calculation unit

304‧‧‧Abnormal Vehicle Detection Department

305‧‧‧ Traffic Status Estimation Department

306‧‧‧Learning Department

307‧‧‧Amendment

Fig. 1 is a schematic view showing an example of an abnormal vehicle detecting system 1 of one embodiment of the present invention.

[Fig. 2] is a diagram showing a part of a road included in the map information.

FIG. 3 is a diagram showing the distribution of vehicle information acquired in the road shown in FIG.

FIG. 4 is a diagram showing an example of the distribution of the vehicle in the target area at a specific time.

FIG. 5 is a diagram showing the traveling position and the traveling speed on the map of the vehicle 400 based on the five pieces of vehicle information S11 to S15 acquired by the vehicle 400.

FIG. 6 is a block diagram showing an example of the configuration of the vehicle-mounted device 100.

FIG. 7 is a block diagram showing a configuration example of the abnormal vehicle detecting device 300.

FIG. 8 is a flowchart for explaining an example of processing performed by the vehicle-mounted device 100.

FIG. 9 is a flowchart for explaining an example of the entire processing performed by the vehicle-mounted device 100.

FIG. 10 is a flowchart for explaining an example of abnormal vehicle extraction processing.

[First Embodiment]

Hereinafter, an example of the abnormal vehicle detecting system 1 of one embodiment of the present invention will be described. Fig. 1 is a schematic view showing an example of an abnormal vehicle detecting system 1 of one embodiment of the present invention.

(all components)

As shown in FIG. 1, the abnormal vehicle detecting system 1 is provided with a vehicle-mounted device 100, a roadside device 200, and an abnormal vehicle detecting device 300.

The vehicle-mounted device 100 is mounted on the vehicle 400, generates vehicle information, and the like, and is sent to the roadside device 200. In the vehicle information, information representing the position of the vehicle 400 and information representing the traveling speed of the vehicle 400 are included.

In addition, although the illustration is omitted, the roadside apparatus 200 receives vehicle information and the like from the vehicle-mounted device 100 of the vehicle 400 that has passed through it, and transmits it to the abnormal vehicle detecting device 300. Therefore, at the abnormal vehicle detecting device 300, vehicle information from a plurality of vehicle-mounted devices 100 is transmitted.

The roadside device 200 is disposed at a specific roadside such as an intersection. The roadside device 200 is a roadside antenna 201 that is disposed at the roadside The connection is made and communicates with the vehicle-mounted device 100 located in the communication area via the roadside antenna 201. The roadside device 200 is required to transmit information such as vehicle information to the vehicle-mounted device 100, and to receive vehicle information from the vehicle-mounted device 100. Here, the vehicle-mounted device 100 transmits all the vehicle information and the like generated after the previous communication with the roadside device 200 to the roadside device 200.

The abnormal vehicle detecting device 300 receives the vehicle information from the roadside devices 200 installed in the respective places, and detects the traveling state as the abnormal vehicle 400 based on the received vehicle information. In the present embodiment, the abnormal vehicle detecting device 300 calculates a traffic state value representing a traffic state in a specific target region in a specific target time zone. The abnormal vehicle detecting device 300 detects the traveling state of the vehicle 400 displayed by the vehicle information as a vehicle that is abnormal in the vehicle 400 traveling in the target region based on the calculated traffic state value.

The abnormal vehicle detecting device 300 can detect the position information of the vehicle included in the vehicle information and the vehicle used in the course processing by some methods by detecting the abnormal vehicle. The location information has been tampered with to make it a violation of the vehicle that appears to have traveled on a general road and evaded the payment of the amount of the toll road. Moreover, the abnormal vehicle detecting device 300 is capable of tampering with the travel time of the vehicle included in the vehicle information by some methods to make it a relief for the amount of the charge on the toll road. Violating the time zone with the vehicle that traveled and evaded the payment of the amount of the class Detected. In addition, in the case where the location information of the vehicle has been tampered with by some methods, the map information such as the map information registered in the vehicle-mounted device 100 is not updated and causes the road to be driven. The erroneous determination is the case of the closest one of the roads included in the map information.

(about map information)

Here, with reference to FIG. 2, map information for obtaining a position on the map of the vehicle 400 at the vehicle-mounted device 100 will be described. Figure 2 is a diagram showing a part of the road included in the map information.

As shown in FIG. 2, in general, in the road on the map, the node ID and the link ID are assigned. The so-called node ID is the identification information representing a specific location (node) on the road. The connection ID is identification information representing a road area (connection) that is sandwiched by two nodes. In the illustrated road, node ID=N1~N14 and link ID=L1~L11 are assigned respectively.

In addition, the road connecting L2 to L4 is a toll road, and the road other than the road is a general road.

In the present embodiment, the target region refers to at least one connection, and the connection included in the target region is determined in advance. In addition, the target area may be a link including a plurality of links (for example, links L2 to L4).

(Regarding the relationship between the processing of the abnormal vehicle detecting device 300 and the traffic state)

Here, with reference to FIG. 3, the density of vehicle information obtained in the road shown in FIG. 2 will be described. Figure 3 is a diagram showing the distribution of vehicle information obtained in the road shown in Figure 2.

In FIG. 3, based on the vehicle information acquired in the target time zone (for example, ○月○日13:00~13:10), the map of the vehicle traveling on the road shown in Fig. 2 is used. Location for display. In addition, in FIG. 3, the map position of the plural number of the same vehicle acquired in the target time zone is included. That is, FIG. 3 shows a state in which all the vehicle information generated in the target time zone is side by side based on the map position.

As shown in the figure, the density of vehicle information is high at links L1, L6~L8, and L5, and the density of vehicle information is low at links L9 to L11. In addition, the density of vehicle information connected to L2~L4 is lower than that of L1, L6~L8, and L5, and is higher than that of L9~L11. If the density of the vehicle information is such as to be connected to L2 to L4, it can be estimated that the traveling speed of the vehicle traveling on the road is somewhat restricted depending on the traffic state of the vehicle traveling on the road. On the other hand, if the density of the vehicle information is such as to be connected to L9 to L11, it can be estimated that the traveling speed of the vehicle is not restricted based on the traffic state of the vehicle traveling on the road.

Therefore, when the density of the vehicle information is equal to or greater than the threshold value, the abnormal vehicle detecting device 300 obtains the traffic of the target area in the target time zone based on the vehicle information acquired from the vehicle-mounted device 100. status. On the other hand, when the density of vehicle information is not above the threshold In other words, the abnormal vehicle detecting device 300 estimates a method other than the method of extracting the traffic state based on the vehicle information from the vehicle 400 traveling in the target area in the target time zone. Traffic status. For example, the abnormal vehicle detecting device 300 seeks to extract the traffic state of the target region in the target time zone that is simulated by the simulator based on the conditions at which the vehicle information was acquired. Further, the abnormal vehicle detecting device 300 can extract the average traffic state based on the vehicle information generated in the past before the target time zone.

Further, even when the density of the vehicle information is equal to or greater than the threshold value, when there is a deviation in the traveling speed of the vehicle 400 included in the vehicle information, there is a possibility that the vehicle information cannot be reproduced based on the vehicle information. The right traffic state. Therefore, when the density of the calculated vehicle information is equal to or greater than the threshold value, the abnormal vehicle detecting device 300 calculates the variance of the speed based on the traveling speed information included in the vehicle information. When the variation number is equal to or greater than the predetermined threshold value, the abnormal vehicle detecting device 300 estimates the calculation of the traffic state value of the target region. On the other hand, when the number of variations is less than the predetermined threshold value, the abnormal vehicle detecting device 300 calculates the traffic state value of the target area based on the vehicle information.

In the example shown in FIG. 3, the abnormal vehicle detecting device 300 extracts the traffic state of the connection L1 to L8 of the target area in the target time zone based on the vehicle information acquired from the vehicle-mounted device 100.

On the other hand, the abnormal vehicle detecting device 300 estimates the traffic connecting the L9 to the L11 in the target area in the target time zone by the simulator. status.

In the present embodiment, the traffic state value representing the traffic state in the target area in the target time zone includes the distribution of the traveling speed of the vehicle 400 that exists in the target time zone and exists in the target time zone. News. Further, the traffic state value includes information indicating the density of the vehicle 400 in the target area and the average speed in the object area. For example, the traffic state value is 80% of the vehicle 400 representing the vehicle 400 present at the target area (link L1) in the target time zone (for example, ○月○日13:00~13:10) Information such as driving at a speed of 10km/h.

(About abnormal vehicles)

Here, an example of an abnormal vehicle will be described with reference to FIG. 4. Fig. 4 is a diagram showing an example of the distribution of vehicles in the target area at a specific time. Fig. 4 is different from Fig. 3, for example, to cut out an instant contained in the object time zone and to present the distribution of the vehicle in the reproduced traffic state. In Fig. 4(a), a state in which the density of the vehicle in the target area is 75% is displayed. In FIG. 4(b), the state in which the density of the vehicle in the target area is 25% is displayed. Further, in the illustrated example, the target area is a straight road having a road length of 30 m, and the number of lanes is two.

In the example shown in Fig. 4 (a), the state in which nine vehicles are traveling at a speed of 29 to 31 km/h is displayed.

In the example shown in Figure 4(b), it is for two vehicles. At a speed of 20km/h, one vehicle is displayed at a speed of 50km/h.

The density of the vehicle in the target area is obtained by the calculation formula of the following formula (1).

Vehicle density = (number of vehicles × length of vehicle) / (road length × number of lanes)... (1)

In addition, the length of the vehicle is the length of the average length of the vehicle in the longitudinal direction, and can be arbitrarily set.

If the state of Fig. 4(a) is substituted to the right of equation (1), the density of the vehicle is calculated as follows.

(9 cars × 5m) / (30m × 2) = 0.75

If the state of Fig. 4(b) is substituted to the right of equation (1), the density of the vehicle is calculated as follows.

(3 x 5m) / (30m × 2) = 0.25

In this manner, the abnormal vehicle detecting device 300 can obtain a density of 75% of the vehicle in the state shown in FIG. 4(a), and the density of the vehicle in the state shown in FIG. 4(b). It is 25%.

The average speed in the object area is determined by the following The calculation formula of (2) is taken out.

The average speed in the target area = (the sum of the travel speeds of the vehicles in the target area) / (the number of vehicles in the vehicle)... (2)

If the state of Fig. 4(a) is substituted to the right of equation (2), the average velocity in the target region is calculated as follows.

(31+30+31+30+30+30+29+30+29)/(9 cars)=30km/h

If the state of Fig. 4(b) is substituted to the right of equation (2), the average speed in the target region is calculated as follows.

(20+20+50)/(3 cars)=30km/h

In this manner, the abnormal vehicle detecting device 300 can extract the average speed in the target region in the state shown in FIGS. 4(a) and 4(b), and both are 30 km/h.

In the state where the density of the general vehicle shown in FIG. 4(a) is high, when the traveling speed (for example, 50 km/h) which is excessively different from the average speed (30 km/h) in the target area is mixed, the vehicle travels. In the case of a vehicle, it can be inferred that the vehicle does not correspond to the traffic state in the target area, that is, there is a possibility that the height may be unable to travel within the target area at a speed corresponding to the traffic state. . Therefore, abnormal vehicles The detecting device 300 is a vehicle in which the traveling speed is 50 km/h in the state shown in FIG. 4(a), and it is considered that the traveling state of the vehicle is abnormal as a vehicle traveling in the target area. And detected.

On the other hand, in the state where the density of the general vehicle shown in FIG. 4(b) is low, although the average speed in the target area is also 30 km/h, even if the mixed speed is 50 km/h. The vehicle does not recognize that the vehicle does not correspond to the traffic state in the target area, that is, it cannot be determined that it has a high degree of possibility that it cannot travel in the target area at a speed corresponding to the traffic state. This is because, in the case where the density (25%) of the vehicle as a general state as shown in FIG. 4(b) is low, it is ensured that it is sufficiently capable of being faster than the average speed in the target area. The space for driving. Therefore, it is possible to determine a state in which the vehicle traveling at a traveling speed that is excessively different from the average speed in the target region is abnormal, and the density of the vehicle is limited to a specific value as in the state shown in the diagram (a). Higher situation.

In the state shown in FIG. 4(b), when the traveling speed of the vehicle 400 is outside the range of the traveling speed when traveling on a normal road, for example, when it is 200 km/h. In the case of the abnormal vehicle detecting device 300, the vehicle 400 having a traveling speed of 200 km/h is regarded as an abnormal state of the vehicle traveling in the target area and detected.

Further, the abnormal vehicle detecting device 300, when the amount of change in the traveling speed of the vehicle 400 in the time series is equal to or greater than the threshold value, or when there is a difference in the amount of change, Detected as an abnormal vehicle. Referring to Fig. 5, a specific example will be described. FIG. 5 is a diagram showing the traveling position and the traveling speed on the map of the vehicle 400 based on the five pieces of vehicle information S11 to S15 acquired by the vehicle 400. The vehicle information S11~S15 is, for example, vehicle information generated every one second. Further, in the illustrated example, it is assumed that the map position of the vehicle information S12 to S14 has been tampered with.

As shown in the figure, in the vehicle information S11 to S15, information indicating that the traveling speed is 31 km/h is included. Further, in the vehicle information S11 to S15, information indicating that the map position is P11 to P15 is included. The abnormal vehicle detecting device 300 calculates the traveling speed of the vehicle 400 between the respective locations based on the distance between the respective locations and the moving time based on the map positions P11 to P15. The abnormal vehicle detecting device 300 calculates the traveling speed between P11 and P12 and between P14 and P15, and assumes that the system is 70 km/h. On the other hand, the travel speed between P12 and P13 and between P13 and P14 is assumed to be 31 km/h. As such, when there is a staggered change in the travel time of the vehicle 400 in the time series, the vehicle 400 is detected as an abnormal vehicle. Further, in such a state, the abnormal vehicle detecting device 300 can determine that the amount of change in the time series of the traveling speed of the vehicle 400 is equal to or greater than the predetermined threshold value, and the vehicle 400 is used as the vehicle 400. Detected by an abnormal vehicle. Thereafter, the abnormal vehicle detecting device 300 can compare with the traveling speed information included in the vehicle information, and determines that the traveling speed between P11 and P12 and between P14 and P15 is abnormal. In this case, the abnormal vehicle detecting device 300 is capable of The possibility of tampering with the location of the map was found to be high vehicle information S12~S14.

(Composition of the vehicle-mounted device 100)

Next, a configuration example of the vehicle-mounted device 100 will be described with reference to FIG. Fig. 6 is a block diagram showing a configuration example of the vehicle-mounted device 100.

The vehicle-mounted device 100 includes a communication unit 11 and a clock 12, a position information acquisition unit 13, a vehicle state detection unit 14, a CPU 15, a storage unit 16, and a reader/writer 17.

The communication unit 11 performs short-range communication with the roadside device 200, for example. The communication unit 11 is not limited thereto. For example, the communication unit 11 can communicate with the roadside device 200 via the Internet.

The clock 12 measures the date and time at which the date is present, and outputs information representing the current date and time (hereinafter referred to as current date and time information) to the CPU 15.

The location information acquisition unit 13 acquires location information representing the current location of the vehicle 400 using a satellite positioning system, for example, and outputs the location information to the CPU 15.

The vehicle state detecting unit 14 is a detecting unit that detects a change in the state of the vehicle 400. The vehicle state detecting unit 14 includes, for example, a sensor that detects the number of revolutions of the engine, and outputs information representing the number of revolutions of the engine of the vehicle 400. Further, the vehicle state detecting unit 14 may include an acceleration sensor, a geomagnetic sensor, and the like, and output information (hereinafter, referred to as orientation information) representing the forward direction of the vehicle 400.

The CPU 15 is a control unit that performs overall control of the vehicle-mounted device 100. The CPU 15 includes a map matching processing unit 101, a speed information calculation unit 102, a vehicle information generation unit 103, a vehicle information output unit 104, and a course processing unit 105.

In the memory unit 16, map information 121, vehicle information 122, and course condition information 123 are stored.

The map information 121 is a general information that is attached to each location on the map and the latitude and longitude, and is used to specify the position on the map according to the latitude and longitude in the map matching processing. .

The vehicle information 122 is the vehicle information generated by the vehicle information generating unit 103 and is information that is temporarily stored until it is sent to the roadside device 200.

The levy condition information 123 is a body that associates the position of the levy area of the toll road and the amount of the levy in the levy area, and extracts the information based on the vehicle 400 during the course of the levy. The general information used when calculating the amount of the course calculated on the map.

The reader/writer 17 reads and writes the amount information for the stored value card 500 having a specific amount of stored value. The reader/writer 17 reads the information representing the amount of the stored value from the stored value card 500 in the course processing performed by the class processing unit 105, and displays the amount from the read amount. The information on the payment of the amount of the amount is written into the stored value card 500.

The map matching processing unit 101 refers to the map information 121 and specifies the position on the map of the vehicle 400 based on the position information input from the position information acquiring unit 13. The map matching processing unit 101 will The information representing the position on the map of the vehicle 400 (hereinafter referred to as a map position) (hereinafter referred to as map position information) is output to the vehicle information generating unit 103. Further, the map matching processing unit 101 can specify the position on the map of the vehicle 400 based on the orientation information detected by the vehicle state detecting unit 14.

The speed information calculation unit 102 acquires the traveling speed of the vehicle 400 based on the detection result of the vehicle state detecting unit 14, and outputs information representing the acquired traveling speed of the vehicle 400 (hereinafter referred to as traveling speed information) to The vehicle information generating unit 103 is located. For example, the speed information calculation unit 102 calculates and detects the rotation of the engine based on the output from the sensor that detects the number of revolutions of the engine among the sensors included in the vehicle state detecting unit 14. The number of corresponding vehicles 400 traveling speed.

The vehicle information generation unit 103 generates a representative based on the map position information input from the map matching processing unit 101, the travel speed information input from the speed information calculation unit 102, and the current date and time information input from the clock 12. The map position and travel speed of the vehicle 400 at the timing of generation of the vehicle information and the vehicle information at the time of the travel date. The timing at which the vehicle information is generated, for example, is determined to be at a timing after a certain time elapses from the generation of the previous vehicle information or after a certain distance is traveled. In the case of the former, the vehicle information generation unit 103 generates a representative vehicle at the time of determination when it is determined that a predetermined time has elapsed since the previous vehicle information was generated based on the information input from the clock 12. 400 map location and driving speed and driving day Vehicle information at the time of the event. In the latter case, the vehicle information generation unit 103 determines that the vehicle 400 has traveled a specific distance from the map position at which the previous vehicle information was generated based on the information input from the speed information calculation unit 102. At the time, vehicle information representing the map position and the traveling speed of the vehicle 400 at the time of determination and the traveling date and time are generated. The vehicle information generation unit 103 outputs the generated vehicle information to the vehicle information output unit 104 and the course processing unit 105, respectively.

Further, the vehicle information generating unit 103 generates vehicle information including identification information unique to the vehicle-mounted device 100. Further, the vehicle information generating unit 103 can also generate, as the map position information, information for displaying the map position obtained by the map matching processing unit 101 by connecting the ID and the node ID.

The vehicle information output unit 104 outputs the vehicle information generated by the vehicle information generating unit 103 to the roadside device 200 via the communication unit 11. Further, the vehicle information output unit 104 outputs information indicating the result of the course processing by the class processing unit 105 (hereinafter referred to as class information) to the roadside device 200 via the communication unit 11.

The class processing unit 105 performs the course process based on the vehicle information input from the vehicle information generating unit 103 with reference to the course condition information 123. Specifically, the class processing unit 105 calculates the amount of the amount requested for the vehicle 400 when the map position of the vehicle 400 is within the course area to be the subject of the examination. The class processing unit 105 subtracts the calculated amount of the course from the stored value of the stored value card 500 through the reader/writer 17.

The class processing unit 105 outputs the class information representing the result of the executed course processing to the vehicle information output unit 104. The class processing unit 105 is based on the output from the clock 12, and includes information on the date and time of the course on which the course processing was performed, in the course information.

(Composition of abnormal vehicle detecting device 300)

Next, a configuration example of the abnormal vehicle detecting device 300 will be described with reference to FIG. 7. FIG. 7 is a block diagram showing a configuration example of the abnormal vehicle detecting device 300.

The abnormal vehicle detecting device 300 includes a communication unit 31, a registration unit 32, a vehicle information DB (Data Base) 33, a speculative information DB (Data Base) 34, a lesson information DB 35, and a CPU 36, and a report. Part 37.

The communication unit 31, for example, receives vehicle information and information from the roadside device 200 via the Internet. The communication unit 31 outputs the received information to the registration unit 32. Further, the communication unit 31 may output the report information input from the report unit 37 to an external report device (not shown).

The registration unit 32 writes the map position, the traveling speed, and the traveling date and time in association with each of the vehicle-mounted devices 100 based on the vehicle information input from the communication unit 31, and writes the map position to the vehicle information DB 33 in association with each other. Further, the registration unit 32 writes the levy amount and the semester date and time to each of the vehicle-mounted devices 100 based on the syllabary information input from the communication unit 31, and writes the levy amount and the semester date and time to the syllabary information. DB35.

In the vehicle information DB 33, for example, information for identifying the map position, the traveling speed, and the traveling date and time is added to the identification information unique to each vehicle-mounted device 100 (hereinafter referred to as the vehicle-mounted device ID). .

In the speculative information DB 34, information useful for estimating the traffic state is stored. The speculative information DB 34 stores, for example, information for simulating a traffic state in response to a condition, information for extracting an average traffic state based on past vehicle information, and the like.

In the class information DB 35, for example, information corresponding to the vehicle-mounted device ID and the class date and the class date and time are added to each other.

The CPU 36 includes a determination unit 301, a traffic state value calculation unit 302, a travel speed calculation unit 303, an abnormal vehicle detection unit 304, a traffic state estimation unit 305, a learning unit 306, and a correction unit 307.

The determination unit 301 determines which of the traffic state value calculation unit 302 or the traffic state estimation unit 305 is to be selected as the target for calculating the traffic state. The determination unit 301 calculates the density of the vehicle information in the target area based on the vehicle information stored in the vehicle information DB 33, and determines whether or not the density of the calculated vehicle information is equal to or greater than a predetermined threshold value. The determination unit 301 calculates the density of the vehicle information based on the calculation formula of the following formula (3), for example.

Density of vehicle information = (sum of vehicle information in the object area in the object time zone) / (road length × number of lanes)... (3)

In addition, the sum of the vehicle information in the target area in the target time zone means that the travel time included in the vehicle information is included in the target time zone and the map position included in the vehicle information is included. The amount of vehicle information in the object area.

When the calculated density of the vehicle information is less than the threshold value, the determination unit 301 instructs the traffic state estimation unit 305 to calculate the traffic state. On the other hand, when the calculated density of the vehicle information is equal to or greater than the threshold value, the determination unit 301 calculates the variance of the speed based on the traveling speed information included in the vehicle information. When the number of the variance is equal to or greater than the predetermined threshold value, the determination unit 301 instructs the traffic state estimation unit 305 to calculate the traffic state of the target region. On the other hand, when the number of variances is less than the threshold value determined in advance, the determination unit 301 instructs the traffic state value calculation unit 302 to calculate the traffic state of the target region.

Further, the determination unit 301 may perform the determination process at every specific time interval, or may perform the instruction by the user through an operation unit (not shown) to give an instruction to the start of the determination process.

The traffic state value calculation unit 302 is instructed to calculate the traffic state value by the determination unit 301. Based on the vehicle information stored in the vehicle information DB 33, the representative is represented at a specific object time. The traffic state value of the traffic state in the specific target area in the zone is calculated. The traffic state value calculation unit 302 substitutes the information displayed by the vehicle information or the like into the equation (1) as the traffic state value, and calculates the density of the vehicle in the target region. Further, the traffic state value calculation unit 302 substitutes the information displayed by the vehicle information or the like into the equation (2) as the traffic state value, and calculates the average speed in the target region. Further, the traffic state value calculation unit 302 can extract the vehicle having the traveling speed included in the specific range before and after the average speed based on the average speed in the target area, and calculate the target area. The density of the vehicle.

In addition, the speed in the target area calculated by the traffic state value calculation unit 302 is not limited to the average value of the traveling speed of the vehicle in the target area, and is a mobile phase of the vehicle in the target area. The corresponding speed can be. For example, the traffic state value calculation unit 302 may extract the speed corresponding to the flow of the vehicle in the target area based on the number of variations based on the predetermined legal speed determined in the target area. Further, the traffic state value calculation unit 302 may generate the vehicle information acquired by the vehicle-mounted device 100 that has a sudden change in the traveling speed based on the vehicle information generated at the different timings from the same vehicle-mounted device 100. Excluded from the objects used in calculating the speed in the target area. As a result, since the vehicle information of the vehicle 400 that does not include a temporary change in speed is included, it is possible to obtain a more accurate traffic state value.

The traveling speed calculation unit 303 displays the same vehicle based on the vehicle information based on the vehicle information stored in the vehicle information DB 33. At the position, the traveling speed of the vehicle between two points is calculated. The traveling speed calculation unit 303 calculates the traveling speed in general as described with reference to Fig. 5 .

The abnormal vehicle detecting unit 304 uses the traffic state value calculated by the traffic state value calculation unit 302 or the traffic state estimation unit 305 to display the traveling state of the vehicle 400 displayed by the vehicle information as the vehicle traveling in the target region. The words are detected for abnormal vehicles. The abnormal vehicle detecting unit 304 generally calculates the traveling speed as described with reference to Figs.

The traffic state estimation unit 305 is when the determination of the traffic state value is instructed by the determination unit 301. Based on the speculative information stored in the speculative information DB 34, the traffic state value representing the traffic state in the specific target area in the specific object time zone is estimated. The traffic state estimation unit 305 may be configured to extract the average value of the traffic state in the specific target region in the specific target time zone based on the past vehicle information, and use it as the traffic state value. Further, the traffic state estimation unit 305 may be configured to use a simulator to simulate a traffic state traveling in the target area based on the current conditions, and to extract a specific object representing the specific time zone of the specific object. The traffic state value of the traffic state within the area.

The learning unit 306 causes the estimation information DB 34 to learn in response to the processing result obtained by the abnormal vehicle detecting unit 304. If the specific description is made, when the abnormal vehicle is detected, the learning unit 306 divides the vehicle information corresponding to the detected abnormal vehicle. Going on, based on the vehicle information DB 33, the speculative information of the speculative information DB 34 is learned. When the abnormal vehicle is not detected, the learning unit 306 learns the estimated information of the estimated information DB 34 based on the vehicle information DB 33.

The correction unit 307 generates information for correcting the levy status with respect to the abnormal vehicle detected by the abnormal vehicle detecting unit 304. For example, the correction unit 307 generates information for correcting the lesson information stored in the lesson information DB 35. Further, the correction unit 307 may be configured to generate information for correcting the information of the server that is managed by the externally set course processing, and transmits the information through the communication unit. 31 to send the server for transmission.

Further, when the abnormal vehicle detecting device 300 finds a vehicle having a high possibility of tampering with the map position from the abnormal vehicle, the correcting unit 307 seeks to take out the tampering with the map position. The possibility that the actual vehicle is likely to be driven is a high map position. For example, in the general road shown in FIG. 2, the vehicle information acquired from the vehicle 400 includes map position information indicating that the system has passed the connection of L6 to L8, but the assumption is for the connection L6~ The driving state of L8 is judged to be abnormal and detected as an abnormal vehicle. In this case, the correction unit 307 determines whether or not there is a branch path other than the connection L6. In the example shown in the figure, since the connection L2 to L4 is branched from the connection L1, the correction unit 307 determines that there is a branch path other than the connection L6, and based on the traffic shape connecting L2 to L4. The state value determines whether the vehicle 400 corresponds to the traffic state connecting L2 to L4. When it is determined that the vehicle 400 corresponds to the traffic state of the connection L2 to L4, the information corresponding to the connection L2 to L4 is obtained as the map position where the vehicle 400 is actually traveling. According to this, since the possibility that the vehicle 400 actually travels on the links L2 to L4 which are the toll roads is high, the correction unit 307 represents that it is necessary to perform the course processing on the vehicle 400. The information is written to the levy information DB35. Further, the correction unit 307 can also report from the report unit 37 that it is necessary to perform the course processing.

The report unit 37 reports that the detected vehicle is an abnormal vehicle when the abnormal vehicle detection unit 304 detects an abnormal vehicle. The report unit 37 may be a display or a speaker that outputs the report information, or may output the report information to the vehicle-mounted device 100 or an external report device via the communication unit 31.

(An example of the processing performed by the vehicle-mounted device)

Next, an example of the processing performed by the vehicle-mounted device 100 will be described with reference to FIG. 8. FIG. 8 is a flow chart for explaining an example of the processing performed by the vehicle-mounted device 100. First, by turning on the power of the vehicle 400, the power of the vehicle-mounted device 100 is also turned ON.

(Step ST101)

When the power of the vehicle-mounted device 100 is turned on, the vehicle information generating unit 103 determines whether or not the timing of occurrence of the vehicle information has arrived. For example, car The information generation unit 103 determines whether or not a specific time has elapsed since the time when the previous vehicle information was generated or a specific distance has elapsed.

(Step ST102)

When it is determined that the vehicle information generation timing has arrived (step ST101: YES), the vehicle information generation unit 103 instructs the map matching processing unit 101 to acquire the map position caused by the map matching processing. The map matching processing unit 101 obtains the position on the map of the current vehicle 400 based on the information output from the position information acquisition unit 13 based on the instruction of the vehicle information generation unit 103, and outputs the map position information to the vehicle information. The generating unit 103 is located.

(Step ST103)

Further, the vehicle information generation unit 103 instructs the speed information calculation unit 102 to acquire the traveling speed. The speed information calculation unit 102 obtains the current traveling speed of the vehicle 400 based on the number of rotations of the engine output by the vehicle state detecting unit 14 in accordance with the instruction of the vehicle information generating unit 103, and outputs the traveling speed information to the vehicle information. The generating unit 103 is located.

(Step ST104)

The vehicle information generation unit 103 is based on the map position information input from the map matching processing unit 101 and the input from the speed information calculation unit 102. Driving speed information to generate vehicle information.

The vehicle information generating unit 103 outputs the generated vehicle information to the vehicle information output unit 104 and the class processing unit 105.

(Step ST105)

When the vehicle information is input from the vehicle information generating unit 103, the class processing unit 105 refers to the course condition information 123, and based on the input vehicle information, determines whether or not the map position of the vehicle 400 is the target of the course. The course is within the area.

(Step ST106)

When it is determined that the map position of the vehicle 400 is in the lesson area (step ST105: YES), the course processing unit 105 calculates the vehicle 400 based on the vehicle information input from the vehicle information generating unit 103. The amount of the requested amount is calculated, and the amount of the credit is stored from the stored value card 500 by the reader/writer 17. The class processing unit 105 outputs the class information representing the result of the course processing performed, to the vehicle information output unit 104, and writes it to the course condition information 123.

(Step ST107)

Next, the vehicle information output unit 104 determines whether or not the output timing of the output vehicle information has been reached.

(Step ST108)

When it is determined that the vehicle information has arrived at the output timing of the vehicle information (step ST107: YES), the vehicle information output unit 104 reads the vehicle information input from the vehicle information generating unit 103 and reads from the storage unit 16. The vehicle information 122 is output to the external device designated in advance via the communication unit 111.

(Step ST109)

On the other hand, when it is not determined that the vehicle information has arrived at the output timing of the vehicle information (step ST107: NO), the vehicle information output unit 104 writes the vehicle information input from the vehicle information generating unit 103 to The vehicle information 122 of the memory unit 16 is included.

(An example of the overall processing of the abnormal vehicle detecting device 300)

Next, an example of the overall processing performed by the abnormal vehicle detecting device 300 will be described with reference to FIG. 9. FIG. 9 is a flow chart for explaining an example of the overall processing performed by the abnormal vehicle detecting device 300. Further, the abnormal vehicle detecting device 300 sequentially specifies the target time zone and the target region, and performs the following processing for each of the target regions in each target time zone.

(Step ST201)

The determination unit 301 determines whether or not the traffic state is estimated when the target time zone and the target zone are specified. In other words, judge The unit 301 determines whether or not the traffic state value calculation unit 302 or the traffic state estimation unit 305 is to be selected as the target for calculating the traffic state value. In the present embodiment, the determination unit 301 reads out the vehicle information corresponding to the designated target time zone and the target area from the vehicle information DB 33, and calculates the target area in the specified target time zone. The density of vehicle information. For example, it is assumed that the link LX is designated as the target area, and 13:00 to 13:10 of the month ○ day is designated as the target time zone. Further, the determination unit 301 calculates the variation of the traveling speed based on the traveling speed information included in the vehicle information.

(Step ST202)

When the density of the vehicle information connected to LX is equal to or greater than the threshold value and the number of variations is less than the threshold value, the determination unit 301 determines that the traffic state is not required to be estimated (step ST201: NO).

In this case, the determination unit 301 instructs the traffic state value calculation unit 302 to calculate the traffic state value of the target region. After that, the traffic state value calculation unit 302 exists in the target area LX based on the presence of the vehicle time information stored in the vehicle information DB 33 in the target time zone (13:00 to 13:10 on the day of the month). The vehicle information of the internal event reproduces the traffic state of the vehicle in the target area, and calculates the traffic state value representing the traffic state in the specific target area in the specific object time zone. In addition, the reproduction of the traffic state, for example, refers to the number of vehicles 400 present in the target area, the positional relationship, the average speed, and the density of the vehicle 400 at each time point in the target time zone. Degrees, etc.

(Step ST203)

On the other hand, when the density of the vehicle information connected to the LX is less than the threshold value, or when the density of the vehicle information connected to the LX is greater than the threshold value and the variation number is equal to or greater than the threshold value, The determination unit 301 determines that it is necessary to estimate the traffic state (step ST201: YES). In this case, the determination unit 301 instructs the traffic state estimation unit 305 to calculate the traffic state value of the target region. Thereafter, the traffic state estimation unit 305 is based on the estimation information stored in the estimation information DB 34, and represents the vehicle condition in the target region estimated in the specific target time zone (for example, representing the vehicle in motion). The information on the map position and the speed of travel is estimated and the result of the speculation is taken out.

(Step ST204)

After that, the traffic state estimation unit 305 reproduces the traffic state of the vehicle in the target area based on the estimation result extracted in step ST203, and calculates the representative target area in the specific target time zone. Traffic status value of traffic status.

(Step ST205)

Next, the abnormal vehicle detecting unit 304 is based on the traffic state value calculated by the traffic state value calculation unit 302 or the traffic state estimation unit 305. The abnormal vehicle detection processing detected by the abnormal vehicle is performed by using the traveling state of the vehicle displayed by the vehicle information as the vehicle traveling in the target area. In addition, the details of this processing content will be described later with reference to FIG.

(Step ST206)

The abnormal vehicle detecting unit 304 determines whether or not an abnormal vehicle has been detected in the processing of step ST205.

(Step ST207)

When it is determined that the abnormal vehicle has been detected (step ST206: YES), the abnormal vehicle detecting unit 304 causes the reporting unit 37 to report that the abnormal vehicle has been detected.

(Step ST208)

Thereafter, the learning unit 306 causes the estimation information DB 34 to learn based on the processing result obtained by the abnormal vehicle detecting unit 304. In the case where the abnormal vehicle is detected in step ST207, the learning unit 306 removes the vehicle information corresponding to the detected abnormal vehicle and makes the estimation based on the vehicle information DB 33. Information on the information of DB34 for learning. When the abnormal vehicle is not detected in step ST207, the learning unit 306 learns the estimated information of the estimated information DB 34 based on the vehicle information DB 33.

(Step ST209)

The abnormal vehicle detecting unit 304 determines whether or not the abnormal vehicle detecting process has been completed for all the target regions. When it is determined that the abnormal vehicle detection processing has not been completed for all the target regions (step ST209: NO), the abnormal vehicle detecting unit 304 returns to step ST201 and repeats the processing. On the other hand, when it is determined that the abnormal vehicle detection processing has been completed for all the target regions (step ST209: YES), the abnormal vehicle detecting unit 304 ends the processing.

(One of the examples of abnormal vehicle detection processing)

Next, an example of abnormal vehicle detection processing will be described with reference to FIG. Fig. 10 is a flow chart for explaining an example of abnormal vehicle extraction processing. Further, the processing shown in Fig. 10 corresponds to the processing of step ST205 shown in Fig. 9.

(Step ST301)

The abnormal vehicle detecting unit 304 acquires the average speed of each target region as the traffic state value from the traffic state value calculating unit 302 or the traffic state estimating unit 305. The abnormal vehicle detecting unit 304 can obtain the average speed of each target region calculated by the traffic state value calculating unit 302 or the traffic state estimating unit 305, and can also be based on the traffic state value calculating unit 302 or the traffic state estimating unit. The traffic state value is derived from 305, and the average speed of each object region is calculated by itself.

(Step ST302)

Next, the abnormal vehicle detecting unit 304 acquires the density of the vehicle in each of the target regions based on the traffic state value obtained from the traffic state value calculating unit 302 or the traffic state estimating unit 305. The abnormal vehicle detecting unit 304 can obtain the density of the vehicle in each target area calculated by the traffic state value calculating unit 302 or the traffic state estimating unit 305, or based on the traffic state value calculating unit 302 or the traffic state estimation unit. The traffic state value from the portion 305 is calculated by itself to calculate the density of the vehicle in each target region.

(Step ST303)

The abnormal vehicle detecting unit 304 determines whether or not the density of the vehicle calculated in step ST302 is equal to or greater than a predetermined threshold value.

(Step ST304)

When it is determined that the density of the vehicle is equal to or greater than the threshold value (step ST303: YES), the abnormal vehicle detecting unit 304 sets an allowable predetermined range in accordance with the density of the vehicle. For example, it can be inferred that when the density of the vehicle is high, the difference in the traveling speed between the vehicles is small, and when the density of the vehicle is low, the difference in the traveling speed between the vehicles is large. Therefore, it is assumed that the allowable range is ±5 km/h when the density of the vehicle is 90% or more, and ±7 km/h when the density of the vehicle is 80% or more and less than 90%. ..., when the density of the vehicle is 50 or more and less than 60%, the allowable range is ±12km/h. Although not shown, it represents the density of this The information of the determined allowable range is stored in the memory unit built in the abnormal vehicle detecting unit 304.

(Step ST305)

Next, the abnormal vehicle detecting unit 304 is for each vehicle based on the vehicle information stored in the vehicle information stored in the vehicle information DB 33 and showing that the vehicle 400 is present in the target area in the target time zone. Further, it is determined whether or not the traveling speed included in the vehicle information is deviated from the average speed in the target region calculated in step ST301. In the specific description, the abnormal vehicle detecting unit 304 determines whether or not the traveling speed included in the vehicle information is included in the allowable range based on the average speed in the target area. For example, when the number of average speeds in the target area is included in the allowable range, the abnormal vehicle detecting unit 304 determines that the traveling speed included in the vehicle information is included in the average of the target area. Speed is within the allowable range of the reference. Further, the abnormal vehicle detecting unit 304 may be configured to determine that the vehicle is included when the ratio of the number of traveling speeds included in the vehicle information is included in the allowable range. The traveling speed included in the information is included in the allowable range based on the average speed in the target area.

(Step ST306)

When it is determined that the traveling speed included in the vehicle information is different from the average speed in the target area (step ST305: YES) The abnormal vehicle detecting unit 304 detects that the traveling speed included in the vehicle information is not included in the allowable range based on the average speed in the target area, and is detected as an abnormal vehicle.

(Step ST307)

Next, the abnormal vehicle detecting unit 304 determines whether or not for all the vehicles based on the vehicle information in which the vehicle 400 is present in the target area in the target time zone, based on the vehicle information stored in the vehicle information DB 33. Both of them have implemented abnormal vehicle detection processing. When it is not determined that the abnormal traveling detection processing is performed for all the vehicles (step ST307: NO), the abnormal vehicle detecting unit 304 returns to step ST304 and repeats the processing. On the other hand, when it is determined that the abnormal traveling detection processing has been executed for all the vehicles (step ST307: YES), the abnormal vehicle detecting unit 304 ends the processing.

(Step ST308)

In the determination of step ST303, when it is determined that the density of the vehicle is less than the threshold (step ST303: NO), the abnormal vehicle detecting unit 304 is based on the vehicle information stored in the vehicle information DB 33. The vehicle information indicating that the vehicle 400 is present in the target area in the target time zone is displayed, and the traveling speed between at least two points of the vehicle 400 exhibited by the map position included in the vehicle information is calculated. For example, the abnormal vehicle detecting unit 304 is based on the vehicle information S1 and S2 acquired from the same vehicle-mounted device 100 at different timings, and according to the following formula (4), The traveling speed between the two points is calculated by calculating the map position P1 at the time T1 at which the vehicle information S1 is generated and the map position P2 at the time T2 at which the next vehicle information S2 is generated.

Travel speed = (distance between P1 and P2) / (time T2 - time T1)... equation (4)

(Step ST309)

The abnormal vehicle detecting unit 304 determines whether or not the traveling speed of the vehicle 400 calculated in step ST308 is abnormal. For example, a vehicle traveling at 200 km/h on a general road is abnormal. When the traveling speed of the vehicle 400 calculated in step ST308 is equal to or higher than the abnormal speed determined in advance, the abnormal vehicle detecting unit 304 determines that the traveling speed itself is abnormal (step ST309: YES). And it progresses to step ST311.

(Step ST310)

When the traveling speed of the vehicle 400 calculated in step ST308 is less than the abnormal speed determined in advance (step ST309: NO), the abnormal vehicle detecting unit 304 determines the vehicle calculated in step ST308. Whether the change in the driving speed of 400 is abnormal. For example, when there is a sudden change in the traveling speed after a few seconds or when there is a sudden change in the reverse, the vehicle traveling as such is abnormal. The abnormal vehicle detecting unit 304, when the vehicle 400 calculated in step ST308 In the change of the time series of the traveling speed, in the case where there is a variation in the change, or in the change in the time series of the traveling speed of the vehicle 400 calculated in step ST308, the amount of change is in advance. When the determined threshold value or more is exceeded, it is determined that the change in the time series of the traveling speed is abnormal (step ST310: YES), and the process proceeds to step ST311.

(Step ST311)

When it is determined in step ST309 or in step ST310 that the body is abnormal (step ST309: YES, step ST310: YES), the abnormal vehicle detecting unit 304 uses the vehicle determined to be abnormal as the abnormal vehicle. Detected.

(Step ST312)

Next, the abnormal vehicle detecting unit 304 determines whether or not for all the vehicles based on the vehicle information in which the vehicle 400 is present in the target area in the target time zone, based on the vehicle information stored in the vehicle information DB 33. Both of them have implemented abnormal vehicle detection processing. When it is not determined that the abnormal traveling detection processing is performed for all the vehicles (step ST312: NO), the abnormal vehicle detecting unit 304 returns to step ST308 and repeats the processing. On the other hand, when it is determined that the abnormal traveling detection processing has been performed for all the vehicles (step ST312: YES), the abnormal vehicle detecting unit 304 ends the processing.

(Other, replacement or change of each component)

In addition, it is preferable to replace the constituent elements in the above-described embodiments with well-known constituent elements within the scope of the gist of the invention. In addition, the technical scope of the present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the spirit and scope of the invention.

For example, the abnormal vehicle detecting unit 304 of the abnormal vehicle detecting device 300 has described the case where the abnormal vehicle is detected based on the traffic state value, but is not limited thereto. For example, the abnormal vehicle detecting unit 304 may determine whether or not there is an abnormal vehicle based on the vehicle information of the target area in the target time zone read from the vehicle information DB 33. As described above, the abnormal vehicle detecting unit 304 detects that the vehicle traveling at a speed of 200 km/h is regarded as an abnormality as a vehicle traveling in the target area. In addition, when the amount of change in the travel time of the vehicle 400 in the time series is equal to or greater than the threshold value, or when there is a difference in the amount of change, the abnormal vehicle detecting unit 304 Detected as an abnormal vehicle.

The class processing unit 105 is not limited to the payment processor that performs the amount of the credit for the stored value card 500, and may be a payment processor that performs the amount of the credit by a credit card or the like.

The vehicle-mounted device 100 can also be connected to a central server (not shown) that transmits map information or course condition information. Thereby, the vehicle-mounted device 100 can specify the vehicle 400 based on the latest map information. Map location and include it in vehicle information. Further, the vehicle-mounted device 100 can perform the course processing based on the latest course condition information. By this, the reliability of the levy system can be improved.

The vehicle-mounted device 100 is not limited to including the map position obtained by the map matching processing unit 101 in the vehicle information, and may be configured to directly include the information acquired by the position information acquiring unit 13 in the vehicle. In the information.

The traffic state value calculation unit 302 and the abnormal vehicle detection unit 304 may be configured to remove the vehicle that is in the stopped state. In this case, the vehicle-mounted device 100 includes information indicating whether or not the engine (ignition device) of the vehicle 400 is turned off, and transmits it to the abnormal vehicle detecting device 300.

The traffic state value calculation unit 302 and the abnormal vehicle detection unit 304 remove the vehicle information that the engine is turned off, and perform specific processing.

The class processing is described with respect to an example in which the vehicle-mounted device 100 is executed. However, the class processing may be performed by an external server.

When the determination unit 301 determines whether or not to estimate the traffic state, the determination unit 301 is not limited to the determination based on the variation of the density of the vehicle information and the traveling speed. For example, when the density of the vehicle information is equal to or greater than the threshold value, the determination unit 301 may be configured to instruct the traffic state value calculation unit 302 to calculate the traffic state value, and when the density of the vehicle information is less than In the case of the threshold value, the traffic state estimation unit 305 is instructed to calculate the traffic state value.

(action and effect)

As described above, the abnormal vehicle detecting device 300 of the present invention includes the abnormal vehicle detecting unit 304 that detects the vehicle based on the representative position of the vehicle-mounted device mounted on the vehicle and the vehicle information of the traveling speed. The driving state of the vehicle exhibited by the information is an abnormal vehicle as a vehicle traveling in the target area.

According to this configuration, the abnormal vehicle detecting device 300 can detect an abnormal vehicle in which the information acquired by the vehicle-mounted device and the actual vehicle condition are different. By this, it is possible to tamper with the vehicle information obtained by the vehicle-mounted device by some methods, so that the vehicle passing through the toll road can be detected by the illegal vehicle that is exempt from the payment of the amount of the passage. And can enhance the trust of the system. Further, it is possible to prevent traffic information representing a traffic jam or a crowded situation from being generated based on a situation different from actual driving information.

Further, the abnormal vehicle detecting device 300 of the present embodiment includes vehicle information based on the representative position of the vehicle-mounted device mounted on the vehicle and the traveling speed, and represents a specific target region represented in the specific target time zone. The traffic state value calculation unit 302 that calculates the traffic state value of the traffic state in the inside.

Further, in the abnormal vehicle detecting device 300 of the present embodiment, when the amount of deviation between the speed in the target region and the traveling speed exhibited by the actual vehicle information exceeds a specific allowable range, it is regarded as an abnormal vehicle. And detected.

With this configuration, the abnormal vehicle detecting device 300 can detect the abnormal vehicle based on the traffic state. Thereby, even when the change in the traveling speed of the vehicle itself or the traveling speed is not abnormal, the vehicle 400 can be performed based on the relationship with the other vehicles traveling on the same road. Judgment of abnormality. Therefore, it is possible to make a vehicle that does not correspond to the traffic state in the target area, that is, to have a height in the target area, and to be able to travel at a speed corresponding to the traffic state, and to detect as an abnormal vehicle. It is detected, and it is possible to tamper with the vehicle information and detect itself as a vehicle that travels in the target area.

Further, in the abnormal vehicle detecting device 300 of the present embodiment, when the density of the vehicle in the target area revealed by the traffic state value is higher than the threshold value, and the speed in the object area displayed by the traffic state value is When the deviation between the travel speeds exhibited by the actual vehicle information exceeds a certain allowable range, it is detected as an abnormal vehicle.

According to this configuration, the abnormal vehicle is detected based on the traffic state in a state where the density of the vehicle traveling in the target area is higher than the threshold. In the traffic state where the density of the vehicle is high, it is possible to obtain most of the vehicle information acquired from the vehicle-mounted device. Therefore, it is possible to calculate the traffic state value representing the average traffic state based on the plurality of vehicle information. Further, in a traffic state in which the density of the vehicle is high, it is conceivable that the interval with other vehicles is narrow, and there is no space that can travel at a faster speed than the average speed in the target area. Therefore, it is possible to The speed traveled in the image area depends on the traffic state and is close to the speed of the traffic state in the object area. In this way, since the abnormal vehicle can be detected based on the traffic state value in a state in which the traveling speed of the vehicle traveling in the target area is restricted to some extent, it is possible to make the abnormal vehicle Detection accuracy is improved.

Further, the abnormal vehicle detecting device 300 of the present embodiment further includes a traveling speed calculating unit 303 based on the vehicle 400 represented by the vehicle information acquired from the same vehicle-mounted device 100 at the timing of the difference. The position information of at least 2 points is used to calculate the traveling speed of the vehicle 400.

With this configuration, it is possible to calculate the traveling speed of the vehicle based on the position of the vehicle based on the position of the vehicle included in the vehicle information. When the position of the vehicle included in the vehicle information has been tampered with, it is conceivable that the traveling speed of the vehicle calculated based on the position of the vehicle may deviate from the actual traveling speed. Therefore, it is possible to detect a vehicle having a high possibility that the position of the vehicle included in the vehicle information has been tampered with as an abnormal vehicle.

Further, the abnormal vehicle detecting device 300 of the present embodiment further includes a traffic state estimating unit 305 for limiting the density of vehicle information in a specific target region in a specific target time zone. In the case of a value, the traffic state of a specific target area in a specific target time is estimated.

With this configuration, the traffic state estimation unit 305 is configured to have less vehicle information in a specific target area in the specific target time zone. It is assumed that the traffic state of a specific target area in a specific object time is estimated. Here, when the density of the vehicle information is low, since only a small amount of vehicle information can be acquired, it is possible to evaluate the traffic state based on the biased vehicle information or to be in a special state according to chance. The state of the vehicle is used to evaluate the traffic status. However, when the density of the vehicle information is lower than the threshold, the traffic state value is not obtained based on the vehicle information acquired in the target time zone, but the traffic state is estimated and based on The estimated traffic state is used to calculate the traffic state value, and even if the vehicle information density is low, the abnormal traffic can be detected based on the average traffic state.

Further, the abnormal vehicle detecting device 300 of the present embodiment further includes a reporting unit 37 for reporting an abnormal vehicle.

With this configuration, it is possible to provide information on the abnormal vehicle, a manager who manages the payment for the toll road, a monitor that monitors the traffic situation based on the vehicle information, or a vehicle that is determined to be an abnormal vehicle. Drive and report.

Further, the abnormal vehicle detecting device 300 of the present embodiment further includes a correction unit 307 that generates information for correcting the course status of the vehicle that is determined to be abnormal by the abnormal vehicle detecting unit 304.

According to this configuration, the correction unit generates information for correcting the situation to be corrected, and the processing for correcting the situation is easily performed.

Further, the abnormal vehicle detecting device 300 of the present embodiment uses the map position included in the vehicle information when calculating the traffic state value.

With this configuration, it is possible to improve the reproduction accuracy of the traffic state as compared with the case where the information showing the latitude and longitude is used as the position information of the vehicle.

Further, a program for realizing the functions of the vehicle-mounted device 100 and the abnormal vehicle detecting device 300 in the present invention can be recorded in a computer-readable recording medium, and a program recorded in the recording medium can be recorded. It is read into the computer system and implemented, whereby engineering is carried out. In addition, the term "computer system" as used herein refers to a hardware including an OS and peripheral devices. In addition, "computer system" refers to a WWW system that also includes a webpage providing environment (or a display environment). Further, the term "computer-readable recording medium" refers to a portable medium such as a floppy disk, a magneto-optical disk, a ROM, a CD-ROM, or the like, and a memory device such as a hard disk embedded in a computer system. Further, the "computer-readable recording medium" also includes a case where a program is transmitted via a network such as the Internet or a communication line such as a telephone line, and the like is a server or a client. The volatile memory (RAM) inside the computer system generally keeps the program for a certain period of time.

Further, the program may be transferred from another computer system to a computer program stored in a memory device or the like via a transmission medium or a propagation wave in the transmission medium. Here, the "transmission medium" of the transmission program refers to a network such as the Internet (through the Internet). The communication network (communication line), such as a telephone line, generally has a function of transmitting information. Further, the above program may be part of the above-described functions. Furthermore, it is also possible to implement the above functions by a combination with a program already recorded in a computer system, that is, a so-called differential file (differential program).

[Industry use possibility]

According to the above-described apparatus, method and program, it is possible to detect a vehicle in which the position of the vehicle obtained by the vehicle-mounted device and the actual position of the vehicle are different.

31‧‧‧Communication Department

32‧‧‧Registration Department

33‧‧‧Vehicle Information DB

34‧‧‧ Speculation information DB

35‧‧‧Information Information DB

36‧‧‧CPU

37‧‧‧Reporting Department

300‧‧‧Abnormal vehicle detection device

301‧‧‧Decision Department

302‧‧‧Traffic status value calculation unit

303‧‧‧Travel speed calculation unit

304‧‧‧Abnormal Vehicle Detection Department

305‧‧‧ Traffic Status Estimation Department

306‧‧‧Learning Department

307‧‧‧Amendment

Claims (10)

An abnormal vehicle detecting device is characterized in that: a traffic state value calculating unit is configured to calculate a representative based on vehicle information representing a position of the vehicle and a traveling speed obtained from a vehicle-mounted device mounted on the vehicle. The traffic state value of the traffic state in the specific target area in the specific target time zone; and the abnormal vehicle detection unit based on the traffic state value calculated by the traffic state value calculation unit and the vehicle from each vehicle The vehicle information acquired by the device detects the traveling state of the vehicle displayed by the vehicle information as a vehicle having an abnormality in the vehicle traveling in the target area. The abnormal vehicle detecting device according to the first aspect of the invention, wherein the abnormal vehicle detecting unit acquires a speed in the target region as the traffic state value calculated by the traffic state value calculating unit. When the amount of deviation between the speed in the target area and the traveling speed of the vehicle exhibited by the aforementioned vehicle information is greater than a specific allowable range, it is determined that the traveling state of the vehicle is abnormal. The abnormal vehicle detecting device according to the second aspect of the invention, wherein the abnormal vehicle detecting unit acquires a vehicle in the target area as the traffic state value calculated by the traffic state value calculating unit. Density, when the density of the vehicle in the target area is higher than the threshold, and the amount of deviation exceeds a specific allowable range, it is determined that the running state of the vehicle is abnormal. If the application of any of the patent scopes 1 to 3 is different The vehicle detection device further includes: a traveling speed calculation unit that is based on position information of at least two points of the vehicle represented by the vehicle information acquired from the same vehicle-mounted device at different timings And calculating the traveling speed of the vehicle, the abnormal vehicle detecting unit determining, based on the traveling speed calculated by the traveling speed calculating unit, the traveling state of the vehicle displayed by the vehicle information as the vehicle traveling in the target area Is there something unusual? The abnormal vehicle detecting device according to any one of claims 1 to 3, further comprising: a traffic state estimating unit, which is a specific target region in a specific target time zone. When the density of the vehicle information in the inside is less than the threshold value, the traffic state in the specific target area in the specific target time zone is estimated, and the traffic state value calculation unit is the density of the vehicle information. When the threshold value is equal to or greater than the threshold value, the traffic state value is calculated, and the abnormal vehicle detecting unit determines the traveling state of the vehicle displayed by the vehicle information based on the traffic state estimated by the traffic state estimating unit. Whether the vehicle traveling in the aforementioned object area is abnormal. The abnormal vehicle detecting device according to any one of the first to third aspects of the present invention, further comprising: a reporting unit that reports that the abnormal vehicle detecting unit determines that the vehicle is abnormal. If the application of any of the patent scopes 1 to 3 is different The normal vehicle detecting device further includes: a correction unit that generates information for correcting a course condition of the vehicle that is determined to be abnormal by the abnormal vehicle detecting unit. An abnormal vehicle detecting device characterized in that: an abnormal vehicle detecting unit is provided based on vehicle information representing a position of the vehicle and a traveling speed obtained from a vehicle-mounted device mounted on the vehicle The vehicle information in the specific target area in the specific target time zone is used to determine whether the traveling state of the vehicle represented by the vehicle information is abnormal as the vehicle traveling in the target area. An abnormal vehicle detecting method characterized by comprising: a traffic state value calculating step of calculating a representative based on vehicle information representing a position and a traveling speed of the vehicle obtained from a vehicle-mounted device mounted on the vehicle a traffic state value of a traffic state in a specific target area in a specific target time zone; and an abnormal vehicle detecting step based on the aforementioned traffic state value calculated in the traffic state value calculation step, and from each vehicle The vehicle information acquired by the vehicle-mounted device detects the traveling state of the vehicle displayed by the vehicle information as a vehicle having an abnormality in the vehicle traveling in the target area. A program is characterized in that a computer functions as a means for calculating a traffic state value based on a vehicle vehicle that is obtained from a vehicle-mounted device mounted on a vehicle and that represents a position and a traveling speed of the vehicle. a traffic state value representing a traffic state in a specific target area in a specific target time zone; and an abnormal vehicle detecting means based on the traffic state value calculated by the traffic state value calculating means, and The vehicle information acquired by the vehicle-mounted device of each vehicle detects the traveling state of the vehicle displayed by the vehicle information as a vehicle having an abnormality in the vehicle traveling in the target area.